Reviewerly/exHarmony huggingface dataset:
Quantum Computing and Intellectual Property Law

What types of intellectual property (IP) rights can be vested in the components of a scalable quantum computer? Are there sufficient market-set innovation incentives for the development and dissemination of quantum software and hardware structures? Or is there a need for open source ecosystems, enrichment of the public domain and even democratization of quantum technology? The article explores possible answers to these tantalizing questions.The article demonstrates that strategically using a mixture of IP rights to maximize the value of the IP portfolio of the quantum computer’s owner, potentially leads to IP protection in perpetuity. Overlapping IP protection regimes can result in unlimited duration of global exclusive exploitation rights for first movers, being a handful of universities and large corporations. The ensuing IP overprotection in the field of quantum computing leads to an unwanted concentration of market power. Overprotection of information causes market barriers and hinders both healthy competition and industry-specific innovation. In this particular case it slows down progress in an important application area of quantum technology, namely quantum computing. In general, our current IP framework is not written with quantum technology in mind. IP should be an exception -limited in time and scope- to the rule that information goods can be used for the common good without restraint. IP law cannot incentivize creation, prevent market failure, fix winner-takes-all effects, eliminate free riding and prohibit predatory market behavior at the same time. To encourage fair competition and correct market skewness, antitrust law is the instrument of choice. The article proposes a solution tailored to the exponential pace of innovation in The Quantum Age, by introducing shorter IP protection durations of 3 to 10 years for Quantum and AI infused creations and inventions. These shorter terms could be made applicable to both the software and the hardware side of things. Clarity about the recommended limited durations of exclusive rights -in combination with compulsory licenses or fixed prized statutory licenses- encourages legal certainty, knowledge dissemination and follow on innovation within the quantum domain. In this light, policy makers should build an innovation architecture that mixes freedom (e.g. access, public domain) and control (e.g. incentive & reward mechanisms).The article concludes that anticipating spectacular advancements in quantum technology, the time is now ripe for governments, research institutions and the markets to prepare regulatory and IP strategies that strike the right balance between safeguarding our fundamental rights & freedoms, our democratic norms & standards, and pursued policy goals that include rapid technology transfer, the free flow of information and the creation of a thriving global quantum ecosystem, whilst encouraging healthy competition and incentivizing sustainable innovation.
Side-channel Programming for Software Integrity Checking

Verifying software integrity for embedded systems, especially legacy and deployed systems, is very challenging.Ordinary integrity protection and verification methods rely on sophisticated processors or security hardware, and cannot be applied to many embedded systems due to cost, energy consumption, and inability of update.Furthermore, embedded systems are often small computers on a single chip, making it more difficult to verify integrity without invasive access to the hardware.In this work, we propose "side-channel programming", a novel method to assist with non-intrusive software integrity checking by transforming code in a functionality-preserving manner while making it possible to verify the internal state of a running device via side-channels.To do so, we first need to accurately profile the side-channel emanations of an embedded device.Using new black-box side-channel profiling techniques, we show that it is possible to build accurate side-channel models of a PIC microcontroller with no prior knowledge of the detailed microcontroller architecture.It even allows us to uncover undocumented behavior of the microcontroller.Then we show how to "side-channel program" the target device in a way that we can verify its internal state from simply measuring the passive side-channel emanations.
Task-Guided Inverse Reinforcement Learning under Partial Information

We study the problem of inverse reinforcement learning (IRL), where the learning agent recovers a reward function using expert demonstrations. Most of the existing IRL techniques make the often unrealistic assumption that the agent has access to full information about the environment. We remove this assumption by developing an algorithm for IRL in partially observable Markov decision processes (POMDPs). The algorithm addresses several limitations of existing techniques that do not take the information asymmetry between the expert and the learner into account. First, it adopts causal entropy as the measure of the likelihood of the expert demonstrations as opposed to entropy in most existing IRL techniques, and avoids a common source of algorithmic complexity. Second, it incorporates task specifications expressed in temporal logic into IRL. Such specifications may be interpreted as side information available to the learner a priori in addition to the demonstrations and may reduce the information asymmetry. Nevertheless, the resulting formulation is still nonconvex due to the intrinsic nonconvexity of the so-called forward problem, i.e., computing an optimal policy given a reward function, in POMDPs. We address this nonconvexity through sequential convex programming and introduce several extensions to solve the forward problem in a scalable manner. This scalability allows computing policies that incorporate memory at the expense of added computational cost yet also outperform memoryless policies. We demonstrate that, even with severely limited data, the algorithm learns reward functions and policies that satisfy the task and induce a similar behavior to the expert by leveraging the side information and incorporating memory into the policy.
Enhancement of the Capability Maturity Model for Improving the Quality of Software Projects in Developing Countries

Business process modeling was suggested by academia and implemented by the industry to trigger device requirements. Maturity models of software processes are also similar in the software industry. Therefore, business software requirement engineering approaches-based process should aim to fulfil with the maturity models. Although researchers in the area of Software Engineering, Project Management, and Business Intelligent have addressed planning and execution and a lot of research still needs to be done, in this study, we focused on doing a questionnaire based on different prominent universities, major companies, and software houses. The purpose of the questionnaire was to dig out the main factors that negatively affect software houses and their products and services, especially in the medical field. A questionnaire was generated to accomplish these reasons, and interviews were conducted to extract the key explanation why software developers and software houses in developing countries are not familiar with the CMMI (Capability Maturity Model Integration) model for medical software projects. This analysis attempted to figure out why the tech enterprises of developing countries are behind foreign competitors. We aimed to determine why software developers do not meet the international requirements for software. The novelty of the research is that attempts were made to strengthen the new approach by adding agile at level 3 to keep the local software industry appropriate and reveal the requirements for medical software life cycle study, because accurate decision support is really necessary for healthcare systems.
A feature‐based approach for guiding the selection of Internet of Things cybersecurity standards using text mining

Abstract Cybersecurity is critical in realizing Internet of Things (IoT) applications and many different standards have been introduced specifically for this purpose. However, selecting relevant standards is not trivial and requires a broad understanding of cybersecurity and knowledge about the available standards. In this study, we present a systematic approach that guides IoT system developers in selecting relevant cybersecurity standards for their IoT projects. The systematic approach has been developed in four stages. First, the common and variant features of IoT cybersecurity have been modeled using a feature model. Second, an up‐to‐date overview of the IoT cybersecurity standards landscape has been mapped by combining existing overviews. Third, a text mining algorithm has been implemented. Fourth, the systematic approach has been modeled using business process modeling notation. Our case study demonstrated that this approach is effective and efficient for guiding the selection of IoT cybersecurity standards.
Saving Human Capital In A Digital Epoch

Human capital, ensuring the well-being and quality of life of the population, is insufficiently used and capitalized in Russia.It is partially due to the fact that the Russian higher education system focuses on economic growth instead of human and personal development.The identification of socio-humanitarian sources of human capital accumulation -personal potential, professional ethos, generating, firstly, the quality of life phenomenon as the psychological well-being of students, seems to be one of the relevant solutions of the problem.The project offers a navigational understanding of human capital for aggregating the "basket" of its accumulation sources.This understanding will be used for developing a model of quality of life management related to the health of Russian youth.It will expand the interpretation of the quality of life and include in its analysis such human capital accumulation sources as autonomy (self-organization), responsibility, reflexivity, meaningful life orientations, professional identity, tolerance for uncertainty, communicative abilities.The reflection of personal, cognitive-reflective, and professional-value positions in improving the quality of life implicit for students as the achievement of psychological well-being, expanding human capabilities and social mobility in higher education practice allows identifying sociohumanitarian sources in human capital development.Such model partially serves to overcome methodological uncertainty in the development of the "human capital", "personal potential", "professional ethos", and "health-related quality of life" concepts.
Expanding Universal Dependencies for Polysynthetic Languages: A Case of St. Lawrence Island Yupik

This paper describes the development of the first Universal Dependencies (UD, Nivre et al., 2016Nivre et al., , 2020) ) treebank for St. Lawrence Island Yupik, an endangered language spoken in the Bering Strait region.While the UD guidelines provided a general framework for our annotations, language-specific decisions were made necessary by the rich morphology of the polysynthetic language.Most notably, we annotated a corpus at the morpheme level as well as the word level.The morpheme level annotation was conducted using an existing morphological analyzer (Chen et al., 2020) and manual disambiguation.By comparing the two resulting annotation schemes, we argue that morpheme-level annotation is essential for polysynthetic languages like St. Lawrence Island Yupik.Word-level annotation results in degenerate trees for some Yupik sentences and often fails to capture syntactic relations that can be manifested at the morpheme level.Dependency parsing experiments provide further support for morpheme-level annotation.Implications for UD annotation of other polysynthetic languages are discussed.
Towards a Standardized Questionnaire for Measuring Agility at Team Level

Abstract Context: Twenty years after the publication of the agile manifesto, agility is becoming more and more popular in different contexts. Agile values are changing the way people work together and influence people’s mindset as well as the culture of organizations. Many organizations have understood that continuous improvement is based on measurement. Objective: The objective of this paper is to present how agility can be measured at the team level. For this reason, we will introduce our questionnaire for measuring agility, which is based on the agile values of the manifesto. Method: We developed a questionnaire comprising 36 items that measure the current state of a team’s agility in six dimensions ( communicative , change-affine , iterative , self-organized , product-driven and improvement-oriented ). This questionnaire has been evaluated with respect to several expert reviews and in a case study. Results: The questionnaire provides a method for measuring the current state of agility, which takes the individual context of the team into account. Furthermore, our research shows, that this technique enables the user to uncover dysfunctionalities in a team. Conclusion: Practitioners and organizations can use our questionnaire to optimize collaboration within their teams in terms of agility. In particular, the value delivery of an organization can be increased by optimizing collaboration at the team level. The development of this questionnaire is a continuous learning process with the aim to develop a standardized questionnaire for measuring agility.
Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality

We propose a randomized algorithm with quadratic convergence rate for convex optimization problems with a self-concordant, composite, strongly convex objective function. Our method is based on performing an approximate Newton step using a random projection of the Hessian. Our first contribution is to show that, at each iteration, the embedding dimension (or sketch size) can be as small as the effective dimension of the Hessian matrix. Leveraging this novel fundamental result, we design an algorithm with a sketch size proportional to the effective dimension and which exhibits a quadratic rate of convergence. This result dramatically improves on the classical linear-quadratic convergence rates of state-of-the-art sub-sampled Newton methods. However, in most practical cases, the effective dimension is not known beforehand, and this raises the question of how to pick a sketch size as small as the effective dimension while preserving a quadratic convergence rate. Our second and main contribution is thus to propose an adaptive sketch size algorithm with quadratic convergence rate and which does not require prior knowledge or estimation of the effective dimension: at each iteration, it starts with a small sketch size, and increases it until quadratic progress is achieved. Importantly, we show that the embedding dimension remains proportional to the effective dimension throughout the entire path and that our method achieves state-of-the-art computational complexity for solving convex optimization programs with a strongly convex component.
A Tutorial on Evaluation Metrics used in Natural Language Generation

There has been a massive surge of Natural Language Generation (NLG) models in the recent years, accelerated by deep learning and the availability of large-scale datasets.With such rapid progress, it is vital to assess the extent of scientific progress made and identify the areas/components that need improvement.To accomplish this in an automatic and reliable manner, the NLP community has actively pursued the development of automatic evaluation metrics.Especially in the last few years, there has been an increasing focus on evaluation metrics, with several criticisms of existing metrics and proposals for several new metrics.This tutorial presents the evolution of automatic evaluation metrics to their current state along with the emerging trends in this field by specifically addressing the following questions: (i) What makes NLG evaluation challenging?(ii) Why do we need automatic evaluation metrics?(iii) What are the existing automatic evaluation metrics and how can they be organised in a coherent taxonomy?(iv) What are the criticisms and shortcomings of existing metrics?(v) What are the possible future directions of research?* Human/Manual Evaluation * Automatic Evaluation -Tutorial Roadmap • Challenges of Automatic Evaluation of NLG tasks (20 min) -Breakdown of evaluation criteria for different tasks * Machine
Post Covid-19 Attitude of Consumers Towards Processed Food – a Study Based on Natural Language Processing

This paper dealt with analyzing consumers attitude towards processed good by using Natural Language processing, particularly text analysis. As a research scholar in his mid-20-s, I always adore canned foods. A doctorate student's life is indeed stressful and processed food makes it a little bit easier. I frequently purchase canned foods, canned vegetables, and my favorite Chicken nuggets from Amazon.com, but as the COVID crisis intensify, I find myself hesitant shopping processed foods online, because of the obvious safety reasons. This unprecedented time completely changed the perception of processed food for many consumers. Using data analytics techniques, this essay analyzes Customer's sentiments about purchasing processed food during Pandemic time and hot it differs from normal time. Also, we have analyzed the significant issues that concern customers buying processed food in the pandemic time. We have collected experiences of people shared online about processed foods in two-time periods. The first period refers to consumer's experiences about processed food shared from July 2019 to November 2019 (Just before the first COVID case was detected). The second period refers to the experiences of consumers shared from February 2020 to July 2020. The results of our analysis have indicated the fact that after the emergence of COVID-19, negative attitude towards processed foods increased to a considerable percentage. Particularly the month of April sees a massive increase in negative sentiments towards processed food. Quality of the product and safety of the purchasing experience was the two most important concerns voiced by the consumers during pandemic time.
Development Prospects of Education System in Russia

The article studies the situation in the education system ofRussiaand lines of upgrading this system in view of country economy rising to a new stage of development, i.e. digitalization of all economic processes. As information technologies grow, unskilled labour becomes a thing of the past and is being replaced by intellectual labour. A lot of specialties that can be replaced by workers using digital technologies are neglected by labour market. The key goal of higher school today is to develop concepts of new specialties, which in its turn requires designing of new programs of teaching, competences, curriculums, etc. Upgrading the education system should be carried out on the basis of all positive achievements of the past. The authors present statistic measurement of education processes and identify stages of transformations and reforms of the education system. Education is a part of our life, which in the future can prove, whether our society will be prosperous and life standard of people will change.
Student Attendance Monitoring System using Face Recognition

There is no reason that a critical educational practise like attendance should be viewed in the old, tedious manner in this age of rapidly evolving new technologies. In the conventional method, it is difficult to manage large groups of students in a classroom. Since it takes time and has a high risk of error when entering data into a system, it is not recommended. Real-Time Face Recognition is a practical method for dealing with a large number of students' attendance on a daily basis. Many algorithms and techniques have been developed to improve face recognition performance, but our proposed model employs the Haarcascade classifier to determine the to determine the positive and negative characteristics of the face, as well as the LBPH (Local binary pattern histogram) algorithm for face recognition, all of which are implemented in Python and the OpenCV library. For user interface purposes, we use the tkinter GUI interface.
Design of Distributed Collection Model of Student Development Information Based on Internet of Things Technology

This paper is aimed at the problem that the process of students’ developmental assessment is too comprehensive and the process of data collection is too old. It is very important but the performance of existing methods cannot meet the actual needs. So, this paper puts forward the design of distributed collection model of students’ developmental information based on Internet of Things technology, which is based on the hardware design of students’ developmental information distributed collection such as RF RC500F chip, TIMSP430 microprocessor, and interface in Internet of Things environment. Experimental results show that the model has less noise interference and strong data transmission ability, has higher collection accuracy of student development information, and can improve the authenticity and comprehensiveness of student development assessment.
Triple-feature-based Particle Filter Algorithm Used in Vehicle Tracking Applications

This work is oriented toward video tracking of vehicles in a typical traffic environment, based on particle filters. The proposed tracking algorithm is based on simultaneous usage of t ...
AI based intelligent travel chatbot for content oriented user queries

ABSTRACTAutomation is the way through which the machine can interact with data as well as a user for proper work or communication. A chatbot is a system which accepts user inputs as queries and respond with suggestions based on the previous inputs and trained models. In this paper, a travel chatbot is being modelled using Deep Neural Network (DNN) where it improves the human and machine interaction seamlessly as the user of the bot does not aware whether he/she is interacting with a machine or a human being. This chatbot suggest safest possible routes, secure and cheaper stay, best places for shopping, etc. to the users. This chatbot respond in a minimal time compared to other systems of similar nature. It also uses Long Short Term Memory (LSTM) to understand the sentence and form the sentence according to the previous reply. It also integrates various open APIs to get the recommended ratings from the internet. As per our analytical results, our chatbot outperforms by at least 20% in handling the user queries and suggest possible recommendations to the end users.