Ron Kenett

Technion – Israel Institute of Technology | technion · Samuel Neaman Institute for National Policy Research

"Politography" refers to the study or portrayal of political events, figures, and systems. It is used to analyze political trends, to visualize data, and create a data driven narrative. Decision support tools (DST) for policy makers tend to be narrowly defined in terms of specific domain applications. In this work, we describe the design and constr...

Introduction Peanut allergy (PA) in children is a major concern. There is a need for better biological material for both diagnosis and oral immunotherapy (OIT) treatments. The unique state of seeds at early reproductive stages may affect the allergenicity of storage proteins, and impact clinical diagnostic and OIT protocols. The objective of this s...

Over the last decade, thousands of papers on machine-learning for diagnosing faults in rotating machinery through vibration signals have been published. Specifically, deep learning, coupled with domain adaptation, has been replacing traditional physical and signal-processing techniques. This study systematically reviews the literature on deep learn...

Background Oral immunotherapy (OIT) is an increasingly acceptable therapeutic option for peanut‐allergic (PA) children, despite significant side effects. Major peanut allergenic proteins are heat‐resistant and are not rendered hypoallergenic after baking or cooking. Lyophilized peanut protein—MH (LPP‐MH) is a novel composition from developing peanu...

HBI0101 is an academic chimeric antigen receptor T (CART) targeted to BCMA for the treatment of relapsed and refractory multiple myeloma (RRMM) and light chain amyloidosis. Herein, we present the Phase Ib/II results of fifty heavily pre-treated RRMM patients dosed with 800x106 CART cells (NCT04720313). Inclusion criteria were relatively permissive...

Developments in digital twins are driven by the availability of sensor technologies, big data, first principles knowledge, and advanced analytics. In this paper, we discuss these changes at a conceptual level, presenting a shift from nominal engineering, aiming at design optimisation, to performance engineering, aiming at adaptable monitoring diagn...

Association rules are used to extract information from transactional databases with a collection of items also called “tokens” or “words.” The aim of association rule analysis is to indicate what and how items go with what items in a set of transactions called “documents.” This approach is used in the analysis of text records, of blogs in social me...

In the evolving landscape of digital technology, the concept of digital twinning has emerged as one of the most important innovations. Digital twinning, characterized by a one‐to‐one correlation with physical structures in a digital environment, has become an important tool in transferring physical dynamics into digital replicas. This platform, int...

Unlabelled: Lipoaspirate has become the preferred source for regenerative cells. The mechanical processing of lipoaspirate has advantages over enzymatic processing but has a lower yield of regenerative cells. A review of the literature shows different techniques of extraction, but the ideal method or combination has not been determined. Methods:...

In recent years, a growing role in digital technologies has been filled by model-based digital twinning. A digital twin produces a one-to-one mapping of a physical structure, operating in the digital domain. Combined with sensor technology and analytics, a digital twin can provide enhanced monitoring, diagnostic, and optimization capabilities. This...

The mathematician and bio‐scientist Sam Karlin is quoted stating that “The purpose of models is not to fit the data but to sharpen the question”. In this paper, we describe a journey between questions, models and data analysis to reach specific goals. This journey is typical in industrial, engineering, biology and social science applications. It co...

Zero hot Learning is a machine learning technique that allows a model to classify objects from previously unseen classes, without any specific training for those classes. It generalizes a predictive analytic model to unseen classes without any additional training.

Data analysis is key in decision‐making processes. The goal of data analysis is to generate information using data, analysis, and contextual knowledge. In this article, we discuss the information quality (InfoQ) framework approach to ensure the quality of information generated by statistical and analytic modeling. We first introduce InfoQ and then...

Control charts are applied in running a process under statistical control. Process capability analysis is conducted retrospectively on data to characterize a process under control and set up the control limits of a control chart. In this article, we expand on the process capability analysis by considering time‐related patterns. Specifically, we foc...

In this article, we focus on the process of moving from numbers to data, information, and insights. This is called “generalizability” in the information quality framework and is related to “interpretability.”

The core of this article is the search for an ‘organizing principle’ for the State of Israel in the present era. To approach this core goal, it conducted 40 interviews with well-known and influential Israeli individuals and attempted to identify common grounds of Israeli society. Analysis of the interviews finds a broad common denominator among tho...

This article describes the journey of the European Network for Business and Industrial Statistics (ENBIS) founded 20 years ago. It describes its various activities including conferences, special topic meetings, webinars, awards, and publications. ENBIS is a proven model where academics and practitioners meet to exchange ideas and information on sta...

The rapid and dynamic pace of Artificial Intelligence (AI) and Machine Learning (ML) is revolutionizing the insurance sector. AI offers significant, very much welcome advantages to insurance companies, and is fundamental to their customer-centricity strategy. It also poses challenges, in the project and implementation phase. Among those, we study A...

Artificial intelligence (AI) is a tool that financial intermediaries and insurance companies use or are willing to use in almost all their activities. AI can have a positive impact on almost all aspects of the insurance value chain: pricing, underwriting, marketing, claims management, and after-sales services. While it is very important and useful,...

Data from measurements over time can be analyzed in different ways. In this article, we compare functional data analysis and nonlinear regression models using, among others, eight information quality dimensions. We present two case studies. The first case study introduces functional data analysis and nonlinear regression models in analyzing dissolu...

‘Big data’ is vast describing volumes of information that can work miracles. Multiple attempts designed at highlighting the relationship between big data analytics and benefits for healthcare organizations have been raised. The big data influence on health organization management is still not clear due to the relationship’s multi-disciplinary natur...

Background: Sesame allergy (SA) is a common cause of life-threatening, persistent food allergy, not only in the Middle East and Asia, but increasingly worldwide. Commercially available tests such as extracts for skin testing or specific IgE for sesame or its components in serum, have very limited predictive values. Therefore the diagnosis is depen...

Artificial intelligence (AI) is a tool that financial intermediaries and insurance companies use in most cases or are willing to use it in almost all their activities. AI can have a positive impact on almost all aspects of the insurance value chain.: pricing, underwriting, marketing, claims management, after-sales services. While it is very importa...

Reallocations of time between daily activities such as sleep, sedentary behavior and physical activity are differentially associated with markers of physical, mental and social health. An individual’s most desirable allocation of time may differ depending on which outcomes they value most, with these outcomes potentially competing with each other f...

In the midst of the COVID-19 experience, we learned an important scientific lesson: knowledge acquisition and information quality in medicine depends more on “data quality” rather than “data quantity.” The large number of COVID-19 reports, published in a very short time, demonstrated that the most advanced statistical and computational tools cannot...

Describing, understanding, predicting, and controlling the improvement of athletic performance are pivotal aspects of sport sciences. Longitudinal trends of the achievements of elite performers, mainly in endurance (e.g., cycling, running, skiing, and swimming) and explosive-power (e.g., jumping, throwing, and weightlifting) sports, were examined i...

This book is about modern industrial statistics and it applications using R, MINITAB and JMP. It is an expanded second edition of a book entitled Modern Industrial Statistics: Design and Control of Quality and Reliability, Wadsworth Duxbury Publishing, 1998, Spanish edition: Estadistica Industrial Moderna: Diseño y Control de Calidad y la Confiabil...

Interpretability, in the context of machine learning, means understanding the predictions made by the machine learning algorithm, with the aim to support human decisions based on them. In this view, interpretability can involve identifying the input features which drive the predictions. This chapter develops different issues and related methodologi...

Analytic methods development, like many other disciplines, relies on experimentation and data analysis. Determining the contribution of a paper or report on a study incorporating data analysis is typically left to the reviewer's experience and good sense, without reliance on structured guidelines. This is amplified by the growing role of machine le...

This chapter is a door opener to computer age statistics. It covers a range of supervised and unsupervised learning methods and demonstrates their use in various applications.

Techniques for sampling finite populations and estimating population parameters are presented. Formulas are given for the expected value and variance of the sample mean and sample variance of simple random samples with and without replacement. Stratification is studied as a method to increase the precision of estimators. Formulas for proportional a...

Modern statistics and machine learning typically involve large amounts of data coupled with computationally intensive methods. In a predictive modeling context, one seeks models that achieve high predictive accuracy on new datasets. This is typically implemented by partitioning the data into training and hold‐out data sets. The allocation is often...

The chapter focuses on statistical variability and various methods of analyzing random data. Random results of experiments are illustrated with distinction between deterministic and random components of variability. The difference between accuracy and precision is explained. Frequency distributions are defined to represent random phenomena. Various...

In this chapter, we present essential parts of time series analysis, with the objective of predicting or forecasting its future development. Predicting future behavior is generally more successful for stationary series, which do not change their stochastic characteristics as time proceeds. We develop and illustrate time series which are of both typ...

The chapter provides the basics of probability theory and theory of distribution functions. The probability model for random sampling is discussed. This is fundamental for statistical inference discussed in Chap. 3 and sampling procedures in Chap. 5. Bayes’ theorem also presented here has important ramifications in statistical inference, including...

In this chapter we introduce basic concepts and methods of statistical inference. The focus is on estimating the parameters of statistical distributions and testing hypotheses about them. Problems of testing if certain distributions fit observed data are also considered.

Apparently, during an informed consent, patients remember little of the information given and their comprehension level is often overestimated by physicians. This study measures level of understanding of informed consent for elective cesarean surgery using an evidence-based informed consent (EBIC) model based on six MERLO assessments. MERLO recogni...

Background Between 25%-30% of peanut allergic (PA) children, have a relatively high threshold peanut allergy (HTPA), with a single maximal tolerated dose (SMTD) higher than 100 mg of peanut protein (PP). However, this threshold may decrease with time, age, exercise, illness, sleep deprivation, and other covariates. Objective To explore the feasibi...

The response to the COVID-19 pandemic has been highly variable. Governments have applied different mitigation policies with varying effect on social and economic measures, over time. This article presents a methodology for examining the effect of mobility restriction measures and the association between health and population activity data. As case...

The COVID-19 pandemic cast a dramatic spotlight on the use of data as a fundamental component of good decision-making. Evaluating and comparing alternative policies required information on concurrent infection rates and insightful analysis to project them into the future. Statisticians in Israel were involved in these processes early in the pandemi...

Samuel Karlin was a mathematician who made fundamental contributions to mathematical theory, functional analysis, operations research, game theory, mathematical economics, stochastic processes, statistics, genetics, population genetics, and computational biology. In this article, we provide an overall review of his career, emphasizing the last two...

The Covid-19 pandemic has spread across the world at a rate never seen before, affecting different countries and having a huge impact not only on health care systems but also on economic systems. Never as in this situation the continuous exchange of views between scientists of different disciplines must be considered the keystone to overcome this e...

The assessment of measurement uncertainty, especially in the context of interlaboratory studies, is at the basis of current discussion in the literature on reproducible research. John Mandel's work provided pioneering contributions to statistical methodology for assessing and handling measurement uncertainty. As an example, the methods he developed...

Peanut allergy is an increasing concern in younger children. Available bedside diagnostic tools, i.e., prick tests with commercial extracts or peanut-containing foods have only limited predictive values. In a cohort of preschoolers with both a history of allergic reactions and sensitization to peanut proteins, we aimed to characterize the impact of...

The challenge in educational technology (EdTech) is to apply modern analytics to educational data in order to derive information. Information quality (InfoQ) has been proposed by Kenett and Shmueli as a framework for assessing the quality of information generated by empirical studies by using specific empirical methods such as regression models, an...

The response to the COVID19 pandemic has been highly variable, both in terms of between-nations variation and within the same nation, at different waves. In this context, governments applied different mitigation policy responses with varying impact on social and economic measures over time. This article examines the effect of mobility restriction m...

The response to the COVID19 pandemic has been highly variable, both in terms of between-nations variation and within the same nation, at different waves. In this context, governments applied different mitigation policy responses with varying impact on social and economic measures over time. This article examines the effect of mobility restriction m...

In Industry 4.0, smart manufacturing is facing its next stage, cybermanufacturing, founded upon advanced communication, computation, and control infrastructure. Cybermanufacturing will unleash the potential of multi-modal manufacturing data, and provide a new perspective called computation service, as a part of service-oriented architecture (SOA),...

The move towards advanced manufacturing and Industry 4.0 is fed by increased demand for speeding up innovation, increasing flexibility, improving maintenance, and becoming more customized while saving on the total cost of operations. This is accompanied by increased dependence on virtual product and process development, data‐driven processes, and p...

Ron S. Kenett and Shirley Y. Coleman outline the roles played by data and statistics in “Industry 4.0”, from monitoring manufacturing processes to the building of “digital twins” Ron S. Kenett and Shirley Y. Coleman outline the roles played by data and statistics in “Industry 4.0”, from monitoring manufacturing processes to the building of “digital...

Association rule mining is a powerful data analytic technique used for extracting information from transaction databases with a collection of itemsets. The aim is to indicate what item goes with what item (ie, an association rule) in a set of collected transactions. It is extensively used in text analytics of text records or social media. Here we u...

This chapter starts with multivariate graphical analysis, using methods available in modern statistical software packages. It introduces the concepts of multivariate frequency distributions and marginal and conditional frequency distributions. The chapter presents the most common methods of correlation and regression analysis, and end with the anal...

Sampling plans for product inspection are quality assurance schemes, designed to test whether the quality level of a product conforms with the required standards. This chapter discusses various sampling and testing procedures, designed to maintain quality standards. It examines single, double, and sequential sampling plans for attributes and single...

This paper considers different perspectives of indicators produced by official statistics agencies, with an emphasis on technical aspects. We discuss statistical methods, impact, scope and action operationalisation of official statistic indicators. The focus is on multivariate aspects in analysing and communicating such indicators. To illustrate th...

Research aims at generating research claims. The paper introduces a "border of meaning", abbreviated BOM, as a mode of representation of research findings that supplements statistical tests. The suggested approach was originally developed in a pedagogical context of promoting conceptual understanding in education. Here we aim at helping better unde...

In Industry 4.0 applications, one sees a growing role of twinning a physical plant with simulation‐based surrogates. Simulating the behavior of a system is a cost‐efficient approach to knowledge building. The paper provides a review of simulation models and computer experiments, with a focus on Industry 4.0 applications. image

Synopsis The Fourth Industrial Revolution presents exceptional challenges and opportunities for the developed industrial countries and the leading industrial companies. Through advanced and "smart" technologies like massive dig-itization, big data analytics, and 3D printing, it is now possible to design innovative products and systems and to produc...

Large bone defects pose an unsolved challenge for orthopedic surgeons. Our group has previously reported the construction of a barrier membrane made of ammoniomethacrylate copolymer USP (AMCA), which supports the adhesion, proliferation, and osteoblastic differentiation of human mesenchymal stem cells (hMSCs). In this study, we report the use of AM...

Human body composition is made up of mutually exclusive and exhaustive parts (e.g. %truncal fat, %non-truncal fat and %fat-free mass) which are constrained to sum to the same total (100%). In statistical analyses, individual parts of body composition (e.g. %truncal fat or %fat-free mass) have traditionally been used as proxies for body composition,...

Data and information are considered today as the “new oil” or the “new gold” in almost all aspects of life and economic domains, such as industry, healthcare, education, entertainment and more. The so‐called 4th Industrial Revolution¹ is based on the digital transformation derived from the Big Data revolution, through the capability of storing huge...

Quality is a crucial dimension of products and processes. It is considered a competitive advantage for companies and organizations in the global market. Quality models and practices went through several evolutionary steps during modern history—from inspection to control, to quality assurance, to quality management and quality by design. These quali...

To help companies advance on the roadmap toward Industry 4.0, the authors developed an assessment tool that assesses the maturity level of a specific or group of companies and sketches a set of focused areas for the companies to pursue in their effort to deploy Industry 4.0 methods. They call this model Industry competence and Maturity for Advanced...

This chapter begins by a review of the challenges and opportunities for the systems engineering discipline and community in the fourth industrial revolution ecosystem, and their consequences. It presents an integrated view of systems engineering, systems thinking, and data analytics. Modeling and simulation and the goal of data‐driven and evidence‐...

Objective To empower residents-in-training through personal mentorship from a senior physician who dedicates time and guidance to their personal development and provides professional and emotional support.MethodsA structured model of personal mentoring for residents was designed and implemented in the Department of Obstetrics & Gynecology. The proc...

This chapter looks at an in-depth application of meaning equivalence reusable learning objects (MERLO) to mathematics education and teacher professional development. The study has been conducted during professional development courses for in-service teachers and is focused on mathematics teachers' praxeologies, namely their didactical techniques an...

Apparently, during an informed consent, patients remember little of the information given and their comprehension level is often overestimated by physicians. This study measures level of understanding of informed consent for elective cesarean surgery using an evidence-based informed consent (EBIC) model based on six MERLO assessments. MERLO recogni...