On-Line Handwritten Character Recognition using Kohonen Networks

This paper presents an efficient Online Handwritten character Recognition System for Malayalam Characters (OHR-M) using Kohonen network. It would help in recognizing Malayalam text entered using pen-like devices. It will be more natural and efficient way for users to enter text using a pen than keyboard and mouse. To identify the difference between similar characters in Malayalam a novel feature extraction method has been adopted-a combination of context bitmap and normalized (x, y) coordinates. The system reported an accuracy of 88.75% which is writer independent with a recognition time of 15-32 milliseconds

Application of MLP and Kohonen networks for recognition of wear patterns of single-point dressers

Grinding is a parts finishing process for advanced products and surfaces. However, continuous friction between the workpiece and the grinding wheel causes the latter to lose its sharpness, thus impairing the grinding results. This is when the dressing process is required, which consists of sharpening the worn grains of the grinding wheel. The dressing conditions strongly affect the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The objective of this study was to estimate the wear of a single-point dresser using intelligent systems whose inputs were obtained by the digital processing of acoustic emission signals. Two intelligent systems, the multilayer perceptron and the Kohonen neural network, were compared in terms of their classifying ability. The harmonic content of the acoustic emission signal was found to be influenced by the condition of dresser, and when used to feed the neural networks it is possible to classify the condition of the tool under study.

Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid Compounds

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.

An Information Model for Pension Fund Management

In this paper the issues of Ukrainian new three-level pension system are discussed. First, the paper presents the mathematical model that allows calculating the optimal size of contributions to the non-state pension fund. Next, the non-state pension fund chooses an Asset Management Company. To do so it is proposed to use an approach based on Kohonen networks to classify asset management companies that work in Ukrainian market. Further, when the asset management company is chosen, it receives the pension contributions of the participants of the non-pension fund. Asset Management Company has to invest these contributions profitably. This paper proposes an approach for choosing the most profitable investment project using decision trees. The new pension system has been lawfully ratified only four years ago and is still developing, that is why this paper is very important.

A tabela periódica dos elementos químicos prevista por redes neurais artificiais de Kohonen

Although several chemical elements were not known by end of the 18th century, Mendeleyev came up with an astonishing achievement: the periodic table of elements. He was not only able to predict the existence of (then) new elements but also to provide accurate estimates of their chemical and physical properties. This is certainly a relevant example of the human intelligence. Here, we intend to shed some light on the following question: Can an artificial intelligence system yield a classification of the elements that resembles, in some sense, the periodic table? To achieve our goal, we have fed a self-organized map (SOM) with information available at Mendeleyev's time. Our results show that similar elements tend to form individual clusters. Thus, SOM generates clusters of halogens, alkaline metals and transition metals that show a similarity with the periodic table of elements.

Oriented texture classification based on self-organizing neural network and Hough transform

This paper presents a technique for oriented texture classification which is based on the Hough transform and Kohonen's neural network model. In this technique, oriented texture features are extracted from the Hough space by means of two distinct strategies. While the first operates on a non-uniformly sampled Hough space, the second concentrates on the peaks produced in the Hough space. The described technique gives good results for the classification of oriented textures, a common phenomenon in nature underlying an important class of images. Experimental results are presented to demonstrate the performance of the new technique in comparison, with an implemented technique based on Gabor filters.

Structural Connectivity Of The Default Mode Network And Cognition In Alzheimer׳s Disease.

Disconnectivity between the Default Mode Network (DMN) nodes can cause clinical symptoms and cognitive deficits in Alzheimer׳s disease (AD). We aimed to examine the structural connectivity between DMN nodes, to verify the extent in which white matter disconnection affects cognitive performance. MRI data of 76 subjects (25 mild AD, 21 amnestic Mild Cognitive Impairment subjects and 30 controls) were acquired on a 3.0T scanner. ExploreDTI software (fractional Anisotropy threshold=0.25 and the angular threshold=60°) calculated axial, radial, and mean diffusivities, fractional anisotropy and streamline count. AD patients showed lower fractional anisotropy (P=0.01) and streamline count (P=0.029), and higher radial diffusivity (P=0.014) than controls in the cingulum. After correction for white matter atrophy, only fractional anisotropy and radial diffusivity remained significantly lower in AD compared to controls (P=0.003 and P=0.05). In the parahippocampal bundle, AD patients had lower mean and radial diffusivities (P=0.048 and P=0.013) compared to controls, from which only radial diffusivity survived for white matter adjustment (P=0.05). Regression models revealed that cognitive performance is also accounted for by white matter microstructural values. Structural connectivity within the DMN is important to the execution of high-complexity tasks, probably due to its relevant role in the integration of the network.

Can We Predict The Clinical Outcomes Of Genitourinary Trauma Patients And Offer Them An Evidence-based Support? The Case For Telemedicine Network.

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[gait Speed, Grip Strength And Self-rated Health Among The Elderly: Data From The Fibra Campinas Network, São Paulo, Brazil].

The article seeks to investigate patterns of performance and relationships between grip strength, gait speed and self-rated health, and investigate the relationships between them, considering the variables of gender, age and family income. This was conducted in a probabilistic sample of community-dwelling elderly aged 65 and over, members of a population study on frailty. A total of 689 elderly people without cognitive deficit suggestive of dementia underwent tests of gait speed and grip strength. Comparisons between groups were based on low, medium and high speed and strength. Self-related health was assessed using a 5-point scale. The males and the younger elderly individuals scored significantly higher on grip strength and gait speed than the female and oldest did; the richest scored higher than the poorest on grip strength and gait speed; females and men aged over 80 had weaker grip strength and lower gait speed; slow gait speed and low income arose as risk factors for a worse health evaluation. Lower muscular strength affects the self-rated assessment of health because it results in a reduction in functional capacity, especially in the presence of poverty and a lack of compensatory factors.

Going Beyond Seizure Control: Can Pharmacotherapy Help To Restore Cognitive Network Function?

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Whole Cortical And Default Mode Network Mean Functional Connectivity As Potential Biomarkers For Mild Alzheimer's Disease.

The search for an Alzheimer's disease (AD) biomarker is one of the most relevant contemporary research topics due to the high prevalence and social costs of the disease. Functional connectivity (FC) of the default mode network (DMN) is a plausible candidate for such a biomarker. We evaluated 22 patients with mild AD and 26 age- and gender-matched healthy controls. All subjects underwent resting functional magnetic resonance imaging (fMRI) in a 3.0 T scanner. To identify the DMN, seed-based FC of the posterior cingulate was calculated. We also measured the sensitivity/specificity of the method, and verified a correlation with cognitive performance. We found a significant difference between patients with mild AD and controls in average z-scores: DMN, whole cortical positive (WCP) and absolute values. DMN individual values showed a sensitivity of 77.3% and specificity of 70%. DMN and WCP values were correlated to global cognition and episodic memory performance. We showed that individual measures of DMN connectivity could be considered a promising method to differentiate AD, even at an early phase, from normal aging. Further studies with larger numbers of participants, as well as validation of normal values, are needed for more definitive conclusions.

[strategies For Integration Of Health Care Practices And Sanitary Surveillance In The Context Of The Implementation Of Rede Cegonha - A Brazilian Mother And Infant Health Care Network].

Mother and infant mortality has been the scope of analysis throughout the history of public health in Brazil and various strategies to tackle the issue have been proposed to date. The Ministry of Health has been working on this and the Rede Cegonha strategy is the most recent policy in this context. Given the principle of comprehensive health care and the structure of the Unified Health System in care networks, it is necessary to ensure the integration of health care practices, among which are the sanitary surveillance actions (SSA). Considering that the integration of health care practices and SSA can contribute to reduce mother and infant mortality rates, this article is a result of qualitative research that analyzed the integration of these actions in four cities in the State of São Paulo/Brazil: Campinas, Indaiatuba, Jaguariúna and Santa Bárbara D'Oeste. The research was conducted through interviews with SSA and maternal health managers, and the data were evaluated using thematic analysis. The results converge with other studies, identifying the isolation of health care practices and SSA. The insertion of SSA in collectively-managed areas appears to be a potential strategy for health planning and implementation of actions in the context under scrutiny.

[child Protection Network And The Intersector Implementation Of The Circle Of Security As Alternatives To Medication].

To describe the clinical history of a child with aggressive behavior and recurring death-theme speech, and report the experience of the team of authors, who proposed an alternative to medication through the establishment of a protection network and the inter-sector implementation of the circle of security concept. A 5-year-old child has a violent and aggressive behavior at the day-care. The child was diagnosed by the healthcare center with depressive disorder and behavioral disorder, and was medicated with sertraline and risperidone. Side effects were observed, and the medications were discontinued. Despite several actions, such as talks, teamwork, psychological and psychiatric follow-up, the child's behavior remained unchanged. A unique therapeutic project was developed by Universidade Estadual de Campinas' Medical School students in order to establish a connection between the entities responsible for the child's care (daycare center, healthcare center, and family). Thus, the team was able to develop a basic care protection network. The implementation of the inter-sector circle of security, as well as the communication and cooperation among the teams, produced very favorable results in this case. This initiative was shown to be a feasible and effective alternative to the use of medication for this child.

[access To Information About How To Prevent Oral Problems Among School Children In The Public School Network].

The scope of this study is to identify the prevalence of access to information about how to prevent oral problems among schoolchildren in the public school network, as well as the factors associated with such access. This is a cross-sectional and analytical study conducted among 12-year-old schoolchildren in a Brazilian municipality with a large population. The examinations were performed by 24 trained dentists and calibrated with the aid of 24 recorders. Data collection occurred in 36 public schools selected from the 89 public schools of the city. Descriptive, univariate and multiple analyses were conducted. Of the 2510 schoolchildren included in the study, 2211 reported having received information about how to prevent oral problems. Access to such information was greater among those who used private dental services; and lower among those who used the service for treatment, who evaluated the service as regular or bad/awful. The latter use toothbrush only or toothbrush and tongue scrubbing as a means of oral hygiene and who reported not being satisfied with the appearance of their teeth. The conclusion drawn is that the majority of schoolchildren had access to information about how to prevent oral problems, though access was associated with the characteristics of health services, health behavior and outcomes.

The Psychedelic State Induced By Ayahuasca Modulates The Activity And Connectivity Of The Default Mode Network.

The experiences induced by psychedelics share a wide variety of subjective features, related to the complex changes in perception and cognition induced by this class of drugs. A remarkable increase in introspection is at the core of these altered states of consciousness. Self-oriented mental activity has been consistently linked to the Default Mode Network (DMN), a set of brain regions more active during rest than during the execution of a goal-directed task. Here we used fMRI technique to inspect the DMN during the psychedelic state induced by Ayahuasca in ten experienced subjects. Ayahuasca is a potion traditionally used by Amazonian Amerindians composed by a mixture of compounds that increase monoaminergic transmission. In particular, we examined whether Ayahuasca changes the activity and connectivity of the DMN and the connection between the DMN and the task-positive network (TPN). Ayahuasca caused a significant decrease in activity through most parts of the DMN, including its most consistent hubs: the Posterior Cingulate Cortex (PCC)/Precuneus and the medial Prefrontal Cortex (mPFC). Functional connectivity within the PCC/Precuneus decreased after Ayahuasca intake. No significant change was observed in the DMN-TPN orthogonality. Altogether, our results support the notion that the altered state of consciousness induced by Ayahuasca, like those induced by psilocybin (another serotonergic psychedelic), meditation and sleep, is linked to the modulation of the activity and the connectivity of the DMN.