current emotion

Early diagnosis of pneumonia is crucial to increase the chances of survival and reduce the recovery time of the patient. Chest X-ray images, the most widely used method in practice, are challenging to classify. Our aim is to develop a machine learning tool that can accurately classify images as belonging to normal or infected individuals. A support vector machine (SVM) is attractive because binary classification can be represented as an optimization problem, in particular as a Quadratic Unconstrained Binary Optimization (QUBO) model, which, in turn, maps naturally to an Ising model, thereby making annealing—classical, quantum, and hybrid—an attractive approach to explore. In this study, we offer a comparison between different methods: (1) a classical state-of-the-art implementation of SVM (LibSVM); (2) solving SVM with a classical solver (Gurobi), with and without decomposition; (3) solving SVM with simulated annealing; (4) solving SVM with quantum annealing (D-Wave); and (5) solving SVM using Graver Augmented Multi-seed Algorithm (GAMA). GAMA is tried with several different numbers of Graver elements and a number of seeds using both simulating annealing and quantum annealing. We found that simulated annealing and GAMA (with simulated annealing) are comparable, provide accurate results quickly, competitive with LibSVM, and superior to Gurobi and quantum annealing.

Frontiers | Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM)

Metode SVM Support Vector Machine Support Vector Machine (SVM) merupakan salah satu metode yang banyak mendapat perhatian dalam Pattern Recognition sebagai state of the art. Di mana pattern recognition, adalah metode pemetaan suatu data ke dalam konsep tertentu yang disebut juga Category atau Class. Selengkapnya dapat dilihat pada: https://ardonstatistika.com/2022/12/06/metode-svm-support-vector-machine/

Metode SVM Support Vector Machine Support Vector Machine (SVM) merupakan salah satu metode yang banyak mendapat perhatian dalam Pattern Recognition sebagai state of the art. Selengkapnya dilihat pada: https://ardonstatistika.com/2022/12/06/metode-svm-support-vector-machine/

If you did not already know

Multi-Distance Support Matrix Machine (MDSMM) Real-world data such as digital images, MRI scans and electroencephalography signals are naturally represented as matrices with structural information. Most existing classifiers aim to capture these structures by regularizing the regression matrix to be low-rank or sparse. Some other methodologies introduce factorization technique to explore nonlinear relationships of matrix data in kernel space. In this paper, we propose a multi-distance support matrix machine (MDSMM), which provides a principled way of solving matrix classification problems. The multi-distance is introduced to capture the correlation within matrix data, by means of intrinsic information in rows and columns of input data. A complex hyperplane is established upon these values to separate distinct classes. We further study the generalization bounds for i.i.d. processes and non i.i.d. process based on both SVM and SMM classifiers. For typical hypothesis classes where matrix norms are constrained, MDSMM achieves a faster learning rate than traditional classifiers. We also provide a more general approach for samples without prior knowledge. We demonstrate the merits of the proposed method by conducting exhaustive experiments on both simulation study and a number of real-word datasets. … Densely Supervised Grasp Detector (DSGD) This paper presents Densely Supervised Grasp Detector (DSGD), a deep learning framework which combines CNN structures with layer-wise feature fusion and produces grasps and their confidence scores at different levels of the image hierarchy (i.e., global-, region-, and pixel-levels). Specifically, at the global-level, DSGD uses the entire image information to predict a grasp and its confidence score. At the region-level, DSGD uses a region proposal network to identify salient regions in the image and predicts a grasp for each salient region. At the pixel-level, DSGD uses a fully convolutional network and predicts a grasp and its confidence at every pixel. The grasp with the highest confidence score is selected as the output of DSGD. This selection from hierarchically generated grasp candidates overcomes limitations of the individual models. DSGD outperforms state-of-the-art methods on the Cornell grasp dataset in terms of grasp accuracy. Evaluation on a multi-object dataset and real-world robotic grasping experiments show that DSGD produces highly stable grasps on a set of unseen objects in new environments. It achieves 96% grasp detection accuracy and 90% robotic grasping success rate with real-time inference speed. … Neural Block Sampling Efficient Monte Carlo inference often requires manual construction of model-specific proposals. We propose an approach to automated proposal construction by training neural networks to provide fast approximations to block Gibbs conditionals. The learned proposals generalize to occurrences of common structural motifs both within a given model and across models, allowing for the construction of a library of learned inference primitives that can accelerate inference on unseen models with no model-specific training required. We explore several applications including open-universe Gaussian mixture models, in which our learned proposals outperform a hand-tuned sampler, and a real-world named entity recognition task, in which our sampler’s ability to escape local modes yields higher final F1 scores than single-site Gibbs. … Knowledge Space Theory Knowledge space theory by Doignon and Falmagne (1999) is a set- and order-theoretical framework which proposes mathematical formalisms to operationalize knowledge structures in a particular domain. … https://analytixon.com/2023/03/09/if-you-did-not-already-know-1985/?utm_source=dlvr.it&utm_medium=tumblr

B-Art x SVM - HIT IT

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Análisis de Ciberataques en una Ciudad Inteligente

libro de transformacion 2021

Estado Del Arte

Miray botnet, un ataque de tipo DDos, realizo ataques utilizando mas de 400,000 dispositivos de manera simultanea y distribuida en equipos zombi.

105 millones de ataques a dispositivos IoT que se originan a partir de direcciones IP únicas en más de 276.000 ubicaciones esto indica que los ciberataques están creciendo exponencialmente en línea con el creciente despliegue de estos dispositivos.

abordamos el uso de máquinas de soporte vectorial para entrenar un algoritmo de aprendizaje automático utilizando el conjunto de datos NSL-KDD con el que queremos predecir conexiones de tipo maligno en función de las características que cada tipo de conexión puede presentar hacia Dispositivos IoT.

Metodologia

mostramos un pequeño diagrama de un modelo de conexión de un prototipo para dispositivos dispositivo IoT.

Empleamos para el entrenamiento del algoritmo, el uso del conjunto de datos NSL KDD el cual contiene 4,900,000 registros de conexiones dentro de las cuales podemos identificar 4 principales grupos de los cuales contienen 42 características, dentro de los registros podremos encontrar conexiones normales como ataques. En la tabla 1, se muestra el nombre de esta característica para cada instancia dentro de la base de datos.

En el set de datos NSL-KDD se encuentra cuatro clases principales en función de las características que presentan cada una de estas y se muestran en la tabla 2.

3.1 Matriz de confusión

En el campo de la inteligencia artificial así como para aprendizaje automático se emplean las matriz de confusión, la cual es una herramienta que nos permitirá previsualizar el desempeño de un algoritmo; dentro de la matriz de confusión cada columna representa el numero de predicciones de cada clase, así como las filas son instancias de las clases reales, así como se presentan en la Tabla 3.

Tabla 3. Conjunto de métricas para la matriz de confusión.

Conclusiones Y Trabajos Futuros.

Los resultados obtenidos con SVM muestran que es un buen algoritmo para trabajar con aprendizaje supervisado, pero sería necesario compararlo con otros algoritmos. Notamos que el algoritmo seleccionado es bueno para el reentrenamiento en caso de actualización de amenazas así como en la escalabilidad de los datos, que son características que nos ayudaron en la selección del algoritmo, mismo que tendremos que comparar con otros algoritmos.

Referencias

[1] H. Sossa, P. Rayón y J. Figueroa. Arquitectura basada en redes neuronales para el reconocimiento de rostros. Soluciones Avanzadas. Año 7, No. 63. Noviembre 1998. [2] P. Rayón and H. Sossa. A procedure to select the vigilance threshold for the ART2 for supervised and unsupervised training. LNAI 1793, pp. 389-400, Springer Verlag, 2000. [3] G.A. Carpenter and S. Grossberg, ART2: self-organizing of stable category recognition codes for analog input patterns. Applied Optics, 26, pp. 4919-4930, 1987. [4] R. Schalkoff, Pattern Recognition: statistical, structural and neural approaches. John Wiley & Sons, Inc., 1992. [5] J. A. Freeman and D. M. Skapura, Neural Networks: algorithms, applications and programming techniques. Addison Wesley, 1992. [6] A. S. Pandya and R. B. Macy, Pattern Recognition with Neural Networks in C++. IEEE Press, 1995. [7] G. Francis, The stability-plasticity dilemma in competitive learning. Department of Psychology Sciences. Purdue University. Technical Report No. 96-1, 1996. [8] C. G. Looney, Pattern Recognition using Neural Networks. Oxford University Press, 1999. [9] Khalid Saeed et. Al Progress in Advanced Computing and Intelligent Engineering. India, Springer, 693 pp.

Support Vector Machine (SVM) merupakan salah satu metode yang banyak mendapat perhatian dalam Pattern Recognition sebagai state of the art. Di mana pattern recognition, adalah metode pemetaan suatu data ke dalam konsep tertentu yang disebut juga Category atau Class.

SHARDA SARVHITKARI MODEL SR SEC SCHOOL SECTOR 40D CHANDIGARH FLUID ACRYLIC  COLOUR ART ACTIVITY   Students of class 6th made beautiful Canvas designs with fluid acrylic colours based on various colour techniques taught by Art Teacher Ms.Rashim.Students showed keen interest in this activity of FLUID COLOUR ART in their drawing class where they learnt many new things of using new colour schemes using acrylic colours. #vidyabharatipunjab #sarvhitkarieducationalsociety #sarvhitkari #svm sarvhitkari.org

Side A: Giovanni

What does music mean to you? How does it make you feel?

So music to me is like the embodiment of human emotions and thoughts and yeah, at the same time it is still something really universal and ethereal because, I don't know, it's the middle of the emotions and the tangible things that we have as humans. And I don't know, it just makes me feel good, man. Like good and sexy, nostalgic, sad, then still sexy then sexy and sexy and sexy and sexy. That's it.

How big of a part does music play in your life and career?

To me, music is definitely one of the biggest part of my life because well, career wise, I would love to work in the music industry. I'm an aspiring artist and yeah, it would be amazing, but I think that whatever plan God has in store for me, definitely music will be a big part of it and it will influence my life a lot. So yeah, it just means a lot. And I wouldn't know how to explain it with words.

What's a song you know word for word, bar for bar?

The song I know word for word, bar by bar - okay my Italian came out - is Mama Saturn by Tanarélle because I don't know, I've listened to that song too much and it's just speaks to me in a different level. It's - wow. Yeah.

Do you collect vinyl? If so what do you enjoy about it? And if not, how come?

I sadly do not collect vinyls because I don't have the player thing - I don't know how to say in English - and they're expensive, but I would love to and I'm really sad that I don't, but I still support my favourite artists by buying tickets for them.

Tell me about your favourite concert that you went to.

I've been to many concerts I enjoyed, no bad concerts, but I think as of lately, Mahmood. My favourite Italian artist came to London [on] May 2nd. It was my birthday so it was really special to me. I had a birthday hat on and so he said happy birthday to me and yeah, that's why I think it was probably the most special, and everyone was Italian in the venue, you know? So it felt like I had a piece of home in that venue that night, so yeah.

Your favourite lyric?

You'd kneel down to the dry land / Kiss the earth that birthed you [Frank Ocean, Pink + White]

Give me the name of a playlist you made with no context.

R&B TO PLAY IN A BENZ

What are your desert island disc albums?

So I have Blond by Frank Ocean for my 'being sad' moments. Ghettolimpo - to remind myself where I'm from - by Mahmood and 4U by Ojerime, 'cause it's a sexy album.

Tell me about music your parents played while you were growing up.

So my mom and my dad were really different in taste. In fact, my dad brought me to the old school Italian music, so like Domenico Modugno, Fabrizio De André; while my mum was really like thee singers, you know, Whitney Houston, Tina Turner. She used to play all of that. And yeah so I grew up with that type of music. And then when I started listening to my own music, a lot of R&B and stuff, they started to listen to that music as well, so yeah.

Briefly talk me through the songs you put in this playlist, what do they mean to you.

My first song is Ghettolimpo by Mahmood because it's just a work of art that song speaks about like his personal life, how he grew up and his relationship with religion and faith, but also just music in general and chasing his dreams, growing up without his dad. 

And then there's Pyramids by Frank Ocean because that song is just simply the greatest song of all time.

SUMMER SALT by Smino because it's my summer song. And Smino was definitely one of the biggest influences in my life.

Out Of My Way by RIMON, cuz that's my party song, it's my favourite party song. 

'A capa e 'o core by SVM & LaHasna is a Neapolitan Italian song. And I love how the lyrics are so angry, but  the song is just - I don't know - it's like you're on a wave, you know, it's so nice. 

And then there's I Know Now (2003) by Ojerime, which is - listen, guys, listen, I don't owe any explanation. 

No Angel by Beyonce because it's underrated as fuck and that's one of her best songs and I don't know, I just love the switch, the beat switch and what she does with her voice. 

Mama Saturn by Tanarélle, 'cause that's a song I know word for word.

Burn by Jorja Smith, 'cause it speaks to me, I'm sure she wrote it for herself and for every person that you know was going through something, especially as a teenager sometimes. 

And the last one is Amore che vieni, amore che vai and it's an Italian old school song, which my dad used to play in the car all the time, so yeah.

The Top 10 Data Science Applications

Applications of data science have not overnight gained importance. Thanks to faster processing and less expensive storage, we can now predict outcomes in a matter of minutes rather than the many hours it may take a human to do so.

Data Science

Data science is a rapidly expanding discipline and field of work. According to figures from LinkedIn, the fastest-growing new employment area is data science. Employers employed people with training in data science at a shocking rate of 37 percent more frequently than normal during the last three years. Data science, which is expanding every day, is transforming practically every business. A Data Science certification course can help students gain the skills and information they need to excel in data analytics.

We share with you 10 applications of data science in this blog that cover a range of topics, including the following:

Fraud and Risk Detection

Healthcare

Internet Search

Targeted Advertising

Website Recommendations

Advanced Image Recognition

Speech Recognition

Airline Route Planning

Gaming

Augmented Reality

Detection of Fraud and Risk

The early applications of data science were in the financial sector. The constant losses and bad debts were getting to the businesses. However, they had a lot of data that had been obtained during the initial loan application procedure. They decided to hire data scientists in order to stop losses.

Banking institutions have mastered the art of data division and control by using customer profiling, past purchases, and other essential variables to estimate the risk and default probability. Furthermore, it made it possible for them to sell their banking services in accordance with the spending power of their clientele.

Healthcare

Data science applications, in particular, have a significant positive impact on the healthcare industry.

1. Medical Image Analysis

To find the optimal parameters for tasks like lung texture categorization, a variety of methodologies and frameworks, including MapReduce, are utilized in procedures like tumor detection, artery stenosis detection, and organ delineation. The classification of solid textures makes use of wavelet analysis, support vector machines (SVM), content-based medical picture indexing, and machine learning algorithms.

2. Genetics & Genomics

High levels of therapeutic customization are also made possible by genetic and genomic research through the use of data science tools. Understanding how our DNA influences our health and locating particular molecular connections between genetics, disorders, and treatment responses are the goals.

Data science tools allow for the integration of many types of data with genomic data in the study of illness, which provides a deeper understanding of hereditary challenges in responding to particular diseases and drugs. As soon as we get access to reliable personal genomic information, we will understand the human genome better.

The improvement of genetic risk prediction will be a key step towards more individualized care.

3. Drug Development

Data science applications and machine learning algorithms streamline and speed up this process by giving context to each step, from the initial The screening of medicinal substances is carried out through the forecast of the success rate based on biological characteristics.

These algorithms use complex mathematical models and simulations to estimate how the chemical would behave in the body rather than performing "lab testing." The creation of computerized representations of physiologically plausible networks with improved prediction capabilities is the aim of computational drug discovery.

4.Virtual assistance for patients and customer support

The foundation for improving the clinical process is the notion that patients frequently do not need to meet doctors in person. A more realistic solution might be to send the doctor immediately to the patient using a mobile application.

The majority of mobile AI-powered apps are chatbots, and they can provide basic healthcare help. You can get crucial information about your medical condition by just describing your symptoms or asking questions. This information is taken from a vast network that links symptoms to causes.

Internet Search

The majority of mobile AI-powered apps are chatbots, and they can provide basic healthcare help. You can get crucial information about your medical condition simply by describing your symptoms or asking questions. This information is taken from a vast network that links symptoms to causes. If necessary, apps can help you set up a doctor's visit and remind you to take your medicine on time.

With this approach, patients no longer need to wait in line for appointments, are encouraged to make healthy choices, and doctors' time is freed up to handle more urgent cases.

Targeted Advertising

This explains why digital ads have a higher CTR than traditional ads, which has a considerably lower CTR. They might be selected in accordance with a user's prior choices.

This explains why you and I might both view a clothing advertisement while looking at information about data science training programmes.

Website Recommendations

We're all used to Amazon suggesting similar things, right? They not only help you identify suitable products among the billions of things they have accessible, but they also greatly enhance the user experience.

This engine has been actively used by many businesses to sell their products in line with consumer demand and informational relevancy. Internet behemoths like Amazon, Twitter, Google Play, Netflix, Linkedin, IMDb, and many others use this strategy to improve the user experience. A user's previous search results are used to generate the suggestions.

Advanced Image Recognition

This automatic tag recommendation tool makes use of face recognition technologies.

In their most recent update, Facebook described the significant progress they've made in this area, highlighting in particular their improvements in image recognition accuracy and capacity.

Google also gives you the opportunity to upload images for search purposes. It uses image recognition to its advantage while providing pertinent search results.

Speech Recognition

Some of the most effective instances of speech recognition software include Google Voice, Siri, Cortana, and others. Using speech recognition technology, you could still communicate even if you were unable to type. Simply say a message aloud to have it converted to text. Soon, you'll learn that speech recognition occasionally performs incorrectly.

Airline Route Planning

On a global level, the airline industry suffers huge losses. Except for a few aircraft service providers, businesses are having trouble maintaining their occupancy rates and operational revenues. Data science is now widely used by airlines and other companies to identify critical areas for development. Data science has enabled airline businesses to:

planning for a flight delay

Choose the sort of aircraft you want to buy.

Whether to get at the objective right away or make a stop along the way

effectively market consumer loyalty programmes.

Two of the top companies that have adopted data science to alter their business practices are Southwest Airlines and Alaska Airlines.

You may better comprehend it by watching the movie that our team created, which beautifully lists all the different fields that Data Science Applications have conquered.

Gaming

Machine learning algorithms are used to develop modern video games, and they improve or evolve when the player reaches higher levels. The computer, your adversary in motion games as well, analyzes your previous plays and modifies the game accordingly. EA Sports, Zynga, Sony, Nintendo, and Activision-Blizzard have all improved the gaming experience through the application of data science.

Augmented Reality

The final application of data science that seems most promise for the future is this one. improved reality

Data science and virtual reality do interact because a VR headset uses computer know-how, algorithms, and data to give you the best viewing experience. Pokemon GO, which is incredibly popular, is a very little step in that direction. navigating obstacles while looking at Pokemon on streets, buildings, and other made-up stuff.

new current emotion

Making Sense of Support Vector Machines (SVM): Mathematical Explanation

by Carla Martins

🔵 https://medium.com/mlearning-ai/making-sense-of-support-vector-machines-svm-mathematical-explanation-560eb87a7b8

AI is everywhere, but the question is how much do you love it?

🟠

Re: commissions.. First, set prices (look around at other ppls prices and don't sell yourself short!). Then once you get buyers, gather their email addresses and communicate through email (not tmblr, twt, etc. email is a better paper trail). Collect payment through PayPal, and deliver the art through email. Where I live, you have to declare taxes on secondary income like that, but, you can deduct PayPal's fees and get it back in your tax return. ;) I hope these tips help a little!!

thank you svm!!! im sure its a lot easier once you get the process started, but aa its so daunting at first :0

thanks for the help tho!! ill keep it in mind

Greenmark Mayfair Apartments

GreenMark Mayfair Apartment in Tellapur promises to deliver premier luxury apartments that combine the best of amenities and lifestyle-enhancing facilities. This 7-tower residential complex is built on 11 acres of lush greenery. There are a total 10 floors in each tower and a total of 778 2-BHK and 3-BHK apartments. The tentative schedule for possession is July 2024.

Mayfair Apartments, Hyderabad, Features

1. 2 BHK and 3 BHK apartments, with sizes ranging from 1,261 sq. ft. to 2,083 sq. ft. The price ranges from ₹68 lakhs to ₹1 crore.

2. 30% of the construction has been completed as of May 2019

3. State-of-the-art club house with swimming pool

4. Two indoor badminton courts, tennis court and squash court

5. Creche facility for working parents

6. CCTV surveillance and compound wall to be fitted with solar fencing

7. 100% Vaastu compliant homes

8. Central park with natural forest-feel plantation and separate play area for children. Rock garden with trees and designer landscape.

9. Outdoor cricket practice net and basketball courts

10. Air-conditioned gym with health and fitness center

11. 100% DG generator back-up

12. Centralized LPG connection

13. Location close to Hitech City and financial district of Gachibowli

14. Home financing options from HDFC, the project’s finance partner. There are other bank loans also available from DHFL and Axis Bank.

15. Grocery and pharmacy shops nearby

16. Close to schools like Holy Cross School, St. Francis Xavier Jr. College, Samashti International School, Serra International Pre-School, Jawahar Navodaya Vidyalaya and more

17. Some well-known hospitals are located in Tellapur, including BHEL Hospital, Citizens Hospital and Mythri Hospital

18. In close proximity to recreation centers and malls like Inorbit Mall, Hypercity and SVM Mall.

19. Branches of SBI, ICICI, ING Vysysa and State Bank of Hyderabad located nearby

20. High speed automatic elevators and one service lift for each tower. All of them will be equipped with V3F for energy efficiency.

21. Intercom facilities and internet connectivity

22. Zero passenger vehicle movement on ground level

23. Close proximity to Lingampally Railway Station and Old MIG bus stop

24. 40 minutes from the Rajiv Gandhi International Airport

Limitations

1. The project is yet to be completed and possession starts only in 2024

2. House prices in Tellapur have appreciated by more than 33.3% in 2018

3. The real estate developer is not very responsive to queries

4. Transportation options are limited in the area, with the locality being served by MMTS trains.

Advantages

1. Promising location

2. Stress on greenery by the builders

3. World-class amenities

4. Close proximity to major attractions

5. Well connected to the IT hub and financial district

6. Metro service is in the pipeline for the area, which will ease commuting in the future

Disadvantages

1. No ready to move in flats yet

2. Tellapur area is still under development

3. Possession is 5 years away, so a lot of factors can change

For More Info About This Project: Greenmark Mayfair Apartments Tellapur Hyderabad | 2 & 3 BHK Flats For Sale

For Special Offers: Share on WhatsApp

Call: 8342063684 or 9019011888

SHARDA SARVHITKARI MODEL SR SEC SCHOOL, SECTOR 40D,CHANDIGARH MEHNDI COMPETITION ORGANISED Students of Sharda Sarvhitkari Model Sr.Sec School Sector 40D Chandigarh participated enthusiastically in Mehndi Competition. They created beautiful designs of Arabic and Indian Art  on their hands. The Competition was held under the supervision of Ms. Rashim, Art Teacher. Prizes were also  given to the winners. Principal Ms.Archana appreciated the unique talent of students of drawing mehndi along with their excellent performance in academics. #vidyabharatipunjab #sarvhitkarieducationalsociety #sarvhitkari #svm sarvhitkari.org