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Consistent High Dimensional Rounding with Side Information [article]

Orr Dunkelman, Zeev Geyzel, Chaya Keller, Nathan Keller, Eyal Ronen, Adi Shamir, Ran J. Tessler
2020 arXiv   pre-print
In standard rounding, we want to map each value X in a large continuous space (e.g., R) to a nearby point P from a discrete subset (e.g., Z). This process seems to be inherently discontinuous in the sense that two consecutive noisy measurements X_1 and X_2 of the same value may be extremely close to each other and yet they can be rounded to different points P_1 P_2, which is undesirable in many applications. In this paper we show how to make the rounding process perfectly continuous in the
more » ... tinuous in the sense that it maps any pair of sufficiently close measurements to the same point. We call such a process consistent rounding, and make it possible by allowing a small amount of information about the first measurement X_1 to be unidirectionally communicated to and used by the rounding process of X_2. The fault tolerance of a consistent rounding scheme is defined by the maximum distance between pairs of measurements which guarantees that they are always rounded to the same point, and our goal is to study the possible tradeoffs between the amount of information provided and the achievable fault tolerance for various types of spaces. When the measurements X_i are arbitrary vectors in R^d, we show that communicating log_2(d+1) bits of information is both sufficient and necessary (in the worst case) in order to achieve consistent rounding for some positive fault tolerance, and when d=3 we obtain a tight upper and lower asymptotic bound of (0.561+o(1))k^1/3 on the achievable fault tolerance when we reveal log_2(k) bits of information about how X_1 was rounded. We analyze the problem by considering the possible colored tilings of the space with k available colors, and obtain our upper and lower bounds with a variety of mathematical techniques including isoperimetric inequalities, the Brunn-Minkowski theorem, sphere packing bounds, and Čech cohomology.
arXiv:2008.03675v1 fatcat:dvidtydbfnhmrmdtuggez4d5v4

Hidden Neuronal Correlations in Cultured Networks

Ronen Segev, Itay Baruchi, Eyal Hulata, Eshel Ben-Jacob
2004 Physical Review Letters  
Utilization of a clustering algorithm on neuronal spatiotemporal correlation matrices recorded during a spontaneous activity of in vitro networks revealed the existence of hidden correlations: the sequence of synchronized bursting events (SBEs) is composed of statistically distinguishable subgroups each with its own distinct pattern of interneuron spatiotemporal correlations. These findings hint that each of the SBE subgroups can serve as a template for coding, storage, and retrieval of a
more » ... etrieval of a specific information.
doi:10.1103/physrevlett.92.118102 pmid:15089177 fatcat:37f2me34jndcxlzli2stvyzhvq

Modified Objective Structured Clinical Examinations for PL-3 Pediatric Residents

Eyal Ben-Isaac, Ronen Zipkin, Michelle Thompson
2016 MedEdPORTAL  
Eyal Ben-Isaac, MD: Director, Pediatric Residency Program, Children's Hospital Los Angeles Ronen Zipkin, MD: Assistant Director, Pediatric Residency Program, Children's Hospital Los Angeles Michelle Thompson  ... 
doi:10.15766/mep_2374-8265.10382 fatcat:pocimnsu5fguldidpuvtocsxx4

A Simple Explanation for the Existence of Adversarial Examples with Small Hamming Distance [article]

Adi Shamir, Itay Safran, Eyal Ronen, Orr Dunkelman
2019 arXiv   pre-print
Eyal Ronen is partially supported by the Robert Bosch Foundation.  ... 
arXiv:1901.10861v1 fatcat:pzbx22vm7bd4taeoaof7ns5eum

Self-Regulated Complexity in Cultured Neuronal Networks

Eyal Hulata, Itay Baruchi, Ronen Segev, Yoash Shapira, Eshel Ben-Jacob
2004 Physical Review Letters  
New quantified observables of complexity are identified and utilized to study sequences (time series) recorded during the spontaneous activity of different size cultured networks. The sequence is mapped into a tiled time-frequency domain that maximizes the information about local time-frequency resolutions. The sequence regularity is associated with the domain homogeneity and its complexity with its local and global variations. Shuffling the recorded sequence lowers its complexity down to
more » ... exity down to artificially constructed ones. The new observables are utilized to identify self-regulation motifs in observed complex network activity.
doi:10.1103/physrevlett.92.198105 pmid:15169451 fatcat:pcdkoxursjcknfbakofeqpjsxq

Tariffs and Non-Tariff Measures: Substitutes or Complements. A Cross-Country Analysis

Eyal Ronen
2017 Social Science Research Network  
Alongside the global tariff liberalization, a growing body of evidence demonstrates the rise in the use of non-tariff measures (NTMs), which suggests a substitution effect between these two import policy instruments. Yet, detailed economic data reveals that in countries with lower tariff rates (developed countries), the use of NTMs is significantly lower compared to developing countries, which implies a possible complementary effect between tariffs and NTMs across nations. Using a dataset of
more » ... ing a dataset of Kee, Nicita and Olarreaga (2009) on ad valorem tariff equivalents of NTMs, at a very disaggregated product level, this paper explores the determinants of NTMs and their substitutability/complementarity relations with tariff barriers. While exploiting the country variation, it demonstrates the decreasing trend of substitutability between the two import policy instruments with the rise in economic development. In particular, a significant complementarity correlation exists between the two trade measures among the wealthiest nations, implying a stronger commitment to freer trade.
doi:10.2139/ssrn.3010212 fatcat:vxza5eotvndlrpgdqk4rtsfyne

Quantifying the Trade Effects of NTMs: A Review of the Empirical Literature

Eyal Ronen
2017 Social Science Research Network  
Ronen (2017a) shows that the substitutability between tariffs and NTMs decreases with the rise in the economic development of nations.  ...  Ronen (2017b) who explores the trade effects of a variety of NTMs on virgin olive oil imports, finds a significant demand-enhancing impact, particularly of MRLs.  ... 
doi:10.2139/ssrn.3010217 fatcat:c3rmct2oane4xho3nc35s7jfpe

IoT Goes Nuclear: Creating a Zigbee Chain Reaction

Eyal Ronen, Adi Shamir, Achi-Or Weingarten, Colin OFlynn
2018 IEEE Security and Privacy  
Epileptic seizures Ronen and Shamir [7] have also shown how the Philips Hue can be used to trigger epileptic seizures. This attack can now be executed from a remote location, covering large areas.  ...  Ronen and Shamir [7] have shown how to use the Philips Hue and LimitlessLed systems to create a covert channel to exfiltrate data from air-gapped networks, and to create strobes that can cause epileptic  ... 
doi:10.1109/msp.2018.1331033 fatcat:4mfskpvcine7xf5crqzxcbdhxy

A Comparative Study of Information Extraction Strategies [chapter]

Ronen Feldman, Yonatan Aumann, Michal Finkelstein-Landau, Eyal Hurvitz, Yizhar Regev, Ariel Yaroshevich
2002 Lecture Notes in Computer Science  
The availability of online text documents exposes readers to a vast amount of potentially valuable knowledge buried therein. The sheer scale of material has created the pressing need for automated methods of discovering relevant information without having to read it all. Hence the growing interest in recent years in Text Mining. A common approach to Text Mining is Information Extraction (IE), extracting specific types (or templates) of information from a document collection. Although many works
more » ... Although many works on IE have been published, researchers have not paid much attention to evaluate the contribution of syntactic and semantic analysis using Natural Language Processing (NLP) techniques to the quality of IE results. In this work we try to quantify the contribution of NLP techniques, by comparing three strategies for IE: naïve co-occurrence, ordered co-occurrence, and the structure-driven method -a rule-based strategy that relies on syntactic analysis followed by the extraction of suitable semantic templates. We use the three strategies for the extraction of two templates from financial news stories. We show that the structure-driven strategy provides significantly better precision results than the two other strategies (80-90% for the structure-driven compared with about only 60% for the co-occurrence and ordered cooccurrence). These results indicate that a syntactical and semantic analysis is necessary if one wishes to obtain high accuracy.
doi:10.1007/3-540-45715-1_36 fatcat:uyqghy5cobbkjj2d7jjgtnveky

Depth keying

Ronen Gvili, Amir Kaplan, Eyal Ofek, Giora Yahav, Andrew J. Woods, Mark T. Bolas, John O. Merritt, Stephen A. Benton
2003 Stereoscopic Displays and Virtual Reality Systems X  
We present a new solution to the known problem of video keying in a natural environment. We segment foreground objects from background objects using their relative distance from the camera, which makes it possible to do away with the use of color for keying. To do so, we developed and built a novel depth video camera, capable of producing RGB and D signals, where D stands for the distance to each pixel. The new RGBD camera enables the creation of a whole new gallery of effects and applications
more » ... s and applications such as multi-layer background substitutions. This new modality makes the production of real time mixed reality video possible, as well as post-production manipulation of recorded video. We address the problem of color spill -in which the color of the foreground object is mixed, along its boundary, with the background color. This problem prevents an accurate separation of the foreground object from its background, and it is most visible when compositing the foreground objects to a new background. Most existing techniques are limited to the use of a constant background color. We offer a novel general approach to the problem with enabling the use of the natural background, based upon the D channel generated by the camera.
doi:10.1117/12.474052 fatcat:uw4llbiwyzdmbnmga35lcgk2au

Sensing with Polarized LIDAR in Degraded Visibility Conditions Due to Fog and Low Clouds

Ayala Ronen, Eyal Agassi, Ofer Yaron
2021 Sensors  
LIDAR (Light Detection and Ranging) sensors are one of the leading technologies that are widely considered for autonomous navigation. However, foggy and cloudy conditions might pose a serious problem for a wide adoption of their use. Polarization is a well-known mechanism often applied to improve sensors' performance in a dense atmosphere, but is still not commonly applied, to the best of our knowledge, in self-navigated devices. This article explores this issue, both theoretically and
more » ... ically and experimentally, and focuses on the dependence of the expected performance on the atmospheric interference type. We introduce a model which combines the well-known LIDAR equation with Stocks vectors and the Mueller matrix formulations in order to assess the magnitudes of the true target signal loss as well as the excess signal that arises from the scattering medium radiance, by considering the polarization state of the E–M (Electro-Magnetic) waves. Our analysis shows that using the polarization state may recover some of the poor performance of such systems for autonomous platforms in low visibility conditions, but it depends on the atmospheric medium type. This conclusion is supported by measurements held inside an aerosol chamber within a well-controlled and monitored artificial degraded visibility atmospheric environment. The presented analysis tool can be used for the optimization of design and trade-off analysis of LIDAR systems, which allow us to achieve the best performance for self-navigation in all weather conditions.
doi:10.3390/s21072510 pmid:33916764 fatcat:bql7fabel5gcnjtussfvjv6lba

Tight Bounds on Online Checkpointing Algorithms

Achiya Bar-On, Itai Dinur, Orr Dunkelman, Rani Hod, Nathan Keller, Eyal Ronen, Adi Shamir
2020 ACM Transactions on Algorithms  
Ronen, and A.  ... 
doi:10.1145/3379543 fatcat:rrj5qyx33fepln56nofp4etyzi

Mining the biomedical literature using semantic analysis and natural language processing techniques

Ronen Feldman, Yizhar Regev, Eyal Hurvitz, Michal Finkelstein-Landau
The information age has made the electronic storage of large amounts of data effortless.The proliferation of documents available on the Internet, corporate intranets, news wires and elsewhere is overwhelming. Search engines only exacerbate this overload problem by making increasingly more documents available in only a few keystrokes. This information overload also exists in the biomedical field, where scientific publications, and other forms of text-based data are produced at an unprecedented
more » ... an unprecedented rate. Text mining is the combined, automated process of analyzing unstructured,natural language text to discover information and knowledge that are typically difficult to retrieve. Here, we focus on text mining as applied to the biomedical literature. We focus in particular on finding relationships among genes, proteins, drugs and diseases, to facilitate an understanding and prediction of complex biological processes. The LitMiner™ system, developed specifically for this purpose; is described in relation to the Knowledge Discovery and Data Mining Cup 2002, which serves as a formal evaluation of the system. REVIEWS RESEARCH FOCUS
doi:10.1016/s1478-5382(03)02330-8 fatcat:flak6ux5crcjnj3l6is7w62kki

Detection and Sorting of Neural Spikes Using Wavelet Packets

Eyal Hulata, Ronen Segev, Yoash Shapira, Morris Benveniste, Eshel Ben-Jacob
2000 Physical Review Letters  
We propose a novel method for the detection and sorting of recorded neural spikes using wavelet packets. We employ the best basis via the Shannon's information cost function and local discriminant basis using mutual information. We demonstrate the efficiency of the method on data recorded in vitro from 2D neural networks. We show that our method is superior both in separation from noise and in identifying superimposed spikes. 05.70.Ln, 82.40.Bj Current technology enables simultaneous recording
more » ... ltaneous recording of electronic signals from many neurons in a neural network (cell cultures, hippocampal slices, and in vivo tissues) [1] [2] [3] [4] [5] [6] . It is expected to improve our understanding of how real neural networks code, learn, and store information. There are three main obstacles in analyzing and recognizing signals from such recordings: (i) The spikes from neurons farther away from the electrode can be embedded in the noise as is shown in Fig. 1. (ii) Signal recognition may be complicated by a superposition of multiple action potential spikes (Fig. 1) . (iii) The volume of data which is present from a simultaneous recording from a multielectrode at a resolution of an action potential is too great. In a typical experiment ϳ250 000 individual spikes can be recorded. Various signal processing techniques have been used to detect and sort neural spikes (see Refs. [7, 8] for reviews). One popular method to detect and classify spikes is to filter the data utilizing a series of templates of the spike waveform of each neuron [7] . Simple variants of this method utilizing principal components analysis have been developed [7] . Here we propose a more efficient method based on wavelet packets decomposition. Our method uses a few packet coefficients for both detection and sorting of neural spikes. The same coefficients enabled good detection and sorting of many different spike waveforms originating from different electrodes and experiments. A comparison between wavelet packets decomposition and principle components analysis is presented below. The neural spikes, being short voltage pulses, are localized functions whose natural analysis is via the use of wavelets transform [9,10], which is the Fourier transform analog for localized functions. Important information often appears through a simultaneous analysis of the signal's time and frequency properties. The wavelet transform which covers the time-frequency domain enables us to visualize the specific properties of the signal at hand [11] . However, a disadvantage of using the wavelet basis is that it divides the time-frequency domain into predetermined frequency bands which are not optimized for neural spikes. Spikes from different neurons can have distinct signatures. Yet, the signature of different neurons might be quite similar. Thus, a simple wavelet transform will require many components to distinguish between spikes of different origins. To overcome this difficulty, we have developed a novel method using wavelet packets decomposition to detect and sort neural spikes. The decomposition uses a family of orthonormal bases from which one optimal basis can be selected. We show how to determine one optimal basis for spike detection and sorting by maximizing the Shannon information function and by using discriminant basis techniques based on mutual information. We present a test of our method by applying it to measurements of neural spikes from cell cultures grown on a multielectrode array. An important feature of our method is that nine coefficients of the optimal basis can both discriminate well between spikes and background noise and also distinguish among spikes from different origins. 5 10 15 20 −150 −100 −50 0 50 msec µV 2 22 2 1 1 1 FIG. 1. Recording from a single electrode which detects signals from three neurons marked. Note that in the presented time we show only two of the spikes detected so we mark only spike 1 and spike 2. The spikes sometimes superimpose one another as partially seen with the two "1's" at the center. 0031-9007͞00͞85(21)͞4637(4)$15.00
doi:10.1103/physrevlett.85.4637 pmid:11082615 fatcat:bgyitf4cnrb63pgktebvsddffa

IoT Goes Nuclear: Creating a ZigBee Chain Reaction

Eyal Ronen, Adi Shamir, Achi-Or Weingarten, Colin OFlynn
2017 2017 IEEE Symposium on Security and Privacy (SP)  
Epileptic seizures Ronen and Shamir [7] have also shown how the Philips Hue can be used to trigger epileptic seizures. This attack can now be executed from a remote location, covering large areas.  ...  Ronen and Shamir [7] have shown how to use the Philips Hue and LimitlessLed systems to create a covert channel to exfiltrate data from air-gapped networks, and to create strobes that can cause epileptic  ... 
doi:10.1109/sp.2017.14 dblp:conf/sp/RonenSWO17 fatcat:nilbphaxljfu5ofhf2a7r2megi
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