Products related to Complexity:
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Nowhere To Be Found : A gripping crime mystery suspense thriller
A dead body. A missing woman. A secret rising to the surface.Lucy has gone missing.Her husband Scott claims to have no idea where she is.But rumours of their marriage swirl and Scott doesn’t seem to be playing the role of a concerned husband well. Meanwhile, DS Kate Munro is investigating another case – a victim found dead floating in a lake.When she learns it was Lucy who first reported the body, Kate realises these cases may be connected. Both investigations lead Kate into dangerous waters and time is running out for Lucy.She must piece together the link between the two crimes, before it’s too late…A nail-biting, unputdownable crime thriller perfect for fans of Lisa Jewell, Clare Mackintosh and Cara Hunter. Previously published under Louisa de Lange. Praise for Nowhere to be Found ‘Brilliantly addictive’ S J Watson‘Smart, dark, with a show-stopping finale!A satisfyingly juicy mystery with a great heroine’ Emma Rowley‘An assured and skilfully written crime thriller that will have you on the edge of your seat’ Alison Belsham‘A compelling thriller with SO many twists I was constantly left guessing about where the story would go’ Carys Jones‘A layered, compelling thriller with a page-turning quality and characters the reader can invest in’ AJ Park‘DS Kate Munro is a really interesting and believable character… The plot was complex, twisty and kept me guessing’ ?????Reader review‘Fluid writing, believable characters, a complex plot, nail biting twists and turns and a wish for it not to end.This book has it all’ ????? Reader review‘Another gripping page-turner. Louisa’s writing really draws you in and you feel like you know the characters’ ?????Reader review
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Born to Die : Mystery, suspense and crime in this gripping thriller
'Shiveringly good suspense!' Lisa GardnerTHE THIRD BOOK IN A GRIPPING SERIES FROM 30 MILLION COPY SELLING AUTHOR. At first Kacey Lambert thinks it's a sad, strange coincidence that two women with an amazing resemblance to her have died suddenly.But detective Selena Alvarez suspects otherwise. An autopsy confirms that one of the women had traces of poison in her blood... And Kacey has started to notice ties between the dead women's lives and her own.They were all close in age. They were born within a few miles of each other. And they all have ties with Trace O'Halleran, the single father Kacey is dating. Soon more lookalikes are dying and as the body count rises, the killer gets bolder and more brutal.All Kacey knows is that it's only a matter of time before hers is the next name on a list of those who were born to die. 'She is one of the best' Harlan CobenTHE NEXT BOOK IN THE SERIES, AFRAID TO DIE, IS AVAILABLE NOW
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Expecting to Die : Mystery, suspense and crime in this gripping thriller
'Shiveringly good suspense!' Lisa GardnerTHE SEVENTH BOOK IN A GRIPPING SERIES FROM 30 MILLION COPY SELLING AUTHOR. THE WOODS ARE DARKSome places earn their bad reputation through tall tales.Grizzly Falls is different. Here, killers aren't just the stuff of legends. Someone is in the nighttime shadows, watching the local teens in the moonlit woods.Waiting for the right moment, the right victim. Waiting to take away a life. AND DEEPDetective Regan Pescoli is counting the days until her maternity leave.Exhausted and emotional, the last thing she needs is another suspected serial killer.Especially when her daughter, Bianca, is swept up in the media storm.AND DEADLY... Another body is found...and another. And as the nightmare strikes closer to home, Pescoli races to find the terror lingering in the darkness, where there are too many places to hide...and countless places to die . . . 'She is one of the best' Harlan CobenTHE NEXT BOOK IN THE SERIES, WILLING TO DIE, IS AVAILABLE NOW
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Think Complexity : Complexity Science and Computational Modeling
Complexity science uses computation to explore the physical and social sciences.In Think Complexity, you’ll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics.Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations.In this updated second edition, you will: Work with NumPy arrays and SciPy methods, including basic signal processing and Fast Fourier Transform Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines Get Jupyter notebooks filled with starter code and solutions to help you re-implement and extend original experiments in complexity; and models of computation like Turmites, Turing machines, and cellular automata Explore the philosophy of science, including the nature of scientific laws, theory choice, and realism and instrumentalism Ideal as a text for a course on computational modeling in Python, Think Complexity also helps self-learners gain valuable experience with topics and ideas they might not encounter otherwise.
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Can complexity be objectively measured?
Complexity can be objectively measured to some extent, especially in the context of information theory and algorithmic complexity. In information theory, complexity can be measured using metrics such as entropy and Kolmogorov complexity, which provide objective measures of the amount of information or computational resources required to describe a system. However, when it comes to measuring the complexity of real-world systems or phenomena, there is often a subjective element involved, as different observers may prioritize different aspects of complexity. Therefore, while certain aspects of complexity can be objectively measured, the overall assessment of complexity may still involve some degree of subjectivity.
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What is the complexity of Mergesort?
The time complexity of Mergesort is O(n log n) in the worst-case scenario, where n is the number of elements in the array. This complexity arises from the fact that Mergesort divides the array into halves recursively and then merges them back together in sorted order. The space complexity of Mergesort is O(n) due to the need for additional space to store the divided subarrays during the sorting process. Overall, Mergesort is an efficient sorting algorithm that performs well on large datasets.
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How can one get rid of complexity?
One can get rid of complexity by breaking down the problem or situation into smaller, more manageable parts. This can help to identify the root causes of the complexity and address them individually. Additionally, simplifying processes, communication, and decision-making can help reduce complexity. It is also important to prioritize and focus on the most important aspects, while letting go of unnecessary details. Finally, seeking input and collaboration from others can provide fresh perspectives and help to streamline complex situations.
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What is the complexity of composing two functions?
Composing two functions has a complexity of O(1), as it involves simply applying one function to the output of the other. The time complexity does not depend on the size of the input, as the functions are applied sequentially. Therefore, the complexity of composing two functions is constant and does not increase with the size of the input.
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The Altar Girls : An addictive crime thriller packed with mystery and suspense
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Find Her Alive : A gripping crime thriller packed with mystery and suspense
Josie treads gently, careful not to disturb the pile of perfect white bones laid out in the grass by her feet. Her voice is little more than a whisper. “No! Not my sister…” Detective Josie Quinn hasn’t heard from her sister since Trinity stormed out of the house in the heat of an argument three weeks ago. So, when human remains are found at the remote hunting cabin where Trinity was last seen, Josie can only assume the worst.Gathering her team, Josie feels a surge of relief when the dental records match a different body – that of a missing single mother from a neighboring town. But now Josie’s is not the only broken family desperate for answers.Dusting the crime scene for prints, a name smudged into the side of a nearby car is the first in a trail of clues Trinity left for Josie. In need of a big story to save her journalism career, it seems Josie’s sister was attempting to make contact with a dangerous serial killer known for creating sculptures with his victim’s bones. And Trinity won’t stop until she’s found him, even if it means becoming his next masterpiece…Josie is certain there’s a critical clue in the ivory hair comb delivered to Trinity just days before she went missing. But as more bones surface, each set more likely to be Trinity’s than the last, time is running out to find her alive. Can Josie’s team trust her instincts in a case that is so deeply personal? Can she find her sister without putting other innocent lives in danger? An unputdownable crime thriller from an Amazon, USA Today and Wall Street Journal bestselling author that will have you sleeping with the light on. This gripping rollercoaster ride is perfect for fans of Angela Marsons, Robert Dugoni and Rachel Caine. Prepare to be totally hooked! What readers are saying about Lisa Regan:‘OMG, they said it was an absolutely gripping crime fiction and they weren't kidding. It reels you in from start to finish. There's plenty of shocks, twists and turns to keep you hooked…. I can't praise it enough and it deserves a lot more than five stars.’ Dawn Clifford, 5 stars‘Wow wow wow. This is the book that wow was meant for. So many wonderful twists.’ Rachel Garner, 5 stars‘A rollercoaster of a crime thriller. Stayed up till 3am to finish it. If I could I would award this book six stars. One of my favourite reads of this year so far.’ Goodreads reviewer, 5 stars‘I read this in three days… I was so engrossed in the story and flipping pages like a mad woman. I immediately turned back to page one to read it again when I was finished… An emotional powerhouse… Best. Book. Ever. An absolute 5-star read! Don’t start this unless you have time to finish it in one sitting because you won’t be able to put it down.’ Goodreads reviewer, 5 stars
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Simply Complexity : A Clear Guide to Complexity Theory
What do traffic jams, stock market crashes, and wars have in common?They are all explained using complexity, an unsolved puzzle that many researchers believe is the key to predicting – and ultimately solving—everything from terrorist attacks and pandemic viruses right down to rush hour traffic congestion. Complexity is considered by many to be the single most important scientific development since general relativity and it promises to make sense of no less than the very heart of the Universe.Using it, scientists can find order emerging from seemingly random interactions of all kinds, from something as simple as flipping coins through to more challenging problems such as the patterns in modern jazz, the growth of cancer tumours, and predicting shopping habits.
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Ecological Complexity
Complexity has received substantial attention from scientists and philosophers alike.There are numerous, often conflicting, accounts of how complexity should be defined and how it should be measured.Much less attention has been paid to the epistemic implications of complexity, especially in Ecology.How does the complex nature of ecological systems affect ecologists' ability to study them?This Element argues that ecological systems are complex in a rather special way: they are causally heterogeneous.Not only are they made up of many interacting parts, but their behaviour is variable across space or time.Causal heterogeneity is responsible for many of the epistemic difficulties that ecologists face, especially when making generalisations and predictions.Luckily, ecologists have the tools to overcome these difficulties, though these tools have historically been considered suspect by philosophers of science.The author presents an updated philosophical account with an optimistic outlook of the methods and status of ecological research.
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What are the Landau symbols for the time complexity?
The Landau symbols for time complexity are commonly used to describe the upper and lower bounds of an algorithm's running time. The most commonly used Landau symbols for time complexity are O (big O) for upper bound, Ω (big omega) for lower bound, and Θ (big theta) for both upper and lower bounds. These symbols are used to express the growth rate of an algorithm's running time in terms of the input size. For example, if an algorithm has a time complexity of O(n^2), it means that the running time of the algorithm grows no faster than n^2 as the input size increases.
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What are the Big O notations for time complexity?
The Big O notations for time complexity are used to describe the upper bound on the growth rate of an algorithm's running time as the input size increases. Some common Big O notations include O(1) for constant time complexity, O(log n) for logarithmic time complexity, O(n) for linear time complexity, O(n^2) for quadratic time complexity, and O(2^n) for exponential time complexity. These notations help in analyzing and comparing the efficiency of different algorithms.
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How do you determine the complexity of a function?
The complexity of a function can be determined by analyzing its time and space requirements. This can be done by examining the number of operations the function performs and the amount of memory it uses. Additionally, the complexity can be influenced by the size of the input data and the efficiency of the algorithm used in the function. By considering these factors, one can determine the complexity of a function, which is often expressed using Big O notation.
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What does the complexity class NP mean in computer science?
In computer science, the complexity class NP (nondeterministic polynomial time) refers to a set of decision problems that can be verified in polynomial time. This means that given a potential solution to a problem, it can be efficiently checked to determine if it is correct. However, finding the solution itself may not be efficient, as it may require trying all possible solutions. NP problems are often associated with the concept of nondeterministic Turing machines, which can guess the correct solution and then verify it in polynomial time. The question of whether NP problems can be solved in polynomial time is one of the most important open problems in computer science, known as the P vs. NP problem.
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