Workers' compensation for non-fatal accidents: review of Hong Kong court cases

Hong Kong is notorious for her high construction accidents rates. Although the accidents rate has dropped from 350 per 1000 workers in mid 1980 to 60 per 1000 workers in 2007, it still accounted for nearly one-fifth of all the industrial accidents in Hong Kong. Contractors were economically pressed and battered by exorbitant compensation over the years. This paper presents a comprehensive study of non-fatal accidents compensation court cases from 2004 to 2008. Although approximately one-third of the cases with injured persons aged between 47 and 56, the percentage of court cases over construction employees by age group was highest in age group 17-26. In terms of trade of workers, General laborers/causal workers stood the highest, then came electrical technicians and painters/decorators/plasterers. The highest rates of injury were falling from height and hitting by falling objects. Increasing from HK$10,997,637 in 2004, the total compensation reached the peak of HK$39,643,353 in 2006. The heaviest compensation was HK$13,800,000 among 101 cases. Most of the victims were compensated under loss of earnings and Pain Suffering and Loss of Amenities. While general labourers marked the highest number of cases, less than one-fourth of them were awarded compensation which exceeded HK$1,500,000. Four out of seven steel benders who filed court cases, however, received compensation greater than HK$1.5 million for each case. Those who were struck by objects had relatively the highest chance to be compensated with a huge sum of money.published_or_final_versio

Performance of turbo codes with fading compensation in multipath channels

This paper studies the performance of turbo-coded system in the frequency non-selective correlated Rayleigh fading channels. The turbo-coded system employs a pilot-symbol-aided (PSA) technique for fading compensation and interleaving for spreading the error bursts to reduce the error rate. The PSA technique is also used to provide the decoder with channel side information (CSI) for better performance in fading channel. Two PSA techniques, three normalized Doppler spreads and different interleaving sizes have been investigated. Results of computer simulations have shown that, an improved first-order fading prediction technique can improve the BER performance by a factor of about 62, relative to those obtained using the pilot symbols only. Results have also shown that an interleaving depth equal to one-quarter the reciprocal of normalized Doppler spread can achieve a good BER performance.published_or_final_versionThe IEEE 49th Vehicular Technology Conference (IEEE-VTS 1999), Houston, TX., 16-20 May 1999. In IEEE-VTS Vehicular Technology Conference Proceedings, 1999, v. 3, p. 2413-241

A new approach to applying discrete sliding mode control to 2D systems

Sliding mode control has been applied previously to a specific form of 2D systems (Roesser model). In this paper a new approach (ID vectorial form) is introduced for this problem. Using ID form to represent 2D systems can be used as an alternative strategy to reduce the inherent complexity of 2D systems and their applications. Unlike Wave Advanced Model (WAM) form (proposed by Porter and Aravena), the suggested ID vectorial form, in this paper, has invariable dimension and consequently can be converted to regular form for sliding mode control (SMC). In this paper, the first Fornasini and Marchesini (FM) model of 2D systems which is a second order recursive form is considered. Meantime, the suggested method can be simply deployed to other first or second order 2D models. ©2013 IEEE

Sliding mode stabilisation of networked systems with consecutive data packet dropouts using only accessible information

© 2016 Informa UK Limited, trading as Taylor & Francis Group. This paper develops a novel stabilising sliding mode for systems involving uncertainties as well as measurement data packet dropouts. In contrast to the existing literature that designs the switching function by using unavailable system states, a novel linear sliding function is constructed by employing only the available communicated system states for the systems involving measurement packet losses. This also equips us with the possibility to build a novel switching component for discrete-time sliding mode control (DSMC) by using only available system states. Finally, using a numerical example, we evaluate the performance of the designed DSMC for networked systems

Spectrum of topics for world congresses and other activities of the International Society for Physical and Rehabilitation Medicine (ISPRM) : a first proposal

Background: One of the objectives of the International Society for Physical and Rehabilitation Medicine is to improve the continuity of World Congresses. This requires the development of an abstract topic list for use in congress announcements and abstract submissions. Methods: An abstract topic list was developed on the basis of the definitions of human functioning and rehabilitation research, which define 5 main areas of research (biosciences in rehabilitation, biomedical rehabilitation sciences and engineering, clinical Physical and Rehabilitation Medicine (PRM) sciences, integrative rehabilitation sciences, and human functioning sciences). For the abstract topic list, these research areas were grouped according to the proposals of congress streams. In a second step, the first version of the list was systematically compared with the topics of the 2003 ISPRM World Congress. Results: The resulting comprehensive abstract topic list contains 5 chapters according to the definition of human functioning and rehabilitation research. Due to the high significance of clinical research, clinical PRM sciences were placed at the top of the list, comprising all relevant health conditions treated in PRM services. For congress announcements a short topic list was derived. Discussion: The ISPRM topic list is sustainable and covers a full range of topics. It may be useful for congresses and elsewhere in structuring research in PRM

Cyber attack protection and control in microgrids using channel code and semidefinite programming

© 2016 IEEE. The smart grid has been considered as a nextgeneration power system to modernize the traditional grid to improve its security, connectivity and sustainability. Unfortunately, the grid is susceptible to malicious cyber attacks, which can create serious technical, economical and control problems in power network operations. In contrast to the traditional cyber attack minimization techniques, this paper proposes a recursive systematic convolutional (RSC) code and Kalman filter based method in the context of microgrids. Specifically, the proposed RSC code is used to add redundancy in the microgrid states, and the log maximum a posterior is used to recover the state information which is affected by random noises and cyber attacks. Once the estimated states are obtained, a semidefinite programming based optimal feedback controller is proposed to regulate the system states. Test results show that the proposed approach can accurately mitigate the cyber attacks and properly estimate and control the system states

Microgrid state estimation and control using Kalman filter and semidefinite programming technique

The design of environment-friendly microgrids at the smart distribution level requires a stable behaviour for multiple state operations. This paper develops a Kalman filter based optimal feedback control method for the microgrid state estimation and stabilization. First, the microgrid is modelled by a discrete-time state space equation. Then the cost-effective smart sensors are deployed in order to obtain the required system information. From the communication point of view, the recursive systematic convolution code is adopted to add the redundancy in the system. At the end, the soft output Viterbi decoder is used to recover the system information from the noisy measurements and transmission uncertainties. Thereafter, the Kalman filter is utilized to estimate the system states, which acts as a precursor for applying the control algorithm. Finally, this paper proposes an optimal feedback control method to stabilize the microgrid based on semidefinite programming. The performance of the proposed approach is demonstrated by extensive numerical simulations

Distributed condition monitoring of renewable microgrids using adaptive-then-combine algorithm

© 2016 IEEE. This paper explores the problem of distributed state estimation including packet losses for the environment-friendly renewable microgrid incorporating electricity generating circuits. The problem is becoming critical due to the global warming, increasing green house gas emissions, and practical infeasibility with computational burden of the large-scale centralized power system monitoring. To address the impending problem, a novel distributed microgrid state estimation algorithm is derived in the context of microgrids. Specifically, after modelling the microgrid, this paper proposes a local microgrid state estimation algorithm considering packet losses. Then a novel optimal weighting factor calculation method for the global state estimation is proposed. Particularly, it can automatically adjust the optimal weighting factors for different sensor measurements based on the observation quality, improving the estimation accuracy of the global estimation. Simulations show that the desired state estimation accuracy is achievable

Distributed State Estimation over Unreliable Communication Networks with an Application to Smart Grids

© 2017 IEEE. In contrast to the traditional centralized power system state estimation methods, this paper investigates the interconnected optimal filtering problem for distributed dynamic state estimation considering packet losses. Specifically, the power system incorporating microgrids is modeled as a state-space linear equation where sensors are deployed to obtain measurements. Basically, the sensing information is transmitted to the energy management system through a lossy communication network where measurements are lost. This can seriously deteriorate the system monitoring performance and even lose network stability. Second, as the system states are unavailable, so the estimation is essential to know the overall operating conditions of the electricity network. Availability of the system states provides designers with an accurate picture of the power network, so a suitable control strategy can be applied to avoid massive blackouts due to losing network stability. Particularly, the proposed estimator is based on the mean squared error between the actual state and its estimate. To obtain the distributed estimation, the optimal local and neighboring gains are computed to reach a consensus estimation after exchanging their information with the neighboring estimators. Then, the convergence of the developed algorithm is theoretically proved. Afterward, a distributed controller is designed based on the semidefinite programming approach. Simulation results demonstrate the accuracy of the developed approaches under the condition of missing measurements

An Adaptive-Then-Combine Dynamic State Estimation Considering Renewable Generations in Smart Grids

© 1983-2012 IEEE. The penetration of renewable distributed energy resources, such as wind turbine, has been dramatically increased in distribution networks. Due to the intermittent property, the wind power generation patterns vary, which may risk distribution network operations. So, it is intrinsically necessary to monitor wind turbines in a distributed way. This paper presents an adaptive-Then-combine distributed dynamic approach for monitoring the grid under lossy communication links between the wind turbines and energy management system. First, the wind turbine is represented by a state-space linear model, with sensors deployed to obtain the system state information. Based on the mean squared error principle, an adaptive approach is proposed to estimate the local state information. The global estimation is designed by combining estimation results with weighting factors which are calculated by minimizing the estimation error covariance based on semidefinite programming. Finally, the convergence analysis indicates that the estimation error is gradually decreased, so the estimated state converges to the actual state. The efficacy of the developed approach is verified using the wind turbine and the IEEE 6-bus distribution system