The performance of devices based on two dimensional (2D) materials is significantly affected upon prolonged exposure to atmosphere. We analyzed time based environmental degradation of electrical properties of HfS2 field effect transistors. Atmospheric entities like oxygen and moisture adversely affect the device surface and reduction in drain current is observed over period of 48 hours. Two corrective measures, namely, PMMA passivation and vacuum annealing, have been studied to address the diminution of current by contaminants. PMMA passivation prevents the device from environment and reduces the effect of Coulomb scattering. Improvement in current characteristics signifies the importance of dielectric passivation for 2D materials. On the other hand, vacuum annealing is useful in removing contaminants from the affected surface. In order to figure out optimum process conditions, properties have been studied at various annealing temperatures. The improvement in drain current level was observed upon vacuum annealing within optimum range of annealing temperature.

In this paper, we propose a novel placement algorithm for mixed-grained reconfigurable architectures (MGRAs). MGRA consists of coarse-grained and fine-grained clusters, in order to implement a combined digital systems of high-speed data paths with multi-bit operands and random logic circuits for state machines and bit-wise operations. For accelerating simulated annealing based FPGA placement algorithm, range limiter has been proposed to control the distance of two blocks to be interchanged. However, it is not applicable to MGRAs due to the heterogeneous structure of MGRAs. Proposed range limiter using connection bounding box effectively keeps the size of range limiter to encourage moves across fine-grain blocks in non-adjacent clusters. From experimental results, the proposed method achieved 47.8% reduction of cost in the best case compared with conventional methods.

This paper proposes a Bayesian approach to image recognition based on separable lattice hidden Markov models (SL-HMMs). The geometric variations of the object to be recognized, e.g., size, location, and rotation, are an essential problem in image recognition. SL-HMMs, which have been proposed to reduce the effect of geometric variations, can perform elastic matching both horizontally and vertically. This makes it possible to model not only invariances to the size and location of the object but also nonlinear warping in both dimensions. The maximum likelihood (ML) method has been used in training SL-HMMs. However, in some image recognition tasks, it is difficult to acquire sufficient training data, and the ML method suffers from the over-fitting problem when there is insufficient training data. This study aims to accurately estimate SL-HMMs using the maximum a posteriori (MAP) and variational Bayesian (VB) methods. The MAP and VB methods can utilize prior distributions representing useful prior information, and the VB method is expected to obtain high generalization ability by marginalization of model parameters. Furthermore, to overcome the local maximum problem in the MAP and VB methods, the deterministic annealing expectation maximization algorithm is applied for training SL-HMMs. Face recognition experiments performed on the XM2VTS database indicated that the proposed method offers significantly improved image recognition performance. Additionally, comparative experiment results showed that the proposed method was more robust to geometric variations than convolutional neural networks.

An application of laser annealing process, which is used to form the P-type Base junction for high-performance low-voltage power MOSFETs (Metal Oxide Semiconductor Field Effect Transistors), is proposed. An equivalent shallow-junction structure for P-Base junction with uniform impurity distribution is achieved by adopting green laser annealing of pulsed mode. Higher impurity activation for the shallow junction has been achieved by the laser annealing of melted phase than by conventional RTA (Rapid Thermal Annealing) of solid phase. The application of the laser annealing technology in the fabrication process of Low-Voltage U-MOSFET is also examined.

An application of laser annealing process, which is used to form the shallow P-type Base junction for 20-V planar power MOSFETs (Metal Oxide Semiconductor Field Effect Transistors) is proposed. We demonstrated that the fabricated devices integrated with laser annealing process have superior electrical characteristics than those fabricated according to the standard process. Moreover, the threshold voltage variation of the devices applied by the new annealing process is effectively suppressed. This is due to that a uniform impurity distribution at the channel region is achieved by adopting laser annealing. Laser annealing technology can be applied as a reliable, effective, and advantageous process for the low-voltage power MOSFETs.

Homemade cooking plays a key role for a healthy and cost-efficient life. Unfortunately, preparing multiple dishes is generally time-consuming. In this paper, an algorithm is proposed to minimize the cooking time by scheduling the cooking-step of multiple dishes. The cooking procedure of a dish is divided into a sequence of six types of cooking-steps to consider the constraints in cooks and cooking utensils in a kitchen. A cooking model is presented to optimize the cooking-step schedule and estimate the cooking time for a given starting order of dishes under various constraints of cooks and utensils. Then, a high-quality schedule is sought by repeating the generation of a new order and the model application based on exhaustive search and simulated annealing. Our simulation results and cooking experiments confirm the effectiveness of our proposal.

The combination of a halogen-free solvent 1,2,4-trimethylbenzene and unmodified fullerene potentially provides a way to develop environmentally-friendly and cost-effective solution-processed organic photocells. In this paper, the thermal annealing effect on the optical absorption spectra in poly(3-hexylthiophene):unmodified-C$_{60}$ composites with various compositions is reported. It is found that the onset temperature of the absorption spectrum change is higher in the composites with higher fullerene content. It is speculated that strong interaction between the polymer main chain and C$_{60}$ tends to suppress the reorientation of polymer main chains in a composite with high C$_{60}$ content.

While Triple modular Redundancy (TMR) is effective in eliminating soft errors in LSIs, the overhead of the triplicated area as well as the triplicated energy consumption is the problem. In addition to the spatial TMR mode where executions are simply tripricated and the majority is taken, the temporal TMR mode is available where only two copies of an operation are executed and the results are compared, then if the results differ, the third copy is executed to get the correct result. Appropriately selecting the power supply voltage is also an effective technique to reduce the energy consumption. In this paper, a method to derive a TMR design is proposed which selects the TMR mode and supply voltage for each operation to minimize the energy consumption within the time and area constraints.

Recently, radar resource management of multifunction radar is a challenging issue in electronically scanned array radar technology. This paper deals with radar beam scheduling, which is a core issue of radar resource management. This paper proposed stochastic scheduler algorithm using Simulated Annealing (SA) and Hybrid scheduler algorithm which automatically selects two different types of schedulers according to the radar load: Rule based scheduler using modified Butler algorithm for underload situations and SA based scheduler for overload situations. The proposed algorithms are evaluated in terms of scheduling latency, the number of scheduled tasks, and time complexity. The simulation results show that the performance of rule based scheduler is seriously degraded in overload situation. However, SA based scheduler and Hybrid scheduler have graceful performance degradation in overload situation. Compared with rule based scheduler, SA based scheduler and Hybrid scheduler can schedule many more tasks on time for the same operation duration in the overload situation. Even though their time complex is relatively high, it can be applied to real applications if the parameters are properly controlled. Especially, Hybrid scheduler has an advantage of low time complexity with good performance.

With the phenomenal explosion in online services, social networks are becoming an emerging ubiquitous platform for numerous services where service consumers require the selection of trustworthy service providers before invoking services with the help of other intermediate participants. Under this circumstance, evaluation of the trustworthiness of the service provider along the social trust paths from the service consumer to the service provider is required and to this end, selection of the optimal social trust path (OSTP) that can yield the most trustworthy evaluation result is a pre-requisite. OSTP selection with multiple quality of trust (QoT) constraints has been proven to be NP-Complete. Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem. However, existing solutions cannot guarantee the search efficiency, that is, they have difficulty in avoiding suboptimal solutions during the search process. Quantum annealing uses delocalization and tunneling to avoid local minima without sacrificing execution time. Several recent studies have proven that it is a promising way to tackle many optimization problems. In this paper, we propose a novel quantum annealing based OSTP selection algorithm (QA_OSTP) for large-scale complex social networks. Experiments show that QA_OSTP has better performance than its heuristic counterparts.

We propose a novel IDDQ outlier screening flow through a two-phase approach: a clustering-based filtering and an estimation-based current-threshold determination. In the proposed flow, a clustering technique first filters out chips that have high IDDQ current. Then, in the current-threshold determination phase, device-parameters of the unfiltered chips are estimated based on measured IDDQ currents through Bayesian inference. The estimated device-parameters will further be used to determine a statistical leakage current distribution for each test pattern and to calculate a and suitable current-threshold. Numerical experiments using a virtual wafer show that our proposed technique is 14 times more accurate than the neighbor nearest residual (NNR) method and can achieve 80% of the test escape in the case of small leakage faults whose ratios of leakage fault sizes to the nominal IDDQ current are above 40%.

Excimer laser annealing at 308nm in UV and semiconductor blue laser-diode annealing at 445nm were performed and compared in term of the crystallization depending on electrical properties of Si films. As a result for the thin Si films of 50nm thickness, both lasers are very effective to enlarge the grain size and to activate electrically the dopant atoms in the CVD Si film. Smooth Si surface can be obtained using blue-laser annealing of scanned CW mode. By improving the film quality of amorphous Si deposited by sputtering for subsequent crystallization, both laser annealing techniques are effective for LTPS applications not only on conventional glass but also on flexible sheet. By conducting the latter advanced annealing technique, small grain size as well as large grains can be controlled. As blue laser is effective to crystallize even rather thicker Si films of 1µm, high performance thin-film photo-sensor or photo-voltaic applications are also expected.

Application-level routing that chooses an end-to-end traffic route that relays other end hosts can improve user-perceived performance metrics such as end-to-end latency and available bandwidth. However, selfish route selection performed by each end user can lead to a decrease in path performance due to overload by route overlaps, as well as an increase in the inter-ISP transit cost as a result of utilizing more transit links compared with native IP routing. In this paper, we first strictly define an optimization problem for selecting application-level traffic routes with the aim of maximizing end-to-end network performance under a transit cost constraint. We then propose an application-level traffic routing method based on distributed simulated annealing to obtain good solutions to the problem. We evaluate the performance of the proposed method by assuming that PlanetLab nodes utilize application-level traffic routing. We show that the proposed routing method can result in considerable improvement of network performance without increasing transit cost. In particular, when using end-to-end latency as a routing metric, the number of overloaded end-to-end paths can be reduced by about 65%, as compared with that when using non-coordinated methods. We also demonstrate that the proposed method can react to dynamic changes in traffic demand and select appropriate routes.

This paper proposes an acoustic modeling technique based on Bayesian framework using multiple model structures for speech recognition. The aim of the Bayesian approach is to obtain good prediction of observation by marginalizing all variables related to generative processes. Although the effectiveness of marginalizing model parameters was recently reported in speech recognition, most of these systems use only “one” model structure, e.g., topologies of HMMs, the number of states and mixtures, types of state output distributions, and parameter tying structures. However, it is insufficient to represent a true model distribution, because a family of such models usually does not include a true distribution in most practical cases. One of solutions of this problem is to use multiple model structures. Although several approaches using multiple model structures have already been proposed, the consistent integration of multiple model structures based on the Bayesian approach has not seen in speech recognition. This paper focuses on integrating multiple phonetic decision trees based on the Bayesian framework in HMM based acoustic modeling. The proposed method is derived from a new marginal likelihood function which includes the model structures as a latent variable in addition to HMM state sequences and model parameters, and the posterior distributions of these latent variables are obtained using the variational Bayesian method. Furthermore, to improve the optimization algorithm, the deterministic annealing EM (DAEM) algorithm is applied to the training process. The proposed method effectively utilizes multiple model structures, especially in the early stage of training and this leads to better predictive distributions and improvement of recognition performance.

This paper proposes a novel method to determine a priority for applying selective triple modular redundancy (selective TMR) against single event upset (SEU) to achieve cost-effective reliable implementation of application circuits onto coarse-grained reconfigurable architectures (CGRAs). The priority is determined by an estimation of the vulnerability of each node in the data flow graph (DFG) of the application circuit. The estimation is based on a weighted sum of the node parameters which characterize impact of the SEU in the node on the output data. This method does not require time-consuming placement-and-routing processes, as well as extensive fault simulations for various triplicating patterns, which allows us to identify the set of nodes to be triplicated for minimizing the vulnerability under given area constraint at the early stage of design flow. Therefore, the proposed method enables us efficient design space exploration of reliability-oriented CGRAs and their applications.

A carbonaceous thin film was deposited on a tungsten single emitter by electrolysis of liquid methanol. The carbonaceous single emitter was thermally treated under vacuum conditions, and changes in its field emission characteristics were examined. The field emission characteristics obeyed the Fowler–Nordheim relationship for all annealing temperatures. The turn-on voltage decreased from 1640 V to 790 V with annealing up to 1373 K.

Resistive switching of metal-insulator-metal (MIM), consisting of a metal-organic chemical vapour deposition (MOCVD) TiO2 layer sandwiched between Pt electrodes, has been measured systematically before and after thermal annealing in different ambiences. With H2 annealing at 400, the current level in the high-resistive state (HRS) significantly decreased while little change in the low-resistive state (LRS) was observed. As a result, the switching ratio over 7 orders of magnitude at the current level was obtained. From the analysis of current-voltage (I-V) characteristics in HRS and LRS, we found that the LRS was characterized with an ohmic conduction, while in the HRS after H2 annealing, charge trapping became significant as a result of a significant decrease in the current level. In a separate experiment, a partial reduction in TiO2 was detected using high-resolution X-ray photoelectron spectroscopy (XPS) after resistant-state switching from HRS to LRS by using a Hg probe as a top electrode, which is associated with filament formation.

Effects of atomic hydrogen annealing (AHA) on the film properties and the electrical characteristics of pentacene organic thin-film transistors (OTFTs) are investigated. The surface energy of SiO2 surface and grain size of pentacene film were decreased with increasing AHA treatment time. For the treatment time of 300 s, pentacene film showed the (00l) and (011') orientation and high carrier mobility in spite of small crystal grain.

Crystallization of amorphous silicon on oxide semiconductors using rapid-thermal annealing in vacuum is investigated. A 30 nm n-type amorphous silicon (a-Si) is deposited on zinc-oxide (ZnO) and aluminum doped zinc-oxide (ZnO:Al) by PECVD on glass substrate. Rapid-thermal annealing for 30 min to 180 min of a-Si on ZnO and ZnO:Al were performed at 600. It is found that crystallization of a-Si on oxide semiconductors can be done in shorter time than that of standard solid-phase crystallization (SPC) of amorphous silicon on glass substrate at 600. It has been verified using Raman spectroscopy that a-Si on ZnO:Al changes into polycrystalline silicon (poly-Si) in 30 min at 600.

Finding a kernel mapping function for support vector machines (SVMs) is a key step towards construction of a high-performanced SVM-based classifier. While some recent methods exploited an evolutional approach to construct a suitable multifunction kernel, most of them searched randomly and diversely. In this paper, the concept of a family of identical-structured kernel trees is proposed to enable exploration of structure space using genetic programming whereas to pursue investigation of parameter space on a certain tree using evolution strategy. To control balance between structure and parameter search towards an optimal kernel, simulated annealing is introduced. By experiments on a number of benchmark datasets in the UCI and text classification collection, the proposed method is shown to be able to find a better optimal solution than other search methods, including grid search and gradient search.