An Output-Recurrent-Neural-Network-Based Iterative Learning Control for Unknown Nonlinear Dynamic Plants

We present a design method for iterative learning control system by using an output recurrent neural network (ORNN). Two ORNNs are employed to design the learning control structure. The first ORNN, which is called the output recurrent neural controller (ORNC), is used as an iterative learning controller to achieve the learning control objective. To guarantee the convergence of learning error, some information of plant sensitivity is required to design a suitable adaptive law for the ORNC. Hence, a second ORNN, which is called the output recurrent neural identifier (ORNI), is used as an identifier to provide the required information. All the weights of ORNC and ORNI will be tuned during the control iteration and identification process, respectively, in order to achieve a desired learning performance. The adaptive laws for the weights of ORNC and ORNI and the analysis of learning performances are determined via a Lyapunov like analysis. It is shown that the identification error will asymptotically converge to zero and repetitive output tracking error will asymptotically converge to zero except the initial resetting error

Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation

While representation learning aims to derive interpretable features for describing visual data, representation disentanglement further results in such features so that particular image attributes can be identified and manipulated. However, one cannot easily address this task without observing ground truth annotation for the training data. To address this problem, we propose a novel deep learning model of Cross-Domain Representation Disentangler (CDRD). By observing fully annotated source-domain data and unlabeled target-domain data of interest, our model bridges the information across data domains and transfers the attribute information accordingly. Thus, cross-domain joint feature disentanglement and adaptation can be jointly performed. In the experiments, we provide qualitative results to verify our disentanglement capability. Moreover, we further confirm that our model can be applied for solving classification tasks of unsupervised domain adaptation, and performs favorably against state-of-the-art image disentanglement and translation methods.Comment: CVPR 2018 Spotligh

What’s Cooking? – Cognitive Training of Executive Function in the Elderly

Executive function involves the efficient and adaptive engagement of the control processes of updating, shifting, and inhibition (Miyake, 2000) to guide behavior toward a goal. It is associated with decrements in many other cognitive functions due to aging (West, 1996; Raz, 2000) with itself particularly vulnerable to the effect of aging (Treitz et al., 2007). Cognitive training in the form of structural experience with executive coordination demands exhibited effective enhancement in the elderly (Hertzog et al., 2008). The current study was thus aimed at the development and evaluation of a training regime for executive function in the elderly. The breakfast cooking task of Craik and Bialystok (2006) was adapted into a multitasking training task in a session (pre-test vs. post-test) by group (control vs. training). In the training condition, participants constantly switched, updated, and planned in order to control the cooking of several foods and concurrently performed a table setting secondary task. Training gains were exhibited on task related measures. Transfer effect was selectively observed on the letter–number sequencing and digit symbol coding test. The cooking training produced short term increase in the efficiency of executive control processing. These effects were interpreted in terms of the process overlap between the training and the transfer tasks

The International Decision-Making and Travel Behavior of Graduates Participating in Working Holiday

After graduation, most graduates find themselves at a significant stage in their life as they have to decide between “further study” and “working.” When faced with this confusion and uncertainty, a “working holiday” combining travel and work has coincidentally becomes a third option. This study employed a qualitative approach through literature review, in-depth interviews, and semi-structured interviews. The research revealed that graduates are influenced by “internal personal thinking” and “external driving forces” when they embark on a working holiday. The former includes negative obstructions and positive stimulus. The latter factor’s stimulus includes attraction of natural landscapes, history and culture, learning foreign languages, safety concerns, difficulties in visa application, and the opportunity to obtain a salaried job. The process of embarking on a working holiday was complex and unpredictable. The traveling behavior of working holiday destinations included short-distance leisure behavior and long-distance traveling behavior. In terms of the influences of short-distance leisure behavior, graduates preferred being employed by service industries that had less working hours, flexible work arrangements and included the purchase of preferential price tickets. Graduates’ long-distance traveling behavior was affected by the work they performed. The travel time was different between various industries

Tension Pneumoperitoneum Following Upper Gastrointestinal Endoscopy

Tension pneumoperitoneum is a potentially lethal complication of numerous iatrogenic procedures, including upper gastrointestinal (UGI) endoscopy. We report a 69-year-old man with UGI bleeding who developed tension pneumoperitoneum and cardiac arrest after UGI endoscopy. He was successfully resuscitated with needle decompression. Emergency surgery revealed a perforated gastric ulcer, and subtotal gastrectomy with Billroth II anastomosis was performed. Recovery was smooth and he was discharged from the hospital 18 days later. Tension pneumoperitoneum should be suspected in all patients who develop circulatory collapse with acutely distended abdomen after UGI endoscopy. Early identification relies on a high index of suspicion. Prompt treatment with needle decompression should not be delayed for confirmatory radiography once the clinical diagnosis is made

Kinematic analysis of the Pakuashan fault tip fold, west central Taiwan: Shortening rate and age of folding inception

The Pakuashan anticline is an active fault tip fold that constitutes the frontal most zone of deformation along the western piedmont of the Taiwan Range. Assessing seismic hazards associated with this fold and its contribution to crustal shortening across central Taiwan requires some understanding of the fold structure and growth rate. To address this, we surveyed the geometry of several deformed strata and geomorphic surfaces, which recorded different cumulative amounts of shortening. These units were dated to ages ranging from ~19 ka to ~340 ka using optically stimulated luminescence (OSL). We collected shallow seismic profiles and used previously published seismic profiles to constrain the deep structure of the fold. These data show that the anticline has formed as a result of pure shear with subsequent limb rotation. The cumulative shortening along the direction of tectonic transport is estimated to be 1010 ± 160 m. An analytical fold model derived from a sandbox experiment is used to model growth strata. This yields a shortening rate of 16.3 ± 4.1 mm/yr and constrains the time of initiation of deformation to 62.2 ± 9.6 ka. In addition, the kinematic model of Pakuashan is used to assess how uplift, sedimentation, and erosion have sculpted the present-day fold topography and morphology. The fold model, applied here for the first time on a natural example, appears promising in determining the kinematics of fault tip folds in similar contexts and therefore in assessing seismic hazards associated with blind thrust faults

An Output-Recurrent-Neural-Network-Based Iterative Learning Control for Unknown Nonlinear Dynamic Plants

We present a design method for iterative learning control system by using an output recurrent neural network (ORNN). Two ORNNs are employed to design the learning control structure. The first ORNN, which is called the output recurrent neural controller (ORNC), is used as an iterative learning controller to achieve the learning control objective. To guarantee the convergence of learning error, some information of plant sensitivity is required to design a suitable adaptive law for the ORNC. Hence, a second ORNN, which is called the output recurrent neural identifier (ORNI), is used as an identifier to provide the required information. All the weights of ORNC and ORNI will be tuned during the control iteration and identification process, respectively, in order to achieve a desired learning performance. The adaptive laws for the weights of ORNC and ORNI and the analysis of learning performances are determined via a Lyapunov like analysis. It is shown that the identification error will asymptotically converge to zero and repetitive output tracking error will asymptotically converge to zero except the initial resetting error

Seismic Anisotropy of the Upper Crust in the Mountain Ranges of Taiwan from the TAIGER Explosion Experiment

Taiwan is known as a strongly anisotropic region observed from SKS 1 - 2 s delay time and other teleseismic phases. An estimate of the crustal contribution to the total anisotropy from the foliated Central Range is essential to understanding the overall teleseismic results. We used P wave arrivals from the dense seismic arrays deployed during the TAIGER active source experiments and the permanent broadband seismic stations to determine the crustal anisotropy. From the arrival time analysis as a function of azimuth, we detected a clear cos(2£c) pattern. The strength of the crustal anisotropy (0 - 15 km depth) reaches 8 - 10% and the fast direction azimuth is around 35 - 43¢X for the overall mountain ranges. The anisotropic variations from the central to the north are found in detail. The results could indicate that the upper crustal delay time contribution of teleseismic shear waves reaches up to 0.45 s. The geological data at the surface and geophysical observations imply a coherent deformation from the surface to the lower crust or even down to the upper mantle