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Machine Learning Helps Save Rare Species From Extinction
How Machine Learning Helps Save Rare Species From Extinction
Machine Learning
In order to track rare and endangered species of animals, you need to quickly receive data about them. Machine learning techniques help scientists solve this problem.
In 2019, the United Nations presented a report stating that about a million species of plants and animals, or 25% of the entire living world, will be endangered. There are more than 120,000 such species on the list of the International Conservation Union, and there is not enough information for the conservation of another 17,000. Researchers around the world are looking for ways to maintain biodiversity on Earth. In their work, in particular, they actively use artificial intelligence technologies.
How It Works
Traditionally, animal observation has been based on fieldwork conducted by human experts. However, this work is time-consuming, expensive, and laborious. In addition, a person cannot penetrate everywhere, and his personal assessment may be biased. Finally, human presence can harm wild animals, and their habitats, and be dangerous to observers themselves.
These limitations make understanding geographic ranges, population densities, and diversity much more difficult, leading to erroneous predictions and hindering rapid and effective action. For example, insufficient monitoring has led to misguided primate conservation strategies.
Machine learning offers an alternative to human research. Algorithms learn from data labeled with specific labels (animal species, etc.) and then make predictions based on the new data.
Population Analysis By Photo
The Translational Data Analytics Institute (TDAI) at The Ohio State University uses machine learning to facilitate species monitoring. They extract biological data from photos and videos.
The team has developed an open-source platform called Wildbook that helps researchers collect and analyze photographs. She also trained the algorithm to examine traits of species, such as spot color or fin length. The algorithm scans publicly available images of a particular kind, using sources ranging from social media to digitized museum collections. The platform has already automatically analyzed 17 million images.
Machine Learning
When analyzed, the AI can scan for details that humans would most likely not notice, such as the color scheme of the tiger moth’s wings. An earlier study showed that the human eye is unable to distinguish between the genotypes of male arboreal tiger moths of different ages.
The team is implementing algorithms that, based on the analysis of datasets, generate averages for various patterned animals such as leopards, zebras, and whale sharks. They then analyze where those values change the most. This allows you to track animals non-invasively and without GPS collars, estimate population size, understand migration patterns, and much more.
The goal of the project is to help wildlife researchers overcome the lack of data and offer protection measures for endangered animals.
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For example, the platform scanned 11,000 images of whale sharks to help researchers identify individual individuals and track their movement. This provided updated information on population size. As a result, the International Union for Conservation of Nature has changed the conservation status of the whale shark from “Vulnerable” to “Endangered”.
Now scientists have begun collaborating with researchers studying leopards in India to compare spotting patterns between adults and their offspring using algorithms.
Discovery Of Obscure Species
Researchers from the Norwegian University of Science and Technology, at the request of the International Union for Conservation of Nature, used machine learning to analyze what happens to those species of animals and plants for which they could not collect enough data for routine observation. They used information on 28,363 well-studied animal species. Experts have trained an algorithm to predict the extinction risk of 7,699 species for which there is insufficient data. The algorithm took into account the factors of human activity – for example, the production of hydroelectric power or plastic pollution.
The researchers found that 56% of these species are endangered. Amphibians turned out to be in the most vulnerable position – in this class, 85% of little-studied species may become extinct. The list includes the Malian squealing frog, the spotted narrow-mouthed frog, and other species. In 76% of cases, the predictions of the algorithm turned out to be correct.
Machine Learning
The authors of the work noted that their tool will provide an accurate and quick preliminary assessment for entering the species into the Red Book, facilitate this procedure and make it more objective.
Camera Trap Analysis Platforms
Researchers are creating machine learning tools to analyze population data on a global scale and even involve ordinary volunteers in this process. For example, Wildlife Insights, a global machine-learning platform, collects data on wild animal populations in real time for monitoring. It was developed by Conservation International, the North Carolina Museum of Natural Sciences, the Smithsonian Institution, the Wildlife Conservation Society, and Google.
Wildlife Insights was trained on data from the International Union for Conservation of Nature to monitor protected areas. It generates data from camera traps around the world.
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With Wildlife Insights, researchers can access, share, and analyze global wildlife data to propose conservation actions.
Two main modules are built into the platform: the Wildlife Identification Service (WIS) and the analytics module. WIS runs on a neural network with a classifier pre-trained to embed images from Inception, a model that is widely used in image processing to identify objects. The model is trained on labeled data with time and geospatial labels. WIS has already processed 18 million of these images and is constantly retraining on new data.
Machine Learning
The information obtained through Wildlife Insights will allow you to track the state of protected areas and plan activities for more effective conservation of species.
And data company Appsilon teamed up with the University of Stirling in Scotland and the Gabon National Parks Agency (ANPN) in 2020 to develop the Mbaza AI image classification algorithm. It allows for the monitoring of biodiversity in Gabonese’s Lope and Waka National Parks.
Conservationists set up camera traps to take pictures of various species, including African forest elephants, gorillas, chimpanzees, and pangolins. To train the algorithm, they used a large data set of more than 1.5 million images from several countries and from different camera trap models. After training, Mbaza AI was used to analyze more than 50,000 images collected from 200 such camera traps. It classifies up to 3,000 images per hour with 96% accuracy. Now conservationists can observe and track animals and quickly spot anomalies or red flags. The project is currently working with hundreds of camera traps.
Population Migration Tracking
In order to protect a certain species, you need to know the territory of its habitat. This allows the creation of protected areas. However, visually locating animals can be difficult, especially in difficult-to-reach environments. For example, humpback whales make characteristic sounds that can travel hundreds of kilometers under water. The National Oceanic and Atmospheric Association (Noaa) uses acoustic recorders in the Pacific Islands to monitor populations of marine mammals in hard-to-reach places. Over 14 years of observation, researchers have accumulated about 190,000 hours of acoustic recordings. They then decided to use Google AI to use machine learning to recognize the humpback whales’ calls.
The developed tool made it possible to identify the songs of humpback whales in the data set and to identify patterns of their migration in the area of the Hawaiian and Mariana Islands. The scientists also found that marine mammals swim up to Kingman Reef, where their presence had not previously been noticed. The model was able to accurately locate the whales 97% of the time. Now researchers can evaluate how whale migration routes have changed over time under the influence of anthropogenic factors.
Animal Behavior Tracking
Information about how behavior changes within it helps to study the state of a population. Researchers from the Center for Advanced Research in Collective Behavior at the University of Konstanz and the Max Planck Institute for Animal Behavior have developed a machine learning tool, DenseNet, that can track changes in animal body position with high speed and accuracy. The algorithm is able to correctly measure the position of animals in images after being trained on just 100 examples. DeepPoseKit can be used to study wild animals in difficult field conditions.
Studying the behavior of species will allow researchers to learn how a population lives and develops, as well as how it interacts with the environment. The tool can be used to study species ranging from flies, locusts and mice under controlled laboratory conditions to large mammals in the wild.
Machine Learning
There are more and more such tracking tools, making it easier to remotely track animal behavior.
Moreover, machine learning tools are used to individually identify animals in a population. For example, researchers at Kyoto University and the Bossou Archive project applied facial recognition techniques to a data set of 1 million images of 23 chimpanzee species in Guinea. The recognition accuracy exceeded 90%. The algorithm successfully recognized, in particular, the gender of the chimpanzee. The authors of the development note that this knowledge will automatically track the natural demographic processes in wild populations. So, scientists have found that since the end of 2003, the size of the chimpanzee community has declined sharply due to an epidemic that caused significant demographic changes, and now it is rapidly aging.
Machine Learning
Now the researchers intend to improve their system so that it can identify and track the life of individual individuals even on raw streaming video, that is, directly from cameras. This will help conservation, as it will allow us to analyze key events in the history of the wild community.
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Fortnite Chapter 4 Season 3 Brings Transformers to Battle Pass
Fortnite, the immensely popular battle royale game, never fails to surprise its millions of players worldwide. With the launch of Fortnite Chapter 4 Season 3, the game has taken an exciting turn, introducing two thrilling elements: Transformers and the return of Raptors. This article delves into the details of these new additions to the Fortnite experience, exploring how they enhance gameplay and captivate players.
GameSpot: Fortnite Chapter 4 Season 3
Transformers in the Battle Pass:
One of the major highlights of Chapter 4 Season 3 is the incorporation of the iconic Transformers franchise into the game’s Battle Pass. Players now have the opportunity to obtain and use Transformers-themed cosmetic items, including character skins, back bling, harvesting tools, and more. This collaboration between Fortnite and Transformers brings beloved Autobots and Decepticons to the game, allowing fans to showcase their favorite robots in the battle arena.
As players progress through the Battle Pass tiers, they unlock various Transformers-themed rewards. From the heroic Optimus Prime and the powerful Bumblebee to the notorious Megatron, the range of available character skins appeals to both Fortnite enthusiasts and Transformers aficionados. This crossover not only adds visual flair to the game but also allows players to embody these legendary characters as they battle it out for victory.
Fortnite Chapter 4 Season 3: The Return of Raptors:
In addition to the Transformers extravaganza, Chapter 4 Season 3 marks the return of a fan-favorite element—Raptors. These prehistoric creatures have made a comeback, roaming the island and adding an element of danger and excitement to the gameplay. Players can encounter and tame Raptors, forming a bond with them as they explore the map and participate in battles.
Taming a Raptor offers several advantages in Fortnite. Raptors can be used as loyal companions, aiding players in combat scenarios. They possess unique abilities, such as the ability to track down nearby enemies or provide enhanced mobility. Players can also ride on the back of Raptors, allowing them to navigate the terrain swiftly and effectively. This reintroduction of Raptors injects a new layer of strategy and excitement into the game, encouraging players to adapt their gameplay tactics to utilize these formidable creatures to their advantage.
Impacts on Gameplay and Community:
GameSpot: Fortnite Chapter 4 Season 3
The introduction of Transformers and the return of Raptors significantly impact the gameplay experience and the Fortnite community as a whole. The addition of beloved Transformers characters and cosmetic items enhances player immersion and personalization, providing a fresh visual appeal and allowing fans to express their individuality within the game. The inclusion of Transformers-themed challenges and rewards also promotes engagement and rewards players for their progress.
Moreover, the reappearance of the Raptors brings back nostalgia for veteran players who may have enjoyed their presence in previous seasons. It also introduces an element of surprise for newcomers, presenting them with unique opportunities to explore the island, form new strategies, and forge connections with these virtual companions. The excitement and speculation surrounding these new additions foster a sense of community and shared enthusiasm among Fortnite players.
Conclusion:
Fortnite Chapter 4 Season 3 continues to captivate players with its innovative and exciting updates. The inclusion of Transformers in the Battle Pass and the return of Raptors offer players fresh and thrilling experiences within the game. The ability to don Transformers-themed cosmetic items and unlock beloved characters from the iconic franchise adds a new layer of personalization and fan engagement. Simultaneously, the return of Raptors injects unpredictability and strategic depth into the gameplay, encouraging players to adapt their tactics and embrace these prehistoric companions.
As Fortnite evolves and expands, these additions demonstrate the game’s commitment to delivering novel experiences and catering to the diverse interests of its player base. Whether players are thrilled to embody their favorite Transformers or eager to tame and ride Raptors, Chapter 4 Season 3 presents an exhilarating journey within the ever-evolving Fortnite universe.
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Federal Indictment Accuses Trump of Lying and Scheming to Keep Documents He Knew Were Classified
In a stunning development that has sent shockwaves through the political landscape, a federal indictment has been filed against former President Donald Trump, accusing him of lying and scheming to retain classified documents during his tenure in office.
The Hollywood Reporter: Trump Accused of Lying and Keeping Classified Documents
The allegations paint a damning picture of a leader willing to flout the law and undermine national security for personal gain. This article explores the details of the indictment and its potential implications for Trump’s legacy and the rule of law.
The Allegations:
According to the federal indictment, Trump knowingly and willfully lied about the classification status of certain documents, falsely claiming that they were unclassified and within his personal purview. In reality, the documents in question were highly sensitive and contained classified information vital to national security. By retaining these documents, Trump allegedly put the nation at risk and violated numerous federal laws and regulations.
The indictment further asserts that Trump engaged in a deliberate scheme to hide and conceal the classified documents from proper authorities. It alleges that he directed his staff to remove them from secure government systems and store them in private, unsecured locations, with the intent to control access to the information and avoid accountability. Such actions would be a clear violation of established protocols and procedures for handling classified information.
Legal Ramifications:
If convicted, Trump could face severe legal consequences, including imprisonment and hefty fines. Lying about the classification of documents and actively scheming to retain them could constitute offenses under the Espionage Act, which prohibits the unauthorized disclosure of classified information. Additionally, charges related to obstruction of justice and abuse of power may also come into play, as Trump’s actions appear to have been aimed at impeding investigations and undermining the integrity of the government.
Implications for National Security:
The indictment raises serious concerns about the potential impact on national security. Classified information is classified for a reason – it contains sensitive data that, if compromised, could endanger lives, compromise intelligence sources, and undermine vital operations. By knowingly retaining such information outside of authorized channels, Trump potentially exposed it to unauthorized access and misuse.
The alleged actions outlined in the indictment also reflect a dangerous disregard for established protocols and safeguards that are in place to protect national security. If those entrusted with the highest levels of authority can act with impunity and ignore the rules, it erodes public trust and weakens the foundations upon which our democratic institutions are built.
Political Fallout:
Beyond the legal ramifications, the indictment is likely to have far-reaching political consequences. Trump’s supporters may rally around him, dismissing the charges as politically motivated or part of a larger conspiracy to undermine his presidency. Conversely, his critics will view the indictment as further evidence of his disregard for the rule of law and his willingness to prioritize personal interests over the welfare of the nation.
The indictment could also impact Trump’s political ambitions, should he choose to run for office again. It will undoubtedly become a focal point in any future campaigns and may influence public opinion and voting patterns. The outcome of the legal proceedings will determine the weight of this indictment on Trump’s political future.
Conclusion:
The federal indictment accusing Donald Trump of lying and scheming to retain classified documents presents a serious challenge to his legacy and the rule of law. The allegations, if proven true, reveal a former president who knowingly violated national security protocols and endangered the country’s well-being for personal gain.
The legal and political implications of the indictment are substantial, and the case will undoubtedly be watched closely by observers around the world. As the proceedings unfold, the nation waits to see how justice will be served and what lasting impact this indictment will have on the United States political landscape.
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Odisha Train Accident Updates: A Tragic Incident and its Aftermath
On a fateful day in Odisha, a train accident shook the nation, resulting in significant loss of life and widespread devastation. This tragic incident has raised concerns about railway safety and highlighted the need for preventive measures to ensure the well-being of passengers. In this article, we will provide an overview of the Odisha train accident and explore the latest updates regarding the incident.
Odisha Train Accident Updates and Aftermath
The Odisha Train Accident:
On [Date], a train traveling from [Origin] to [Destination] in Odisha met with a disastrous accident. The train, carrying a significant number of passengers, derailed in the [Location] area, leading to a horrific chain of events. The precise cause of the accident is yet to be determined, but preliminary investigations suggest that it might be attributed to a faulty track or mechanical failure.
Casualties and Rescue Efforts:
The train accident resulted in a tragic loss of life and left numerous passengers injured. The exact number of casualties is still being verified, as rescue operations are ongoing. Upon receiving information about the accident, local authorities and railway personnel immediately mobilized resources for rescue and relief operations. Rescue teams, including medical personnel, were dispatched to the accident site to provide immediate assistance to the survivors.
Medical teams worked tirelessly to treat the injured and provide necessary medical aid. The injured passengers were quickly transported to nearby hospitals and medical facilities for further treatment. The local administration, along with railway authorities, coordinated their efforts to ensure timely and efficient rescue and relief operations.
Investigations and Accountability:
Following the Odisha train accident, investigations were initiated to determine the exact cause and to hold those responsible accountable. Railway authorities, along with experts from relevant fields, conducted thorough examinations of the accident site, the train, and the tracks. The investigation aims to identify any lapses in maintenance, safety protocols, or other factors that might have contributed to the accident.
Railway Safety Measures:
In the wake of the Odisha train accident, railway authorities have intensified their focus on enhancing safety measures. Regular track inspections and maintenance routines have been reinforced to identify and rectify any potential issues promptly. Additionally, technology-driven solutions, such as track monitoring systems and advanced signaling systems, are being explored to prevent similar accidents in the future.
The Indian Railways, which is one of the largest railway networks in the world, is constantly striving to improve safety standards. Lessons learned from such accidents are crucial in driving reforms and implementing robust safety protocols across the entire rail network.
Assistance to Victims and Their Families:
The government and railway authorities have extended their support to the victims and their families affected by the Odisha train accident. Compensation packages, including financial aid and medical assistance, have been announced for the victims and their kin. Special helplines and counseling services have also been set up to provide psychological support to those traumatized by the incident.
Conclusion:
The Odisha train accident serves as a tragic reminder of the importance of maintaining and upgrading railway infrastructure and safety protocols. As the investigations progress, it is hoped that the causes behind the accident will be identified, and measures will be taken to prevent similar incidents in the future. The focus must remain on ensuring the safety and well-being of passengers, and efforts should be made to implement the lessons learned from such incidents to create a more secure and reliable railway system.
While the nation mourns the loss of innocent lives, it is imperative that authorities and stakeholders work together to prevent such accidents from occurring again. By prioritizing safety, investing in infrastructure, and employing advanced technologies, we can strive to make railway travel in Odisha and across the country safer for everyone involved.
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