Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantificação de imagens tomográficas para cálculo de dose em diagnose e terapia em medicina nuclear

The nuclear medicine area has an increasing slope in the therapy of diseases, particularly in the treatment of radiosensitive tumors. Due to the high dose levels in radionuclide therapy, it is very important the accurate quantify of the dose distribution to avoid deleterious effects on healthy tissues. In Brazil, the internal dosimetry system used is the MIRD (Medical Internal Radiation Dose) based on a reference model that does not have adequate patient data to obtain a dose accurate assessment in therapy. However, in recent years, internal radionuclide dosimetry evaluates the spatial dose distribuition basead on information obtained from CT and SPECT or PET images together with the using of Monte Carlo codes. Those systems are called patient-specific dosimetry systems. In the Nuclear Engineering Center at IPEN, this methodology is in development. When the CT images are inserted into the Monte Carlo code MCNP5 through of use of a interface software called SCMS the dosimetry can be accomplished using patient-specific data, resulting in a more accurate energy deposition in organs of interest. This work aim to contribute with the development of part of that patient-specific dosimetry for therapy. To achieve this goal we have proposed three specific objectives: (1) Development of a software to convert images from Computed Tomography (CT) in the tissue parameters (ρ, ω(i)); (2) Development of a software to perform attenuation correction in nuclear medicine tomographic images (SPECT or PET) and to provide the map of relative activity and (3) Provide data to the SCMS code by these two softwares. The software developed for the first specific objective was the Image Converter Computed Tomography (ICCT), which obtained a good accuracy to determine the density and the tissue composition; the elements that had high variation were carbon and oxygen. Fortunately, this variation for the energy range used in radionuclide therapy is not detrimental to the dose distribution. A major advantage is the high accuracy obtained to calcium and phosphorus which have great influence on the dose distribution calculation. For the second objective it was developed the Attenuation Corretion SPECT PET (ACPS) software which performs the attenuation correction in PET and SPECT images through of 1 order Chang method and create the relative activity distribution within of patient. Finally, the data generated by the two softwares, was formatted to SCMS which in provides the complete information do the MCNP5 Monte Carlo code for radiation transport simulation for dose distribution estimation.
Ants learn fast and do not forget: associative olfactory learning, memory and extinction in Formica fusca

Learning is a widespread phenomenon that allows behavioural flexibility when individuals face new situations. However, learned information may lose its value over time. If such a memory endures, it can be deleterious to individuals. The process of extinction allows memory updating when the initial information is not relevant anymore. Extinction is widespread among animals, including humans. We investigated associative appetitive learning in an ant species that is widely distributed in the Northern Hemisphere, Formica fusca. We studied acquisition and memory between 1 h and one week after conditioning, as well as the extinction process. Ants learn very rapidly, their memory lasts up to 3 days, decreases slowly over time and is highly resistant to extinction, even after a single conditioning trial. Using a pharmacological approach, we show that this single-trial memory critically depends on protein synthesis (long-term memory). These results indicate that individual ant workers of F. fusca show remarkable learning and memory performances. Intriguingly, they also show a strong resistance to updating learned associations. Resistance to extinction may be advantageous when the environment is stochastic and individuals need to switch often from one learned task to another.
Modeling odometry and uncertainty propagation for a Bi-Steerable car

This paper addresses the problem of modeling the odometry (dead-reckoning) for a Bi-Steerable car (BS-car) and its uncertainty propagation model. The attractive feature of BS-robots is their enhanced maneuverability compared to car-like robots. At first, we take into account the steering ability of a BS-car in order to obtain the odometry model for vehicles showing this type of kinematics. Subsequently, we obtain a generic model for the uncertainty propagation of the odometry model by using a Bayesian probability approach. We show how it is possible to derive from this generic model a specific error propagation model for a particular system, under clearly stated hypothesis. We evaluate qualitatively and quantitatively the performance of the odometry model by experimenting with our BS-platform, the Cycab robot.
Programmable IIR filter using bitstream processing

This paper presents a compact CMOS realization of cascaded biquad digital filters using 2nd order /spl Delta//spl Sigma/ modulators requiring no multibit multiplier. A bitstream biquad is derived with just one /spl Delta//spl Sigma/ modulator for each pair of poles which leads to a very compact implementation. No significant degradation of sensitivity nor of dynamic range is observed. The analog interfaces are highly simplified due to the bitstream input and output formats.
Error Reduction Method with Two Cameras on Shape Measurement using Whole-Space Tabulation Method

Shape measurement using the whole-space tabulation method (WSTM) is a non-contact approach that has high accuracy. However, unfocused images affect measurement accuracy in practical applications. Errors occur in the analyzed phase near boundary areas with large contrast in unfocused images. In this study, measurement error is reduced. First, experiments are performed to confirm that low reflectance areas are significantly affected by high reflectance areas. Second, an error reduction method using two cameras for the WSTM is proposed. When two cameras capture images from the left and right sides of the projector, the phase-coordinate tables are nearly reversed. Thus, the measurement errors are also nearly reversed in the measurement results of these two cameras. The measurement accuracy is increased by averaging the two sets of measurement results. The WSTM measurement results of the two cameras share the same coordinate system because the WSTM uses a table with a shared reference plane. Therefore, the synthesis of the left and right measurement results is simple using the WSTM.
The Edinburgh Concurrent Supercomputer: project and applications

The Edinburgh Concurrent Supercomputer (ECS) project is built around a Meiko Computing Surface, and offers a networked multi-user facility for academic, industrial and commercial applications. The authors describe first the background to the project, and the present status of funding, hardware and software. The facility has presently more than 100 registered users, the authors describe some of the applications which are in production or under development.
A Primary Research on Gabor Tensor Sparse Features Representation for Whispered Speech Recognition

Due to differences between normal and whispered speech, traditional feature performed poorly for whispered recognition. In this paper, a novel approach for whispered speech feature representation is proposed based on Gabor filtering and tensor factorization. The sparse feature is extracted by processing the data samples in tensor structure. The simulation results indicate that our proposed feature is able to improve the whispered speech recognition performance. Keywords-speech recognition; whispered speech; Gabor filtering; feature extraction
An Exploratory Study of Mobile Application Privacy Policies

I reviewed the privacy policies for the 110 apps included in a study of sensitive data sharing by mobile apps. [1] I focused on (1) the prevalence of privacy policies for mobile applications and (2) what, if anything, those policies said about the use of encryption for data in transit. 37 41 15 12 3 2 0% 20% 40% 60% 80% 100% iOS apps Android apps Link Dead link No link Graves J. An Exploratory Study of Mobile Application Privacy Policies. Technology Science. 2015103002. October 30, 2015. http://techscience.org/a/2015103002/ 2 Results summary: For the 110 apps I reviewed, the app store pages provided working links to privacy policies for 67% of the iOS apps and 75% of the Android apps. Of the apps with accessible privacy policies, 62% contained general language saying that security measures would be used but did not specifically promise that encryption would be used, 31% included language implying that the apps encrypted some types of data in transit, 5% said nothing about security, and one policy (2%) affirmatively stated that encryption was not used (although, according to our testing, it actually did).
Real Coded Genetic Algorithm for Optimal Parameters Selection in Circular Mellin Feature Extractors

Abstract Texture is an important clue in region-based segmentation of images. Robust rotation and scale-invariant texture are important for digital image libraries and multimedia databases. Texture feature extraction operators, which comprise linear filtering followed by postprocessing, are considered. The CMF (Circular Mellin Feature) represents the spectral decomposition of the image scene in the polar-log coordinate system and is invariant to both scale and orientation of the target texture pattern. CMFs are used for rotation and scale-invariant texture classification. The image and CMFs are correlated, due to which the unique shift invariance property of the correlator architecture is also coupled. CMFs are based on log polar coordinate system. In this paper we present Real coded Genetic Algorithm (RcGA) for the parameter selection of CMFs. The simple genetic algorithm (GA) is search algorithms based on the mechanics of natural selection and genetics. It involves copying and swapping partial strings of data. A modified genetic algorithm is the RcGA, which basically employs real value vectors for representation of the chromosomes, and is widely applied to many optimization problems.
Application of neural network approach for MAP-MRF model-based MEG source imaging

Magnetoencephalography (MEG) source image reconstruction is an important and difficult problem in image processing applications. It can be formulated as an inherent ill-posed and highly underdetermined linear inverse problem, encompassing a great variety of signal modeling and processing methods. According to anatomical and physiological knowledge, source distributed image is modeled by a Markov random field (MRF), and the reconstruction is defined as the maximum a posteriori estimate (MAP) based on a Bayesian framework. To acquire a global minimum solution from the posterior energy function, many optimization methods (such as GA, SA, MFA, etc.) appear in the literature are investigated. In this paper, we incorporate the ideas of artificial neural networks into this difficult optimization task. Several computer experiments were conducted in order to assess the performance of the introduced technique.
State Estimation of Non-monotonic, Partially Non-deterministic Software with Sparse Probing using an Unscented Kalman Filter Combined with Logic Reasoning

Abstract : This report describes a technique for assessing the state of a general-purpose system using partial probing. The technique utilizes an Unscented Kalman Filter (UKF) combined with in-process and post-process reasoning. While Kalman Filters (KF) Extended Kalman Filres (EKF), and UKF are typically applied to state-space systems, where an underlying theory provides the a-priori knowledge, this report suggests the application of UKF to monitor general-purpose software systems that do not have an underlying first-principles theory. The suggested technique uses a reasoning component compute the a-priori evaluation. An important aspect differentiating state-space systems from general-purpose software is that the latter is often concurrent, with a plurality or concurrently executing threads, processes, or devices. As a result, relative execution time of these components (and the derivative state space) is for all intents and purposes non-deterministic. In addition, the suggested technique enables monitoring with probing that is sparse in time and space namely, probing that occurs only one in n cycles or probing that only probes a subset of the software-systems state-space.
Star + Transcription Rules = Reliable Readability Index

STAR, a computer program that computes Flesch Reading Ease scores and reading grade level estimates is described. This program processes text samples in an on-line environment The readability indicators are a function of number of syllables per word and number of words per sentence. Six text transcription rules are described to maximize the reliability of computer processing. Nineteen varied samples are analyzed by STAR and compared to hand calculations done by Flesch. The results show that the STAR program, coupled with the described transcription rules, is an extremely reliable analysis tool.
Online Handwritten Character Recognition of Devanagari and Telugu Characters using Support Vector Machines

A system for recognition of online handwritten characters has been presented for Indian writing systems. A handwritten character is represented as a sequence of strokes whose features are extracted and classied. Support vector machines have been used for constructing the stroke recognition engine. The results have been presented after testing the system on Devanagari and Telugu scripts.
Fingerprint Scaling for Sensor Interoperability

The need for sensor interoperability has increased tremendously in many large-scale fingerprint applications such as e-commerce, welfare-disbursement and e-education. In this paper, we present fingerprint scaling, an innovative fingerprint system module, which resizes the fingerprint images to solve the problem of sensor interoperability with minimum modification to existing system. In template-based scaling methods, we have developed an estimation method using Delaunay triangulation algorithm. The efficacy of the scaling technique has been assessed by embedding a scaling module into a traditional fingerprint recognition system. Our experiments have shown very positive results. Experimental results indicated that the accuracy and robustness of fingerprint system can be improved effectively by embedding such a scaling module into the traditional framework of fingerprint systems under multi-sensor situation.
Dog sperm swimming parameters analysed by computer‐assisted semen analysis of motility reveal major breed differences

Dogs have undergone an intensive artificial selection process ever since the beginning of their relationship with humans. As a consequence, a wide variety of well-defined breeds exist today. Due to the enormous variation in dog phenotypes and the unlikely chance of gene exchange between them, the question arises as to whether they should still be regarded as a single species or, perhaps, they be considered as different taxa that possess different reproductive traits. The aim of this study was therefore to characterize some male reproductive traits, focusing on kinematic characteristics of dog spermatozoa from several breeds. Thirty-seven dogs from the following breeds were used: Staffordshire Bull Terrier, Labrador Retriever, Spanish Mastiff, Valencian Rat Hunting Dog, British Bulldog and Chihuahua. Semen samples were obtained via manual stimulation and diluted to a final sperm concentration of 50 million/ml, and they were subsequently analysed by the computer assisted semen analysis (CASA-Mot) ISAS® v1 system. Eight kinematic parameters were evaluated automatically. All parameters showed significant different values among breeds and among individuals within each breed. The fastest sperm cells were those of Staffordshire Bull Terriers and the slowest were recorded in Chihuahuas. The intra-male coefficient of variation (CV) was higher than the inter-male CV for all breeds with the Staffordshire Bull Terrier showing the lowest values. When taking into consideration the cells by animal and breed, discriminant analyses showed a high capability to predict the breed. Cluster analyses showed a hierarchical classification very close to that obtained after phylogenetic studies with genome markers. In conclusion, future workers on dog spermatozoa should bear in mind major differences between breeds and realize that results cannot be extrapolated from one to another. Because sperm characteristics are associated with breed diversity, dogs may represent a good model to examine changes in reproductive parameters associated with selection processes.
Design of ATM Accessing System for Blind using Real-Time Video Processing through Gestures

million people are visually impaired worldwide: 39 million are blind and 246 million have low vision (severe or moderate visual impairment) preventable cause are as high as 80% of the total global visual impairment burden. Globally, uncorrected refractive errors are the main cause of visual impairment. Cataracts are the leading cause of blindness 65% of visually impaired, and 82% of blind people are over 50 years of age, although this age group comprises only 20% of the world population(1). Blindness can be classified into 3 types, Complete blindness, Night blindness, Color blindness. The main problems faced by blind people: during financial transactions especially in ATMs. In the existing ATMs, Braille is inscribed on the keypad to facilitate blind. But, What if the people doesn't know Braille, how to insert a card? The friend accompanying him might get to know the password or someone else can come to know of his pin number. A stranger might try to help the blind win the trust and rob him. So, we propose to design and develop a safer and secure ATM accessing system for the blind.
Guest Editorial: Simulation in Language Learning

The initial impetus for this symposium issue on using simulations in second or foreign language classes began 8 years ago, during the first graduate Materials Adaptation andDevelopment seminar I taught on the use of simulations and games. It was fortunate that the scheduling of the class coincided with the ISAGA ’94 conference. That year, the conference offered a bargain: two-for-one registration for a professor accompanied by a student. In addition, that year the conference was in North America. We could not resist such a wonderful opportunity. Seven of the students in that seminar went with me to Ann Arbor, Michigan, and presented their work at the conference. Tânia Gastão Saliés’s article, “Promoting Strategic Competence: What Simulations CanDoForYou,” remindsme of the remarks shemade as amember of theYoungEducators panel at that conference. Her article on the benefits and drawbacks of using simulations in a composition class had its beginnings that summer as well. Mary Dean Spelman began to create a simulation around a fictitious, multinational corporation (GLOBECORP) in that seminar, and in her article, she compares the effectiveness of her semester-long simulation with more traditional methods of instruction. Rebecca Damron and I began our collaboration on a game for international students on the plane home from ISAGA ’94, and our article with Carol Lynn Moder (in this issue) describes one of the semester-long simulations we have developed together.
Models of scientific software development

Over the past decade, I have performed several field studies with scientists developing software either on their own or together with software engineers. Based on these field study data, I identify a model of scientific software development as practiced in many scientific laboratories and communities. This model does not fit the standard software engineering models. For example, the tasks of requirement elicitation and software evaluation are not clearly delineated. Nevertheless, it appears to be successful within the context in which it is used. In the context in which scientists collaborate with software engineers, however, I describe problems which arose from the clash of this model with a traditional,phased software engineering model. Given these models, I discuss the issues which have to be addressed in order to determine the software techniques and tools which might best support scientific software development in different contexts.
Simulador virtual para acoso escolar en niños y adolescentes: Un estudio piloto en México

El acoso escolar es un problema que tiene consecuencias criticas en las victimas, que van desde una baja autoestima, depresion y en casos extremos hasta el suicidio. En Mexico el 14% de los estudiantes reporta haber sido victimas de acoso escolar, recibiendo golpes, apodos, malos tratos de forma intencional y continua por parte de sus companeros. Ante este panorama, se han creado diversos programas para prevenir y disminuir los efectos del acoso escolar, muchos de estos programas se enfocan en el desarrollo de conductas prosociales, entre ellas la asertividad. El presente estudio tuvo por objetivo evaluar en una muestra de ninos y adolescentes una aplicacion de realidad virtual de bullying y verificar cambios en las respuestas asertivas de los participantes frente a situaciones simuladas de acoso. Se llevo a cabo un estudio preprueba-posprueba, con un muestreo intencional no probabilistico, en el que se utilizo una aplicacion de realidad virtual que recrea tridimensionalmente 12 situaciones de acoso escolar, en donde se puede dar una respuesta agresiva, pasiva o asertiva. Para evaluar el indice de asertividad se empleo la Escala de Asertividad de Rathus. Los datos obtenidos muestran un incremento en el indice de asertividad al finalizar la aplicacion, ademas de un alto porcentaje de respuestas asertivas en comparacion con las agresivas y pasivas en las situaciones interactivas de acoso.
Prediction in Teaching Pronunciation

Learners and teachers of English as a second or foreign language (ESL/EFL) take for granted that learning grammar means learning rules. They do not often think of learning rules for pronunciation. Instead, images of listening and speaking come to mind. Keywords: esl/efl; language teaching; perception; phonology; pronunciation; prosody
Human thermoregulation; A synergy between physiology and mathematical modeling

This dissertation studies the regulation of the body temperature in both young and old people. Both the skin blood flow (regulation and heat release) and the energy use (heat production) were studied in a cool environment. In old people the core temperature went down, in contrast to the young people. There was, however, no difference in the change of the skin blood flow. On the other hand, young people increased the heat production, whereas that decreased in the elderly. Also, the blood pressure increased three times as much in the elderly as it did in the young people. The newly developed mathematical model shows that the decrease of heat production in the elderly is caused by cooling of the body. As opposed to young people, elderly people lose the capacity to compensate this decrease.
The Research on Bus Scrambling Technology of Cipher SoC Chip

This paper provides a complete solution for bus security protection of cipher SoC chip from the technology of bus security protection. The structure has a scrambling transformation on the data bus of whole cipher chip with the word oriented stream cipher algorithm, and has a scrambling transformation on the address bus of memory cells especially the EFlash with more efficient Benes permutation network. Relative to the cipher SoC chip, the scrambling transformation is transparent and can ensure the security of information transferred on the bus, improve the efficiency of bus scrambling, reduce the area overhead at the same time.