Feature Extraction Methods Based on Linear Predictive Coding and Wavelet Packet Decomposition for Recognizing Spoken Words in Malayalam

Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations

Integrating TPM and QFD for improving quality in maintenance engineering

To provide maintenance engineering community with a model named “Maintenance quality function deployment” (MQFD) for nourishing the synergy of quality function deployment (QFD) and total productive maintenance (TPM) and enhancing maintenance quality of products and equipment.The principles of QFD and TPM were studied. MQFD model was designed by coupling these two principles. The practical implementation feasibility of MQFD model was checked in an automobile service station.Both QFD and TPM are popular approaches and several benefits of implementing them have been reported worldwide. Yet the world has not nourished the synergic power of integrating them. The MQFD implementation study reported in this paper has revealed its practical validity

On-the-Fly Maintenance of Series-Parallel Relationships in Fork-Join Multithreaded Programs

A key capability of data-race detectors is to determine whether one thread executes logically in parallel with another or whether the threads must operate in series. This paper provides two algorithms, one serial and one parallel, to maintain series-parallel (SP) relationships "on the fly" for fork-join multithreaded programs. The serial SP-order algorithm runs in O(1) amortized time per operation. In contrast, the previously best algorithm requires a time per operation that is proportional to Tarjan’s functional inverse of Ackermann’s function. SP-order employs an order-maintenance data structure that allows us to implement a more efficient "English-Hebrew" labeling scheme than was used in earlier race detectors, which immediately yields an improved determinacy-race detector. In particular, any fork-join program running in T₁ time on a single processor can be checked on the fly for determinacy races in O(T₁) time. Corresponding improved bounds can also be obtained for more sophisticated data-race detectors, for example, those that use locks. By combining SP-order with Feng and Leiserson’s serial SP-bags algorithm, we obtain a parallel SP-maintenance algorithm, called SP-hybrid. Suppose that a fork-join program has n threads, T₁ work, and a critical-path length of T[subscript ∞]. When executed on P processors, we prove that SP-hybrid runs in O((T₁/P + PT[subscript ∞]) lg n) expected time. To understand this bound, consider that the original program obtains linear speed-up over a 1-processor execution when P = O(T₁/T[subscript ∞]). In contrast, SP-hybrid obtains linear speed-up when P = O(√T₁/T[subscript ∞]), but the work is increased by a factor of O(lg n).

Social network measures for "nosduocentered" networks, their predictive power on performance

Our purpose in this article is to define a network structure which is based on two egos instead of the egocentered (one ego) or the complete network (n egos). We describe the characteristics and properties for this kind of network which we call “nosduocentered network”, comparing it with complete and egocentered networks. The key point for this kind of network is that relations exist between the two main egos and all alters, but relations among others are not observed. After that, we use new social network measures adapted to the nosduocentered network, some of which are based on measures for complete networks such as degree, betweenness, closeness centrality or density, while some others are tailormade for nosduocentered networks. We specify three regression models to predict research performance of PhD students based on these social network measures for different networks such as advice, collaboration, emotional support and trust. Data used are from Slovenian PhD students and their s

Bullying and cyberbullying : Overlapping and predictive value of the co-occurrence

Resumen tomado de la publicaci??n

Intraovarian sperm storage in Helicolenus dactylopterus dactylopterus fertilitzation, crypt formation and maintenance of stored sperm

The females of the bluemouth rockfish, Helicolenus dactylopterus dactylopterus (DelaRoche, 1809), store sperm within their ovaries for periods of up to 10 months. Twenty six females with standard lengths between 152 and 257 mm and six males with standard lengths between 253 and 209 mm were caught storage crypts with stored spermatozoa and to describe their evolution over the year. After internal fertilization and once sperm reaches the ovary, a crypt forms probably by an epithelial inclusion at the base of the lamellae of one or several spermatozoa groups that are floating freely in the interlamellar space of the ovarian lumen. Stored spermatozoa have a large cytoplasm bag surrounding their heads. This bag could serve as a nutritive reservoir during the long storage period. Many desmosonal and tight junctions between the crypt cells ensure tha male sex cells are protected against the female immune system

Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields

A Gain Scheduling Model Predictive Controller for Blood Glucose Control in Type 1 Diabetes

This paper presents a control strategy for blood glucose(BG) level regulation in type 1 diabetic patients. To design the controller, model-based predictive control scheme has been applied to a newly developed diabetic patient model. The controller is provided with a feedforward loop to improve meal compensation, a gain-scheduling scheme to account for different BG levels, and an asymmetric cost function to reduce hypoglycemic risk. A simulation environment that has been approved for testing of artificial pancreas control algorithms has been used to test the controller. The simulation results show a good controller performance in fasting conditions and meal disturbance rejection, and robustness against model–patient mismatch and errors in meal estimation

Predictive motion control of a mirosot mobile robot

This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obtained dynamic model, an integrated predictive control algorithm is proposed to position precisely with either stationary or moving obstacle avoidance. This objective is achieved automatically by introducing distant constraints into the open-loop optimization of control inputs. Simulation results demonstrate the feasibility of such control strategy for the deduced dynamic model

Objective quality of life, optimism, and social-juridical variables, as predictive ones of the subjective quality of life in disarmed Colombian persons

The goal of this research was to identify predic- tive psychosocial factors of the subjective quality of life in a group of 60 people, with ages between 19 and 57, from both sexes, included in the program of demobilization and social inclusion of the Pro- grama de la Alta Consejería para la Reintegración Social y Económica de Personas y Grupos Alzados en Armas en Colombia. this research was a predic- tive correlational descriptive study. the Question- naire of optimism/Pessimism was used to assess the optimist or pessimist trend, and, for assess the quality of life, these strategies were combined: a home visit to value the objective quality of life, the Analogous scale of subjective Quality of Life to value satisfaction and well-being, and a general format to collect socio-demographic and juridical information. Results show that some variables as perceived health, optimism, educational level, re- ligious believes, objective quality of life, type of demobilization and years spent in the armed group operating outside the law, are associated to better levels of perceived quality of life. The findings and limitations of the study are discussed.  

A predictive study of reading comprehension in third-grade Spanish students

Resumen tomado de la publicación

Is semantic impairment a predictive sign for Alzheimer disease?

Resumen basado en el de la publicaci??n

Self-deception as a mechanism for the maintenance of drug addiction

Resumen tomado de la publicaci??n

Local model predictive control for navigation of a wheeled mobile robot using monocular information

Aquesta tesi està inspirada en els agents naturals per tal de planificar de manera dinàmica la navegació d'un robot diferencial de dues rodes. Les dades dels sistemes de percepció són integrades dins una graella d'ocupació de l'entorn local del robot. La planificació de les trajectòries es fa considerant la configuració desitjada del robot, així com els vértexs més significatius dels obstacles més propers. En el seguiment de les trajectòries s'utilitzen tècniques locals de control predictiu basades en el model, amb horitzons de predicció inferiors a un segon. La metodologia emprada és validada mitjançant nombrosos experiments.