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Purpose Electrocardiogram (ECG) is one of the most essential tools for detecting heart problems. Till today most of the ECG records are available in paper form. It can be challenging and time-consuming to manually assess the ECG paper records. Hence, automated diagnosis and analysis are possible if we digitize such paper ECG records. Methods The proposed work aims to convert ECG paper records into a 1-D signal and generate an accurate diagnosis of heart-related problems using deep learning. Camera-captured ECG images or scanned ECG paper records are used for the proposed work. Effective pre-processing techniques are used for the removal of shadow from the images. A deep learning model is used to get a threshold value that separates ECG signal from its background and after applying various image processing techniques threshold ECG image gets converted into digital ECG. These digitized 1-D ECG signals are then passed to another deep learning model for the automated diagnosis of heart diseases into different classes such as ST-segment elevation myocardial infarction (STEMI), Left Bundle Branch Block (LBBB), Right Bundle Branch Block (RBBB), and T-wave abnormality. Results The accuracy of deep learning-based binarization is 97%. Further deep learning-based diagnosis approach of such digitized paper ECG records was having an accuracy of 94.4%. Conclusions The digitized ECG signals can be useful to various research organizations because the trends in heart problems can be determined and diagnosed from preserved paper ECG records. This approach can be easily implemented in areas where such expertise is not available. Supplementary Information The online version contains supplementary material available at 10.1007/s40846-021-00632-0.

Microfluidic paper-based analytical devices (μPADs) are the futuristic microfluidic paper-based analytical diagnostic devices that are utilized to perform the laboratory-based test (ex: water, blood, urine, etc..,) at the user location. Microfluidic paper-based analytical devices (μPADs) are known as a robust analytical platform that can fulfil the stipulations. This analysis aims to offer a detailed assessment of the μPADs that are advanced for the estimation of vital water pH values. The significant challenge for users with the μPAD based diagnostic is that, the user is unable to evaluate the precise outcome of the diagnostic result. Here, the water pH diagnostic test is considered on the μPADs, since water pollutant is a severe environmental hassle that affect thousands of humans and as a result it increases the demand for common water first-class monitoring. The necessity for analytical systems that merge extreme sensibleness, selectivity and accuracy with low cost, portability and consumer friendliness remains as a prominent part. This research work proposes a technique to detect the pH value of the water by acquiring the images of the tested μPADs, extract the shape of the test zone area and perform colourimetric analysis to determine the pH value of the test zone area on scale 0-13. The main advantages of the μPADs are comparatively low cost and accessible abundance, reduce the overall cost of testing, and reduce the number of visits to the research laboratory.

The EU White Paper on AI mentions healthcare as one of the sectors where AI applications might pose high risks. These comments provide the vision on the regulatory framework for high-risk healthcare AI applications. The key takeaways concern transparency, preventing bias, safety and quality of AI applications used for medical purposes. I suggest that the transparency of AI shall not be equated to its explainability. To increase transparency and ensure the safety of AI healthcare applications, cooperation between manufacturers and users of AI (healthcare providers) shall be improved. I highlight that biased AI decisions alert on the inaccuracy of algorithms. While discrimination and stigmatization are difficult to identify and prove, especially for AI and especially for healthcare, controlling of AI’s accuracy is an efficient tool to prevent and mitigate biases in AI systems. Finally, I briefly compare the two regulations that might apply to AI tools in healthcare - the Medical Devices Regulation (EU) 2017/745 (MDR) and the In-vitro Diagnostic Medical Devices Regulation (EU) 2017/746 (IVDR). I conclude that the IVDR is more tailored to AI characteristics while it is more detailed and more focused on data quality and relevance. Thus, the IVDR rules can be a good starting point for clarifying and implementing a regulatory framework for high-risk AI healthcare applications.

Our research objective is making quantum computing real with Qiskit for USAF-Pentagon JADC2 (Joint All Domain Command & Control) thus contributing to USAF-DoD core missions. JADC2 is the US Air Force led and Joint Staff coordinated key effort central to Joint Services C4I-ISR and C2 (Command & Control) integration enabling the new Joint Warfighting Concept for All-Domain Operations. The resulting ‘New American Way of War’ is anticipated to yield “significant advantage over everybody in the world for a long time” according to the Vice-Chairman of the Joint Chiefs General John Hyten.

White papers are likely the primary source of information provided to potential Initial Coin Offering (ICO) investors in platform-based ventures that may reduce information asymmetry between ICO issuers and investors. We use textual analysis to measure the information content of white paper documents. We examine how an informative white paper content signal and a concurrent potentially biased expert rating signal correlate with measures of ICO funding success, ICO underpricing, and post-ICO performance. Our empirical results suggest that high-quality ICO issuers signal their type by providing more informative white paper content, i.e. excess or new textual information not contained in recent and peer white papers. However, investors rely on the expert ratings signal in their decision to buy tokens that "jams" the white paper informative content signal. Once listed tokens receive a market valuation, white paper informative content is positively associated with our measures for underpricing, returns, and liquidity, while the expert ratings signal is rendered irrelevant.

The Internet of Things (IoT) based remote monitoring of the environment gained tremendous attention from researchers. Wireless monitoring is offered through the IoT-enabled technologies under applications like Intelligent Transport System (ITS), healthcare, home automation, precision agriculture, etc. The working of IoT applications has been the basis on different kinds regards sensor nodes that were deployed for field data sensing & transmitting through a base station (BS). The Wireless Sensor Network (WSN)- assisted IoT networks to suffer from two challenges like energy-efficiency & various security threats such as sinkhole, black hole, Daniel of Service attacks, etc. This survey paper, studying the recent security measures to protect communications from such attackers. A systematic review conducted on lightweight security solutions like trust-based & probe route-based mechanisms under this research. Comparative analysis of such methods presented in terms of security technique, attacks, performance metrics, etc. The outputs of this paper have been critics of research observed through the comparative analysis of reviewed methods.

Augmented Reality (AR) systems have seen a rapid adaptation in both training and in virtual assembly instructions. AR systems assist the operator by enhancing user perception of reality, reducing the defects, and lead-time. However, there is a significant lack in the existing literature to compare AR systems and conventional work instructions. The aim of this research is to provide an empirical evidence of comparing task completion time, number of errors, workload index and system usability of AR and conventional paper-based work instructions. For this purpose, we designed an experiment where participants use paper based instructions and AR instructions to assemble a planetary gearbox. The task was assessed using NASA-TLX and System Usability Scale (SUS) tests, which allowed further analysis using descriptive statistics. Moreover, the qualitative interview at the end of the experiment gave more insights about participant’s overall experience.

Academic reading, a form of active reading, often involves interaction with the text. Highlighting and annotating are some of the most common strategies of interacting with academic texts, yet we have limited understanding of exactly how such interaction affects reading comprehension in digital versus analog reading environments. In this paper, we compare how university students (N=50) interact with a digital and a physical text, focusing on highlights and annotations. We compare reading speed, interaction with, and subsequent memory of the texts. We make nine observations about reading speed, highlighting frequency and memory scores between paper and laptop. We find indications that highlighting and annotating when reading a digital text has a higher impact on memory than when reading a paper text, and suggest that the main challenge for designers of digital reading support tools appears to be better designs for active annotation.

This White Paper summarizes the current state of discussion regarding the main technological challenges in cybersecurity and impact of those, including ways and approaches to addressing them, on key fundamental values. It provides an overview on current cybersecurity threads and countermeasures and focuses on ethical dilemmas that emerge when counteracting those threads. It also points to the fact that the cybersecurity community relies much more on interpersonal relations when sharing intelligence and data than in explicit national or supranational regulations. Furthermore, the White Paper presents advanced cryptographic techniques and data anonymization techniques that may help to solve or minimize some of the ethical dilemmas.

This document sets out guidance on the re-design of courses from face-to-face teaching to online asynchronous and synchronous1 learning in response to circumstances of COVID-19. We created these guidelines to help us in our thinking before we began to re-develop the courses we lead. In our case, these courses were hosted on the Moodle VLE. We had to keep our redesign do-able. We knew it would involve significant amounts of work, but by focusing effort on the points below prior to undertaking the redesign, we were able to redevelop existing courses effectively, putting students and their learning at the heart of the process. We read, talked to those with expertise in online learning, reflected on our own understandings of effective online learning and the nature of what it was we wanted our students to learn. From this, we created a set of guiding principles (Section 1) and some associated practical considerations (Section 2). We then deepened this by identifying some key messages from published evidence about online learning which we summarised in a table (Section 3). In redesigning our courses, the summary points in the table have been central.

The assessment of the student will be done by conducting of the examination in different levels. Setting of the question paper is the challenging task for the teacher in educational institutions. Question papers setting must follow certain standard methods. Each question will be specified with cognitive level of the course outcome defined by the expert teacher in an institute. A qualified question paper setting will sound the standardization of the educational institute. This will lead to judge the student performance in a qualitative way. Tools are required to design for atomicity of qualitative question papers generation. Most of the researchers are suggested to considered different parameters like cognitive levels, descriptions, duration etc. Atomicity of question paper generation is based on specified scheduled time along with security, authentication & control of the authorities. The proposed system is the smart question paper generation system based on schedule and authenticity. It will generate the question paper in a pdf format based on authenticated scheduling time. Examination paper automaticity is based on cognitive levels specified in the question bank that will store in data repository. Authentication is achieved by giving permissions through keys to generate & decrypt the unique exam paper by the authorized personnel in a given schedule time. Exam paper generation authenticity certificates are produced by the system based on schedule time of generation.

This paper proposes a roadmap for implementing a public platform for the Indian justice system, based on the principles and ideas described in Whitepaper series on Next Generation Justice Platform, Paper 1: The Vision (Paper 1). The paper focuses on the Indian judiciary and the functions, tasks, and services that support it, describing the historical evolution of its information systems with the goal of understanding challenges unique to the Indian context and how they can be overcome. The features and services that the paper proposes have been identified based on the principles outlined in Paper 1. The path to implementing these solutions takes into account the features and implementation status of present systems.

This is a template for designing a scholarly manuscript in the context of business and management related research. I use the example of a literature review for illustration, as over-viewing what we know about a specific topic is a challenge that many new to academic writing will face at some point. Instead of writing a classic “How to”-guide this paper provides readers with a template designed in an instant “guide-while-you-write”-format. The text addresses typical barriers that prevent the dissemination of new knowledge and is presented and formatted as a practical template. The paragraph structure provides an implicit checklist of typical components of academic papers and gives hands-on advice for future or current PhD students and early career academics - or academics who generally struggle to get their ideas on paper independent of their stage in the academic career. Readers will learn about how they can structure their work, construct an abstract, hook the reader in their own introductions, illustrate their methods, report their findings and close the loop in their conclusion chapters. The paper contains examples on making good use of the scholarly apparatus and shares observations on typical flaws in submissions I received in various roles associated with doctoral supervision, reviewing academic work and organizing larger scale review processes. This paper provides a helpful basis for drafting academic papers. It might be seen as a helpful starting point for your own academic writing.

Gestures which are the movement of a part of the body to express an idea or meaning or to act in order to convey a feeling or intention. Every day, gestures are used like waving hand without us thinking about them. Gestures are an important part of communication. The objective of this paper is to use hand and gaze detection to interact with the computer for various different purposes. Compared to existing methods, hand gesture methodology has the bonus of being simple to use. By using this method, the traditional way to use the mouse and keyboard is modified because you can instead communicate with hand gestures device. Gaze tracking is a mouse movement technique which moves the mouse according to the movement of your eye ball along with the head movement to interact with the machine or the computer system. In this paper, an attempt has been made to combine both these algorithms to achieve more accuracy.

So far, the debate on contact tracing technologies to fight COVID19 heavily focused on the ethical and legal aspects concerning privacy and data protection. This Commentary (working paper) analyses the applicability of the EU Medical Devices Directive to the software for decentralized privacy-preserving proximity tracing by following MEDDEV 2.1/6 guidelines’ five-step approach. It concludes that the software at stake might qualify as a medical device.

This paper presents a PV based hybrid energy storage(HES) configuration for DC motor application. A three port bidirectional buck boost converter is used to interface both PV and HES with the dc link. A hybrid energy storage system as a combination of battery and supercapacitor is used for the better performance by balancing the power fluctuations due to both PV and load disturbances with increased life time and reduced size of battery. Power balance along with maximum power point operation of PV, Inherent PV voltage boosting and supercapacitor voltage regulation with a simple control structure having lesser number of sensors is used. The proposed model is designed and simulated in MATLAB/SIMULINK environment.

We consider a principal who periodically offers a fixed, binary, and costly non-monetary reward to agents endowed with private information, to incentivize the agents to invest effort over the long run. An agent's output, as a function of his effort, is a priori uncertain and is worth a fixed per-unit value to the principal. The principal's goal is to design an attractive reward policy that specifies how the rewards are to be given to an agent over time, based on that agent's past performance. This problem, which we denote by P, is motivated by practical examples from both academia (a reduced teaching load for achieving a certain research-productivity threshold) and industry ("Supplier of the Year" awards in recognition of excellent past performance). The following "limited-term'' reward policy structure has been quite popular in practice: The principal evaluates each agent periodically; if an agent's performance over a certain (limited) number of periods in the immediate past exceeds a pre-defined threshold, then the principal rewards him for a certain (limited) number of periods in the immediate future. For the deterministic special case of problem P, where there is no uncertainty in any agent's output given his effort, we show that there always exists an optimal policy that is a limited-term policy and also obtain such a policy. When agents' outputs are stochastic, we show that the class of limited-term policies may not contain any optimal policy of problem P but is guaranteed to contain policies that are arbitrarily near-optimal: Given any epsilon>0, we show how to obtain a limited-term policy whose performance is within epsilon of that of an optimal policy. This guarantee depends crucially on the use of sufficiently long histories of the agents' outputs for the determination of the rewards. In situations where access to this historical information is limited, we derive structural insights on the role played by (i) the length of the available history and (ii) the variability in the random variable governing an agent's output, on the performance of this class of policies. Finally, we introduce and analyze the class of "score-based'' reward policies - we show that this class is guaranteed to contain an optimal policy and also obtain such a policy.

This survey reviews several approaches of HPDM from many research groups world wide. Modern computer hardware supports the development of high-performance applications for data analysis on many different levels. The focus is on modern multi-core processors built into today's commodity computers, which are typically found at university institutes both as small server and workstation computers. So they are deliberately not high-performance computers. Modern multi-core processors consist of several (2 to over 100) computer cores, which work independently of each other according to the principle of "multiple instruction multiple data'' (MIMD). They have a common main memory (shared memory). Each of these computer cores has several (2-16) arithmetic-logic units, which can simultaneously carry out the same arithmetic operation on several data in a vector-like manner (single instruction multiple data, SIMD). HPDM algorithms must use both types of parallelism (SIMD and MIMD), with access to the main memory (centralized component) being the main barrier to increased efficiency.

As these days population is increasing hugely, we tend to face heaps problems thanks to that, pollution is one in every of the, and additionally govt have launched several schemes to create our society, country clean and healthy , we tend to here centred on a connected issue that cause pollution and additionally cause several diseases, government put in dustbins in nearly each area of the many cities to create a town clean and healthy however that doesn’t appears to successful drawback isn't resolved , as once the bin is stuffed there's nobody to create it empty not even municipal corporation aware bout that and bin is overflowed and cause diseases, thus we tend to area unit planned to remodel a traditional bin into good bins, with the assistance microcontroller Arduino UNO, inaudible device, servo motor IR device and a GSM module. Inaudible device is placed at the highest of the bin which can live the stature of the bin. the brink stature is ready as 10cm. Arduino are going to be programmed in such the simplest way that once the bin is being stuffed with facilitate of Arduino and GSM module a message is shipped to the closest swiper thereto bin. Once the bin is press, individuals will recycle the bin. At regular intervals bin are going to be press. Once these good bins area unit enforced on an oversized scale, by commutation our ancient bins gift nowadays, waste may be managed with efficiency because it avoids surplus lumping of wastes on wayside. Foul smell from these rotten wastes that stay untreated for a protracted time, thanks to negligence of authorities and carelessness of public could result in future issues.

Data and analytics are being enlisted to play a role in understanding and preventing the spread of COVID-19 This chapter focuses on digital “apps,” which are b

Aspect-Oriented Programming (AOP) is an extension to the Object-Oriented Programming (OOP). There are four main principles of the OOP: inheritance, polymorphism, encapsulation and abstraction. When anyone develops large software in OOP, some common features as logging, security, etc are scattered in different modules. For large software there may be a large number of methods included in a module along with the common features of the software. In an OOP a module suffers from code tangling and scattering problems. AOP is developed to reduce the scattering and tangling problem of OOP. This is the new technique. Many research works are going on the AOP. Here we reviewed many research papers on the AOP testing. We have included many papers from good Journals/Conferences.

Data mining is utilized for mining data from databases and discovering significant examples from the database. Numerous associations are currently utilizing these data mining strategies. This paper surveys the idea just as the techniques for the data mining and gives the total a thought regarding the idea The paper also discusses about the type of the classification in the data mining. The paper also describes the various methods which are used in the process of the data mining. In short the paper gives the complete information regarding the data mining and its concepts.

The advancement of electric grid into smart grid has become possible by integrating communication network with the component of power system for free disturbance and effective power distribution. Advanced metering infra-structure (AMI) is used for measurement, collection, analysis and the electricity consumption of the customer. This AMI has variety of sensors for the consumption of electricity usage, smart meter, data concentrators, various server and different communication network. The implementation of net-work for making information available all the time introduces the cyber security concern on metering data of the customer. The modification or adulteration on metering data may lead to Financial loss during billing, false pre-diction of required energy and physical damage to the equipment present in the entire infrastructure. Hence it become essential to ensure confidentiality and integrity of metering data. In this paper various security algorithm has been surveyed to understand the factor for achieving the confidentiality and integrity of smart metering data. At last comparative work and future scope is discussed to identify factors and their importance for cyber security on metering data of the customer has been identified.

Higher noise level in heavy industries is harmful for workers. It causes ill effects like hearing loss, tired, weakness, higher blood pressure on health of industrial workers. Therefore, to improve the environment of the workplace and reduce unwanted noise in industries it is very important to find out effective and harmless noise control methods. The research work was conducted to investigate use of natural materials for industrial noise reduction to give effective solution for existing industrial noise problem .specimens having size of 75 mm (dia.) and 12.5mm, 25mm (thick.) were cast. Noise reduction coefficients of prepared specimens were calculated by using an experimental set-up. Experimental set-up consisted Noise level meter, function generator, speaker. Noise reduction capacity of materials was calculated by using Noise reduction coefficient (NRC). Effectiveness of natural materials for industrial noise reduction is discussed in this paper.

Battery powered electric vehicles are gaining popularity worldwide. This trend is driven by several factors including the need to reduce air and noise pollution, and dependence on fossil fuels. The main drawback of today’s electric vehicle is its limited range, and the long time duration that is required to charge the electric batteries. In recent years, significant progress (through research and development) has been made to accelerate the charging time of the electric vehicle batteries through pulse charging rather than supplying continuous current and/or voltage. The part to be focused on estimation of electrical parameters of the battery in the electrical vehicle, which is the most important factor to get information about possible available driving range. If the amount of remaining battery capacity can be displayed for the driver then it is possible to make decision on the time of recharging the battery. To know battery behavior under different conditions, it is necessary to know various battery performance parameters.

Intrusion Detection System (IDS) has been an effective way to achieve higher security in detecting malicious activities for the past couple of years. Anomaly detection is an intrusion detection system. Current anomaly detection is often associated with high false alarm rates and only moderate accuracy and detection rates because it’s unable to detect all types of attacks correctly. An experiment is carried out to evaluate the performance of the different machine learning algorithms using KDD-99 Cup and NSL-KDD datasets. Results show which approach has performed better in term of accuracy, detection rate with reasonable false alarm rate.

This paper discusses the legal issues generated by the introduction of Artificial Intelligence (“AI”) and cognitive robotics technologies in the area of law enforcement. This can be referred to as “automated law enforcement”. The paper starts by providing a quick reminder on “law enforcement” (1). It moves on to provide an overview of “automated law enforcement” systems (2). It then discusses philosophical issues (3) and conventional legal issues (4).

The present paper provides a template for a reproducible scientific paper written in R Markdown. Below I outline some of the "tricks"/code (e.g., referencing tables, sections etc.) I had to figure out to produce this document. The underlying files which produce this document can be downloaded here (see paper). I think I got pretty far but there is always room for improvement and more automatization, in parallel to the incredible developments in R and Rstudio (bookdown etc.). I intend to update this file when I discover more convenient code.

This paper was written as part of the policy paper series produced by the Secured Transactions Law Reform Project, which exists to consider the need for and shape of reform in this area of law in the UK, as well as to study and inform discussion about the reform of secured transactions law around the world. The paper is a working paper intended to stimulate discussion. The paper considers, in some detail, arguments relating to different registration systems and sets out for discussion two possible schemes: a notice filing scheme and a priority notice scheme. It is an attempt to articulate some of the arguments for and against these two different types of systems, and to identify further arguments relating to the shape and operation of a modern secured transactions register. It is assumed that the most modern technology would be available. Section 2 of the paper considers the rationales for registration, section 3 sets out the parameters resulting from the agreed core of a modern secured transactions law and the arguments for and against each parameter, and section 4 considers what information should be included in the register. Section 5 looks at two specific problems: identification (which arises particularly when non-corporate debtors are included) and empty filing (which arises particularly from advance filing). Section 6 compares document filing and notice filings, section 7 sets out the two schemes and section 8 concludes. The discussion, particularly in sections 5 and 7, is informed by comparative analysis of a number of notice filing systems. This analysis is included in four appendices, which account, in part, for the length of the paper.

This draft paper discusses the theories underlying 'platform neutrality' and search engine regulation. The draft focusses on instances of search engine regulation in the United States and the EU, and on related free speech considerations in the context of First Amendment Protection in the US.

Bitcoin scripts currently do not enable loops. Therefore, they are commonly considered to be not Turing Complete. This limits the types of algorithms the Bitcoin scripts can execute to linear or tree-like instructions. This white paper describes the invention of an Oracle module that: • Continuously monitors the state of Blockchain. • Makes decisions based on the current state. • Generates the next set of transactions to be written onto the Blockchain. The above processes is executed continuously by the Oracle in parallel to the Blockchain network. It therefore implements looping constructs that makes the combined Oracle and Blockchain system Turing Complete. As old blocks cannot be erased from the Blockchain, but new blocks can be added, the Oracle and the Blockchain will work as a non-erasable Turing Machine as described in Minsky et al. (1967). We will discuss the use of the Oracle in applications including: • Distributed data storage • Distributed computing • The control of drones. We will also describe how metadata storage and digital signature authorization on the Blockchain can be useful features for implementing these applications.

This White Paper introduces and contributes the first implementation of the Decentralized Voting Algorithm. First, Part I provides an overview for the software structures relevant to this work. Second, Part II introduces a decentralized voting algorithm for transferring value on blockchain networks. Third, Part III explains the voting algorithm’s implementation in reach, including the backend architecture, web deployment, and quantum integration. Perhaps most significantly, this paper solves the Decentralized Voting Problem with a new quantum consensus system.

Adoption of disruptive technologies, such as blockchain and artificial intelligence, is more and more raising citizens’ suspiciousness based on (i) lack of trusted information, (ii) perception of intrusiveness on privacy and human rights, (iii) disrespect of legal obligations (including GDPR), and (iv) misalignment and lack of cross-fertilization between technology and legal experts. This paper aims at demonstrating how the technology is not a per se issue, as it can be used to create an ecosystem which can deliver a significant and measurable value to citizens and customers and the whole community. In this perspective, this paper describes the legal framework, the method and the results that are behind the compliance analysis of the Blockchain-based platform developed within the context of the PoSeID-on project. The paper, in order to identify the ethics and legal requirements used to perform the assessment of the PoSeID-on technology, introduces the ethics and regulatory framework on human rights, privacy, and data protection. The procedure for the assessment of the technology is described as well. An overview of the Poseidon project and its implemented Blockchain-based platform allows the reader to fully understand the objectives of the project, as well as the peculiarity of the specific implemented technology that has been designed to overcome many obstacles (e.g. regulation compliancy, individuals and organizations trust, investment size). Consequently, the paper describes the results of the compliance assessment performed on the PoSeID-on Blockchain-based platform. The paper concludes by showing that important aspects such as trustworthiness and sustainability can definitely contribute to improve the social acceptance of disruptive technologies, such as the PoSeID-on one, and consequently their wide adoption.

Inference and testing in general point process models such as the Hawkes model is predominantly based on asymptotic approximations for likelihoodbased estimators and tests, as originally developed in Ogata (1978). As an alternative, and to improve finite sample performance, this paper considers bootstrap-based inference for interval estimation and testing. Specifically, for a wide class of point process models we consider a novel bootstrap scheme labeled 'fixed intensity bootstrap' (FIB), where the conditional intensity is kept fixed across bootstrap repetitions. The FIB, which is very simple to implement and fast in practice, naturally extends previous ideas from the bootstrap literature on time series in discrete time, where the so-called 'fixed design' and 'fixed volatility' bootstrap schemes have shown to be particularly useful and effective. We compare the FIB with the classic recursive bootstrap, which is here labeled 'recursive intensity bootstrap' (RIB). In RIB algorithms, the intensity is stochastic in the bootstrap world and implementation of the bootstrap is more involved, due to its sequential structure. For both bootstrap schemes, no asymptotic theory is available; we therefore provide here a new bootstrap (asymptotic) theory, which allows to assess bootstrap validity. We also introduce novel 'nonparametric' FIB and RIB schemes, which are based on resampling time-changed transformations of the original waiting times. We show effectiveness of the different bootstrap schemes in finite samples through a set of detailed Monte Carlo experiments. As far as we are aware, this is the first detailed Monte Carlo study of bootstrap implementations for Hawkes-type processes. Finally, in order to illustrate, we provide applications of the bootstrap to both financial data and social media data.

In this short paper, we outline geometric and arithmetic compound formulae for interest rate swaps. We also present ISDA protocol when compounding with a floating spread.

With only ten years left to achieve the Sustainable Development Goals (SDGs), development organizations rapidly need to innovate their approach to decision making and problem solving. New lessons and understandings, born from emerging uses of technology, can enable these innovations. This position paper uses the new paradigm of intelligence — which includes data intelligence, artificial intelligence, collective intelligence, and embodied intelligence — to provide development practitioners, policymakers, and decision-makers with an overview of the benefits and risks associated with various emerging uses of technologies. These assessments are illustrated where possible with examples from the field. It recommends the creation of a decision-making framework to help practitioners determine whether to invest in emerging technologies and how such technologies can effectively support development objectives. This early framework iteration focuses on carefully defining the relevant development objectives while taking into account the prevailing environment before addressing the solution by assessing the maturity, challenges, cost implications and risks of the technology’s use as well as the presence of enablers or disablers that could determine its impact and appropriateness.

Last September, this article’s three authors were Contributing Editors to a new White Paper published by the EAM Research Consortium (“Ensemble Active Management – The Next Evolution in Investment Management”1) which introduced the public to the breakthrough potential of Ensemble Active Management (“EAM”). The Paper explained how EAM Portfolios are the result of applying time‐tested “Ensemble Methods” (a core component of Artificial Intelligence (“AI”) and Machine Learning for decades) to the high conviction stock selections of actively managed portfolios, and that the superior performance for EAM Portfolios are both repeatable and persistent. The EAM White Paper focused on the AI and mathematical principles enabling EAM, The White Paper did not, however, include a comprehensive discussion of the time‐tested investment principles that explained how, and why, EAM Portfolios performed as well as the White Paper demonstrated. This article is designed to address that omission.

This short paper discusses my experiences designing asynchronous online law school courses. It is meant to serve as a quick resource for professors moving classes online to deal with Covid-19 live class cancellations.

The automatic hand sanitizer dispensing machine is a machine controlled instrument. It is a non-contact, alcohol is the solvent primarily based hand sanitizer. This instrument is used in hospitals, workplaces, offices, intuitions and etc. Alcohol is the largest used solvent with compared to any other. Alcohol is the disinfected compared to the soap or any other solid soap and it does not require water to clean it because it is a volatile in the nature and evaporates initially when we apply to our hands. Reports says that alcohol level is high in killing the corona virus in our hands. The concentration of the alcohol is greater than 70 percentage.

In this paper we discuss general identification results for Structural Vector Autoregressions (SVARs) with external instruments, considering the case in which r valid instruments are used to identify g Ï 1 structural shocks, where r Ï g. We endow the SVAR with an auxiliary statistical model for the external instruments which is a system of reduced form equations. The SVAR and the auxiliary model for the external instruments jointly form a "larger" SVAR characterized by a particularly restricted parametric structure, and are connected by the covariance matrix of their disturbances which incorporates the "relevance" and "exogeneity" conditions. We discuss identification results and likelihood-based estimation methods both in the "multiple shocks" approach, where all structural shocks are of interest, and in the "partial shock" approach, where only a subset of the structural shocks is of interest. Overidentified SVARs with external instruments can be easily tested in our setup. The suggested method is applied to investigate empirically whether commonly employed measures of macroeconomic and financial uncertainty respond on-impact, other than with lags, to business cycle fluctuations in the U.S. in the period after the Global Financial Crisis. To do so, we employ two external instruments to identify the real economic activity shock in a partial shock approach.

Full Paper is available at: https://ssrn.com/abstract=3127710 Updated Web Appendix for the paper "Dynamic Multilevel Covariance Structure Models for Analyzing Rolling Cross-Sectional Tracking Surveys." This Web Appendix contains the following sections: A. Supplementary Tables discussed in Manuscript, B. Dynamic Linear Model specification, C. Simulation Studies, and D. Unit Roots Testing. Across all the sections, equations are numbered sequentially with section letter such as E1, E2, and so on; similarly, all tables and figures are numbered as T1, T2, and F1, F2, and so on.

I introduce binscatterhist, a command that extends the functionality of the popular binscatter command (Stepner, 2013, Statistical Software Components S457709, Department of Economics, Boston College). binscatter allows researchers to summarize the relationship between two variables in an informative and versatile way by collapsing scattered points into bins. However, information about the variables’ frequencies gets lost in the process. binscatterhist solves this issue by allowing the user to further enrich the graphs by plotting the variables’ underlying distribution. The binscatterhist command includes options for different regression methods, including reghdfe (Correia, 2014, Statistical Software Components S457874, Department of Economics, Boston College) and areg, and robust and clustered standard errors, with automatic reporting of estimation results and sample size., The Stata Journal, 22 (2), ISSN:1536-867X, ISSN:1536-8734

After scrutinizing technical, legal, financial, and actuarial aspects of cyber risk, a new approach for modelling cyber risk using marked point processes is proposed. Key covariates, required to model frequency and severity of cyber claims, are identified. The presented framework explicitly takes into account incidents from malicious untargeted and targeted attacks as well as accidents and failures. The resulting model is able to include the dynamic nature of cyber risk, while capturing accumulation risk in a realistic way. The model is studied with respect to its statistical properties and applied to the pricing of cyber insurance and risk measurement. The results are illustrated in a simulation study.

A comparison of "Governance and Taxes" with a previous working paper version reveals a number of irregularities that together suggest the analysis was not performed as described in the published version. In particular, the two versions claim to use different main empirical specifications, but the numbers in all 11 tables are exactly the same in both versions. An assessment of other comparisons between the two versions suggests that it is unlikely that these irregularities are unintentional errors. Instead, a straightforward explanation of these anomalies is data falsification: the working paper version accurately describes the main specification, and the published version misstates the main specification. I conclude by demonstrating that the main result, when accurately described, fails a simple placebo test and is therefore spurious.

Full Paper is available at: https://www.ssrn.com/abstract=2526509 In this Internet Appendix, we perform further tests in order (i) to assess the robustness of the main findings, (ii) to evaluate whether the magnitude of our results changes in different settings, and (iii) to provide further insight on our main empirical constructs.

This White Paper questions the superiority of the traditional Active Management paradigm. Do stand-alone, ‘single-expert’ investment managers or management teams, with well-defined yet rigidly entrenched philosophies and methodologies, deliver optimal results? The conclusion, derived from a database reflecting 30,000 test portfolios and 165 million data points, was that they do not. A new approach to investment management, referred to as “Ensemble Active Management” and representing the intersection of Artificial Intelligence and traditional Active Management, was proven the superior option.

Full paper is available at: https://ssrn.com/abstract=2427106 “What Counts and What Gets Counted” (Bloomfield 2016) is an innovative way of teaching managerial accounting. The 1st edition of the book won the 2014 Jim Bulloch Award for Innovations in Management Accounting Education, and has only gotten better since then. However, the book suffers from two significant limitations. First, the book was intended primarily for MBA students, not for accounting undergrads. As a result, the book doesn’t go into sufficient depth on some of the technical topics that accounting majors need to understand. Second, the book lacks a bank of practice problems and solutions for students to use as they are learning material. Here I present two supplemental readings and a set of practice problems that can be used to supplement “What Counts and What Gets Counted” and make it more appropriate for use by undergraduate accounting majors. Send error information to Jeremiah Bentley - UMass Amherst.

One of the most important skills a public sector leader must cultivate is the ability to frame a problem. While this may seem trivial, in practice – it’s vitally important to clearly understand which problem you are trying to solve, the key aspects of its context, and the available solution space. This Background Note explains the kinds of questions that must be answered to properly frame a problem. When used as part of a public sector course in management (where the course has a term paper/project component), students can submit a short mid-course paper (the Problem Definition Memo) that explains the problem they intend to solve/address in their final paper, using this Background Note as a guide for the mid-course paper.