Codenamed it as TOAST …stands for The Object And Space state Transform, the expression T in angular bracket indicates generalness as applied to any domains such as scientific, commercial, medical, robotics etc….
The space by itself represents layered structure in term of inner space, micro inner space as well as set of outer spaces lik...e mega, ultra, super….thereby representing subatomic to cosmic [light year] spaces. It is possible to define regions of spaces which in turn are space by them self. The spaces can have vectors operating at space level or at point level as discrete effect.
You can add objects in spaces which are nothing but bound space along with number of properties, behaviors, transforms and tendencies. The objects can interact with other objects and spaces by it. Every object, space, point in space has relative time dimension, thereby enabling “Relativity”. You may also define virtual spaces for business data mining.
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barch_1st sem_anna univ. affl._msajaa_INTRODUCTION TO ARCHITECTURE_ELEMENTS OF ARCHITECTURE_ELEMENTS OF ARCHITECTURE – FORM_ELEMENTS OF ARCHITECTURE – SPACE_PRINCIPLES OF ARCHITECTURE
This paper extends the notion that the profile of knowledge is
dynamic and oscillates continuously. It is derived/interpreted
ceaselessly from information, experience, social interactions,
Internet, etc. On an individual basis, the contours of
knowledge thus derived are altered in numerous dimensions
(as the user learns from the events in the society) thus altering
its geometry. The dynamically updated knowledge blends
onto concepts. The main theme of the paper includes time as
a dimension in the knowledge space wherein nature, humans,
and machines influence noun „objects‟. Further, in this paper,
we also introduce a virtual object „knowbula‟. This word is
derived as a merge of two words knowledge and Nebula.
Mathematically, knowbula is a 3-D envelope of the all
activities in any field of human endeavor, whatsoever. Such
an assertion has three prerequisites: (a) that human activity
deals with objects (real, abstract, virtual, or just about
anything(s)), that bear coordinates in an more encompassing
universal knowledge space, (b) objects relates to what they
do, how they do what they do, or how they are affected by the
actions of other objects, and (c) that there is time constraint
(i.e., begin, middle and end identifiers) associated with such
actions. Knowledge is thus contained in the knowbula and the
change in the contour/image of this knowbula during/after the
interval of activity: activity thus produces the incremental
change of knowledge. Thus knowbula starts to become a three
dimensional virtual object, with the (noun) objects (objective,
subjective, or virtual) along the X-first, axis, the correlated
(verb) functions or activity, (active, passive, or hypothetical)
along the Y-second, axis and time along the Z-third, axis.
Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful, patterns from large spatial datasets. Clustering is one of the most valuable methods in spatial data mining. As there exist a number of methods for clustering. We analyses different approaches to clustering spatial data, we present some solutions devised to manipulate such data and we find out the main strengths and drawbacks of each method. Then, we present a new method for clustering complex training observations arranged in a graph (called discrete spatial structure). The method, named COSSO (Clustering Of Structured Spatial Objects), clusters observations on the basis of two criteria: i) each cluster should correspond to a connected sub graph of the original discrete spatial structure, and ii) observations in a cluster should be similar according to a similarity measure defined for structured objects (i.e., objects described by multiple database relations). Finally, we present specific issues of the proposed method, namely the selection of the seed observations and the evaluation of the homogeneity of a cluster.
11. Define a simple deformable model to detect a half-circular shape.pdffeetshoemart
11. Define a simple deformable model to detect a half-circular shape (may be rotated). What will
be the energy function?
Solution
shape is a recurring theme in computer vision. For example, shape is one of the main sources of
information that can be used for object recognition. In medical image analysis, geometrical
models of anatomical structures play an important role in automatic tissue segmentation. The
shape of an organ can also be used to diagnose diseases. In a completely different setting, shape
plays an important role in the perception of optical illusions (we tend to see particular shapes)
and this can be used to explain how our visual system interprets the ambiguous and incomplete
information available in an image. Our main goal is to develop techniques that can be used to
represent and detect relatively generic objects in images. The techniques we present here revolve
around a particular shape representation, based on the description of objects using triangulated
polygons. Triangulated polygons allow us to describe complex shapes using simple building
blocks. As we show in the next section, the triangles that decompose a polygon without holes are
connected together in a tree structure, and this has important algorithmic consequences. By
picking a particular triangulation for the polygons we obtain decompositions of objects into
meaningful parts. This yields a discrete representation closely related to Blum’s medial axis
transform [6]. In this paper we concentrate on the task of finding the location of a deformable
shape in an image. This problem is important for the recognition of non-rigid objects. Moreover,
objects in many generic classes can be described as deformed versions of an ideal template. In
this setting, the location of an object is given by a continuous map from a template to an image.
Figure 1 illustrates how we use a deformable template to detect a particular anatomical structure
in an MR image. We will show how triangulated polygons provide rich models for deformable
shapes. These models can capture both boundary and interior information of an object and can be
deformed in an intuitive way. Equally important, we present an efficient algorithm for finding
the optimal location of a deformable shape in an image. In contrast, previous methods that take
into account the interior of deformable objects.
The geometric properties of rigid objects are well understood. We know how three dimensional
features such as corners or edges project into images, and there are a number of methods that can
be used to represent rigid shapes and locate their projections. Some techniques, such as the
alignment method [23], use explicit three dimensional representations. Other techniques, such as
linear combination of views [36], capture the appearance of three dimensional shapes using a
small number of two dimensional pictures. These and similar techniques assume that all shape
variation comes from the viewpoint dependency of two dimensiona.
Extending the knowledge level of cognitive architectures with Conceptual Spac...Antonio Lieto
Extending the knowledge level of cognitive architectures with Conceptual Spaces (+ a case study with Dual-PECCS: a hybrid knowledge representation system for common sense reasoning). Talk given at Stockholm, September 2016.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
barch_1st sem_anna univ. affl._msajaa_INTRODUCTION TO ARCHITECTURE_ELEMENTS OF ARCHITECTURE_ELEMENTS OF ARCHITECTURE – FORM_ELEMENTS OF ARCHITECTURE – SPACE_PRINCIPLES OF ARCHITECTURE
This paper extends the notion that the profile of knowledge is
dynamic and oscillates continuously. It is derived/interpreted
ceaselessly from information, experience, social interactions,
Internet, etc. On an individual basis, the contours of
knowledge thus derived are altered in numerous dimensions
(as the user learns from the events in the society) thus altering
its geometry. The dynamically updated knowledge blends
onto concepts. The main theme of the paper includes time as
a dimension in the knowledge space wherein nature, humans,
and machines influence noun „objects‟. Further, in this paper,
we also introduce a virtual object „knowbula‟. This word is
derived as a merge of two words knowledge and Nebula.
Mathematically, knowbula is a 3-D envelope of the all
activities in any field of human endeavor, whatsoever. Such
an assertion has three prerequisites: (a) that human activity
deals with objects (real, abstract, virtual, or just about
anything(s)), that bear coordinates in an more encompassing
universal knowledge space, (b) objects relates to what they
do, how they do what they do, or how they are affected by the
actions of other objects, and (c) that there is time constraint
(i.e., begin, middle and end identifiers) associated with such
actions. Knowledge is thus contained in the knowbula and the
change in the contour/image of this knowbula during/after the
interval of activity: activity thus produces the incremental
change of knowledge. Thus knowbula starts to become a three
dimensional virtual object, with the (noun) objects (objective,
subjective, or virtual) along the X-first, axis, the correlated
(verb) functions or activity, (active, passive, or hypothetical)
along the Y-second, axis and time along the Z-third, axis.
Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful, patterns from large spatial datasets. Clustering is one of the most valuable methods in spatial data mining. As there exist a number of methods for clustering. We analyses different approaches to clustering spatial data, we present some solutions devised to manipulate such data and we find out the main strengths and drawbacks of each method. Then, we present a new method for clustering complex training observations arranged in a graph (called discrete spatial structure). The method, named COSSO (Clustering Of Structured Spatial Objects), clusters observations on the basis of two criteria: i) each cluster should correspond to a connected sub graph of the original discrete spatial structure, and ii) observations in a cluster should be similar according to a similarity measure defined for structured objects (i.e., objects described by multiple database relations). Finally, we present specific issues of the proposed method, namely the selection of the seed observations and the evaluation of the homogeneity of a cluster.
11. Define a simple deformable model to detect a half-circular shape.pdffeetshoemart
11. Define a simple deformable model to detect a half-circular shape (may be rotated). What will
be the energy function?
Solution
shape is a recurring theme in computer vision. For example, shape is one of the main sources of
information that can be used for object recognition. In medical image analysis, geometrical
models of anatomical structures play an important role in automatic tissue segmentation. The
shape of an organ can also be used to diagnose diseases. In a completely different setting, shape
plays an important role in the perception of optical illusions (we tend to see particular shapes)
and this can be used to explain how our visual system interprets the ambiguous and incomplete
information available in an image. Our main goal is to develop techniques that can be used to
represent and detect relatively generic objects in images. The techniques we present here revolve
around a particular shape representation, based on the description of objects using triangulated
polygons. Triangulated polygons allow us to describe complex shapes using simple building
blocks. As we show in the next section, the triangles that decompose a polygon without holes are
connected together in a tree structure, and this has important algorithmic consequences. By
picking a particular triangulation for the polygons we obtain decompositions of objects into
meaningful parts. This yields a discrete representation closely related to Blum’s medial axis
transform [6]. In this paper we concentrate on the task of finding the location of a deformable
shape in an image. This problem is important for the recognition of non-rigid objects. Moreover,
objects in many generic classes can be described as deformed versions of an ideal template. In
this setting, the location of an object is given by a continuous map from a template to an image.
Figure 1 illustrates how we use a deformable template to detect a particular anatomical structure
in an MR image. We will show how triangulated polygons provide rich models for deformable
shapes. These models can capture both boundary and interior information of an object and can be
deformed in an intuitive way. Equally important, we present an efficient algorithm for finding
the optimal location of a deformable shape in an image. In contrast, previous methods that take
into account the interior of deformable objects.
The geometric properties of rigid objects are well understood. We know how three dimensional
features such as corners or edges project into images, and there are a number of methods that can
be used to represent rigid shapes and locate their projections. Some techniques, such as the
alignment method [23], use explicit three dimensional representations. Other techniques, such as
linear combination of views [36], capture the appearance of three dimensional shapes using a
small number of two dimensional pictures. These and similar techniques assume that all shape
variation comes from the viewpoint dependency of two dimensiona.
Extending the knowledge level of cognitive architectures with Conceptual Spac...Antonio Lieto
Extending the knowledge level of cognitive architectures with Conceptual Spaces (+ a case study with Dual-PECCS: a hybrid knowledge representation system for common sense reasoning). Talk given at Stockholm, September 2016.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
How world-class product teams are winning in the AI era by CEO and Founder, P...
Space Object State transform
1. THE SPACE OBJECT STATE TRANSFORM Framework to realize spacesand objects . To define and perform transforms, behaviors actions SHRIPADRAJ MUJUMDAR [ PRASANNA] prasannam@yahoo.com
2.
3. In modern mathematics spaces are defined as sets with some added structure. They are frequently described as different types of manifolds which are spaces that locally approximate to Euclidean space and where the properties are defined largely on local connectedness of points that lie on the manifold. There are however, many diverse mathematical objects that are called spaces. For example, function spaces in general have no close relation to Euclidean space.
4. Theories such as string theory and M-theory predict that physical space in general has in fact 10 and 11 dimensions, respectively. The extra dimensions are spatial. We perceive only three spatial dimensions, and no physical experiments have confirmed the reality of additional dimensions. A possible explanation that has been suggested is that space acts as if it were "curled up" in the extra dimensions on a subatomic scale, possibly at the quark/string level of scale or below Shripadraj Mujumdar [ Prasanna] prasannam@yahoo.com
5. Overview Geometry is concerned with questions of size, shape, relative position of figures, and the properties of space. Geometry is one of the oldest sciences. Initially a body of practical knowledge concerning lengths, areas, and volumes, in the 3rd century BC geometry was put into an axiomatic form by Euclid, whose treatment—Euclidean geometry—set a standard for many centuries to follow. Since the 19th-century discovery of non-Euclidean geometry, the concept of space has undergone a radical transformation. Contemporary geometry considers manifolds, spaces that are considerably more abstract than the familiar Euclidean space, which they only approximately resemble at small scales. These spaces may be endowed with additional structure, allowing one to speak about length. Modern geometry has multiple strong bonds with physics, exemplified by the ties between Riemannian geometry and general relativity. One of the youngest physical theories, string theory, is also very geometric in flavor. Shripadraj Mujumdar [ Prasanna] prasannam@yahoo.com
6. Framework Concept Codenamed it as TOAST …stands for The Object And Space state Transform, the expression T in angular bracket indicates generalness as applied to any domains such as scientific, commercial, medical, robotics etc…. The Framework being discussed here , allows you to create various types of spaces of complex nature as we saw It allows both mathematical and virtual model The Mathematical model is useful for statistical, scientific, engineering applications The Virtual Model is useful for representing data across non numeric dimensions, like we do in data warehousing The Hybrid Model- you can mix both models to create your own complex domain representation as domain space Shripadraj Mujumdar [ Prasanna] prasannam@yahoo.com
7. Framework Concept A physical body is an enduring object that exists throughout a particular trajectory of space and orientation over a particular duration of time, and which is extended in the world of physical space. You can add objects to spaces. Object by itself holds space inside it and in fact represent a bound space. The objects have set of properties, behaviors, constraints ,transforms, abilities, tendencies Objects may have Vectors, operating within them, on them The Objects and Spaces are connected to each other through references and events Shripadraj Mujumdar [ Prasanna] prasannam@yahoo.com
8. Framework Use and Benefits Shripadraj Mujumdar [ Prasanna] prasannam@yahoo.com
9. THE SPACE OBJECT STATE TRANSFORM SPACE Shripadraj Mujumdar [ Prasanna] prasannam@yahoo.com
10. DEFINITION OF SPACE Supported Possible Typical Space The space by itself represents layered structure in term of inner space, micro inner space as well as set of outer spaces like mega, ultra, super….thereby representing subatomic to cosmic [light year] spaces. It is possible to define regions of spaces which in turn are space by them self. The spaces can have vectors operating at space level or at point level as discrete effect.
11. OBJECT CONTAINMENT IN TYPICAL SPACE OBJECT You can add objects in spaces which are nothing but bound space along with number of properties, behaviors, transforms and tendencies. The objects can interact with other objects and spaces by it. Every object, space, point in space has relative time dimension, thereby enabling “Relativity”. You may also define virtual spaces for business data mining.
12. SPACER OBJECT MODEL Abstract Generic Numerical Virtual Layer Numerical, varieties Domain Customized Virtual Layer The diagram illustrates types of spaces, essentially all are multidimensional, The Virtual space essentially can be numeric underlying if need be. The hybrid spaces can be constructed by using various types of dimensions
14. POINTS SPACE DIMENSIONS DIMENSIONAL COORDINATES Space is defined by dimensions, each dimension has set of coordinates. Space can hold a minimal object of zero dimensional values, a Point . Point can be physical or virtual based on type of space
18. THE SPACE OBJECT STATE TRANSFORM INTERACTION Shripadraj Mujumdar [ Prasanna] prasannam@yahoo.com
19. SPACE OBJECT INTERACTION Spaces and objects can be acted by external actions. Changes in space composition will result in event being generated, which can be heard inside or outside the boundary of space. The objects in space can move in multiple directions, The objects can change their constituent elements. Whenever there is change in objects elements events are raised. Events of objects also can be heard either inside or outside thee boundary of space External Actions Object External Actions Object External Actions
20. VECTORS Object Spaces can have vectors, acting inside in various directions. The direction is also characterized as multidimensional in nature . The Vectors can exist loosely in space , in and around objects and at specific points. The exact nature of vector depends on domain of application. E.g. in Physical Space the vector can be say Gravitational or Spin
21. TRANSFORMATION AND BEHAVIOR Object Object Spinning Object Object The Objects and space can get transformed , under external or internal influences, and the influence also may be created by interactions. The transformation can be related to any of the characteristics ,such as change in dimensions, change in properties etc. The Objects and Spaces as well can show specific behaviors which potentially can be set of repeated transforms. Object
25. Distributed architecture with devices Space Actors Load Balanced Services Service Endpoint Object Related code moves to different execution space , can support device oriented mechanism UI Presentation Service
26. Distributed architecture with devices Space Access mechanisms The Device can carry copy of space if its relatively static Carry GUID of space, and access the details through service Service