Toward development of PreVoid alerting system for nocturnal enuresis patients: A fuzzy-based approach for determining the level of liquid encased in urinary bladder

Preventive and accurate assessment of bladder voiding dysfunctions necessitates measuring the amount of liquid encapsulated within urinary bladder walls in a non-invasive and real-time manner. The real-time monitoring of urine levels helps patients with urological disorders such as Nocturnal Enuresis (NE) by preventing the occurrence of enuresis via a pre-void stage alerting system. Although some advances have been achieved toward developing a non-invasive approach for determining the amount of accumulated urine inside the bladder, there is still a lack of an easy-to-implement technique which is suitable to embed in a wearable pre-warning device. This study aims to develop a machine-learning empowered technique to quantify to what extent an individual's bladder is filled by observing the filling-voiding pattern of a patient over a training period. In this experiment, a pulse-echo sonar element is used to generate ultrasound pulses while the probe surface is positioned perpendicular to the bladder's position. From the reflected echoes, four features which show sufficient sensitiveness and therefore could be modulated noticeably by different levels of liquid encased in the bladder, are extracted. The extracted features are then fed into a novel intelligent decision support system- known as FECOC - which is based on hybridization of fuzzy inference systems (FIS) and error correcting output codes (ECOC). The proposed scheme tends to achieve better results when examined in real case studies.

An Image-Recognition System Implemented On Hierarchical Parallel Architectures

The paper describes a parallel implementation of a vision system based on associative memories. The proposed real-time image-recognition system is based on the associative 'noise-like coding' model and is implemented on transputer-based tree structures. A high-performance device, the 'complex node' (CN), is introduced. The CN integrates two transputers by a dual-port memory and supports a total of eight links. Tree structures increase their throughput performance when CNs are included. A CN-including tree architecture is compared with a standard transputer-based tree structure having the same computational power. A comparative performance analysis shows the improvement in efficiency obtained when the novel device is used. In addition, theoretical derivations lead to a formula for the system's efficiency, and one demonstrates that expected values fit with measured ones, thus confirming the validity of the overall approach.

Representation and generalization properties of class-entropy networks

Using conditional class entropy (CCE) as a cost function allows feedforward networks to fully exploit classification-relevant information. CCE-based networks arrange the data space into partitions, which are assigned unambiguous symbols and are labeled by class information. By this labeling mechanism the network can model the empirical data distribution at the local level. Region labeling evolves with the network-training process, which follows a plastic algorithm. The paper proves several theoretical properties about the performance of CCE-based networks, and considers both convergence during training and generalization ability at run-time. In addition, analytical criteria and practical procedures are proposed to enhance the generalization performance of the trained networks. Experiments on artificial and real-world domains confirm the accuracy of this class of networks and witness the validity of the described methods.

Circular backpropagation networks embed vector quantization

This letter proves the equivalence between vector quantization (VQ) classifiers and circular backpropagation (CBP) networks. The calibrated prototypes for a VQ schema can be plugged in a CBP feedforward structure having the same number of hidden neurons and featuring the same mapping. The letter describes how to exploit such equivalence by using VQ prototypes to perform a meaningful initialization for BP optimization. The approach effectiveness was tested considering a real classification problem (NIST handwritten digits).

[Investigation in a slaughter house and processing of pork meat. Repetitive task work and osteo-articular and musculotendinous pathology of the upper limbs]

The investigation concerned 47 workers (43 males and 4 females), whose average age was 41.5 years and average length of service 12 years. The aim of the study was to quantify the presence in an abattoir and meat processing plant of risk factors represented by repetitive movements requiring the use of force, and to describe the work-related musculo-skeletal disorders (WMSDs) of the upper limbs found in a group of workers exposed to such risk factors. The work was found to feature high speeds and very particular operations which, for most of the workers, required highly repetitive actions often associated with the use of force. Almost all the tasks had duration cycles of less than 30 seconds and a medium-high rate of actions/minute (from 20 to 60), with peak rates reached in the boning operations; the postural involvement was also considerable, particularly for the right wrist. The amount of force employed-calculated as a percentage of the Maximum Voluntary Contraction-averaged 50%. With very few exceptions, there were no significant pauses during the cycle. The group displayed a high prevalence of pain and paraesthesia and joint disorders, particularly in the over 35 age groups; statistically significant differences emerged with respect to the data from a matched population sample given the same anamnestic and clinical protocol. The group also exhibited significantly different Carpal Tunnel Syndromes with respect to the control population: 7 right-hand CTSs and five left-hand. CTS affected two out of every three women aged over 35 and 3 out of every 23 men over 35. The authors discuss the results in the light of previous studies and of the definition of CTS. The study concludes that investigating and preventing WMSDs in the meat processing industry is a justified, albeit very difficult, task whilst the protection afforded by current legislation appears to be most inadequate.