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Прародитель T1000: алгоритм динамической морфологии мягких роботов

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Первые роботы, чей внешний вид напоминал Железного Дровосека, постепенно уступают дорогу мягким роботам, спектр применения которых растет с каждым новым исследованием. Мягкие роботы могут оперировать в условиях и средах, которые были бы недостижимы их жестким собратьям. Однако, развитие и совершенствование мягкой робототехники далеко от завершения. К примеру, ученые из Массачусетского технологического института (Кембридж, США) разработали новый метод машинного обучения, который позволит динамически управлять роботами с адаптируемой морфологией. В чем суть данного метода, насколько он эффективен, и где могут быть применены «желеобразные» роботы? Ответы на эти вопросы мы найдем в докладе ученых.

Основа исследования


Морфология — это термин, которые имеет множество применений в зависимости от направления науки, в котором он применяется. Говоря о биологии, морфология является наукой о форме и строении организмов. За миллионы лет существования планеты морфология живых организмов многократно менялась в ходе эволюции в ответ на изменения окружающей среды. Также стоит отметить изменения морфологии, которые протекают за период жизни того или иного организма. Подобные изменения могут быть разительными в аспекте габаритов (например, когда из небольшого семечка вырастает огромное дерево), так и по форме (например, когда из головастика вырастает лягушка).

Подобные биологические процессы являются практически неисчерпаемым источником вдохновения для инженеров, занимающихся разработкой новых типов роботов. Если же говорить о роботах с динамической морфологией, то необходимо обеспечить его системой, позволяющей ему верно обрабатывать изменения среды и соответствующим образом на это реагировать.

Разработка реконфигурируемых роботов пока еще сталкивается с большим числом сложностей, как в сфере материального, так и в сфере программного обеспечения. В рассматриваемом нами сегодня труде ученые определили три основные проблемы в алгоритмическом исследовании реконфигурируемых роботов и предложили способы их решения.

Как отмечают ученые описать, что такое реконфигурируемый робот, в теории достаточно легко, однако единого мнения о том, как моделировать этих роботов и как можно параметризовать их действия, пока еще нет. Ученые предлагают моделировать мягких реконфигурируемых роботов с помощью метода материальной точки* (MPM от Material Point Method), одновременно изменяя обновление напряжения Коши*, чтобы включить в него актуацию, заданную через непрерывное мышечное поле.
Метод материальной точки* — это числовой метод, используемый для моделирования поведения твердых тел, жидкостей, газов и любого объемного материала. В частности, это устойчивый метод дискретизации пространства для моделирования многофазовых взаимодействий (твердое тело-жидкость-газ).
Тензор напряжений* (иногда тензор напряжений Коши, тензор натяжений) — тензор второго ранга, описывающий механические напряжения в произвольной точке нагруженного тела, возникающих в этой точке при его (тела) малых деформациях.
Это приводит к моделированию недавно описанного реконфигурируемого магнитного робота-слизня («Reconfigurable Magnetic Slime Robot: Deformation, Adaptability, and Multifunction»). В результате появляется возможность формализовать управление реконфигурируемым роботом в задачу обучения с подкреплением, используя двумерное непрерывное мышечное поле в качестве пространства действия.

Еще более важным моментом является тот факт, что неструктурированная природа мягких роботов делает традиционные алгоритмы управления непригодными. В то время как методы, основанные на обучении, такие как обучение с подкреплением (RL от reinforcement learning), превосходны в решении множества неструктурированных задач управления, реконфигурируемые роботы представляют собой уникальную задачу из-за чрезвычайно многомерного пространства действий, необходимого даже для малейшего изменения морфологии.

Например, для успеха RL необходимо гарантировать, что случайное движение приведет к значимым морфологическим изменениям. На практике это означает, что действия должны перемещать большие части робота за раз. С другой стороны, для выполнения детальных действий, таких как ходьба, пространство действий должно поддерживать детальные действия.

Наконец, не существует стандартного эталона для детализированных реконфигурируемых роботов. Ученые представили DittoGym, первый тест RL для реконфигурируемых роботов. DittoGym — это набор из восьми долгосрочных задач, которые требуют различной степени морфологических изменений. Четыре среды требуют, чтобы робот несколько раз менял свою морфологию во время выполнения задачи.

Теоретическая основа


Метод материальной точки (MPM) — это универсальный метод компьютерного моделирования на основе частиц, широко используемый в области механики твердого тела и вычислительной физики. Будучи гибридом методов Эйлера и Лагранжа, MPM включает в себя операции как на основе сетки, так и на основе частиц. Этап сетки в первую очередь служит для обработки граничных условий, а этап частиц ориентирован на взаимодействие между тысячами частиц.

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Изображение №1

На этом последнем этапе важнейшей задачей является вычисление деформации материала, также известной как напряжение Коши, поскольку она глубоко влияет на последующее движение частиц. Напряжение Коши определяется следующим уравнением:

Cauchy Stress = 2μ(Fp − r)FTp + diag(λ(Jp − 1)Jp)

где μ и λ представляют параметры материала, rp — ортогональная матрица, полученная в результате полярного разложения в MPM, а Jp — определитель Fp.

Критерий текучести фон Мизеса используется для прогнозирования момента, когда материал подвергнется пластической деформации. Градиент деформации Fp можно разложить с помощью разложения по сингулярным значениям (SVD от Singular Value Decomposition) для получения диагональной матрицы Σp, которая представляет масштаб деформации для каждой частицы. Пластическая деформация начинается, когда норма этой матрицы, обозначенная как ∥Σp2, превышает критерий текучести Yieldm. На этом этапе материал «забывает» свое первоначальное состояние, что требует проекции градиента деформации для учета этого отклонения от исходной конфигурации.

Ученые использовали обучение с подкреплением (RL), где задача моделировалась как марковский процесс принятия решений* (MDP от Markov Decision Process), характеризуемый пятью переменными (S, A, P, r, γ), где: S обозначает пространство состояний, A обозначает пространство действий, P: S × A → S инкапсулирует динамику перехода среды, r(s, a): S × A → R определяет количественную оценку вознаграждений, а γ ∈ (0, 1] управляет временным дисконтированием вознаграждений. Цель RL агента — получить политику πθ(at|st), параметризованную глубокой нейронной сетью.
Марковский процесс принятия решений* — математический формализм для марковского дискретного стохастического процесса управления, основа для моделирования последовательного принятия решений в ситуациях, где результаты частично случайны и частично зависят от лица, принимающего решения.

Детали разработанного метода


Как говорилось ранее, ученые определили три основные проблемы в области алгоритмизации реконфигурируемых роботов: отсутствие формализации, отсутствие соответствующего алгоритма и отсутствие эталона.

Управление реконфигурируемыми роботами — это неструктурированная задача управления, которая, естественно, подходит для методов проб и ошибок, таких как обучение с подкреплением. Таким образом, ученые формализовали задачу управления в виде строительных блоков MDP. Чтобы определить динамику перехода в MDP, необходимо формализовать реконфигурируемых мягких роботов в моделируемую систему.

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Изображение №2

Чтобы этого достичь, ученые использовали MPM в качестве основы моделирования мягких роботов. Как показано выше, для моделирования реалистичных деформаций ученые черпали вдохновение из предыдущих работ, вводя критерий текучести фон Мизеса в алгоритм MPM. Этот критерий моделирует робота как упругопластический материал, демонстрирующий упругую деформацию при малых напряжениях и пластическую деформацию при более высоких напряжениях.

Также была использована модификация уравнения напряжения Коши, позволяющая частицам растягивать или сжимать свою форму в ответ на сигнал действия, аналогично естественным мышцам. В результате робот демонстрирует макроскопические изменения в морфологии, когда воздействие заставляет значительную часть частиц подвергаться пластической деформации, в то время как напряжение ниже предела текучести фон Мизеса приводит к упругим деформациям, служащим пружинным механизмом, обеспечивающим например, средства передвижения.

Final Cauchy Stress = 2μ(Fp — r)FTp + diag (λ(Jp — 1)Jp) + Fpcp FTp

Вышеупомянутая динамика перехода MDP требует указания вектора срабатывания для каждой отдельной частицы. Стоит отметить, что MPM — это метод моделирования на основе частиц, который аппроксимирует непрерывную динамику в непрерывном пространстве. Следовательно, пространство действий должно также представлять собой непрерывное поле, где каждая координата внутри робота имеет вектор действия. Это также отражает управление магнитным роботом-слизнем с помощью внешнего магнитного поля.

Определив пространство действий, легко определить остальные компоненты MDP: состояние — это просто состояние всех частиц в моделировании MPM, тогда как существует возможность выбирать функции наблюдения и вознаграждения в индивидуальном порядке для разных сценариев среды. Таким образом, ученые формализовали абстрактную задачу управления реконфигурируемым роботом в задачу MDP, которую можно решить с помощью обучения с подкреплением.

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Изображение №3

Модель была разработана с полностью сверточной архитектурой, что позволяет ей анализировать наблюдения на уровне пикселей за формой робота и его скоростью. На основе этого анализа она генерирует дискретные сигналы действия, которые способствуют аппроксимации идеального силового поля, как показано на изображении выше.

MDP требует бесконечномерного пространства действия в виде непрерывного двумерного силового поля, действующего на робота. Бикубическая интерполяция может интерполировать регулярную сетку n-D объектов в отображение любой координаты n-D на объект. Таким образом, параметризация была выполнена с помощью нейронной сети, которая выводит дискретную сетку действий n-D и интерполирует ее в непрерывное пространство действий.

Хотя дискретная параметризация обеспечивает дифференцируемый способ задания пространственно непрерывного действия, необходимо достаточно высокое разрешение дискретизации, чтобы контролировать мельчайшие изменения морфологии. Высокие разрешения приводят к созданию многомерного пространства действий, что оказалось сложной задачей для традиционных алгоритмов обучения с подкреплением. Ученые решили использовать полностью сверточную сеть для параметризации политики, которая может совместно использовать параметры в разных пространственных местоположениях, эффективно уменьшая размер пространства поиска. Эта сеть принимает изображения реконфигурируемого робота и его непосредственного окружения в качестве входных данных и генерирует 2D-выходные данные, которые аппроксимируют непрерывное мышечное поле посредством бикубической интерполяции.

Подготовка к опытам


Цифровые эталонные среды широко используются исследователями алгоритмов управления для ускорения своих исследований и облегчения честного сравнения. Используемый учеными в данном труде тест DittoGym учитывает отсутствие стандартизированных тестов для реконфигурируемых мягких роботов с малейшими изменениями морфологии. В набор из шести OpenAI сред Gym было включено формализованное моделирование. Для моделирования деформируемых мягких роботов и внешних объектов, взаимодействующих с ними, было реализовано моделирование соответствующих материалов в методе материальной точки (MPM от Material Point Method) с использованием фреймворка Taichi. Следовательно, DittoGym не только предоставляет удобный Python интерфейс, но также полностью использует аппаратные ускорители, такие как графические процессоры, для моделирования частиц MPM.

В качестве пространства наблюдения было использовано растровое двумерное изображение квадратной области вокруг геометрического центра робота, где в качестве каналов используются как занятость, так и скорость. Пространство действий реализовано в виде 2D-сетки срабатываний для одного и того же квадрата с максимально возможным разрешением для моделирования. Каждый двумерный вектор в двумерной сетке действий контролирует напряжение, приложенное к соответствующей точке, где величина определяет, произойдет ли пластическая или упругая деформация.

В рамках этой структуры ученые реализовали множество задач, включая сопоставление форм, локомоция, растяжение и манипулирование. Каждая задача требует морфологической адаптации для удовлетворения конкретных детальных требований, иногда требуя множественных морфологических изменений для достижения желаемых целей.

Результаты опытов


В ходе экспериментов основная задача заключалась в поиске ответов на три вопроса:

  • может ли используемая формализация в сочетании с соответствующими алгоритмами позволить моделируемым мягким роботам выполнять задачи, требующие мельчайших изменений морфологии?
  • может ли DittoGym тест в достаточной степени оценить алгоритмы, предназначенные для контроля мелких изменений морфологии мягких роботов?
  • насколько эффективна выборка CFP (от Coarse-to-Fine Policy) для управления реконфигурируемым роботом по сравнению с соответствующими базовыми показателями?

54hy_y0d35h2ye8gvhjs_eisosu.png
Изображение №4

Одним из основных результатов исследования, как отмечают ученые, является формализация управления реконфигурируемым роботом в задаче обучения с подкреплением. На изображении №1 была визуализирована многоэтапная задача, которую можно реализовать с помощью исследуемой платформы. На изображении выше показаны четыре дополнительных задания из DittoGym, которые требуют от робота изменения своей морфологии во время их выполнения.

В задаче «SHAPE MATCH» робот может успешно имитировать форму целевого символа, подчеркивая способность робота перенастраиваться под произвольные целевые формы.

В задаче «GROW» учится удлинять и изгибать свое тело. Эта новая форма позволяет роботу обходить препятствия и достигать целевой точки, подобно тому, как это делают семена в процессе произрастания.

В задаче «OBSTACLE» робот удлиняет свое тело и наклоняется вперед, чтобы использовать силу гравитации и быстро преодолеть препятствие. Впоследствии робот формирует два отростка, похожие на ноги, и использует их для ходьбы, обеспечивая эффективное продвижение вперед.

Наконец, для задачи «SLOT» робот уменьшает свою высоту, одновременно отращивая две очень короткие ноги, чтобы маневрировать в исключительно узком пространстве, напоминая мышь, бегущую по трубе. Чтобы открыть деревянную крышку на конце трубы, робот удаляет ноги и вытягивает туловище вверх, чтобы эффективно взаимодействовать с крышкой.

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Изображение №5

Прежде чем количественно оценить CFP по сравнению с базовыми показателями в DittoGym, необходимо доказать, что DittoGym действительно требует мельчайших изменений морфологии, чтобы мягкий робот достигал высоких результатов.

В количественном отношении ученые использовали экспертные политики, обученные с учетом каждой детализации пространства действий, и визуализировали максимальное вознаграждение, которого они могут достичь. Ученые изучили эту метрику для трех разных уровней детализации: грубого (4×4×2), среднего (8×8×2) и тонкого (16×16×2). Как показано выше, более высокое разрешение действий почти всегда приводит к более высокому возможному результату во всех 8 средах. Эта тенденция подтверждает, что DittoGym требует от агента изучения мелких морфологических изменений.

xsz5cdhnn4in7jyoe1ae8kbmlrs.png
Изображение №6

Качественно возможно визуализировать поведение экспертной политики на разных уровнях детализации. На изображении выше показана визуализация лучшей формы, которую робот может достичь в задаче «SHAPE MATCH» при различных разрешениях действий. При более грубом разрешении робот может вносить значимые изменения в форму, но не может генерировать высокочастотные детали целевой формы, такие как кончики каждого луча звезды. С другой стороны, параметризация действий с высоким разрешением позволяет роботу изменять свою морфологию, чтобы соответствовать целевой форме.

В заключении исследования ученые попытались понять, имеет ли CFP более высокую производительность по сравнению с базовыми показателями при управлении реконфигурируемыми роботами с мельчайшими изменениями морфологии. Поэтому ученые сравнили CFP и вышеупомянутые базовые показатели в 8 различных средах DittoGym.

ygxcybfkcwmau7kc0uccv0eaeay.png
Изображение №7

Выше показаны кривые результатов за единичный опыт для всех восьми сред. Тестируемый алгоритм CFP последовательно превосходит все базовые показатели во всех задачах с точки зрения общей эффективности выборки. Кроме того, CFP может постоянно получать более высокие результаты за опыт при конвергенции. При визуализации политики только CFP способен добиться успеха в долгосрочных многоэтапных средах, представляя его как единственный жизнеспособный вариант решения сложных задач.

Как количественное сравнение, так и качественный анализ демонстрируют эффективность CFP в DittoGym, иллюстрируя его уникальную способность управлять реконфигурируемыми мягкими роботами для выполнения долгосрочных задач, требующих мельчайших изменений формы.

Для более детального ознакомления с нюансами исследования рекомендую заглянуть в доклад ученых, дополнительные материалы к нему, а также на их GitHub.

Эпилог


В рассмотренном нами сегодня труде ученые рассказали о разработанном ими алгоритме, который может эффективно управлять изменениями морфологии мягких роботов для повышения эффективности выполне6ния сложных и многоэтапных задач.

Вдохновением для данного исследования, как не удивительно, стала природа. Многие организмы претерпевают морфологические изменения не только за тысячи лет эволюции, но и в период своей жизни: гусеницы превращаются в бабочек, головастики в лягушек и т. д. Научить робота подобной трансформации, даже если он обладает материальным обеспечением, крайне сложно.

Авторы исследования стали первыми, кто смог реализовать инновационную параметризацию реконфигурируемых роботов как мягкого материала, приводимого в действие мышечным полем. Затем ученые представили фреймворк CFP (от Coarse-to-Fine Policy), который использует полностью сверточную оценку состояния и параметризацию действий, дополненную учебной программой, которая гарантирует значимое исследование пространства при сохранении возможностей детального управления.

Разработанный учеными тест, названный DittoGym, использовал восемь сред, которые требуют радикальных изменений морфологии мягкого робота для выполнения поставленных задач. В результате роботы, обученные с помощью CFP, научились динамически изменять свою морфологию несколько раз в течение одного периода активности для выполнения тех или иных задач.

Несмотря на то, что мягкие роботы с динамической морфологией еще далеки от своего создания, данное исследование позволяет создать фундамент для эффективного управления такими роботами будущего. Авторы исследования также уверены, что их труд послужит вдохновением не только для создания вышеописанных роботов, но и для использования двумерных пространств для тестирования и реализации других сложных задач управления.

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Источник

  • 07.09.23 16:24 CherryTeam

    Cherry Team atlyginimų skaičiavimo programa yra labai naudingas įrankis įmonėms, kai reikia efektyviai valdyti ir skaičiuoti darbuotojų atlyginimus. Ši programinė įranga, turinti išsamias funkcijas ir patogią naudotojo sąsają, suteikia daug privalumų, kurie padeda supaprastinti darbo užmokesčio skaičiavimo procesus ir pagerinti finansų valdymą. Štai keletas pagrindinių priežasčių, kodėl Cherry Team atlyginimų skaičiavimo programa yra naudinga įmonėms: Automatizuoti ir tikslūs skaičiavimai: Atlyginimų skaičiavimai rankiniu būdu gali būti klaidingi ir reikalauti daug laiko. Programinė įranga Cherry Team automatizuoja visą atlyginimų skaičiavimo procesą, todėl nebereikia atlikti skaičiavimų rankiniu būdu ir sumažėja klaidų rizika. Tiksliai apskaičiuodama atlyginimus, įskaitant tokius veiksnius, kaip pagrindinis atlyginimas, viršvalandžiai, premijos, išskaitos ir mokesčiai, programa užtikrina tikslius ir be klaidų darbo užmokesčio skaičiavimo rezultatus. Sutaupoma laiko ir išlaidų: Darbo užmokesčio valdymas gali būti daug darbo jėgos reikalaujanti užduotis, reikalaujanti daug laiko ir išteklių. Programa Cherry Team supaprastina ir pagreitina darbo užmokesčio skaičiavimo procesą, nes automatizuoja skaičiavimus, generuoja darbo užmokesčio žiniaraščius ir tvarko išskaičiuojamus mokesčius. Šis automatizavimas padeda įmonėms sutaupyti daug laiko ir pastangų, todėl žmogiškųjų išteklių ir finansų komandos gali sutelkti dėmesį į strategiškai svarbesnę veiklą. Be to, racionalizuodamos darbo užmokesčio operacijas, įmonės gali sumažinti administracines išlaidas, susijusias su rankiniu darbo užmokesčio tvarkymu. Mokesčių ir darbo teisės aktų laikymasis: Įmonėms labai svarbu laikytis mokesčių ir darbo teisės aktų, kad išvengtų baudų ir teisinių problemų. Programinė įranga Cherry Team seka besikeičiančius mokesčių įstatymus ir darbo reglamentus, užtikrindama tikslius skaičiavimus ir teisinių reikalavimų laikymąsi. Programa gali dirbti su sudėtingais mokesčių scenarijais, pavyzdžiui, keliomis mokesčių grupėmis ir įvairių rūšių atskaitymais, todėl užtikrina atitiktį reikalavimams ir kartu sumažina klaidų riziką. Ataskaitų rengimas ir analizė: Programa Cherry Team siūlo patikimas ataskaitų teikimo ir analizės galimybes, suteikiančias įmonėms vertingų įžvalgų apie darbo užmokesčio duomenis. Ji gali generuoti ataskaitas apie įvairius aspektus, pavyzdžiui, darbo užmokesčio paskirstymą, išskaičiuojamus mokesčius ir darbo sąnaudas. Šios ataskaitos leidžia įmonėms analizuoti darbo užmokesčio tendencijas, nustatyti tobulintinas sritis ir priimti pagrįstus finansinius sprendimus. Pasinaudodamos duomenimis pagrįstomis įžvalgomis, įmonės gali optimizuoti savo darbo užmokesčio strategijas ir veiksmingai kontroliuoti išlaidas. Integracija su kitomis sistemomis: Cherry Team programinė įranga dažnai sklandžiai integruojama su kitomis personalo ir apskaitos sistemomis. Tokia integracija leidžia automatiškai perkelti atitinkamus duomenis, pavyzdžiui, informaciją apie darbuotojus ir finansinius įrašus, todėl nebereikia dubliuoti duomenų. Supaprastintas duomenų srautas tarp sistemų padidina bendrą efektyvumą ir sumažina duomenų klaidų ar neatitikimų riziką. Cherry Team atlyginimų apskaičiavimo programa įmonėms teikia didelę naudą - automatiniai ir tikslūs skaičiavimai, laiko ir sąnaudų taupymas, atitiktis mokesčių ir darbo teisės aktų reikalavimams, ataskaitų teikimo ir analizės galimybės bei integracija su kitomis sistemomis. Naudodamos šią programinę įrangą įmonės gali supaprastinti darbo užmokesčio skaičiavimo procesus, užtikrinti tikslumą ir atitiktį reikalavimams, padidinti darbuotojų pasitenkinimą ir gauti vertingų įžvalgų apie savo finansinius duomenis. Programa Cherry Team pasirodo esanti nepakeičiamas įrankis įmonėms, siekiančioms efektyviai ir veiksmingai valdyti darbo užmokestį. https://cherryteam.lt/lt/

  • 08.10.23 01:30 davec8080

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  • 06.09.24 01:44 Celinagarcia

    HOW TO RECOVER MONEY LOST IN BITCOIN/USDT TRADING OR TO CRYPTO INVESTMENT !! Hi all, friends and families. I am writing From Alberton Canada. Last year I tried to invest in cryptocurrency trading in 2023, but lost a significant amount of money to scammers. I was cheated of my money, but thank God, I was referred to Hack Recovery Wizard they are among the best bitcoin recovery specialists on the planet. they helped me get every penny I lost to the scammers back to me with their forensic techniques. and I would like to take this opportunity to advise everyone to avoid making cryptocurrency investments online. If you ​​​​​​have already lost money on forex, cryptocurrency or Ponzi schemes, please contact [email protected] or WhatsApp: +1 (757) 237–1724 at once they can help you get back the crypto you lost to scammers. BEST WISHES. Celina Garcia.

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  • 23.09.24 18:56 matthewshimself

    At first, I was admittedly skeptical about Worldcoin (ref: https://worldcoin.org/blog/worldcoin/this-is-worldcoin-video-explainer-series), particularly around the use of biometric data and the WLD token as a reward mechanism for it. However, after following the project closer, I’ve come to appreciate the broader vision and see the value in the underlying tech behind it. The concept of Proof of Personhood (ref: https://worldcoin.org/blog/worldcoin/proof-of-personhood-what-it-is-why-its-needed) has definitely caught my attention, and does seem like a crucial step towards tackling growing issues like bots, deepfakes, and identity fraud. Sam Altman’s vision is nothing short of ambitious, but I do think he & Alex Blania have the chops to realize it as mainstay in the global economy.

  • 01.10.24 14:54 Sinewclaudia

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  • 02.10.24 22:27 Emily Hunter

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  • 18.10.24 09:34 freidatollerud

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  • 31.10.24 00:13 ytre89

    Can those who have fallen victim to fraud get their money back? Yes, you might be able to get back what was taken from you if you fell prey to a fraud from an unregulated investing platform or any other scam, but only if you report it to the relevant authorities. With the right plan and supporting documentation, you can get back what you've lost. Most likely, the individuals in control of these unregulated platforms would attempt to convince you that what happened to your money was a sad accident when, in fact, it was a highly skilled heist. You should be aware that there are resources out there to help you if you or someone you know has experienced one of these circumstances. Do a search using (deftrecoup (.) c o m). Do not let the perpetrators of this hoaxes get away with ruining you mentally and financially.

  • 02.11.24 14:44 diannamendoza732

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  • 12.11.24 00:50 TERESA

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  • 17.11.24 09:31 Vivianlocke223

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  • 19.11.24 03:06 [email protected]

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  • 19.11.24 03:07 [email protected]

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    Being a parent is great until your toddler figures out how to use your devices. One afternoon, I left my phone unattended for just a few minutes rookie mistake of the century. I thought I’d take a quick break, but little did I know that my curious little genius was about to embark on a digital adventure. By the time I came back, I was greeted by two shocking revelations: my toddler had somehow managed to buy a $5 dinosaur toy online and, even more alarmingly, had locked me out of my cryptocurrency wallet holding a hefty $75,000. Yes, you heard that right a dinosaur toy was the least of my worries! At first, I laughed it off. I mean, what toddler doesn’t have a penchant for expensive toys? But then reality set in. I stared at my phone in disbelief, desperately trying to guess whatever random string of gibberish my toddler had typed as a new password. Was it “dinosaur”? Or perhaps “sippy cup”? I felt like I was in a bizarre game of Password Gone Wrong. Every attempt led to failure, and soon the laughter faded, replaced by sheer panic. I was in way over my head, and my heart raced as the countdown of time ticked away. That’s when I decided to take action and turned to Digital Tech Guard Recovery, hoping they could solve the mystery that was my toddler’s handiwork. I explained my predicament, half-expecting them to chuckle at my misfortune, but they were incredibly professional and empathetic. Their confidence put me at ease, and I knew I was in good hands. Contact With WhatsApp: +1 (443) 859 - 2886  Email digital tech guard . com  Telegram: digital tech guard recovery . com  website link :: https : // digital tech guard . com Their team took on the challenge like pros, employing their advanced techniques to unlock my wallet with a level of skill I can only describe as magical. As I paced around, anxiously waiting for updates, I imagined my toddler inadvertently locking away my life savings forever. But lo and behold, it didn’t take long for Digital Tech Guard Recovery to work their magic. Not only did they recover the $75,000, but they also gave me invaluable tips on securing my wallet better like not leaving it accessible to tiny fingers! Who knew parenting could lead to such dramatic situations? Crisis averted, and I learned my lesson: always keep my devices out of reach of little explorers. If you ever find yourself in a similar predicament whether it’s tech-savvy toddlers or other digital disasters don’t hesitate to reach out to Digital Tech Guard Recovery. They saved my funds and my sanity, proving that no challenge is too great, even when it involves a toddler’s mischievous fingers!

  • 21.11.24 08:02 Emily Hunter

    If I hadn't found a review online and filed a complaint via email to support@deftrecoup. com , the people behind this unregulated scheme would have gotten away with leaving me in financial ruins. It was truly the most difficult period of my life.

  • 22.11.24 04:41 [email protected]

    I never could have imagined the nightmare of losing access to my digital wallet. All of my cryptocurrency holdings were abruptly imprisoned, inaccessible, and appeared to be lost forever following a catastrophic hardware breakdown. Years of meticulous investment and careful saving were reduced to nothing more than strings of code that I could no longer control, and I could feel the dread and sorrow that swept through me at that very instant. Thankfully, during my worst moment, I came into (TRUST GEEKS HACK EXPERT), a professional service devoted to recovering lost or inaccessible digital data. With optimism, I went out to their team of skilled technologists, laying bare the full nature of my issue. What followed was a laborious, multi-step process that required an almost surgical level of digital forensics and Bitcoin skill. In order to create a thorough profile of my wallet's contents and activities, the (TRUST GEEKS HACK EXPERT) team first thoroughly examined the transaction history and metadata connected to it. Next, they implemented a series of advanced recovery techniques, using cutting-edge software tools to bypass the access barriers that had left me locked out. The entire process was shrouded in secrecy and discretion, with the (TRUST GEEKS HACK EXPERT) team working tirelessly to protect the confidentiality of my sensitive financial information. After what felt like an eternity of nervous anticipation, the day finally arrived when I received the triumphant notification – my wallet had been successfully restored, and all of my precious digital assets had been returned to my control. The sense of relief was indescribable, as I could finally breathe easy knowing that the fruits of my financial discipline had been safeguarded. While the experience of losing access to my wallet was undoubtedly traumatic, (TRUST GEEKS HACK EXPERT) intervention allowed me to emerge from the ordeal with my cryptocurrency holdings intact, and a renewed appreciation for the importance of proactive digital asset management. You can contact Them through EMAIL: [email protected] - TELEGRAM: TRUSTGEEKSHACKEXPERT

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  • 22.11.24 23:43 teresaborja

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  • 24.11.24 02:21 [email protected]

    I never could have imagined the nightmare of losing access to my digital wallet. All of my cryptocurrency holdings were abruptly imprisoned, inaccessible, and appeared to be lost forever following a catastrophic hardware breakdown. Years of meticulous investment and careful saving were reduced to nothing more than strings of code that I could no longer control, and I could feel the dread and sorrow that swept through me at that very instant. Thankfully, during my worst moment, I came into (TRUST GEEKS HACK EXPERT), a professional service devoted to recovering lost or inaccessible digital data. With optimism, I went out to their team of skilled technologists, laying bare the full nature of my issue. What followed was a laborious, multi-step process that required an almost surgical level of digital forensics and Bitcoin skill. In order to create a thorough profile of my wallet's contents and activities, the (TRUST GEEKS HACK EXPERT) team first thoroughly examined the transaction history and metadata connected to it. Next, they implemented a series of advanced recovery techniques, using cutting-edge software tools to bypass the access barriers that had left me locked out. The entire process was shrouded in secrecy and discretion, with the (TRUST GEEKS HACK EXPERT) team working tirelessly to protect the confidentiality of my sensitive financial information. After what felt like an eternity of nervous anticipation, the day finally arrived when I received the triumphant notification – my wallet had been successfully restored, and all of my precious digital assets had been returned to my control. The sense of relief was indescribable, as I could finally breathe easy knowing that the fruits of my financial discipline had been safeguarded. While the experience of losing access to my wallet was undoubtedly traumatic, (TRUST GEEKS HACK EXPERT) intervention allowed me to emerge from the ordeal with my cryptocurrency holdings intact, and a renewed appreciation for the importance of proactive digital asset management. You can contact Them through EMAIL: [email protected] - TELEGRAM: TRUSTGEEKSHACKEXPERT

  • 25.11.24 02:19 briankennedy

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  • 26.11.24 21:59 [email protected]

    In a world brimming with enticing investment opportunities, it is crucial to tread carefully. The rise of digital currencies has attracted many eager investors, but along with this excitement lurk deceitful characters ready to exploit the unsuspecting. I learned this lesson the hard way, and I want to share my story in the hopes that it can save someone from making the same mistakes I did. It all began innocently enough when I came across an engaging individual on Facebook. Lured in by promises of high returns in the cryptocurrency market, I felt the electric thrill of potential wealth coursing through me. Initial investments returned some profits, and that exhilarating taste of success fueled my ambition. Encouraged by a meager withdrawal, I decided to commit even more funds. This was the moment I let my guard down, blinded by greed. As time went on, the red flags started to multiply. The moment I tried to withdraw my earnings, a cascade of unreasonable fees appeared like a thick mist, obscuring the truth. “Just a little more,” they said, “Just until the next phase.” I watched my hard-earned money slip through my fingers as I scraped together every last cent to pay those relentless fees. My trust had become my downfall. In the end, I lost not just a significant amount of cash, but my peace of mind about $1.1 million vanished into the abyss of false promises and hollow guarantees. But despair birthed hope. After a cascade of letdowns, I enlisted the help of KAY-NINE CYBER SERVICES, a team that specializes in reclaiming lost funds from scams. Amazingly, they worked tirelessly to piece together what had been ripped away, providing me with honest guidance when I felt utterly defeated. Their expertise in navigating the treacherous waters of crypto recovery was a lifeline I desperately needed. To anyone reading this, please let my story serve as a warning. High returns often come wrapped in the guise of deception. Protect your investments, scrutinize every opportunity, and trust your instincts. Remember, the allure of quick riches can lead you straight to heartbreak, but with cautious determination and support, it is possible to begin healing from such devastating loss. Stay informed, stay vigilant, and may you choose your investment paths wisely. Email: kaynine @ cyberservices . com

  • 26.11.24 23:12 rickrobinson8

    FAST SOLUTION FOR CYPTOCURRENCY RECOVERY SPARTAN TECH GROUP RETRIEVAL

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  • 27.11.24 00:39 [email protected]

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  • 27.11.24 09:10 Michal Novotny

    The biggest issue with cryptocurrency is that it is unregulated, wh ich is why different people can come up with different fake stories all the time, and it is unfortunate that platforms like Facebook and others only care about the money they make from them through ads. I saw an ad on Facebook for Cointiger and fell into the scam, losing over $30,000. I reported it to Facebook, but they did nothing until I discovered deftrecoup . c o m from a crypto community; they retrieved approximately 95% of the total amount I lost.

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