Taiwanese opera is the important culture inheritance in Taiwan, however, this culture inheritance is dying in recently years. Although the Taiwan government and various Taiwanese opera troupes have worked hard for many years to promote this culture to campuses, and held several interest courses; this culture inheritance is still losing and dying. For elder people, Taiwanese opera and Taiwanese cultures are both precious culture treasures and parts of their childhood memories. Nowadays, young people in Taiwan are no longer familiar to Taiwanese, neither to Taiwanese opera singings. It is hard for young people to learn how appreciating this traditional culture. In this study, we refer to the current promotion methods of drama troupes which learn the singing method and posture of Taiwanese opera, we combine artificial intelligence techniques into traditional Taiwanese opera on singing and posture. The proposed system could analyzes students’ voice and postures, and then assists teachers to improve the learning performance of students. Students could compare their singing skill or postures with professional actors and adjust their singing and posture. Students of Taiwanese opera interest class can practice independently without professional teacher's guidance at home. In campus promotion, this game-like promotion method brings young people more acceptance of Taiwanese opera.

In this study, a detection system of congestive heart failure (CHF) based on multiple input neural network was proposed. In previous research, the majority of studies focused on 24-hour electrocardiogram (ECG) data analysis for classification. To provide a convenient and rapid screen process, we proposed to offer a short- term analysis with the data size of 7-minute segment of ECG signal. The proposed detection system consisted of four steps: data pre- processing, model- establishment, multi-input configuration, and deep learning model classification. We proposed RR intervals instead of raw ECG data for the model input to reduce computation complexity. Also, by feeding in RR interval signal in both time and frequency domain, we can leverage the model performance by the known study results from HRV analysis to obtain the significant features more easily. The recognition accuracy between CHF and conctrol groups of proposed detection system is up to 93.76% for training set, and 86.74% for testing set.

There are two main research topics about ECG signal proposed. One is the noise reduction, and the other is R peaks detection. Both of the two algorithms are based on discrete wavelet transform (DWT). DWT is efficient for analyzing nonstationary signals like ECG signal. The Symlets wavelets (sym5) and soft-thresholding are chosen as the wavelet function and thresholding method to do noise correction at the first denoising stage. The second stage is R wave detection. The MIT-BIH arrhythmia database is used to verify proposed algorithm. We reconstruct the decomposition level 3 to 5. Choosing the adaptive threshold and window size are the key points to reduce error rate. Applying two thresholds leads to better performance, compared to applying one threshold. At the last stage, we do noise correction again.With the information of R wave position, a novel method is proposed to eliminate the electromyogram (EMG) signal. The algorithm for R wave detection has a sensitivity of 99.70% and a positive predictivity of 99.65%. The error rate is 0.65% under all kinds of situation (0.37% if ignoring 3 worst cases). For noise correction, the SNR improvement is achieved at least 10dB at SNR 5dB, and most of the improvement SNR are better than other methods at least 1dB at different SNR. To apply presented algorithms for the portable ECG device, all R peaks can be detected no matter when people walk, run or move at the speed below 9km/hr.

With the rise of location based services (LBS), indoor and outdoor localization using RF based network has been popular in recent years. Since the outdoor location determination is dominated by global positioning system (GPS), the outdoor part of localization is not included in our discussion. Here we propose a novel indoor localization method deploying WiFi access points (APs) called cluster k-NN algorithm, which does not cost extra money for infrastructures and still offers decent accuracy comparing to other indoor localization techniques. According to the offline simulation, the complexity of cluster k-NN is lower, while the accuracy is up to 98.67%. As a result, the complexity and the calculation are greatly decreased, while the accuracy is still maintained. We have also made the application including our algorithm and data on Android based smart phones with intuitive user interface and quick access to change parameters, in order to briefly demonstrate our result to determine the location of users in real time. Online positioning was tested under cluster k-NN with the optimal parameters obtained through offline simulation. The tested environment was the LaRC laboratory on the fourth floor in the TSMC building in National Tsing Hua University (NTHU). With the background dimension in 227.59 m2, the average error rate of our algorithm is 4.75%, and the average error distance is 3.728m, which is a satisfactory result. Compared to other designs, the accuracy of our algorithm does not differ much. However, the complexity is at least a third less. With such accuracy and portability, precise position of every patient is sent to the cloud server and computed real-time, which enables doctors to be fully informed, with the reduced energy consumption and longer time the devices can stand by.

Triple patterning lithography (TPL) has received more and more attentions from industry as one of the leading candidate for 14nm/11nm nodes. In this paper, we propose a high performance layout decomposer for TPL. Density balancing is seamlessly integrated into all key steps in our TPL layout decomposition, including density-balanced semi-definite programming (SDP), density-based mapping, and density-balanced graph simplification. Our new TPL decomposer can obtain high performance even compared to previous state-of-the-art layout decomposers which are not balanced-density aware, e.g., by Yu et al. (ICCAD'11), Fang et al. (DAC'12), and Kuang et al. (DAC'13). Furthermore, the balanced-density version of our decomposer can provide more balanced density which leads to less edge placement error (EPE), while the conflict and stitch numbers are still very comparable to our non-balanced-density baseline.

Conventional buffer insertion in timing ECO involves only minimizing the arrival time of the most critical sink in one multi-pin net and neglects the obstacles and the topology of routed wire segments, which may worsen the arrival times of other sinks and burden subsequent timing ECO. This work develops a topology-aware ECO timing optimization (TOPO) flow that comprises three phases - buffering pair scoring, edge breaking and buffer connection, and topology restructuring. TOPO effectively improves the arrival times of violation sinks without worsening those of other sinks. Experimental results indicate that TOPO improves the worst negative slack (WNS) and total negative slack (TNS) of benchmarks by an average of 79.2% and 84.3%, respectively. The proposed algorithm improves the arrival time that is achieved using conventional two-pin net-based buffer insertion by an average of 40.4%, at the cost of consuming 19× runtime. To speed up routing and further improve sink slack, a highly scalable massively parallel maze routing on Graphics Processing Unit (GPU) platform is also developed to enable the proposed flow to explore more solution candidates. High scalability and parallelism are realized by block partitioning and staggering. Experiments reveal that the proposed GPU-based parallel maze routing can achieve near 12× runtime speedup for two-pin routings. With parallelized maze routing, WNS violations in four out of five cases can be resolved.

TPL-friendly detailed routers require a systematic approach to detect TPL conflicts. However, the complexity of conflict graph (CG) impedes directly detecting TPL conflicts in CG. This work proposes a token graph-embedded conflict graph (TECG) to facilitate the TPL conflict detection while maintaining high coloring-flexibility. We then develop a TPL aware detailed router (TRIAD) by applying TECG to a gridless router with the TPL stitch generation. Compared to a greedy coloring approach, experimental results indicate that TRIAD generates no conflicts and few stitches with shorter wirelength at the cost of 2.41x of runtime.

The printed image of a layout that satisfies the double patterning lithograph (DPL) constraints may not have good fidelity if the layout neglects optical proximity correction (OPC). Simultaneously considering DPL and OPC becomes necessary when gene rating layouts, especially in routing stage. Moreover, one decomposed design with balanced mask density has a lower edge placement error (EPE)than an unbalance done[6]. This work proposes a compre-hensive conflict graph (CCG)to enable detailed routers to simultaneously consider DPL, OPC, and mask density to gene rate litho-friendly layouts. This work then develops an DPL-aware and OPC-friendly gridless detailed routing (DOPPLER) by applying CCG in a gridless routing model. A density variation threshold annealing-based routing flow is also proposed to prevent DOPPLER from falling into a sub-optimal mask density balance. Compared with existing DPL-aware detailed routing works, DOPPLER demon-stratesanaverage 73.84% of EPE hotspot reduction with a satisfactory mask density at the cost of an average increase of 0.08% wire-length, 15.14% number of stitches, and 77.28% runtime.

For modern designs, delay optimization significantly facilitates success in design closure owing to its more realistic metric than wirelength in routing. Obstacle-avoiding rectilinear Steiner tree (OARST) construction is an essential routing problem. With the trends toward Internet protocol-block-based system-on-chip designs, OARST with buffer insertion has been surveyed to diminish the delay of long wires. Previous works on performance-driven (PD) OARST without and with buffer insertion can only handle small circuits. This paper develops a novel routing algorithm in obstacle-avoiding spanning graph to construct OARST with optimized delay efficiently. The proposed multisource single-target maze routing is first employed to identify the critical trunks, and the critical-trunk-based tree growth mechanism connects the unconnected pins to critical trunks under delay constraints of every sink. We apply the proposed critical-trunk-based tree growth mechanism to solve PD and slack-driven (SD) OARST problems. The proposed algorithms are extended to consider buffer insertion during PD and SD OARST constructions. Experimental results demonstrate that the proposed algorithms achieve an average 25.84% improvement in the maximum delay over obstacle-avoiding rectilinear Steiner minimal tree in the PD OARST problem and successfully solve 66.67% worst negative slack violations in the SD OARST problem. Compared to the simultaneous routing and buffer insertion approach, the proposed buffer-aware (BA) algorithm generates satisfactory timing results with almost identical wire length (WL). Moreover, the proposed BA SD OARST algorithm utilizes less WL than the BA rectilinear Steiner tree construction does by 17.99% on average. The runtime comparison with previous works shows the efficiency and scalability of this paper.

While via failure significantly contributes to yield loss during manufacturing, post-routing redundant via insertion method is the conventional means of reducing the via failure rate, but only alive vias can be protected. As existing dead vias still lower manufacturing yield, identifying a routing result with fewer dead vias can increase the redundant via insertion rate, subsequently enhancing the yield of chips. This work presents, for the first time, a redundant-via-aware routing system to retain redundant via resources in track assignment, in which redundant vias are inserted in detailed routing. The proposed via prediction scheme performs trial route using L-shaped patterns to estimate via positions. Meanwhile, the proposed redundant-via-aware detailed router gradually relaxes the limitation on the number of generated dead vias during path searching to minimize the number of dead vias. Experimental results indicate that the proposed redundant-via-aware routing system is, to our knowledge, the first routing system that can achieve 100% redundant via insertion rate with all MCNC benchmark circuits.

Double patterning lithography (DPL) is the most feasible solution for sub-32nm nodes owing to the recurrent delay in next generation lithography. DPL attempts to decompose a single layer of one layout into two masks in order to increase pitch size and improve depth of focus (DOF). Considering DPL at detailed routing stage can improve the flexibility of layout decomposition as compared to the post-routing layout decomposition. The conflict graph proposed in [8] provides a global view of all nets in a layout to obtain a highly decomposable layout with less yield loss. However, adopting conflict graph in routing process using grid-based model or gridless model both brings huge overhead. This work presents an innovative conflict graph (ICG) to realize adopting conflict graph in a routing process. Three routing-friendly characteristics of ICG are constant-time conflict cycle detection, lazy ICG update, and light-weight routing overhead. To efficiently utilize routing resources for a crowded region, gridless models provide a better solution space than grid-based models do. This work also develops, to our knowledge, the first DPL-aware gridless detailed routing with ICG to generate a highly decomposable routing result. Moreover, greedily assigning colors for routed nets may cause unnecessary stitches or even a coloring conflict. This work presents a deferred coloring assignment-based routing flow to escape local optimum of a greedy coloring approach. Experimental results indicate that DPL-aware routing results contain no coloring conflicts, and the stitches produced by the proposed router are less than those produced by a greedy coloring approach by 41% on average with only 0.22% and 30% increment in wirelength and runtime, respectively.

In 2001, the sanitizable signature was proposed by Steinfeld et al. Until now, many sanitizable signature schemes have been proposed. However, current sanitizable signature schemes are faced with the dishonest sanitizer or additional sanitizing problem due to the sanitizer can modify the signed document unrestrictedly. Therefore, a flexible sanitizable signature scheme based on bilinear mapping will be proposed in this paper. According to our security analysis, this proposed scheme is not only to keep the security requirement of sanitizable signature but also improve the disadvantage of related schemes.

Traditional layout migration focuses on area minimization, thus suffered wire distortion, which caused loss of layout topology. A migrated layout inheriting original topology owns original design intention and predictable property, such as wire length which determines the path delay importantly. This work presents a new rectangular topological layout to preserve layout topology and combine its flexibility of handling wires with traditional scan-line based compaction algorithm for area minimization. The proposed migration flow contains devices and wires extraction, topological layout construction, unidirectional compression combining scan-line algorithm with collinear equation solver, and wire restoration. Experimental results show that cell topology is well preserved, and a several times runtime speedup is achieved as compared with recent migration research based on ILP (integer linear programming) formulation.

Obstacle-avoiding rectilinear Steiner tree (OARST) construction is a fundamental problem associated with the trend toward IP-block-based System-on-Chip designs. The objective of previous studies on obstacle-avoiding rectilinear Steiner minimal tree (OARSMT) has been to minimize the total wirelength of the constructed Steiner tree. Studies of performance-driven Steiner trees have demonstrated that the minimization of wirelength may worsen the performance of the Steiner tree. This work is the first to construct OARST while considering the Elmore delay. A critical-trunk-based tree growth mechanism is proposed. The critical trunks are constructed by extended single-source single-target maze routing called multi-source single-target maze routing. The unconnected pins are connected to critical trunks under the delay constraints of every sink. The proposed critical trunk can be applied to solve performance-driven and slack-driven OARST problems. Experimental results demonstrate that the proposed algorithms achieve an average 24.12% improvement in the maximum delay over OARSMT in performance-driven OARST problem and successfully solve 66.67% worst negative slack (WNS) violations in slack-driven OARST problem while running faster than previous OARSMT algorithms.

With rapid developments in science and technology, we now see the ubiquitous use of different types of safety-critical systems in our daily lives such as in avionics, consumer electronics, and medical systems. In such systems, unintentional design faults might result in injury or even death to human beings. To make sure that safety-critical systems are really safe, there is a need to verify them formally. However, the verification of such systems is getting more and more difficult because designs are becoming very complex. To cope with high design complexity, currently, model-driven architecture design is becoming a well-accepted trend. However, existing methods of testing and standards conformance are restricted to implementation code, so they do not fit very well with model-based approaches. To bridge this gap, we propose a model-based formal verification technique for safety-critical systems. In this work, the model-checking paradigm is applied to the Safecharts model, which was used for modeling but not yet used for verification. Our contributions listed are as follows: first, the safety constraints in Safecharts are mapped to semantic equivalents in timed automata for verification. Second, the theory for safety constraint verification is proven and implemented in a compositional model checker (that is, the state-graph manipulator (SGM)). Third, prioritized and urgent transitions are implemented in SGM to model the risk semantics in Safecharts. Finally, it is shown that the priority-based approach to mutual exclusion of resource usage in the original Safecharts is unsafe and corresponding solutions are proposed. Application examples show the feasibility and benefits of the proposed model-driven verification of safety-critical systems