Technion – Israel Institute of Technology

About: Technion – Israel Institute of Technology is a education organization based out in Haifa, Israel. It is known for research contribution in the topics: Population & Upper and lower bounds. The organization has 31714 authors who have published 79377 publications receiving 2603976 citations. The organization is also known as: Technion Israel Institute of Technology & Ṭekhniyon, Makhon ṭekhnologi le-Yiśraʼel.

Proofs that yield nothing but their validity or all languages in NP have zero-knowledge proof systems

Abstract: In this paper the generality and wide applicability of Zero-knowledge proofs, a notion introduced by Goldwasser, Micali, and Rackoff is demonstrated. These are probabilistic and interactive proofs that, for the members of a language, efficiently demonstrate membership in the language without conveying any additional knowledge. All previously known zero-knowledge proofs were only for number-theoretic languages in NP fl CONP. Under the assumption that secure encryption functions exist or by using "physical means for hiding information, '' it is shown that all languages in NP have zero-knowledge proofs. Loosely speaking, it is possible to demonstrate that a CNF formula is satisfiable without revealing any other property of the formula, in particular, without yielding neither a satis@ing assignment nor properties such as whether there is a satisfying assignment in which xl = X3 etc. It is also demonstrated that zero-knowledge proofs exist "outside the domain of cryptography and number theory. " Using no assumptions. it is shown that both graph isomorphism and graph nonisomor- phism have zero-knowledge interactive proofs. The mere existence of an interactive proof for graph nonisomorphism is interesting, since graph nonisomorphism is not known to be in NP and hence no efficient proofs were known before for demonstrating that two graphs are not isomorphic.

Dictionaries for Sparse Representation Modeling

Abstract: Sparse and redundant representation modeling of data assumes an ability to describe signals as linear combinations of a few atoms from a pre-specified dictionary. As such, the choice of the dictionary that sparsifies the signals is crucial for the success of this model. In general, the choice of a proper dictionary can be done using one of two ways: i) building a sparsifying dictionary based on a mathematical model of the data, or ii) learning a dictionary to perform best on a training set. In this paper we describe the evolution of these two paradigms. As manifestations of the first approach, we cover topics such as wavelets, wavelet packets, contourlets, and curvelets, all aiming to exploit 1-D and 2-D mathematical models for constructing effective dictionaries for signals and images. Dictionary learning takes a different route, attaching the dictionary to a set of examples it is supposed to serve. From the seminal work of Field and Olshausen, through the MOD, the K-SVD, the Generalized PCA and others, this paper surveys the various options such training has to offer, up to the most recent contributions and structures.

A group-level model of safety climate: testing the effect of group climate on microaccidents in manufacturing jobs.

Abstract: This article presents and tests a group-level model of safety climate to supplement the available organization-level model. Climate perceptions in this case are related to supervisory safety practices rather than to company policies and procedures. The study included 53 work groups in a single manufacturing company. Safety climate perceptions, measured with a newly developed scale, revealed both within-group homogeneity and between-groups variation. Predictive validity was measured with a new outcome measure, microaccidents, that refers to behavior-dependent on-the-job minor injuries requiring medical attention. Climate perceptions significantly predicted microaccident records during the 5-month recording period that followed climate measurement, when the effects of group- and individual-level risk factors were controlled. The study establishes an empirical link between safety climate perceptions and objective injury data.

Switching and Finite Automata Theory

Abstract: Understand the structure, behavior, and limitations of logic machines with this thoroughly updated third edition. Many new topics are included, such as CMOS gates, logic synthesis, logic design for emerging nanotechnologies, digital system testing, and asynchronous circuit design, to bring students up-to-speed with modern developments. The intuitive examples and minimal formalism of the previous edition are retained, giving students a text that is logical and easy to follow, yet rigorous. Kohavi and Jha begin with the basics, and then cover combinational logic design and testing, before moving on to more advanced topics in finite-state machine design and testing. Theory is made easier to understand with 200 illustrative examples, and students can test their understanding with over 350 end-of-chapter review questions.