WordNet and ImageNet

WordNet

WordNet is a large lexical database for the English language, a combination of dictionary and thesaurus. Nouns, verbs, adjectives and adverbs are grouped into sets of cognitive synonym rings (synsets), each expressing a distinct concept. Synsets are interlinked by means of conceptual-semantic and lexical relations. It is accessible to human users via a web browser, but its primary use is in automatic natural language processing and artificial intelligence applications.

The database (lexicographer files) and software tools (compiler called grind and reverse morphology program called morphy) have been released under a BSD style license and are freely available for download from the WordNet website. The database contains about 160.000 words, organized in about 120.000 synsets, for a total of about 200.000 word-sense pairs (see detailed statistics). The current version 3.1 has a size of about 12 MB in compressed form.

WordNet was created in the Cognitive Science Laboratory of Princeton University under the direction of psychology professor George Armitage Miller, starting in 1985, and has been directed in recent years by Christiane Fellbaum.

Christiane Fellbaum, together with Piek Vossen, founded in 2000 the Global WordNet Association.

Global WordNet Association

GWA (Global WordNet Association) is a free, public and non-commercial organization that provides a platform for discussing, sharing and connecting wordnets for all languages in the world. A list of wordnets in other languages are published on the GWA website. Wordnets of the neighbouring countries of Luxembourg are listed hereafter :

The first GWA conference (GWC2002) was organized in January 2002 in Mysore, India. The most recent conference (GWC2014) was organized in Tartu, Estonia.

A major project of the GWA is the creation of a completely free worldwide wordnet grid, build around a shared set of concepts, such as the Common Base Concepts, and the Suggested Upper Merged Ontology (SUMO) owned by the IEEE.

SUMO

The Suggested Upper Merged Ontology (SUMO) and its domain ontologies form the largest formal public ontology in existence today. They are being used for research and applications in search, linguistics and reasoning. SUMO is the only formal ontology that has been mapped to all of the WordNet lexicons. The Technical editor of SUMO is Adam Pease.

WordNet Relations

Verena Heinrich from the University of Tübingen created a few images for GermaNet which visualize examples of WordNet relations. These copyrighted pictures are used here with permission.

Antonymy

WordNet Antonymy

WordNet Antonymy

Synonymy

WordNet Synonymy

WordNet Synonymy

Pertainymy

WordNet Pertainymy

WordNet Pertainymy

Hypernymy

WordNet Hypernymy

WordNet Hypernymy

Meronymy

WordNet Meronymy

WordNet Meronymy

Holonymy

WordNet Holonymy

WordNet Holonymy

Association

WordNet Association

WordNet Association

Multiple Relations

WordNet Multiple Relations

WordNet Multiple Relations

WordNet Search Results

The following figures show the results of WordNet searches for the term

pedestrian = piéton = Fussgänger
Online WordNet Search at the Princeton University

Online WordNet Search at the Princeton University

WordNet

Online Search at WoNeF – WordNet du Français

ImageNet

ImageNet is an image database organized according to the WordNet hierarchy (currently only the nouns), in which each node of the hierarchy is depicted by hundreds and thousands of images (an average of over five hundred images per node).

ImageNet does not own the copyright of the images. ImageNet only provides thumbnails and URLs of images, in a way similar to what image search engines do, by compiling an accurate list of web images for each synset of WordNet. The list is freely available.

ImageNet provides the download of SIFT (Scale-Invariant Feature Transform) features, of object bounding boxes for about 1 million pictures and of object attributes, both annotated and verified through Amazon Mechanical Turk.

ImageNet is managed by a research team from the universities of Stanford, Princeton, Michigan and North-Carolina. The project is sponsored by the Stanford Vision Lab, Stanford University, Princeton University, Google Research and A9, a subsidiary of Amazon.com based in Palo Alto, California, that develops search and advertising technology.

The following figure shows the results of the search for pedestrian in the ImageNet database.

ImageNet Search Result

ImageNet  Result Page for a “pedestrian” query

ImageNet

ImageNet Pictures (1.518) for the synset “pedestrian crossing, zebra crossing”

For comparison, the results of a Google Image Search for the same term pedestrian is shown below :

Goggle Image Search for pedestrian

Goggle Image Search for pedestrian

Started in 2010 (ILSVRC2010), the ImageNet Team organizes an annual challenge to measure improvements in the state of machine vision technology.

Large Scale Visual Recognition Challenge

The Large Scale Visual Recognition Challenge is based on pattern recognition software that can be trained to recognize objects in digital images and is made possible by the ImageNet database.

In 2012 (ILSVR2012) the contest was won by Geoffrey E. Hinton, a cognitive scientist at the University of Toronto, and his students Alex Krizhevsky and Ilya Sutskever. All three joined Google in 2013.

In 2014 (ILSVR2014), the challenge drew 38 entrants from 13 countries. The groups used advanced software, in most cases modeled loosely on the biological vision systems, to detect, locate and classify a huge set of images taken from Internet sources. Contestants run their recognition programs on high-performance computers based in many cases on specialized processors called GPUs, for graphic processing units. All of the entrants used a variant of an approach known as a convolutional neural network, an approach first refined in 1998 by Yann LeCun, a French computer scientist who recently became director of artificial intelligence research at Facebook.

The results of the 2014 challenge have been published at the ImageNet website.

Language : fr, de, en, lb, eo

Last update : October 24, 2017

Language is the human capacity for acquiring and using complex systems of communication, and a language is any specific example of such a system. The scientific study of language is called linguistics.

In the context of a text-to-speech (TTS) and automatic-speech-recognition (ASR) project, I assembled the following informations about the french, german, english, luxembourgish and esperanto languages.

French

French is a romance language spoken worldwide by 340 million people. The written french uses the 26 letters of the latin script, four diacritics appearing on vowels (circumflex accent, acute accent, grave accent, diaeresis) and the cedilla appearing in ç. There are two ligatures, œ and æ. The french language is regulated by the Académie française. The language codes are fr (ISO 639-1), fre, fra (ISO 639-2) and fra (ISO 639-3).

The spoken french language distinguishes 26 vowels, plus 8 for Quebec french. There are 23 consonants. The Grand Robert lists about 100.000 french words.

German

German is a West Germanic language spoken by 120 million people. In addition to the 26 standard latin letters, German has three vowels with Umlauts and the letter ß called Eszett. German is the most widely spoken native language in the European Union. The german language is regulated by the Rat für deutsche Rechtschreibung. The language codes are de (ISO 639-1), ger, deu (ISO 639-2) and 22 variants in ISO 630-3.

The spoken german language uses 29 vowels and 27 consonants. The 2013 relase of the Duden lists about 140.000 german words.

English

English is a West Germanic language spoken by more than a billion people. It is an official language of almost 60 sovereign states and the third-most-common native language in the world. The written english uses the 26 letters of the latin script, with rare optional ligatures in words derived from Latin or Greek. There is no regulatory body for the english language. The language codes are en (ISO 639-1) and eng (ISO 630-2 and ISO 639-3).

The spoken english language distinguishes 25 vowels and 34 consonants, including the variants used in the United Kingdom and the United States. The Oxford English Dictionary lists more than 250,000 distinct words, not including many technical, scientific, and slang terms.

Luxembourgish

Luxembourgish (Lëtzebuergesch) is a Moselle Franconian variety of West Central German that is spoken mainly in Luxembourg by about 400.000 native people. The Luxembourgish alphabet consists of the 26 Latin letters plus three letters with diacritics: é, ä, and ë. In loanwords from French and German, the original diacritics are usually preserved. The luxembourgish language is regulated by the Conseil Permanent de la Langue Luxembourgeoise (CPLL). The language codes are lb (ISO 639-1) and ltz (ISO 630-2 and ISO 639-3).

The spoken luxembourgish language uses 22 vowels (14 monophthongs, 8 diphthongs) and 26 consonants. The luxembourgish-french dictionary dico.lu icludes about 50.000 words, the luxembourgish-german disctionary luxdico lists about 26.000 words. The full online Luxembourgish dictionary www.lod.lu is in construction, at present words beginning with A-S may be accessed via the search engine.

Esperanto

Esperanto is a constructed international auxiliary language. Between 100,000 and 2,000,000 people worldwide fluently or actively speak Esperanto. Esperanto was recognized by UNESCO in 1954 and Google Translate added it in 2012 as its 64th language. The 28 letter Esperanto alphabet is based on the Latin script, using a one-sound-one-letter principle. It includes six letters with diacritics: ĉ, ĝ, ĥ, ĵ, ŝ (with circumflex), and ŭ (with breve). The alphabet does not include the letters q, w, x, or y, which are only used when writing unassimilated foreign terms or proper names. The language is regulated by the Akademio de Esperanto. The language codes are eo (ISO 639-1) and epo (ISO 630-2 and ISO 639-3).

Esperanto has 5 vowels, 23 consonants and 2 semivowels that combine with the vowels to form 6 diphthongs. The core vocabulary of Esperanto contains 900 roots which can be expanded into tens of thousands of words using prefixes, suffixes, and compounding.

Links

A list with links to websites with additional informations about the five languages (mainly luxembourgish) is shown hereafter :

Human Brain Parts and Regions

Last update : October 11, 2014

human brain regions

brain regions

The brain is the center of the nervous system in all vertebrate and most invertebrate animals. From a philosophical point of view, what makes the brain special in comparison to other organs is that it forms the physical structure that generates the mind. Through much of history, the mind was thought to be separate from the brain. Even for present-day neuroscience, the mechanisms by which human brain activity gives rise to consciousness and thought remain very challenging to understand: despite rapid scientific progress, much about how the human brain works remains a mystery. The operations of individual brain cells are now understood in considerable detail, but the way they cooperate in ensembles of millions has been very difficult to decipher.

The human brain has three main parts :

  1. The cerebrum, or telencephalon (Grosshirn, cerveau), that fills up most of the skull, is involved in cognition and also controls movement.
  2. The cerebellum, or little brain (Kleinhirn, cervelet), that sits at the back of the head, under the cerebrum, controls coordination and balance.
  3. The brainstem (Hirnstamm, tronc cérébral), that sits beneath the cerebrum in front of the cerebellum, connects the brain to the spinal cord and controls automatic functions such as breathing, digestion, heart rate and blood pressure.

The human brain is divided into right and left halves (hemispheres). The left half controls movement on the body’s right side. The right half controls the body’s left side. In most people, the language area is mainly on the left. Preserved brains have a grey color, hence the name grey matter.

The brain’s wrinkled surface is a specialized outer layer of the cerebrum, called the cerebral cortex (what we see when we look at the brain). Each bump on the surface of the human brain is known as a gyrus, while each groove is known as a sulcus.

In a typical human the cerebral cortex is estimated to contain 15–33 billion neurons, each connected by synapses to several thousand other neurons. These neurons communicate with one another by means of long protoplasmic fibers called axons, which carry trains of signal pulses called action potentials to distant parts of the brain or body targeting specific recipient cells..

Traditionally the cerebral cortex is divided into four sections, which are known as lobes :

english latin deutsch français
Frontal Lobe Lobus frontalis Stirnlappen lobe frontal
Parietal lobe Lobus parietalis Scheitellappen lobe pariétal
Temporal lobe Lobus temporalis Schläfenlappen lobe temporal
Occipital lobe Lobus occipitalis Hinterhauptlappen lobe occipital

The Terminologia Anatomica (TA), the international standard on human anatomic terminology, developed by the Federative Committee on Anatomical Terminology (FCAT) and the International Federation of Associations of Anatomists (IFAA), released in 1998, defines two additional lobes : The limbic lobe, associated to emotion and memory and the insular cortex, associated to pain and some other senses.

The frontal lobe is associated with reasoning, motor skills, higher level cognition, and expressive language. The parietal lobe is associated with processing tactile sensory information such as pressure, touch, and pain. The temporal lobe is the location of the primary auditory cortex, which is important for interpreting sounds and the language we hear. The hippocampus is also located in the temporal lobe, which is why this portion of the brain is heavily associated with the formation of memories. The occipital lobe is associated with interpreting visual stimuli and information. The primary visual cortex, which receives and interprets information from the retinas of the eyes, is located in the occipital lobe.

The cerebral cortex is also segmented in cortical areas which are functionally or anatomically defined. Some examples are listed below :

human brain areas

brain areas

The brainstem is comprised of the hindbrain (rhombencephalon) and midbrain. The hindbrain contains structures including medulla oblongata, the pons and the reticular formation.

The limbic system contains glands which help relay emotions. Many hormonal responses that the body generates are initiated in this area. The limbic system includes the amygdala, hippocampus, hypothalamus and thalamus.

Great progresses in the analysis which parts of the brain are involved in a particular mental process have been made in the last years with the functional magnetic resonance imaging (fMRI).

More informations about human brain parts and regions are available at the following links:

at Wikipedia :

other sources :

Biological and artificial neurons

Biological neurons

A biological neuron (nerve cell) is an electrically excitable cell that processes and transmits information through electrical and chemical signals. A chemical signal occurs via a synapse, a specialized connection with other cells. Neurons connect to each other to form neural networks. Neurons are the core components of the nervous system, which includes the brain, spinal cord, and peripheral ganglia. There are different types of neurons: sensory neurons, motor neurons and interneurons.

A typical neuron possesses a soma (perkaryon or cyton = cell body with nucleus), dendrites and an axon. Neurons do not undergo cell division.

Neurons

Neuron (Wikipedia)

Dendrites are thin structures that arise from the cell body, branching multiple times and giving rise to a complex dendritic tree. An axon is a special cellular extension that arises from the cell body and travels for long distances (as far as 1 meter in humans). The cell body of a neuron gives rise to multiple dendrites, but never to more than one axon, although the axon may branch hundreds of times before it terminates. The axon terminal contains synapses, specialized structures where neurotransmitter chemicals are released to communicate with target neurons. At the majority of synapses, signals are sent from the axon of one neuron to a dendrite of another, however there are a lot of exceptions.

All neurons are electrically excitable, maintaining voltage gradients across their membranes by means of metabolically driven ion (sodium, potassium, chloride, calcium) pumps. Changes in the cross-membrane voltage can alter the function of voltage-dependent ion channels. Each time the electrical potential inside the soma reaches a certain threshold, an all-or-none electrochemical pulse called an action potential is fired, which travels rapidly along the cell’s axon, and activates synaptic connections with other cells when it arrives.

Artificial neurons

An artificial neuron is a mathematical function conceived as an abstraction of biological neurons. The artificial neuron receives one or more inputs (representing the dendrites) and sums them to produce an output (representing the axon). Usually the sums of each node are weighted, and the sum is passed through a non-linear function known as an activation function or transfer function.

The first artificial neuron was the Threshold Logic Unit (TLU) first proposed by Warren McCulloch and Walter Pitts in 1943. This model is still the standard of reference in the field of neural networks and called a McCulloch–Pitts neuron. However, artificial neurons of simple types, such as the McCulloch–Pitts model, are sometimes characterized as caricature models, in that they are intended to reflect one or more neurophysiological observations, but without regard to realism.

In the 1980s computer scientist Carver Mead, who is widely regarded as the father of neuromorphic computing, demonstrated that sub-threshold CMOS circuits behave in a similar way to the ion-channel proteins in cell membranes. Ion channels, which shuttle electrically charged sodium and potassium atoms into and out of cells, are responsible for creating action potentials. Using sub-threshold domains mimicks action potentials with little power consumption.

At the Neuromorphic Cognitive Systems Institute of Neuroinformatics of the University of Zurich and ETH Zurich, a research group leaded by Giacomo Indiveri is currently developing, using the sub-threshold-domain principle, neuromorphic chips that have hundreds of artificial neurons and thousands of synapses between those neurons.

Neuromorphic computing

neuromorphic computing by Spike Gerrell

credit : Spike Gerrell for the Economist

Neuromorphic computing is a concept developed by Carver Mead, describing the use of very-large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures present in the nervous system. Carver Mead is a key pioneer of modern microelectronics.

Today the term neuromorphic is used to describe analog, digital, and mixed-mode analog/digital VLSI and software systems that implement models of neural systems. Neuromorphic computing is a new interdisciplinary discipline that takes inspiration from biology, physics, mathematics, computer science and engineering to design artificial neural systems and autonomous robots, whose physical architecture and design principles are based on those of biological nervous systems.

The goal is to make computers more like brains and to design computers that have  features that brains have and computers do not have up to now :

  • low power consumption (human brains use about 20 watts)
  • fault tolerance (brains lose neurons all time without impact)
  • lack of need to be programmed (brains learn and change)

An important property of a real brain is that each neuron has tens of thousands of synaptic connections with other neurons, which form a sort of small-world network. Many neuromorphic chips use what is called a cross-bar architecture, a dense grid of wires, each of which is connected to a neuron at the periphery of the grid, to create this small-world network. Other chips employs what is called synaptic time multiplexing.

The Economist published a few days ago a great article “Neuromorphic computing – The machine of a new soul” with illustrations from the London-based illustrator Spike Gerrell.

Some neuromorphic computing reletad projects are listed below :

Neuromorphic computing is dominated by European researchers rather than American ones. The following links provide additional informations about neuromorphic computing related institutions and topics :

A look inside mice brains

A team of researchers at the Stanford University, lead by Mark Schnitzer, an associate professor of biology and applied physics, planted tiny probes inside mice brains to detect what were essentially mouse memories. The study was published February 10, 2013, in the online edition of Nature Neuroscience.

inside mice brains

Read a mouse’s mind

The experiment involved the insertion of a needlelike microscope into the hippocampus of the mice brains. The microscope detected cellular activity and broadcast digital images through a cell phone camera sensor that fit like a hat over the heads of the critters as they were running around. Over the course of a month, the scientists were able to document patterns of activity in about 1000 neurons of the mice brains where they store long-term information. To get the results, an engineered gene was injected into the mice brains so that their proteins were sensitive to calcium ions. That caused the magnified cells to light up on the computer screen in flashes of green fluorescence when the neurons were activated.

Three students, who worked on the project, have formed a startup company called Inscopix, and they plan to sell the technology to neuroscience researchers.

More informations are available at the news website of Stanford University.

RoboRoach : control a living insect

RoboReach image

RoboR0ach image

RoboRoach is is the world’s first commercially available cyborg. Cockroaches use the antennas on their head to navigate the world around them. When these antennas touch a wall, the cockroach turns away from the wall. The antenna of a cockroach contains neurons that are sensitive to touch and smell. These neurons convey information back to the brain using electricity in the form of spikes. To control cockroaches, microstimulation (neurotechnology) can be used by sending small electrical pulses directly to the neurons of the cockroach antennas via a backpack. A learning kit, called RoboReach kit, has been created by neuroscientists, engineers and educators of the University of Michigan. The cockroach undergoes a short surgery in which wires are placed inside the antenna. Once the insect recovers, a backpack is temporarily placed on its back.

RoboRoach

RoboRoach photo

Tim Marzullo and Greg Gage of the University of Michigan founded Backyard Brains, a small company that makes neuroscience educational equipment and experiments for students of all ages. Backyard Brains terminated succesfully in July 2013 a Kickstarter campaign to support the RoboRoach Kit.

Of course, there are underlying ethical questions attached to such experimentation involving living things. People don’t always recognize insects as valuable life forms, but some critics are already speaking out against RoboRoach. Animal rights group PETA has spoken of the project as retrogressive and morally dubious.

In defence of the cockroach: RoboRoach Kickstarter ignores ethics is the title of a contribution posted by Liat Clark in wired.co.uk.

Backyard Brain has responded to criticisms with this statement on its website:
Our experiments are not philosophically perfect and without controversy; however, we believe the benefits outweigh the cost due to the inaccessibility of neuroscience in our current age.

Backyard Brains sells other products in their online shop : Spikerbox, EMG Spikerbox, Completo, 3D manipulator, RoachScope.

Le portail internet luxembourgeois consacré à la médiation scientifique

www.science.lu, le site scientifique du Luxembourg destiné au grand public, vient d’être lancé. Il s’agit d’un portail internet commun consacré à la médiation scientifique de tous les acteurs de la science et de la recherche au Luxembourg. Une trentaine d’institutions et d’associations participent à ce site. Le portail dispose également d’une page Facebook.

Portail luxembourgeois des sciences; rubrique Juniors

Portail luxembourgeois des sciences; rubrique Juniors

Functional magnetic resonance imaging (fMRI)

Last update : August 7, 2013

Functional MRI (fMRI) is a magnetic resonance imaging procedure that measures brain activity by detecting associated changes in blood flow. This technique relies on the fact that cerebral blood flow and neuronal activation are coupled. Since the early 1990s, fMRI has come to dominate brain mapping research. The primary form of fMRI uses the blood-oxygen-level-dependent (BOLD) contrast discovered by Seiji Ogawa at the AT&T Bell labs.

fMRI is used both in the research world (cognitive neuroscience, cognitive psychology, neuropsychology, and social neuroscience), and to a lesser extent, in the clinical world.

Links to additional informations about fMRI and related topics are provided in the following list :

Parcellation of the brain : fRMI

Parcellation of the brain

The Gallant Lab provides free access to several publications, links to websites and tools of the lab and a WebGL brain viewer.

Pycortex WebGL fMRI brain viewer

Pycortex WebGL MRI brain viewer

Guilfords Structure of Intellect (SI)

Last update : August 6, 2013

Joy Paul Guilford, a United States psychologist, designed in 1955 a model of intelligence, based on factor analysis. In the Guilfords Structure of Intellect (SI), all mental abilities are conceptualized within a three-dimensional framework. There are three features of intellectual tasks: the content, or the type of information; the product, or the form in which the information is represented; and the operation, or type of mental activity performed.

These 5 x 6 x 6 = 180 mental abilities are listed below :

Content features in the Guilfords Structure of Intellect

Five content dimensions (broad areas of information to which the human intellect applies operations) :

  1. Visual : information perceived through seeing
  2. Auditory : information perceived through hearing
  3. Symbolic : information perceived as symbols or signs that stand for something else (arabic numerals, letters of an alphabet, musical and scientific notations)
  4. Semantic : concerned with verbal meaning and ideas
  5. Behavioral : information perceived as acts of people

Product features in the Guilfords Structure of Intellect

Six products, in increasing complexity :

  1. Units : single items of knowledge
  2. Classes : sets of units sharing common attributes
  3. Relations : units linked as opposites or in associations, sequences, or analogies
  4. Systems : multiple relations interrelated to comprise structures or networks
  5. Transformations : changes, perspectives, conversions, or mutations to knowledge
  6. Implications : predictions, inferences, consequences, or anticipations of knowledge

Operation features in the Guilfords Structure of Intellect

Six operations (general intellectual processes) :

  1. Cognition : the ability to understand, comprehend, discover, and become aware of information
  2. Memory recording : the ability to encode information
  3. Memory retention : the ability to recall information
  4. Divergent production : the ability to generate multiple solutions to a problem; creativity
  5. Convergent production : the ability to deduce a single solution to a problem; rule-following or problem-solving
  6. Evaluation : the ability to judge whether or not information is accurate, consistent, or valid

Guilford’s original model was composed of 120 components, because he combined Visual and Auditory content in a common Figural Content and he combined Memory Recording and Memory Retention in a common Memory Operation. Guilford’s model is an open system such that it allows for newly discovered categories to be added in any of the three directions.

Guilfords Structure of Intellect has few supporters today, but Joy Paul Guilford is considered as one of the founders of the Psychology of Creativity. He emphasized the distinction between convergent and divergent thinking. In 1976 he introduced the developed model of Divergent Thinking as the main ingredient of creativity. Guilford appointed the following characteristics for creativity :

  • Fluency : the ability to produce great number of ideas or problem solutions
  • Flexibility : the ability to simultaneously propose a variety of approaches to a specific problem
  • Originality : the ability to produce new, original ideas
  • Elaboration : the ability to systematize and organize the details of an idea in a head and carry it out

Peter Nilsson uses the following example to measure the creativity of people based on Guilford’s concept of divergent production :

Creativity Measurement based on the Guilfords Structure of Intellect

Creativity Measurement

Links to additional informations about the Guilfords Structure of Intellect and about the measurement of creativity are provided in the following list :