Electromagnetic waves consist of oscillating electric and magnetic fields perpendicular to each other that propagate through space carrying electromagnetic radiant energy. The electromagnetic spectrum ranges from gamma rays to radio waves and includes visible light, which is a small portion of the full spectrum. Electromagnetic waves travel at the speed of light and their wavelength and frequency are related by the equation that defines the speed of light. Reflection and refraction of light can be described using laws of optics and ray diagrams. Reflection occurs when light changes direction upon contact with a new medium, and refraction is the bending of light that occurs when passing from one medium to another due to the speed of light changing.
Light - Reflection and Refraction, Class X, CBSE, ScienceDevesh Saini
PowerPoint Presentation covering all the concepts and topics of the chapter : Light- Reflection and Refraction of class X (CBSE).
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Light - Reflection and Refraction, Class X, CBSE, ScienceDevesh Saini
PowerPoint Presentation covering all the concepts and topics of the chapter : Light- Reflection and Refraction of class X (CBSE).
This is exactly what you are looking for.
Don't forget to comment and give feedback.
SMK Ungku Aziz (SMKUA) berasal dari sekolah menengah kebangsaan yang ditubuhkan pada tahun 1959. Sekolah ini antara beberapa buah sekolah Melayu ditubuhkan di Sabak Bernam, Parit Baru dan Sungai Besar. Sekolah ini dengan rasminya dibuka pada 27 Julai 1964 oleh Yang Berhormat Menteri Pelajaran Malaysia ketika itu iaitu Encik Abdul Rahman Talib, PJK. Nama sekolah ini juga diambil sempena nama tokoh yang terkenal pada masa itu iaitu Profesor Diraja Ungku Aziz, Naib Censelor Universiti Malaya.
FOKUS KAJIAN DAN ISU KEPRIHATINAN
Kajian yang dilakukan ini adalah berfokuskan kepada kebolehan pelajar untuk memahami konsep rangkaian dan menggunakan rangkaian LAN (Local Area Network) sebagai kaedah bagi memahami konsep rangkaian. Saya juga menggunakan kaedah amali bagi melengkapi fokus kajian saya. Di dalam refleksi pengajaran dan pembelajaran sebelum ini mendapati terdapat beberapa kelemahan yang perlu diatasi terutamanya dari segi kaedah pengajaran, gaya penyampaian dan pendekatan yang diambil. Sebagai contoh ketika proses pengajaran dan pembelajaran sebelum ini, murid tidak mendapat gambaran yang jelas tentang topik yang diajar kerana guru lebih banyak membaca slaid berbanding membuat penerangan secara terperinci dan memberi contoh.
Bagi topik yang diajar pada sesi lepas, ia sebenarnya memerlukan lebih daripada contoh kerana topik ini melibatkan konsep yang sangat abstract bagi pelajar yang rata-rata masih baru didalam dunia teknolgi. Seperti yang kita tahu, kefahaman pelajar terhadap topik yang diajar sangat penting. Oleh itu, saya akan menggunakan kaedah pengajaran berasaskan amali dan menggunakan model pengajaran ASSURE untuk melengkapkan kajian saya ini.
OBJEKTIF KAJIAN
Selepas kajian ini dijalankan, adalah diharapkan murid akan mencapai objektif berikut:
Objektif umum :
Memberi kefahaman kepada pelajar dengan lebih jelas dengan kaedah pengajaran yang betul dan dibantu alat bahan bantu mengajar yang sesuai supaya pelajar dapat terlibat secara aktif di dalam kelas seterusnya meningkatkan fokus pelajar.
Objektif Khusus:
1. Meningkatkan tumpuan pelajar terhadap proses pembelajaran.
2. Menarik minat pelajar dengan penggunaan gambar.
3. Memberi kefahaman yang lebih terperinci.
6.0 KUMPULAN SASARAN
Kumpulan pelajar yang terlibat dalam kajian ini ialah 16 orang pelajar Tingkatan 4 IT untuk memahami jenis-jenis rangkaian di dalam subjek Teknologi Maklumat dan Komunikasi.
7.0 PELAKSANAAN KAJIAN
Kajian ini dilakukan dengan menggunakan model ASSURE untuk melengkapkan proses dapatan kajian. Menggunakan enam elemen didalam model ASSURE akan menjadi satu proses lengkap dalam menyediakan hasil kajian yang bakal dilakukan. Model ini mengetengahkan beberapa faktor utama iaitu dari segi kaedah pengajaran dan alat bantu mengajar yang mana akan menjadi keutamaan dalam kajian ini.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Deep Software Variability and Frictionless Reproducibility
LIGHT , REFACTION AND REFRACTION CLASS 10TH
1.
2.
3. Electromagnetic Waves
Magnetic field wave perpendicular to an electric field wave
All objects emit EMWs.
Temp EMW
Electromagnetic spectrum
Range of all frequencies of light
Visible light is a very small portion of that entire spectrum.
4.
5. c
Speed of Light - 3.00 x 108m/s.
= (wavelength) x (frequency)
c = ƒ
7. Visible Light
Part of the EMS humans can see
Red - 750nm (x10-9m)
Purple - 380nm
Bees, Birds – UV
Snakes – IR
8. Reflection
Light waves usually travel in straight paths
Change in substance changes direction
Opaque - does not permit light
some light reflected
some light absorbed as heat
9. Reflection
Texture affects reflection
Diffuse reflection (rough)
reflects light in many different directions,
Specular reflection (smooth)
reflects light in only one direction
Smooth – variations in surface
15. Concave Spherical Mirrors
Reflective surface is on the interior of a curved surface
C – center of curvature
R – Radius (distance to C)
f – Focal Point (1/2 R)
Principal axis
any line that passes through C
usually oriented with an object
19. Concave Spherical Mirror Rules
A ray traveling through C will reflect back through C
A ray traveling through (f) will reflect parallel to the PA
A ray traveling to the intersection of the PA and the mirror will reflect at
the same angle below the PA.
A ray traveling parallel to PA will reflect through the focal point
20. Ray Diagrams
Draw three rays
The image forms at the point of intersection
Example
f = 10.0cm
p = 30.0cm
h = 3.00cm
23. Rules
A ray parallel to the PA will reflect directly away from f.
A ray towards f will reflect parallel to the PA
A ray towards C will reflect directly away from C.
A ray to the intersection of PA and mirror will reflect at the same
angle below the OA.
Trace the 3 diverging lines back through the mirror to reveal the
location of the image which is always virtual
26. Parabolic Mirrors
Rays that hit spherical mirrors far away from the OA often
reflect though other points causing fuzzy images, spherical
aberration.
Telescopes use parabolic mirrors as they ALWAYS focus the
rays to a single point.
27.
28. Refraction
Substances that are transparent or translucent allow light to
pass though them.
Changes direction of light
Due to the differences in speed of light
29. Analogy
A good analogy for refracting light is a lawnmower
traveling from the sidewalk onto mud
30. Index of Refraction (n)
The ratio of the speed of light in a
vacuum to the speed of light in a
medium
n - c
35. Total Internal Reflection
If the angle of incidence of a ray is greater than a certain critical
angle the ray will reflect rather than reflect
This principal is responsible for the properties of fiber optic
cables.
Remember the lawn mower analogy…
36.
37. Critical Angle
sin Θc = nr / ni
As long as nr < ni
What is the critical angle for light traveling from
Diamond to Air?
39. Converging Lens Diagram
1. Ray parallel to PA, refracts through far focal point
2. Ray through center of lens, continues straight line
3. Ray through near focal point, refracts through lens, continues
parallel to PA
Treat lens as though it were a flat plane.
40.
41. Diverging Lens Diagram
Because the rays that enter a diverging lens do not intersect a virtual
image is formed by tracing back the refracted rays.
Ray 1 - parallel to PA, refracts away from near f, trace back to near f.
Ray 2 - ray toward far f, refracts parallel to PA, trace back parallel to PA
Ray 3 - ray through center, continues straight, trace back toward object
42.
43. Sign Conventions for Lens
Sign p q F
+ Near side
of lens
Far side of
lens
Convergin
Lens
– Far side of
lens
Near side
of lens
Diverging
Lens