Verilog - Operators
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Dialetheists' Lies About the Liar
PRINCIPIA 22(1): 59–85 (2018) doi: 10.5007/1808-1711.2018v22n1p59 Published by NEL — Epistemology and Logic Research Group, Federal University of Santa Catarina (UFSC), Brazil. DIALETHEISTS’LIES ABOUT THE LIAR JONAS R. BECKER ARENHART Departamento de Filosofia, Universidade Federal de Santa Catarina, BRAZIL [email protected] EDERSON SAFRA MELO Departamento de Filosofia, Universidade Federal do Maranhão, BRAZIL [email protected] Abstract. Liar-like paradoxes are typically arguments that, by using very intuitive resources of natural language, end up in contradiction. Consistent solutions to those paradoxes usually have difficulties either because they restrict the expressive power of the language, orelse because they fall prey to extended versions of the paradox. Dialetheists, like Graham Priest, propose that we should take the Liar at face value and accept the contradictory conclusion as true. A logical treatment of such contradictions is also put forward, with the Logic of Para- dox (LP), which should account for the manifestations of the Liar. In this paper we shall argue that such a formal approach, as advanced by Priest, is unsatisfactory. In order to make contradictions acceptable, Priest has to distinguish between two kinds of contradictions, in- ternal and external, corresponding, respectively, to the conclusions of the simple and of the extended Liar. Given that, we argue that while the natural interpretation of LP was intended to account for true and false sentences, dealing with internal contradictions, it lacks the re- sources to tame external contradictions. Also, the negation sign of LP is unable to represent internal contradictions adequately, precisely because of its allowance of sentences that may be true and false. -
Technical Report TR-2020-10
Simulation-Based Engineering Lab University of Wisconsin-Madison Technical Report TR-2020-10 CryptoEmu: An Instruction Set Emulator for Computation Over Ciphers Xiaoyang Gong and Dan Negrut December 28, 2020 Abstract Fully homomorphic encryption (FHE) allows computations over encrypted data. This technique makes privacy-preserving cloud computing a reality. Users can send their encrypted sensitive data to a cloud server, get encrypted results returned and decrypt them, without worrying about data breaches. This project report presents a homomorphic instruction set emulator, CryptoEmu, that enables fully homomorphic computation over encrypted data. The software-based instruction set emulator is built upon an open-source, state-of-the-art homomorphic encryption library that supports gate-level homomorphic evaluation. The instruction set architecture supports multiple instructions that belong to the subset of ARMv8 instruction set architecture. The instruction set emulator utilizes parallel computing techniques to emulate every functional unit for minimum latency. This project re- port includes details on design considerations, instruction set emulator architecture, and datapath and control unit implementation. We evaluated and demonstrated the instruction set emulator's performance and scalability on a 48-core workstation. Cryp- toEmu shown a significant speed up in homomorphic computation performance when compared with HELib, a state-of-the-art homomorphic encryption library. Keywords: Fully Homomorphic Encryption, Parallel Computing, Homomorphic Instruction Set, Homomorphic Processor, Computer Architecture 1 Contents 1 Introduction 3 2 Background 4 3 TFHE Library 5 4 CryptoEmu Architecture Overview 7 4.1 Data Processing . .8 4.2 Branch and Control Flow . .9 5 Data Processing Units 9 5.1 Load/Store Unit . .9 5.2 Adder . -
UNIT-I Mathematical Logic Statements and Notations
UNIT-I Mathematical Logic Statements and notations: A proposition or statement is a declarative sentence that is either true or false (but not both). For instance, the following are propositions: “Paris is in France” (true), “London is in Denmark” (false), “2 < 4” (true), “4 = 7 (false)”. However the following are not propositions: “what is your name?” (this is a question), “do your homework” (this is a command), “this sentence is false” (neither true nor false), “x is an even number” (it depends on what x represents), “Socrates” (it is not even a sentence). The truth or falsehood of a proposition is called its truth value. Connectives: Connectives are used for making compound propositions. The main ones are the following (p and q represent given propositions): Name Represented Meaning Negation ¬p “not p” Conjunction p q “p and q” Disjunction p q “p or q (or both)” Exclusive Or p q “either p or q, but not both” Implication p ⊕ q “if p then q” Biconditional p q “p if and only if q” Truth Tables: Logical identity Logical identity is an operation on one logical value, typically the value of a proposition that produces a value of true if its operand is true and a value of false if its operand is false. The truth table for the logical identity operator is as follows: Logical Identity p p T T F F Logical negation Logical negation is an operation on one logical value, typically the value of a proposition that produces a value of true if its operand is false and a value of false if its operand is true. -
X86 Assembly Language Syllabus for Subject: Assembly (Machine) Language
VŠB - Technical University of Ostrava Department of Computer Science, FEECS x86 Assembly Language Syllabus for Subject: Assembly (Machine) Language Ing. Petr Olivka, Ph.D. 2021 e-mail: [email protected] http://poli.cs.vsb.cz Contents 1 Processor Intel i486 and Higher – 32-bit Mode3 1.1 Registers of i486.........................3 1.2 Addressing............................6 1.3 Assembly Language, Machine Code...............6 1.4 Data Types............................6 2 Linking Assembly and C Language Programs7 2.1 Linking C and C Module....................7 2.2 Linking C and ASM Module................... 10 2.3 Variables in Assembly Language................ 11 3 Instruction Set 14 3.1 Moving Instruction........................ 14 3.2 Logical and Bitwise Instruction................. 16 3.3 Arithmetical Instruction..................... 18 3.4 Jump Instructions........................ 20 3.5 String Instructions........................ 21 3.6 Control and Auxiliary Instructions............... 23 3.7 Multiplication and Division Instructions............ 24 4 32-bit Interfacing to C Language 25 4.1 Return Values from Functions.................. 25 4.2 Rules of Registers Usage..................... 25 4.3 Calling Function with Arguments................ 26 4.3.1 Order of Passed Arguments............... 26 4.3.2 Calling the Function and Set Register EBP...... 27 4.3.3 Access to Arguments and Local Variables....... 28 4.3.4 Return from Function, the Stack Cleanup....... 28 4.3.5 Function Example.................... 29 4.4 Typical Examples of Arguments Passed to Functions..... 30 4.5 The Example of Using String Instructions........... 34 5 AMD and Intel x86 Processors – 64-bit Mode 36 5.1 Registers.............................. 36 5.2 Addressing in 64-bit Mode.................... 37 6 64-bit Interfacing to C Language 37 6.1 Return Values.......................... -
Bitwise Operators in C Examples
Bitwise Operators In C Examples Alphonse misworships discommodiously. Epigastric Thorvald perishes changefully while Oliver always intercut accusatively.his anthology plumps bravely, he shown so cheerlessly. Baillie argufying her lashkar coweringly, she mass it Find the program below table which is c operators associate from star from the positive Left shift shifts each bit in its left operand to the left. Tying up some Arduino loose ends before moving on. The next example shows you how to do this. We can understand this better using the following Example. These operators move each bit either left or right a specified number of times. Amazon and the Amazon logo are trademarks of Amazon. Binary form of these values are given below. Shifting the bits of the string of bitwise operators in c examples and does not show the result of this means the truth table for making. Mommy, security and web. When integers are divided, it shifts the bits to the right. Operators are the basic concept of any programming language, subtraction, we are going to see how to use bitwise operators for counting number of trailing zeros in the binary representation of an integer? Adding a negative and positive number together never means the overflow indicates an exception! Not valid for string or complex operands. Les cookies essentiels sont absolument necessaires au bon fonctionnement du site. Like the assembly in C language, unlike other magazines, you may treat this as true. Bitwise OR operator is used to turn bits ON. To me this looks clearer as is. We will talk more about operator overloading in a future section, and the second specifies the number of bit positions by which the first operand is to be shifted. -
Proof-Assistants Using Dependent Type Systems
CHAPTER 18 Proof-Assistants Using Dependent Type Systems Henk Barendregt Herman Geuvers Contents I Proof checking 1151 2 Type-theoretic notions for proof checking 1153 2.1 Proof checking mathematical statements 1153 2.2 Propositions as types 1156 2.3 Examples of proofs as terms 1157 2.4 Intermezzo: Logical frameworks. 1160 2.5 Functions: algorithms versus graphs 1164 2.6 Subject Reduction . 1166 2.7 Conversion and Computation 1166 2.8 Equality . 1168 2.9 Connection between logic and type theory 1175 3 Type systems for proof checking 1180 3. l Higher order predicate logic . 1181 3.2 Higher order typed A-calculus . 1185 3.3 Pure Type Systems 1196 3.4 Properties of P ure Type Systems . 1199 3.5 Extensions of Pure Type Systems 1202 3.6 Products and Sums 1202 3.7 E-typcs 1204 3.8 Inductive Types 1206 4 Proof-development in type systems 1211 4.1 Tactics 1212 4.2 Examples of Proof Development 1214 4.3 Autarkic Computations 1220 5 P roof assistants 1223 5.1 Comparing proof-assistants . 1224 5.2 Applications of proof-assistants 1228 Bibliography 1230 Index 1235 Name index 1238 HANDBOOK OF AUTOMAT8D REASONING Edited by Alan Robinson and Andrei Voronkov © 2001 Elsevier Science Publishers 8.V. All rights reserved PROOF-ASSISTANTS USING DEPENDENT TYPE SYSTEMS 1151 I. Proof checking Proof checking consists of the automated verification of mathematical theories by first fully formalizing the underlying primitive notions, the definitions, the axioms and the proofs. Then the definitions are checked for their well-formedness and the proofs for their correctness, all this within a given logic. -
Logic, Proofs
CHAPTER 1 Logic, Proofs 1.1. Propositions A proposition is a declarative sentence that is either true or false (but not both). For instance, the following are propositions: “Paris is in France” (true), “London is in Denmark” (false), “2 < 4” (true), “4 = 7 (false)”. However the following are not propositions: “what is your name?” (this is a question), “do your homework” (this is a command), “this sentence is false” (neither true nor false), “x is an even number” (it depends on what x represents), “Socrates” (it is not even a sentence). The truth or falsehood of a proposition is called its truth value. 1.1.1. Connectives, Truth Tables. Connectives are used for making compound propositions. The main ones are the following (p and q represent given propositions): Name Represented Meaning Negation p “not p” Conjunction p¬ q “p and q” Disjunction p ∧ q “p or q (or both)” Exclusive Or p ∨ q “either p or q, but not both” Implication p ⊕ q “if p then q” Biconditional p → q “p if and only if q” ↔ The truth value of a compound proposition depends only on the value of its components. Writing F for “false” and T for “true”, we can summarize the meaning of the connectives in the following way: 6 1.1. PROPOSITIONS 7 p q p p q p q p q p q p q T T ¬F T∧ T∨ ⊕F →T ↔T T F F F T T F F F T T F T T T F F F T F F F T T Note that represents a non-exclusive or, i.e., p q is true when any of p, q is true∨ and also when both are true. -
Logic, Sets, and Proofs David A
Logic, Sets, and Proofs David A. Cox and Catherine C. McGeoch Amherst College 1 Logic Logical Statements. A logical statement is a mathematical statement that is either true or false. Here we denote logical statements with capital letters A; B. Logical statements be combined to form new logical statements as follows: Name Notation Conjunction A and B Disjunction A or B Negation not A :A Implication A implies B if A, then B A ) B Equivalence A if and only if B A , B Here are some examples of conjunction, disjunction and negation: x > 1 and x < 3: This is true when x is in the open interval (1; 3). x > 1 or x < 3: This is true for all real numbers x. :(x > 1): This is the same as x ≤ 1. Here are two logical statements that are true: x > 4 ) x > 2. x2 = 1 , (x = 1 or x = −1). Note that \x = 1 or x = −1" is usually written x = ±1. Converses, Contrapositives, and Tautologies. We begin with converses and contrapositives: • The converse of \A implies B" is \B implies A". • The contrapositive of \A implies B" is \:B implies :A" Thus the statement \x > 4 ) x > 2" has: • Converse: x > 2 ) x > 4. • Contrapositive: x ≤ 2 ) x ≤ 4. 1 Some logical statements are guaranteed to always be true. These are tautologies. Here are two tautologies that involve converses and contrapositives: • (A if and only if B) , ((A implies B) and (B implies A)). In other words, A and B are equivalent exactly when both A ) B and its converse are true. -
Lecture 1: Propositional Logic
Lecture 1: Propositional Logic Syntax Semantics Truth tables Implications and Equivalences Valid and Invalid arguments Normal forms Davis-Putnam Algorithm 1 Atomic propositions and logical connectives An atomic proposition is a statement or assertion that must be true or false. Examples of atomic propositions are: “5 is a prime” and “program terminates”. Propositional formulas are constructed from atomic propositions by using logical connectives. Connectives false true not and or conditional (implies) biconditional (equivalent) A typical propositional formula is The truth value of a propositional formula can be calculated from the truth values of the atomic propositions it contains. 2 Well-formed propositional formulas The well-formed formulas of propositional logic are obtained by using the construction rules below: An atomic proposition is a well-formed formula. If is a well-formed formula, then so is . If and are well-formed formulas, then so are , , , and . If is a well-formed formula, then so is . Alternatively, can use Backus-Naur Form (BNF) : formula ::= Atomic Proposition formula formula formula formula formula formula formula formula formula formula 3 Truth functions The truth of a propositional formula is a function of the truth values of the atomic propositions it contains. A truth assignment is a mapping that associates a truth value with each of the atomic propositions . Let be a truth assignment for . If we identify with false and with true, we can easily determine the truth value of under . The other logical connectives can be handled in a similar manner. Truth functions are sometimes called Boolean functions. 4 Truth tables for basic logical connectives A truth table shows whether a propositional formula is true or false for each possible truth assignment. -
Hardware Abstract the Logic Gates References Results Transistors Through the Years Acknowledgements
The Practical Applications of Logic Gates in Computer Science Courses Presenters: Arash Mahmoudian, Ashley Moser Sponsored by Prof. Heda Samimi ABSTRACT THE LOGIC GATES Logic gates are binary operators used to simulate electronic gates for design of circuits virtually before building them with-real components. These gates are used as an instrumental foundation for digital computers; They help the user control a computer or similar device by controlling the decision making for the hardware. A gate takes in OR GATE AND GATE NOT GATE an input, then it produces an algorithm as to how The OR gate is a logic gate with at least two An AND gate is a consists of at least two A NOT gate, also known as an inverter, has to handle the output. This process prevents the inputs and only one output that performs what inputs and one output that performs what is just a single input with rather simple behavior. user from having to include a microprocessor for is known as logical disjunction, meaning that known as logical conjunction, meaning that A NOT gate performs what is known as logical negation, which means that if its input is true, decision this making. Six of the logic gates used the output of this gate is true when any of its the output of this gate is false if one or more of inputs are true. If all the inputs are false, the an AND gate's inputs are false. Otherwise, if then the output will be false. Likewise, are: the OR gate, AND gate, NOT gate, XOR gate, output of the gate will also be false. -
Fractal Surfaces from Simple Arithmetic Operations
Fractal surfaces from simple arithmetic operations Vladimir Garc´ıa-Morales Departament de Termodin`amica,Universitat de Val`encia, E-46100 Burjassot, Spain [email protected] Fractal surfaces ('patchwork quilts') are shown to arise under most general circumstances involving simple bitwise operations between real numbers. A theory is presented for all deterministic bitwise operations on a finite alphabet. It is shown that these models give rise to a roughness exponent H that shapes the resulting spatial patterns, larger values of the exponent leading to coarser surfaces. keywords: fractals; self-affinity; free energy landscapes; coarse graining arXiv:1507.01444v3 [cs.OH] 10 Jan 2016 1 I. INTRODUCTION Fractal surfaces [1, 2] are ubiquitously found in biological and physical systems at all scales, ranging from atoms to galaxies [3{6]. Mathematically, fractals arise from iterated function systems [7, 8], strange attractors [9], critical phenomena [10], cellular automata [11, 12], substitution systems [11, 13] and any context where some hierarchical structure is present [14, 15]. Because of these connections, fractals are also important in some recent approaches to nonequilibrium statistical mechanics of steady states [16{19]. Fractality is intimately connected to power laws, real-valued dimensions and exponential growth of details as resulting from an increase in the resolution of a geometric object [20]. Although the rigorous definition of a fractal requires that the Hausdorff-Besicovitch dimension DF is strictly greater than the Euclidean dimension D of the space in which the fractal object is embedded, there are cases in which surfaces are sufficiently broken at all length scales so as to deserve being named `fractals' [1, 20, 21]. -
Problem Solving with Programming Course Material
Problem Solving with Programming Course Material PROBLEM SOLVING WITH PROGRAMMING Hours/Week Marks Year Semester C L T P/D CIE SEE Total I II 2 - - 2 30 70 100 Pre-requisite Nil COURSE OUTCOMES At the end of the course, the students will develop ability to 1. Analyze and implement software development tools like algorithm, pseudo codes and programming structure. 2. Modularize the problems into small modules and then convert them into modular programs 3. Apply the pointers, memory allocation techniques and use of files for dealing with variety of problems. 4. Apply C programming to solve problems related to scientific computing. 5. Develop efficient programs for real world applications. UNIT I Pointers Basics of pointers, pointer to array, array of pointers, void pointer, pointer to pointer- example programs, pointer to string. Project: Simple C project by using pointers. UNIT II Structures Basics of structure in C, structure members, accessing structure members, nested structures, array of structures, pointers to structures - example programs, Unions- accessing union members- example programs. Project: Simple C project by using structures/unions. UNIT III Functions Functions: User-defined functions, categories of functions, parameter passing in functions: call by value, call by reference, recursive functions. passing arrays to functions, passing strings to functions, passing a structure to a function. Department of Computer Science and Engineering Problem Solving with Programming Course Material Project: Simple C project by using functions. UNIT IV File Management Data Files, opening and closing a data file, creating a data file, processing a data file, unformatted data files. Project: Simple C project by using files.