Stability of time-varying systems in the absence of strict Lyapunov functions

When a non-linear system has a strict Lyapunov function, its stability can be studied using standard tools from Lyapunov stability theory. What happens when the strict condition fails? This paper provides an answer to that question using a formulation that does not make use of the specific structure of the system model. This formulation is then applied to the study of the asymptotic stability of some classes of linear and non-linear time-varying systems.Peer ReviewedPostprint (author's final draft

Seismic Analysis and Design of Hospital Building by Equivalent Static Analysis

Structural design is the primary aspect of civil engineering. The foremost basic in structural engineering is the design of simple basic components and members of building viz., slabs, beams, columns and footings. The first step in any design is to decide the plan of the particular building. The location of beams and columns are decided. Then the vertical loads like dead and live loads are calculated. Once the loads are obtained, the component which takes the load first i.e. the slabs can be designed. From the slabs, the loads are transferred to the beams. The loads coming from the slabs onto the beam may be trapezoidal or triangular. Depending on this, the beam may be designed. The loads (mainly shear) from the beams are then transferred to the columns. For designing columns, it is necessary to know the moments they are subjected to. For this purpose, frame analysis is done by Moment Distribution Method. Most of the columns designed in this project were considered to be axially loaded with uniaxial bending. Finally, the footings are designed based on the loading from the column and also the soil bearing capacity value for that particular area. All component parts are checked for strength and stability. The building was initially designed as per IS 456: 2000 without considering earthquake loads using STAAD.pro software. Then the building was analyzed for earthquake loads as per Equivalent static analysis method and after obtaining the base shear as per IS1893: 2002, again detailing has been obtained using ETABs

アフガニスタンにおける気候変動が旱魃深刻度、水資源持続可能性、農業の潜在的可能性に及ぼす影響の統合的評価

Tohoku University博士（学術）要約のみthesi

Spatio temporal pattern in the changes in availability and sustainability of water resources in Afghanistan

Water is gradually becoming scarce in Afghanistan like in many other regions of the globe. The objective of this study was to evaluate the spatial changes in the availability and sustainability of water resources in Afghanistan. The Terrestrial Water Storage (TWS) data of the Gravity Recovery and Climate Experiment (GRACE) satellite obtained from three different institutes, having 1° × 1° spatial resolutions for the period 2002–2016 was used for this purpose. Sen’s slope method was used to assess the rate of change, and the Modified Mann–Kendall test was used for the evaluation of the significance of trends in TWS. After, the concept of reliability–resiliency–vulnerability (RRV) was used for assessing the spatial distribution of sustainability in water resources. The results revealed a significant decrease in water availability in the country over the last 15 years. The decrease was found to be highest in the central region where most of the population of the country resides. The reliability in water resources was found high in the northeast Himalayan region and low in the southwest desert; resilience was found low in the central region, while vulnerability was found high in the south and the southeast. Overall, the water resources of the country were found most sustainable in the northeast and southwest and least in the south and the central parts. The maps of water resource sustainability and the changes in water availability produced in the present study can be used for long-term planning of water resources for adaptation to global changes. Besides, those can be used for the management of water resources in a sustainable and judicious manner

アフガニスタンにおける気候変動が旱魃深刻度、水資源持続可能性、農業の潜在的可能性に及ぼす影響の統合的評価

othe

Recognition, Analysis, and Assessments of Human Skills using Wearable Sensors

One of the biggest social issues in mature societies such as Europe and Japan is the aging population and declining birth rate. These societies have a serious problem with the retirement of the expert workers, doctors, and engineers etc. Especially in the sectors that require long time to make experts in fields like medicine and industry; the retirement and injuries of the experts, is a serious problem. The technology to support the training and assessment of skilled workers (like doctors, manufacturing workers) is strongly required for the society. Although there are some solutions for this problem, most of them are video-based which violates the privacy of the subjects. Furthermore, they are not easy to deploy due to the need for large training data. This thesis provides a novel framework to recognize, analyze, and assess human skills with minimum customization cost. The presented framework tackles this problem in two different domains, industrial setup and medical operations of catheter-based cardiovascular interventions (CBCVI). In particular, the contributions of this thesis are four-fold. First, it proposes an easy-to-deploy framework for human activity recognition based on zero-shot learning approach, which is based on learning basic actions and objects. The model recognizes unseen activities by combinations of basic actions learned in a preliminary way and involved objects. Therefore, it is completely configurable by the user and can be used to detect completely new activities. Second, a novel gaze-estimation model for attention driven object detection task is presented. The key features of the model are: (i) usage of the deformable convolutional layers to better incorporate spatial dependencies of different shapes of objects and backgrounds, (ii) formulation of the gaze-estimation problem in two different way, as a classification as well as a regression problem. We combine both formulations using a joint loss that incorporates both the cross-entropy as well as the mean-squared error in order to train our model. This enhanced the accuracy of the model from 6.8 by using only the cross-entropy loss to 6.4 for the joint loss. The third contribution of this thesis targets the area of quantification of quality of i actions using wearable sensor. To address the variety of scenarios, we have targeted two possibilities: a) both expert and novice data is available , b) only expert data is available, a quite common case in safety critical scenarios. Both of the developed methods from these scenarios are deep learning based. In the first one, we use autoencoders with OneClass SVM, and in the second one we use the Siamese Networks. These methods allow us to encode the expert’s expertise and to learn the differences between novice and expert workers. This enables quantification of the performance of the novice in comparison to the expert worker. The fourth contribution, explicitly targets medical practitioners and provides a methodology for novel gaze-based temporal spatial analysis of CBCVI data. The developed methodology allows continuous registration and analysis of gaze data for analysis of the visual X-ray image processing (XRIP) strategies of expert operators in live-cases scenarios and may assist in transferring experts’ reading skills to novices