Clock drawing test digit recognition using static and dynamic features

The clock drawing test (CDT) is a standard neurological test for detection of cognitive impairment. A computerised version of the test promises to improve the accessibility of the test in addition to obtaining more detailed data about the subject's performance. Automatic handwriting recognition is one of the first stages in the analysis of the computerised test, which produces a set of recognized digits and symbols together with their positions on the clock face. Subsequently, these are used in the test scoring. This is a challenging problem because the average CDT taker has a high likelihood of cognitive impairment, and writing is one of the first functional activities to be affected. Current handwritten digit recognition system perform less well on this kind of data due to its unintelligibility. In this paper, a new system for numeral handwriting recognition in the CDT is proposed. The system is based on two complementary sources of data, namely static and dynamic features extracted from handwritten data. The main novelty of this paper is the new handwriting digit recognition system, which combines two classifiers—fuzzy k-nearest neighbour for dynamic stroke-based features and convolutional neural network for static image- based features, which can take advantage of both static and dynamic data. The proposed digit recognition system is tested on two sets of data: first, Pendigits online handwriting digits; and second, digits from the actual CDTs. The latter data set came from 65 drawings made by healthy people and 100 drawings reproduced from the drawings by dementia patients. The test on both data sets shows that the proposed combination system can outperform each classifier individually in terms of recognition accuracy, especially when assessing the handwriting of people with dementi

An investigation of the mechanical properties of metallic lattice structures fabricated using selective laser melting

Metallic lattice structures manufactured using selective laser melting are widely used in fields such as aerospace and automobile industries in order to save material and reduce energy consumption. An essential element of metallic lattice structures design is determining their mechanical behaviors under loading conditions. Theoretical method based on beam theory has been proposed for evaluating the behaviors of the commonly used body-centered cubic lattice structures. However, it is difficult to predict theoretically the properties of the uniaxially reinforced lattice structures based on the body-centered cubic structures. Since the reinforced structures have superior strength to weight ratio and are deemed promising in lightweight-design applications, this article proposed a force-method-based theoretical method to calculate the mechanical properties of the body-centered cubic structure and its two types of uniaxially reinforced structures fabricated via selective laser melting. The finite element analysis and compression experiment study of selective laser melting samples made using Ti6Al4V powders demonstrated the validity of the proposed analytical method

Routing protocol for heterogeneous wireless mesh networks

The introduction of heterogeneous wireless mesh technologies provides an opportunity for higher network capacity, wider coverage, and higher quality of service (QoS). Each wireless device utilizes different standards, data formats,protocols, and access technologies. However, the diversity andcomplexity of such technologies create challenges for traditionalcontrol and management systems. This paper proposes aheterogeneous metropolitan area network architecture thatcombines an IEEE 802.11 wireless mesh network with a long-term evolution (LTE) network. In addition, a new heterogeneous routing protocol and a routing algorithm based on reinforcement learning called Cognitive Heterogeneous Routing (CHR) are proposed to select the appropriate transmission technology based on parameters from each network. The proposed heterogeneous network overcomes the problems of sending packets over long paths, island nodes and interference in wireless mesh network and increases the overall capacity of the combined network by utilizing unlicensed frequency bands instead of buying more license frequency bands for LTE. The work is validated through extensive simulations that indicate that the proposed heterogeneous wireless mesh network outperforms the LTE and Wi-Fi networks when used individually. The simulation results show that the proposed network achieves an increase of up to 200% increase in throughput compared with Wi-Fi-only networks or LTE-only networks