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Comparison between low-cost and high-end sEMG sensors for the control of a transradial myoelectric prosthesis

Comparison between low-cost and high-end sEMG sensors for the control of a transradial myoelectric prosthesis

As discussed before, the average classifier accuracies from each setting were compared between the three train-test sets used. As it could be observed in Figure 4.10 and 4.11, the average accuracies from both systems have a very noticeable increase between train-test set 1 and 2 and a lower increase between train-test set 2 and 3. In train-test set 1, the data from session 1 is used as training set and the data from session 2 is used for testing. On the other hand, in train-test set 2, 25% from the session 2 data set is added to the data from session 1 for training and the remaining 75% from session 2 is used for testing. The difference between the accuracies from train-test 1 and train-test 2 show that it is better to add data from the present session to the training set than to just use data from a previous session. However, the accuracy differences between train-test set 2 and train-test set 3, which only uses 25% from the present session for training and 75% for testing, show that it is better to delete all data from the previous session and to just use data from the present session for training the classifier. In practical terms, this means that it is better to recalibrate a myoelectric prosthesis when it is taken off and placed again the residual limb. The learning algorithm should be re-trained with new data and forget all the data used for training on a previous session. This is quite justifiable by the fact that when the system is taken off and placed again on the forearm, it is not guaranteed that the sensors will be in the same exact position, therefore the sEMG signals will also have different patterns. This also depends on the way the subject performed the gestures in each of the sessions, the flexion of the wrist might have been different, different levels of force might have been applied, amongst other factors. These are, apparently small differences, but the sEMG patterns are heavily influenced by these factors, which causes the data from one session to be distinctive from another. This directly affects the classifier if the training set contains data from a different session from the data used for the testing set. This could be observed in the results presented. Since the higher accuracies were calculated using train-test set 3, a deeper examination was given to these results.
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On the importance of the distance measures used to train and test knowledge-based potentials for proteins.

On the importance of the distance measures used to train and test knowledge-based potentials for proteins.

TSA, which stands for ‘‘Test Sets All’’ is a large heterogeneous collection of decoy sets that were generated by many different techniques (see Materials and methods for details). Some of these decoy sets are high-resolution, i.e. contains mostly native-like structures, while others are more diverse, containing decoys that are very different from their corresponding native structures, both in terms of secondary structure content and three-dimensional organization. To assess the importance of this diversity, we selected within the TSA group of decoy sets two subgroups, those for which the decoys have average TM score larger than 0.5, and those with average TM score smaller than 0.5. This 0.5 cutoff was again chosen based on the observation made by Xu and Zhang that two decoys belong to the same fold when their TM-scores to a native structure is higher than 0.5 [47]. Table 1 shows that TSA TM-score. 0.5 generally contain longer chains with fewer decoys when compared to the TSA TM-score ,0.5 set. The two sets are fully listed in File S1 and File S2. Tables 2 and 3 show that the distance measures behave on the high-resolution subgroup (TM. 0.5) as on the Titan-HRD test set, i.e. with high correlations and high R scores, meaning that they are very similar to each other. On the low-resolution subgroup (TM ,0.5) however, the distance
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A field based 3D QSAR model of novel anti-microtubule agent noscapine and its derivatives

A field based 3D QSAR model of novel anti-microtubule agent noscapine and its derivatives

models of these compounds were built,energy minimized and geometry optimized. The data set was randomly divided into 43 training and 10 test set molecules. Amino noscapine was considered as template molecule for the calculation of hydrophobic, steric, electrostatic and volume field points. These field based descriptors were used to align the training set molecules with the template molecule.A Partial Least Square (PLS) model was built based on field points using sphere exclusion algorithm. RESULTS:A statistically significant model (R train 2 2 LOO = 0.875) was obtained with the
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Automatic identification of bat species using supervised learning

Automatic identification of bat species using supervised learning

In recent years, given the need to find alternatives to fossil fuels, there has been an increase in the focus on renewable energies, especially wind power. However, the installation of wind farms is not free of negative environmental impacts, such as direct mortality of bats and birds. Bats are unique animals that play an important ecological role and their conservation is of the utmost importance. Acoustic identification is fundamental to assess the impact of wind farms on bat communities. The need to speed up the identification process of bat species led us to develop a methodology to identify species of bats from South Africa using machine learning methodologies. The Analook software was used to extract variables related to the frequency, slope, and duration of echolocation pulses from specialist-identified recordings. With this information a database was compiled and divided into training and test sets. The training set was used to train models to identify individual bat species, using an array of algorithms that included random forests, support vector machine, extreme gradient boosting and flexible discriminant analysis. The predictive power of the models was evaluated using the test set. In this work it was possible to obtain high identification accuracy rates for a set of species considered of greater interest in the context of impact studies in wind farms. In the near future, the methodology developed in this work will enhance the process of recording identification and reduce the associated costs. Moreover, gathering new records will improve the database, and allow for more precise predictions on the identification of bat species.
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Detecting Robotic Anomalies using RobotChain

Detecting Robotic Anomalies using RobotChain

way. By using a blockchain, we increase the security of the data that is registered in an environment that is susceptible to human interaction. This ensures that if a robotic failure occurs, it gets registered in the blockchain and once there, it can’t be manually altered. By having such a system, we use smart- contracts to store the information about a UR3 robot in the blockchain and created four datasets, one train, one validation, and two test sets to develop, validate and test a method that can leverage the information acquired from the blockchain to detect robotic anomalies. Our method for detecting anomalies was capable of detecting anomalies induced by counteracting the movement of the arm while performing a pick and place repetitive task. This method shows that it’s possible to use the blockchain with robotics and with such a modular system, innovative methods for different purposes can be added by using oracles.
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The influence of playing a nonreward game on motor ability and executive function in Parkinson’s disease

The influence of playing a nonreward game on motor ability and executive function in Parkinson’s disease

Assessment included the Unified Parkinson’s Dis- ease Rating Scale (UPDRS), Folstein Mini-Mental State Examination (MMSE), Beck Depressive Inven- tory (BDI) [13], Finger Tapping Test [14], 14-meter walking test (14-MWT) and the Stroop test (Phase 3, time in seconds measured) [15]. Measures were tak- en before and immediately after experiment. Protocol consisted of playing a game of dominoes, starting at 8:00 AM (with 30 minutes of tolerance) with one previ- ous training session. Training and playing lasted about 40 minutes. Patients were randomized for playing or not and those that did not play were asked to sit and while sitting, they read a magazine or watched a movie. Experiment was started within 15-30 minutes after the first daily dose of levodopa. All measures were taken before and after playing the game. Examiners were blind to which group patients belonged.
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Complete set of documents

Complete set of documents

Official Docu- Proposed Program and Budget Estimates. ment No[r]

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Complete set of documents

Complete set of documents

CD30/DT/1 Increasing the Operational Capacity of the Health Services for the Attainment of the Goal of Health for All by the Year 2000. CD30/DT/2, Rev[r]

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DATA SET AND INSTRUMENTATION

DATA SET AND INSTRUMENTATION

pothanòpihaçâo heal e potencial são calculadas com o conjunto de dados obtidos na ãhea. de {lohesta thopicai, utilizando a equação clássica de Penman-Monteith.. Ducke), rural (UEPAE) and[r]

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A HYBRID METHOD FOR AUTOMATIC SPEECH RECOGNITION PERFORMANCE IMPROVEMENT IN REAL WORLD NOISY ENVIRONMENT

A HYBRID METHOD FOR AUTOMATIC SPEECH RECOGNITION PERFORMANCE IMPROVEMENT IN REAL WORLD NOISY ENVIRONMENT

This study uses all categories of environment to train the system so that word recognition accuracy will be increased. The categories of environment include different types of noise and SNR level like, clean, known SNR level noise, unknown SNR level noise in prior and real world environment. Artificial noise are taken from standard databases.

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A New Approach for Real Time Train Energy Efficiency Optimization

A New Approach for Real Time Train Energy Efficiency Optimization

For the last case (case D) a total distance of 3955 m to be accomplished in 200 s is considered. As shown in Table 4, at a travelling distance of 3727 m, velocity limit changes from 110 km/h to 80 km/h. Nevertheless, despite this being used by OSP algorithm, actual velocity, at this distance, is always lower so this constraint does not appear in the simulated output profile. Figure 16 shows both velocity profiles (in dashed black the measured train velocity and in blue OSP output). Besides the energy consumption reduction, OSP output advices a speed profile that accomplishes the original scheduling imposed by railway operator. The improvements to energy consumption can be seen in Figure 17. Simulated results have no error in travelling time. Real one has a 14 s delay. Distance errors are negligible in both cases. Again, the algorithm running time is compatible with real-time DAS.
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Set-Valued Graphs

Set-Valued Graphs

Firstly, it is not difficult to verify that no graph with at most four vertices satisfies all the given properties, viz., a set-sequential graph H having an edge ab with d(a) = d(b) and d(a) + d(b) ≥ 2 n−1 − 1, where n is the cardinality of the ground set X with respect to which there is a set-sequential labeling of H. Therefore, G has at least five vertices whence, by invoking the Acharya-Hegde necessary condition for a graph to be set-sequential, we see that n ≥ 3. If n = 3, it may be verified that q ≤ 2. Further, no graph on at least five vertices and at most two edges is set-sequential. Therefore, n ≥ 4. If n > 4 then it is not difficult to verify that p would never be an integer solution to the quadratic inequality
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Acoustic estimation of seafloor parameters: a Radial Basis Functions approach

Acoustic estimation of seafloor parameters: a Radial Basis Functions approach

The second, more important, consideration is that, through the training set, we can impose additional physical constraints on the approximated inverse. This can be achieved in several different ways and depends on the spe- cific a priori knowledge, if any. One can bias the random generation of models by forcing some specific structure, like a positive gradient of some of the parameters as a function of depth, or by allowing only weak negative gradients etc. It is up to the designer of the network to choose what sort of constraints, if any, is best suited for the specific problem he has at hand. Note in particular that, depending on the param- etrization chosen, known correlations among the parameters can also be inserted at this stage.
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Relatorio Mestrado Set 2016

Relatorio Mestrado Set 2016

Sem se centrar na comparação entre as alternativas da prestação de cuidados à pessoa dependente, Duque (2009) prefere chamar a atenção para a importância do conh[r]

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A Logical Framework for Set Theories

A Logical Framework for Set Theories

Set Theory G ¨odel’s classical work [11] on the constructible universe L is best known for its use in con- sistency and independence proofs. However, it is of course of great interest also for the study of the general notion of constructions with sets. Thus for characterizing the “constructible sets” G ¨odel identified a set of operations on sets (which we may call “computable”), that can be used for “effectively” constructing new sets from given ones. For example, binary union and intersection are “effective”, while the powerset operation is not. G ¨odel has provided a finite list of basic oper- ations, from which all other “effective” (for his purposes) constructions can be obtained through compositions. Another very important idea which was introduced in [11] is absoluteness — a key property (see [13]) of formulas which are used for defining “constructible sets”. Roughly, a formula is absolute if its truth value in a transitive class M, for some assignment v of objects from M to its free variables, depends only on v, but not on M.
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A methodology for the assessment of the train running safety on bridges

A methodology for the assessment of the train running safety on bridges

Figure 5.9 presents the contact angles in the left γ lft and right γ rht wheels obtained in the test case A1.2, in which the lateral displacement of the wheelset is combined with yaw rotations. The contact angle in the right wheel reaches the maximum value for a lateral displacement of 6.5 mm accompanied by a yaw rotation of 15.6 mrad and, like the rolling radius difference, suffers an abrupt increase when the contact point jumps to the flange. The results obtained with the proposed method for the right contact angle show a good match with those obtained with all the tested softwares. Regarding the left contact angle, the proposed method follows the same trend as the softwares GENSYS, NUCARS and VAMPIRE, which are widely used in railway vehicle simulations. The other two trends are followed by VOCOLIN and by the softwares LaGer and CONTACT PC92. The discrepancies obtained with VOCOLIN derive from the non-consideration of the roll rotation of the wheelset to locate the contact point, while the trend followed by LaGer and CONTACT PC92 is justified by the fact that the output given by these codes are related to the wheelset coordinate system rather than to the track centerline coordinate system (see Appendix A for the definition of these coordinate systems).
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The world on a train: global narration in Geoff Ryman’s 253

The world on a train: global narration in Geoff Ryman’s 253

Geoff Ryman’s novel 253 was originally released online as 253, or tube theatre: a novel for the Internet on London Underground in Seven Cars and a Crash and two years later, in 1998, as a ‘print remix’. The action of the novel, which in print adds up to 366 pages, takes place on 11 January 1995, from 8.35 to 8.42 in the morning, amounting to a total time span of just seven and a half minutes. The setting is a London underground train on the Bakerloo line, which at full capacity accommodate 253 people including the driver. The action starts as the train leaves Embankment, then continues via Waterloo and Lambeth North to the Elephant and Castle, where it crashes after the driver falls asleep. In Ryman’s novel each passenger’s identity is rehearsed in three separate sections dedicated to ‘outward appearance’, ‘inside information’, and ‘what he or she is thinking or doing’, amounting to exactly 253 words irrespective of how eccentric or non-descript the passenger under scrutiny turns out to be. Emulating Woolf’s method in Jacob’s Room Ryman names all his characters, thus highlighting everybody’s unique individuality as well as the transience and ultimate inconsequence of their existence. Showing its characters in transit, wholly immersed in mega-urban anonymity, the novel is at the same time rooted in a very speciic locale through
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ARTICULATING SUMMATIVE AND FORMATIVE ASSESSMENT PRACTICES

ARTICULATING SUMMATIVE AND FORMATIVE ASSESSMENT PRACTICES

The first results evidence that only 63% of the students accomplished these tasks. For this group of students, a large majority considers that this practices helps them to learn, what is confirmed by a positive progress from the test to the set of tasks. From the different resources used, their own school notebook is detached. Although these first results have positive aspects, a special attention has to be given to the students that are not involved in this strategy.

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