A Comparison of a Computer Programming Approach to a Textbook Approach in Teaching the Mathematics Concept Variable to Sixth Graders.

The purpose of this study was to investigate whether there was a significant difference in understanding the concept of variable and in attitudes toward mathematics among sixth-grade students who programmed LOGO graphics, students who used textbook-based activities, and students who received no instruction on the concept of variable. The subjects were 89 sixth-grade students (47 female, 42 male) from two middle schools in the East Baton Rouge Parish School System. The Test of Logical Thinking (TOLT), Robustness Semantic Differential (RSD), and Comprehensive Test of Basic Skills (CTBS) were administered as pre-treatment tests. The study was conducted in two phases, pre-treatment and treatment. The pre-treatment phase consisted of five fifty-minute lessons designed to teach all students the LOGO basic primitive commands. After there lessons were completed, the students were randomly assigned to either the computer, textbook, or control group. The treatment phase consisted of two approaches for teaching the concept of variable: computer programming and textbook-based. The computer programming approach consisted of five fifty-minute lessons in which students used variables in their graphic procedures (programs). The textbook-based approach consisted of five fifty-minute lessons on the use of variables. The control group worked on mathematics activities during the treatment time but did not receive instruction on the concept of variable. The data were analyzed using univariate analysis of variance procedures. The results indicated that there were no significant differences between computer and textbook groups\u27 posttest scores, textbook and control groups\u27 posttest scores and control and textbook groups\u27 retention test (given three weeks after treatment) scores. Also, no significant difference was found among students\u27 attitudes toward mathematics at the end of treatment. There were significant differences between computer and control groups\u27 posttest scores, computer and textbook groups\u27 retention test scores and computer and control groups\u27 retention test scores. The significant differences favored the computer group. Also, there was a significant positive correlation between students\u27 posttest and retention test scores and their CTBS, TOLT and computer-related RSD scores. The results are discussed with respect to the effect of computer programming instruction on sixth-grade students\u27 understanding of the concept of variable

Taming Wild Faces: Web-Scale, Open-Universe Face Identification in Still and Video Imagery

With the increasing pervasiveness of digital cameras, the Internet, and social networking, there is a growing need to catalog and analyze large collections of photos and videos. In this dissertation, we explore unconstrained still-image and video-based face recognition in real-world scenarios, e.g. social photo sharing and movie trailers, where people of interest are recognized and all others are ignored. In such a scenario, we must obtain high precision in recognizing the known identities, while accurately rejecting those of no interest. Recent advancements in face recognition research has seen Sparse Representation-based Classification (SRC) advance to the forefront of competing methods. However, its drawbacks, slow speed and sensitivity to variations in pose, illumination, and occlusion, have hindered its wide-spread applicability. The contributions of this dissertation are three-fold: 1. For still-image data, we propose a novel Linearly Approximated Sparse Representation-based Classification (LASRC) algorithm that uses linear regression to perform sample selection for l1-minimization, thus harnessing the speed of least-squares and the robustness of SRC. On our large dataset collected from Facebook, LASRC performs equally to standard SRC with a speedup of 100-250x. 2. For video, applying the popular l1-minimization for face recognition on a frame-by-frame basis is prohibitively expensive computationally, so we propose a new algorithm Mean Sequence SRC (MSSRC) that performs video face recognition using a joint optimization leveraging all of the available video data and employing the knowledge that the face track frames belong to the same individual. Employing MSSRC results in a speedup of 5x on average over SRC on a frame-by-frame basis. 3. Finally, we make the observation that MSSRC sometimes assigns inconsistent identities to the same individual in a scene that could be corrected based on their visual similarity. Therefore, we construct a probabilistic affinity graph combining appearance and co-occurrence similarities to model the relationship between face tracks in a video. Using this relationship graph, we employ random walk analysis to propagate strong class predictions among similar face tracks, while dampening weak predictions. Our method results in a performance gain of 15.8% in average precision over using MSSRC alone

Levels Of Learning In Mathematics Teaching And Learning

This paper presents the levels of teaching and learning (concrete, representational and abstract) that could be used to present ideas and concepts in different content areas at different grade levels. When used properly, the levels of learning are powerful tools, facilitators of students’ development of abstract thinking (which happens in the student’s mind), and effective instructional tools for meeting students’ specific learning styles and interests

An approach to the poetry of Rubén Darío and Juan Ramón Jiménez: erotic poetry, poetic eroticism

A través del estudio de la primera poesía de Juan Ramón Jiménez, se indaga en las claves de su poética. Así, se propone una clasificación de su obra en dos ciclos que se fundamenta en los conceptos que el propio autor maneja. Ambos guardan relación con el tratamiento del erotismo: en un primer ciclo, la poética se basa en una concepción transcendente del erotismo y en un segundo ciclo, acontece la renuncia a la dimensión carnal dentro del proceso de depuración poética, identificado con la poesía desnuda. Se abordan los primeros poemarios y el inédito Libros de amor.Trough the study of the first poem of Juan Ramón Jiménez, the keypoints of his poems are explored. This had led to a classification of his works into two phases, which are based on the ideas that the author himself uses. These two phases are closely related to the treatment of eroticism: in the first phase, his poetry is based on a vital idea of eroticism, while in the second phase, which is marked by a transcended eroticism. We have the renunciation of the flesh inside the process of purification of poetry. His first poems and his unpublished book Libros de amor are the ones addressed

Episiotomia e laceração perineal no parto vertical.

Trabalho de Conclusão de Curso - Universidade Federal de Santa Catarina, Centro de Ciências da Saúde, Departamento de Tocoginecologia, Curso de Medicina, Florianópolis, 199

La tasa por ocupación del dominio público por parte de empresas explotadoras de servicios de suministros : problemas actuales

La llamada "tasa del 1,5 por 100" presenta un alto grado de conflictividad juridica en buena medida debida al proceso de liberalización de los servicios públicos de suministros. Esta conflictividad se ha trasladado igualmente a la doctrina científica,que ha llegado incluso a poner en tela dejuicio la propia naturaleza de tasa de la figura. Determinados aspectos de la regulación de esta tasa han resultado especialmente polémicos en el pasado, como la realización del hecho imponible por empresas que no son titulares de las redes que ocupan el dominio público, y otros lo siguen siendo hoy como la delimitación del concepto "ingresos brutos procedentes de la facturación"; aspectos que, entre otros, son analizados en este trabajo.Publicad

Seminario Ética y ciudad

En el seminario se plantearon diversas problemáticas que afectan gravemente la convivencia y el disfrute de nuestras ciudades, cuestionando su viabilidad y posible sostenibilidad social, económica y ambiental. Todo ello nos enfrenta a grandes desafíos en los que el debate sobre la ética es urgente e insoslayable. Sin embargo, la ética del desarrollo urbanístico actualmente está centrada en el crecimiento económico, propiciando una profunda crisis civilizatoria. En contraparte, también se profundizó en algunas transformaciones que se han venido haciendo en México y Latinoamérica, como son: el derecho a la ciudad, la producción social del hábitat y la gestión participativa de las ciudades y del hábitat humano en general en su interacción con la naturaleza.ITESO, A.C

Effects of crop rotation and nitrogen fertilization on soil nitrate concentration and corn yield

Increasing concerns about production cost and environmental impacts of N fertilization require improving N management. The objectives of this study were to evaluate effects of cropping sequences and N fertilization on (1) corn yield and yield stability and (2) soil nitrate concentration in two Iowa long-term rotation experiments and (3) to assess the performance of the late spring nitrate test (LSNT) to assess N availability for corn in several cropping sequences. The experiments were near Kanawha (20 yrs) and Nashua (26 yrs) and N fertilization rates for corn were 0, 90, 180, 270 kg N ha -1. Rotations in Kanawha were continuous corn with spring N (Csp), continuous corn with fall N (Cfl), corn-corn-corn-oat, corn-soybean, corn-soybean-corn-oat, corn-corn-oat-alfalfa, and corn-oat-alfalfa-alfalfa. Rotations in Nashua were continuous corn, corn-soybean, corn-corn-soybean, corn-corn-corn-soybean, and corn-corn-oat-alfalfa. The results indicated that corn yield was higher and yield response to N was lower in the order corn after alfalfa \u3e after soybean or oat undersown with alfalfa, and after alfalfa. There were no significant differences between response to N of continuous corn and second- or third-year corn after soybean. On average, N rates producing maximum observed net returns ranged from 270 kg N ha-1 for corn after corn to zero N for corn after alfalfa. On average, Csp yielded 8.7 more than Cfl and the highest N rate used did not produce yield as high as those observed for corn in rotation. Corn yield across time was higher and more stable with N fertilization and when legumes were included in rotation. Observed maximum net returns to N increased over the time but the relative response to N fertilization did not change consistently. The highest soil nitrate concentrations were observed for corn after alfalfa and corn with N fertilization. Soil nitrate concentrations were higher for Csp than Cfl. Fertilization increased soil nitrate linearly for all corn crops and rates of increase were similar, except for smaller increases for Cfl and Csp. A certain nitrate concentration resulted in higher relative corn yield for corn after alfalfa. The results support guidelines for use of the LSNT test in Iowa

Memory properties of spatially-extended disordered materials

Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2023, Tutor: Jordi Ortín RullMemory is a fascinating phenomenon that has many interesting applications. This work focuses on Return-Point Memory (RPM), which is a particular type of memory present on ferromagnetic, spatially-extended disordered systems that manifests through quasistatic hysteresis. By modelling these materials using the fluctuationless Random Field Ising Model (T=0 RFIM) and computing the magnetization trajectories via a cellular automaton, we observe RPM, thus proving the validity of the model for this purpose, and analyze it qualitatively both at macroscopic and microscopic scales. We also perform a study on energy dissipation in this model and its relation with hysteresis and Barkhausen magnetization jump

View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network

This paper describes the details of Sighthound's fully automated vehicle make, model and color recognition system. The backbone of our system is a deep convolutional neural network that is not only computationally inexpensive, but also provides state-of-the-art results on several competitive benchmarks. Additionally, our deep network is trained on a large dataset of several million images which are labeled through a semi-automated process. Finally we test our system on several public datasets as well as our own internal test dataset. Our results show that we outperform other methods on all benchmarks by significant margins. Our model is available to developers through the Sighthound Cloud API at https://www.sighthound.com/products/cloudComment: 7 Page