Artificial Intelligence

1911 Submissions

[16] viXra:1911.0282 [pdf] submitted on 2019-11-16 12:26:40

Creating a More Human-Like AI Entity

Authors: Keith D. Foote
Comments: 1 Page.

This paper initiates and explores the concept of recording the visual and audio experiences of individuals to be used as a foundation for AI entities. The goal is to provide more human like behavior.
Category: Artificial Intelligence

[15] viXra:1911.0245 [pdf] submitted on 2019-11-13 22:50:11

Exploring [ Spring Tools 4 for Eclipse/JamVM/ Prolog Development Tool - PDT ] in the Context of Prolog/Palladio Studio/IoT/HPC Heterogeneous Systems & Environments - A Simple Understanding of JamVM [ Java Virtual Machine ]

Authors: Nirmal Tej Kumar
Comments: 4 Pages. Short Communication & Technical Notes

Exploring [ Spring Tools 4 for Eclipse/JamVM/ Prolog Development Tool - PDT ] in the Context of Prolog/Palladio Studio/IoT/HPC Heterogeneous Systems & Environments - A Simple Understanding of JamVM [ Java Virtual Machine ]interaction With Spring Boot Framework.
Category: Artificial Intelligence

[14] viXra:1911.0230 [pdf] submitted on 2019-11-13 07:14:31

Deep Learning Nuclear Waste

Authors: George Rajna
Comments: 49 Pages.

A research collaboration between Lawrence Berkeley National Laboratory (Berkeley Lab), Pacific Northwest National Laboratory (PNNL), Brown University, and NVIDIA has achieved exaflop performance on the Summit supercomputer with a deep learning application used to model subsurface flow in the study of nuclear waste remediation. [28] A team of scientists at Freie Universität Berlin has developed an Artificial Intelligence (AI) method that provides a fundamentally new solution of the "sampling problem" in statistical physics. [27]
Category: Artificial Intelligence

[13] viXra:1911.0221 [pdf] submitted on 2019-11-12 19:58:51

Deep Clustering for Mars Rover Image Datasets

Authors: Vikas Ramachandra
Comments: 6 Pages.

In this paper, we build autoencoders to learn a latent space from unlabeled image datasets obtained from the Mars rover. Then, once the latent feature space has been learnt, we use k-means to cluster the data. We test the performance of the algorithm on a smaller labeled dataset, and report good accuracy and concordance with the ground truth labels. This is the first attempt to use deep learning based unsupervised algorithms to cluster Mars Rover images. This algorithm can be used to augment human annotations for such datasets (which are time consuming) and speed up the generation of ground truth labels for Mars Rover image data, and potentially other planetary and space images.
Category: Artificial Intelligence

[12] viXra:1911.0211 [pdf] submitted on 2019-11-11 13:23:32

Формальная теория жизнедеятельности психики человека

Authors: Кондратенко Виктория Александровна
Comments: 19 Pages.

Множество исследований в области искусственного интеллекта не могут быть завершены, или проведены вообще, из-за отсутствия на текущий момент корректной теории функционирования человеческого мозга, связанного с его интеллектуальной деятельностью, хотя бы на концептуальном уровне. Нет пока комплексных предложений исследователей, на каких принципах должны основываться модели элементарных и структурированных смыслов, обрабатываемых мозгом в процессе жизнедеятельности человека, не говоря уже о формальных языках и их грамматиках, или, тем более, о формальных теориях, предназначенных для этих целей. Цель статьи заключается в восполнении отмеченного только что пробела в научных знаниях о человеческом мозге.
Category: Artificial Intelligence

[11] viXra:1911.0170 [pdf] submitted on 2019-11-09 05:20:34

Deep Learning Convert Images

Authors: George Rajna
Comments: 40 Pages.

A UCLA research team has devised a technique that extends the capabilities of fluorescence microscopy, which allows scientists to precisely label parts of living cells and tissue with dyes that glow under special lighting. [25] Social, economic, environmental and health inequalities within cities can be detected using street imagery. [24] Citizen science is a boon for researchers, providing reams of data about everything from animal species to distant galaxies. [23] In early 2018, with support from IBM Corporate Citizenship and the Danish Ministry for Foreign Affairs, IBM and the Danish Refugee Council (DRC) embarked on a partnership aimed squarely at the need to better understand migration drivers and evidence-based policy guidance for a range of stakeholders. [22]
Category: Artificial Intelligence

[10] viXra:1911.0156 [pdf] submitted on 2019-11-08 14:10:21

Nonconvex Stochastic Nested Optimization via Stochastic ADMM

Authors: Zhongruo Wang
Comments: 28 Pages.

We consider the stochastic nested composition optimization problem where the objective is a composition of two expected-value functions. We proposed the stochastic ADMM to solve this complicated objective. In order to find an $\epsilon$ stationary point where the expected norm of the subgradient of corresponding augmented Lagrangian is smaller than $\epsilon$, the total sample complexity of our method is $\mathcal{O}(\epsilon^{-3})$ for the online case and $\cO \Bigl((2N_1 + N_2) + (2N_1 + N_2)^{1/2}\epsilon^{-2}\Bigr)$ for the finite sum case. The computational complexity is consistent with proximal version proposed in \cite{zhang2019multi}, but our algorithm can solve more general problem when the proximal mapping of the penalty is not easy to compute.
Category: Artificial Intelligence

[9] viXra:1911.0142 [pdf] submitted on 2019-11-08 07:59:07

Machine Learning Light-Beam

Authors: George Rajna
Comments: 49 Pages.

Nishimura said that the buzzwords "artificial intelligence" seem to have trended in and out of the research community for many years, though, "This time it finally seems to be something real." [27] Navid Borhani, a research-team member, says this machine learning approach is much simpler than other methods to reconstruct images passed through optical fibers, which require making a holographic measurement of the output. [26] Scientists from the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a way to use machine learning to dramatically accelerate the design of microbes that produce biofuel. [25]
Category: Artificial Intelligence

[8] viXra:1911.0129 [pdf] submitted on 2019-11-07 00:55:27

Exploring IoT/Smart Devices based Multi-disciplinary Informatics Research Using Minsky Machines & Machine Learning With C++.

Authors: Nirmal Tej Kumar
Comments: 3 Pages. Short Communication & Technical Notes

Exploring IoT/Smart Devices based Multi-disciplinary Informatics Research Using Minsky Machines & Machine Learning With C++.
Category: Artificial Intelligence

[7] viXra:1911.0119 [pdf] submitted on 2019-11-07 09:28:16

Психика человека в образе формальной модели диалектической логики управления её жизнеобеспечивающими функциями

Authors: Кондратенко Виктория Александровна
Comments: 9 Pages. на русском языке

Концептуальные знания о жизнедеятельности каждой исследуемой функциональной системы человека должны предшествовать описанию сущности логики управления ею. Психика человека является одной из важнейших функциональных систем его организма. В статье представлены основополагающие концепты жизнедеятельности этой системы, которые позволят выявить сущность диалектической логики управления еѐ жизнеобеспечивающими функциями. Однако и акцентированию внимания естествоиспытателей-биологов на отсутствие необходимых знаний в области диалектической логики управления функциональной системой психики человека также уделено особое внимание, так как страдает процесс формализации знаний в области теоретической медицины, касающихся жизнедеятельности функциональной системы психики человека. Именно этим специалистам, как никому лучше, видно, какие знания и каким путѐм могут быть получены за минимальное время. Освещению этих проблем и посвящена статья.
Category: Artificial Intelligence

[6] viXra:1911.0112 [pdf] submitted on 2019-11-06 01:12:05

Light Weight Online Signature Verification Framework by Compound Feature Selection and Few-shot Separable Convolution Based Deep Learning

Authors: Chandra Sekhar Vorugunti
Comments: 9 Pages. Submitted to WACV

Online Signature Verification (OSV) is an extensively used biometric trait aims to verify genuineness of a test signature by computing unique features of the signature. The advancements in mobile and communication technologies resulted in usage of computationally sparse mobile devices in critical applications like m-commerce etc., demands for OSV frameworks which are able to classify the dynamic test signature with fewer number of training signature samples and lesser number of features. The recent advancements in Deep Learning (DL) technologies, resulted in exponential improvements of accuracy in traditional tasks like Object Detection, Scene Text Detection etc. The main disrupt in usage of DL based frameworks for OSV is the requirement of extensive number of training samples and larger number of parameters to learn. To overcome the above pitfalls, we propose a novel dimensionality reduction technique which reduces the dimensionality of a feature set from 100 to 3 in case of MCYT-100 and 47 to 3 in case of SVC, SUSIG datasets respectively. In addition to it, we propose a depth wise separable (DWS) convolution based OSV framework which enables one/few shot learning for test signature verification. To inspect the robustness of our proposed dimensionality reduction technique and DWS OSV framework, exhaustive experiments are conducted with three widely used datasets i.e. MCYT-100, SUSIG and SVC. We have attained state of the art EER in majority of experimentation categories compared to many recent and state-of-the art OSV models.
Category: Artificial Intelligence

[5] viXra:1911.0096 [pdf] submitted on 2019-11-06 09:47:27

Intelligence Metasurface Recognizer

Authors: George Rajna
Comments: 63 Pages.

The Internet of Things (IoT) and cyber physical systems have opened up possibilities for smart cities and smart homes, and are changing the way for people to live. [38] This camera is currently the fastest electron detector in the world, capturing atomic snapshots at 87,000 frames per second: about 50 times faster than the current state of the art. [37] "We put the optical microscope under a microscope to achieve accuracy near the atomic scale," said NIST's Samuel Stavis, who served as the project leader for these efforts. [36] Researchers have designed an interferometer that works with magnetic quasiparticles called magnons, rather than photons as in conventional interferometers. [35] A technique to manipulate electrons with light could bring quantum computing up to room temperature. [34] The USTC Microcavity Research Group in the Key Laboratory of Quantum Information has perfected a 4-port, all-optically controlled non-reciprocal multifunctional photonic device based on a magnetic-field-free optomechanical resonator. [33] To address this technology gap, a team of engineers from the National University of Singapore (NUS) has developed an innovative microchip, named BATLESS, that can continue to operate even when the battery runs out of energy. [32] Stanford researchers have developed a water-based battery that could provide a cheap way to store wind or solar energy generated when the sun is shining and wind is blowing so it can be fed back into the electric grid and be redistributed when demand is high. [31] Researchers at AMOLF and the University of Texas have circumvented this problem with a vibrating glass ring that interacts with light. They thus created a microscale circulator that directionally routes light on an optical chip without using magnets. [30] Researchers have discovered three distinct variants of magnetic domain walls in the helimagnet iron germanium (FeGe). [29] Magnetic materials that form helical structures-coiled shapes comparable to a spiral staircase or the double helix strands of a DNA molecule-occasionally exhibit exotic behavior that could improve information processing in hard drives and other digital devices. [28]
Category: Artificial Intelligence

[4] viXra:1911.0089 [pdf] submitted on 2019-11-05 02:22:40

[ Neo4j-Python Driver ] Interaction with [ Imageai-Python ai Tool/z3 Api-Python(theorem Prover)/qrng-Python Lib/qrng ] Python Programming Environment in the Context of Medical Image Processing/electron Microscopy( em ) Image Processing R&D

Authors: Nirmal Tej Kumar
Comments: 2 Pages. Short Communication

[ Neo4j-Python driver ] Interaction with [ ImageAI-Python AI Tool/Z3 API-Python(Theorem Prover)/qrng-Python lib/QRNG ] Python Programming Environment in the Context of Medical Image Processing/Electron Microscopy( EM ) Image Processing R&D – A Novel Suggestion. [ Monitoring Graph Data Base System/Image Processing Frameworks with qrng-services/qrng-Devices + AI ]
Category: Artificial Intelligence

[3] viXra:1911.0062 [pdf] submitted on 2019-11-04 01:02:18

Understanding Graph Data Base Systems Using [ Java/JI Prolog ] – A Simple Suggestion to Implement [ AI/IoT/HPC/BIG DATA ] Informatics Systems.

Authors: Nirmal Tej Kumar
Comments: 4 Pages. Short Communication & Technical Notes

JI Prolog+Neo4j+JikesRVM-Research Virtual Machine/JVM-Java Virtual Machine/IoT/HPC Heterogeneous Environments in the Context of BIG DATA Analytics based on Bio-informatics.Exploring Graph Data Base Systems Using Java for Next Generation Bio-informatics Frameworks Using IoT/HPC Systems.We are testing the above mentioned informatics frameworks using RVM – Research Virtual Machine – a highly experimental TESTBED.Since Java is well suited for IoT/HPC- Heterogeneous Environments and its associated challenges,we are presenting here,a simple challenging Informatics Framework to probe next generation Bio-informatics R&D. [ Researching Algorithms for Next Generation Bio-informatics Platforms ]
Category: Artificial Intelligence

[2] viXra:1911.0036 [pdf] submitted on 2019-11-02 02:47:31

Exploring Henon Maps for Next Generation Medical Imaging Algorithms Using Python Based Software Involving Ai/qrng/iot/hpc Concepts.

Authors: Nirmal Tej Kumar
Comments: 3 Pages. Short Communication & Technical Notes

Understanding & Implementing [ Henon Maps/QRNG/ImageAI ] – Python based Informatics Framework to ProbeMedical Images Using DICOM – A Simple & Novel Suggestion in the Context of [ AI/IoT/HPC /LLVM ] Heterogeneous Environment/s.We derived our inspiration based on our references mentioned below,please check our references.
Category: Artificial Intelligence

[1] viXra:1911.0011 [pdf] submitted on 2019-11-01 04:05:21

Medical Center AI Infrastructure

Authors: George Rajna
Comments: 48 Pages.

An artificial intelligence (AI) infrastructure developed at the Utrecht University Medical Center (UMC) has enabled easier deployment of AI algorithms and enhanced workflow in daily routine practice, according to a presentation given at the European Society of Medical Imaging Informatics (EuSoMII) annual meeting in Valenca, Spain. [26] A team from Heidelberg University Hospital and the German Cancer Research Centre has developed a new method for the automated image analysis of brain tumors. [25]
Category: Artificial Intelligence