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| viXra.org > Artificial Intelligence > 2002 |
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[10] viXra:2002.0533 [pdf] submitted on 2020-02-25 20:18:28
Authors: Quang Pham Minh, Huynh Le Vinh, Phuoc, Minh Hiếu Đào, An Nguyen Truong, Tran Phuc Hai, Nam, Louis WY LIU
Comments: 6 Pages.
A printed circuit board (PCB) with a non-flat surface is very common in radio frequency applications. For this reason, we have designed and produced a PCB milling machine capable of milling a PCB with a non-uniform flatness. Method: By embedding the suggested machine with a G-code reconstruction software, the milling device is programmed to implement the following tasks: Step 1, the machine executes the probing
procedure to generate the PCB’s Heightmap; Step 2, the machine transforms the input probing signal to a surface map which is a 2-dimensional grid, Step 3, When the machine is running, the
height of the drill tip is adjusted according to the PCB surface flatness condition, and the machine before the actual milling operation. As a result, the proposed machine is capable of milling elastic and unlevelled PCBs at high speed with height differences ranging up to 150mm and an ability to halt when the plane angle
varies severely. The proposed machine has been used to fabricate microwave print circuits. A close agreement has been obtained between the measured and simulated S-parameters. Although the
machine works properly and is equipped with all basic safety functions, it only costs around US$1500 while the market price of a related German product is about US$70000. Conclusion: A
machine able to mill microwave PCBs with an uneven surface and equipped with safety function has been successfully built at
the Vietnamese - German University a cost of US$1500, which is far less than the market price of similar ones.
Category: Artificial Intelligence
[9] viXra:2002.0496 [pdf] submitted on 2020-02-25 07:00:48
Authors: Scott T Cohen
Comments: 10 Pages.
This paper presents Global Density Clustering, (GDC), an algorithm that has several major advantages over the most popular existing clustering algorithms: (1) No parameters are chosen at the outset of the function; rather, the user can control the desired resolution as clustering proceeds. (2) GDC is efficient enough to work on a large dataset even when there are a sizable number of features. It is O(MN log N) where M is the number of features, i.e. the dimension, and N is the number of data points, i.e. the dataset size. It is suitable for big data. (3) GDC has the advantage of the powerful and intuitive definition of clusters as: points within a cluster are closer than distance dist to their nearest neighbor in the cluster (dist is not picked at the outset but rather that is chosen as the algorithm is progressing) and all points outside the cluster are further than dist from any point in the cluster. (4) GDC supports variable density without the plethora of special data structures such as HDBSCAN needs. (5) Other advantages are described. An essential reason that GDC has these advantages is it searches for and considers points whose nearest neighbor are furthest apart before searching for those that are closer together. It is a top-down or “global” consideration of distances that other density algorithms do from a bottom-up or “local” view. Other novel approaches to the main problems of clustering such as noisy backgrounds are described.
Category: Artificial Intelligence
[8] viXra:2002.0361 [pdf] submitted on 2020-02-19 01:59:24
Authors: George Rajna
Comments: 57 Pages.
As an example, in the most commonly used method for solving such problems, the so-called maximum entropy (MaxEnt) approach, prior knowledge is added by specifying a default distribution that corresponds to expected results in the absence of data. [32] MIT neuroscientists have performed the most rigorous testing yet of computational models that mimic the brain's visual cortex. [31] For people with hearing loss, it can very difficult to understand and separate voices in noisy environments. This problem may soon be history thanks to a new groundbreaking algorithm that is designed to recognise and separate voices efficiently in unknown sound environments. [30] While researchers have taken steps to HYPERLINK "https://doi.org/10.1017/S0140525X00023992" comprehensively catalogue the preferences of men and women, we still don't know which traits are the most important contributors to a person's attractiveness. [29] A group of researchers from MIT have already developed an AI robot that can assist in a labour room. [28] Researchers at Fukuoka University, in Japan, have recently proposed a design methodology for configurable approximate arithmetic circuits. [27] Researchers at Google have recently developed a new technique for synthesizing a motion blurred image, using a pair of un-blurred images captured in succession. [26] Constructing a neural network model for each new dataset is the ultimate nightmare for every data scientist. [25] Algorithmic fairness is increasingly important because as more decisions of greater importance are made by computer programs, the potential for harm grows. [24] Intel's Gadi Singer believes his most important challenge is his latest: using artificial intelligence (AI) to reshape scientific exploration. [23] Artificial intelligence is astonishing in its potential. It will be more transformative than the PC and the Internet. Already it is poised to solve some of our biggest challenges. [22] In the search for extraterrestrial intelligence (SETI), we've often looked for signs of intelligence, technology and communication that are similar to our own. [21]
Category: Artificial Intelligence
[7] viXra:2002.0357 [pdf] submitted on 2020-02-19 04:16:40
Authors: George Rajna
Comments: 83 Pages.
In a new paper published in Light Science & Application, a team of European scientists and engineers from ICFO and IRIS in Spain, Ipsumio B.V. in the Netherlands, the Technical University of Denmark, the Technische Universität Dresden in Germany and the University of Leeds in the UK, has developed a new micro-particle size analyser by combining consumer electronics products and artificial intelligence. [50] Researchers in Australia have found a way to manipulate laser light at a fraction of the cost of current technology. [49] The proposed design breaks the current bandwidth limit in the transmission-type coding metasurfaces, indicating wide application potentials in radar and wireless communication systems. [48] In a similar vein, scientists are working to create twisting helical electromagnetic waves whose curvature allows more accurate imaging of the magnetic properties of different materials at the atomic level and could possibly lead to the development of future devices. [47] In a recent study, materials scientists Guojin Liang and his coworkers at the Department of Materials Science and Engineering, City University of Hong Kong, have developed a self-healing, electroluminescent (EL) device that can repair or heal itself after damage. [46] A team of researchers based at The University of Manchester have found a low cost method for producing graphene printed electronics, which significantly speeds up and reduces the cost of conductive graphene inks. [45] Graphene-based computer components that can deal in terahertz "could be used, not in a normal Macintosh or PC, but perhaps in very advanced computers with high processing rates," Ozaki says. This 2-D material could also be used to make extremely high-speed nanodevices, he adds. [44] Printed electronics use standard printing techniques to manufacture electronic devices on different substrates like glass, plastic films, and paper. [43] A tiny laser comprising an array of nanoscale semiconductor cylinders (see image) has been made by an all-A*STAR team. [42]
Category: Artificial Intelligence
[6] viXra:2002.0314 [pdf] submitted on 2020-02-16 11:58:01
Authors: Egger Mielberg
Comments: 27 Pages.
A purely decentralized Internet would allow its users to create or get access to a public or private informational worldwide network with a guarantee not to be spammed, interrupted or attacked by a third party at all. Semantic Normalizer (SN) would improve the user's Internet search experience and diminish search time greatly. SN eliminates double-answering and double meaning problems. It is a part of the architectural solution of ArLLecta and requires no additional pre-installations. We propose a solution to the nontransparent and domain-centered Internet problem using a decentralized sense-to-sense network. S2S network allows creating public or private zones for business or personal needs. The data of each user, individual or corporate, is decoded and published only by direct permission. The architecture of S2S network prevents the centralization of its data by a single user. However, each user can create or join or leave any zone. The main task of the S2S network is to give each user a possibility for a quick sense-focused search and save its data from unauthorized third parties.
Category: Artificial Intelligence
[5] viXra:2002.0305 [pdf] submitted on 2020-02-16 07:19:52
Authors: Aleksey A. Demidov
Comments: 5 Pages.
Here I provide a short review of the paper "Collectives of Automata for Building of Active Systems of Artifical Intelligence" -- what I find was done and what has to be done.
Category: Artificial Intelligence
[4] viXra:2002.0251 [pdf] submitted on 2020-02-13 07:16:54
Authors: George Rajna
Comments: 40 Pages.
As machine learning continues to surpass human performance in a growing number of tasks, scientists at Skoltech have applied deep learning to reconstruct quantum properties of optical systems. [27] To overcome these harsh limitations, the researchers exploited an artificial neural network (ANN) to learn the atomic interactions from quantum mechanics. [26] A new tool is drastically changing the face of chemical research-artificial intelligence. In a new paper published in Nature, researchers review the rapid progress in machine learning for the chemical sciences. [25] A new type of artificial-intelligence-driven chemistry could revolutionise the way molecules are discovered, scientists claim. [24] Tired of writing your own boring code for new software? Finally, there's an AI that can do it for you. [23] Welcome to Move Mirror, where you move in front of your webcam. [22] Understanding how a robot will react under different conditions is essential to guaranteeing its safe operation. [21] Marculescu, along with ECE Ph.D. student Chieh Lo, has developed a machine learning algorithm-called MPLasso-that uses data to infer associations and interactions between microbes in the GI microbiome. [20] A team of researchers from the University of Muenster in Germany has now demonstrated that this combination is extremely well suited to planning chemical syntheses-so-called retrosyntheses-with unprecedented efficiency. [19] Two physicists at ETH Zurich and the Hebrew University of Jerusalem have developed a novel machine-learning algorithm that analyses large data sets describing a physical system and extract from them the essential information needed to understand the underlying physics. [18]
Category: Artificial Intelligence
[3] viXra:2002.0178 [pdf] submitted on 2020-02-09 01:14:30
Authors: Ali Mehmani, Payam Ghassemi, Souma Chowdhury
Comments: 11 Pages.
Wearable sensors are revolutionizing the health monitoring and medical diagnostics arena. Algorithms and software platforms that can convert the sensor data streams into useful/actionable knowledge are central to this emerging domain, with machine learning and signal processing tools dominating this space. While serving important ends, these tools are not designed to provide functional relationships between vital signs and measures of physical activity. This paper investigates the application of the metamodeling paradigm to health data to unearth important relationships between vital signs and physical activity. To this end, we leverage neural networks and a recently developed metamodeling framework that automatically selects and trains the metamodel that best represents the data set. A publicly available data set is used that provides the ECG data and the IMU data from three sensors (ankle/arm/chest) for ten volunteers, each performing various activities over one-minute time periods. We consider three activities, namely running, climbing stairs, and the baseline resting activity. For the following three extracted ECG features – heart rate, QRS time, and QR ratio in each heartbeat period – models with median error of <25% are obtained. Fourier amplitude sensitivity testing, facilitated by the metamodels, provides further important insights into the impact of the different physical activity parameters on the ECG features, and the variation across the ten volunteers.
Category: Artificial Intelligence
[2] viXra:2002.0127 [pdf] submitted on 2020-02-07 08:53:52
Authors: George Rajna
Comments: 71 Pages.
Important insights into the mechanisms underlying spiral nanostructure formation in solidifying metal alloys have been gained by Ashwin Shahani at the University of Michigan and colleagues. [44] A team of researchers from Bilkent University and Sabanci University SUNUM Nanotechnology Research Center has developed a way to control buckling in a nanoscale beam using electrostatic effects. [43] A nanoscale gold butterfly provides a more precise route for growing/synthesizing nanosized semiconductors that can be used in nano-lasers and other applications. [42] Magnetic vortices are nanoscale whirls that gyrate like spinning tops, tracing out paths in a clockwise or counterclockwise manner in nanometer-thick materials. [41] Now a team of Australian scientists has discovered diamond can be bent and deformed, at the nanoscale at least. [40] Researchers at the Okinawa Institute of Science and Technology Graduate University (OIST) have fabricated a novel glass and synthetic diamond foundation that can be used to create miniscule micro-and nanostructures. [39] Osaka University-led researchers demonstrated that the perturbation of laser imprinting on a capsule for nuclear fusion fuel made from stiff and heavy materials was mitigated. [38] Scientists found that relatively slow electrons are produced when intense lasers interact with small clusters of atoms, upturning current theories. [37] Lasers that emit ultrashort pulses of light are critical components of technologies, including communications and industrial processing, and have been central to fundamental Nobel Prize-winning research in physics. [36] A newly developed laser technology has enabled physicists in the Laboratory for Attosecond Physics (jointly run by LMU Munich and the Max Planck Institute of Quantum Optics) to generate attosecond bursts of high-energy photons of unprecedented intensity. [35]
Category: Artificial Intelligence
[1] viXra:2002.0099 [pdf] submitted on 2020-02-05 00:12:45
Authors: Nirmal Tej Kumar
Comments: 9 Pages. Short Communication
A Deep Learning(DL) Framework Using JIT Compiler with Haskell & LLVM in the Context of Medical Image Processing/Electron Microscopy(EM) Image Processing/Satellite Imagery Software R&D Using Mandelbrot Algorithms is suggested.Exploring Functional Programming+Deep Learning for designing Advanced Image Processing Algorithms
R&D-is it the right choice ? - Keep going on with Haskell+Grenade,to refine the image processing tasks based on Deep Learning(DL) concepts.Haskell is a good choice for Image Processing R&D using Deep Learning.
Category: Artificial Intelligence
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