Reviewerly/exHarmony huggingface dataset:
Monetary Policy, Private Capital Formation and Economic Growth – The Case of Sub-Saharan Africa

The study sought to test the impact of the policy rate on growth and investment in some selected countries in the Sub-Saharan Africa region. Data for nine (9) countries over a 23-year period was captured and a dynamic panel model estimated. Based on the study results, the major findings were: growth in SSA is cyclical whilst private capital formation is a persistent and smooth function in the region. Growth is positively related to the policy rate, following the McKinnon and Shaw (1973) hypothesis, but stock market development has no effect on growth or private capital formation. The overall impact of trade openness is ambiguous and the policy rate is not a critical factor to private capital formation in the SSA region. Based on the purpose of the study it can be concluded, that while private capital is obviously positively influential on growth, the formation of private capital to stimulate growth is not driven by the monetary policy stance.
CURRENT FORMS OF ASSESSMENT IN PRIMARY EDUCATION WITH A FOCUS ON FORMATIVE ASSESSMENT

Assessment can be understood as an activity that pursues both the result as well as the process of achieving the goal, it monitors the conditions and means of achieving these goals and the activities of the pupil and teacher in the process of achieving goals. School assessment is a process that leads to determining the qualities and achievements showed by a pupil or a group of pupils; it is a systematic activity, i.e. prepared, organised and repeatedly performed, whereby the results are subject to revisions or corrections. Formative assessment is continuous feedback, where the learner obtains information in the learning process that compares the current situation with respect to the starting position and especially to the stated goal. The aim of our research was primarily to identify various forms of assessment at primary school and then to understand how teachers work with formative assessment in teaching practice. In view of the research objectives, a mixed research strategy was chosen. Within the quantitative survey, which focused on the assessment of various forms of assessment at school, a questionnaire of our own construction was used and was administered. The second step was implementing a qualitative survey, where semi-structured interviews were carried out focusing on the issue of format assessment in primary education. Results show that teachers often use alternative forms to the most common (summative) assessment in the form of pupils' portfolio, stamps, stickers, credits or letters. In terms of formative assessment, its contribution to pupils' development is appreciated as well as its greater informative value, but interestingly, many teachers use formative assessment without knowing that the chosen assessment method is known by this term. Keywords: Primary education, school assessment, formative assessment, teaching methodology, methods of assessment
The LTI-USP Strategy to the 2020/2021 Multi-Agent Programming Contest

This paper presents the main features and strategies of the LTI-USP which has participated in the 2020/2021 Multi-Agent Programming Contest. The team was developed using Jason programming language, and its main feature is that agents switch between three different behaviors during the game. We discuss the strengths and weaknesses of our team, particularly using data from the matches that we have participated in the Contest.
Multi‐view facial action unit detection via deep feature enhancement

Multi-view facial action unit (AU) analysis has been a challenging research topic due to multiple disturbing variables, including subject identity biases, variational facial action unit intensities, facial occlusions and non-frontal head-poses. A deep feature enhancement (DFE) framework is presented to tackle some of these coupled complex disturbing variables for multi-view facial action unit detection. The authors' DFE framework is a novel end-to-end three-stage feature learning model with taking subject identity biases, dynamic facial changes and head-pose into consideration. It contains three feature enhancement modules, including coarse-grained local and holistic spatial feature learning (LHSF), spatio-temporal feature learning (STF) and head-pose feature disentanglement (FD). Experimental results show that the proposed method achieved state-of-the-art recognition performance on the FERA2017 dataset. The code is released at http://aip.seu.edu.cn/cgtang/.
Predicting Software Aging With a Hybrid Weight-Based Method

Since software aging problems have been found in many areas, how to find an optimal time to rejuvenate is vital for software aging problems. In this paper, the authors propose a newly hybrid method to predict resource depletion of a web server suffered from software aging problems. The proposed method comprises three parts. First, a smoothing method, self-organized map, is used to make resource consumption series glossier. Second, several sub-optimal methods are utilized to fit resource consumption series. Third, an optimization method is proposed to combine all single methods to predict software aging. In experiments, the authors use the real commercial running dataset to validate the effect of the proposed method. And the presented method has a better prediction result for both available memory and heap memory under two metrics: root mean square error and mean average error.
Comparative Study of Keccak and Blake2 Hash Functions

Hashing is so crucial for integrity. Indeed, in order to respond to new technologies requirements, hash functions have always been subject to evolution and optimization. In the same context, NIST organized a competition in 2012 for a Sha-3 hashing function. BLAKE and KECCAK were two interesting functions in terms of speed and security. Keccak was the winner of the competition. It is different from the antecedent of SHA family because it combines the sponge construction to the Keccak-f-permutations. Therefore, it is optimized for security and hardware use. The Blake function is based on the same principle of the Sha-2, and it also presents many advantages of security and speed. The Blake was improvised for the BLAKE2, which is more optimized, faster, and more efficient. In this paper, we present the Keccak and the BLAKE2 algorithms; then, we will compare the performance parameters of the functions: Blake-256, Blake-512, Keccak-256, Keccak-512, Blake2b, and Blake2s.
Implementation and effectiveness of the National Incident Management System’s Incident Command System in law enforcement since 2003

This paper investigates the use of the National Incident Management System (NIMS)’s Incident Command System (ICS) in law enforcement since Homeland Security Presidential Directive 5 was issued in 2003. It attempts to answer the following questions: (a) To what degree has law enforcement adopted the NIMS style ICS?; (b) To what degree has the NIMS/ICS framework been applicable to law enforcement?; and (c) Is the NIMS style ICS effective in the law enforcement response environment? The research includes a review of relevant case studies and literature and also includes the analysis of a survey instrument sent to 1,220 current and former law enforcement practitioners across the United States. The survey includes both open- and closed-ended questions. The data from closed-ended questions were compiled and displayed. Data from open-ended questions were grouped thematically. Responses were then assessed and compared with information gleaned from the literature review. Results indicate the system has been widely adopted by law enforcement, and its use is applicable and effective in some law enforcement responses. Its use in the highly chaotic initial phase of incidents, however, remains an open question.
Other Azure Security Services

You will continue to learn about other Azure security services that not only are stand-alone but support Azure Sentinel. You should be aware that these solutions can work together to support the overall Azure security layers to protect the business and customer data. These security services are all cloud native, so there is no need to update hardware or software. However, each of these services requires a dedicated book to help explore the benefits, and we are limited to an overview of each in this chapter.
Identification of Unintentional Perpetrator Attack Vectors using Simulation Game: A Case Study

In our digital era, insider attacks are among the serious underresearched areas of the cybersecurity landscape.A significant type of insider attack is facilitated by employees without malicious intent.They are called unintentional perpetrators.We proposed mitigating these threats using a simulationgame platform to detect the potential attack vectors.This paper introduces and implements a scenario that demonstrates the usability of this approach in a case study.This work also helps to understand players' behavior when they are not told upfront that they will be a target of social engineering attacks.Furthermore, we provide relevant acquired observations for future research.
How Many Costly Simulations Do we Need to Create Accurate Metamodels? A Case Study on Predicting HIV Viral Load in Response to Clinically Relevant Intervention Scenarios

Computer simulations are used in precision medicine to assist in adapting treatment plans for varying patient characteristics, especially for diseases like HIV where these characteristics have a major impact on disease trajectory. However, simulations are computationally intensive, which can be prohibitive at scale. Meta-models for HIV progression have been developed previously to approximate these simulation results more efficiently, but we are interested in determining how much data is required to build an accurate meta-model. Using many different amounts of data from two HIV simulation models, we build machine learning classification meta-models to predict if an HIV patient is at risk for AIDS based on treatment parameters. Our findings indicate that the amount required to achieve high meta-model accuracy varies for different computer simulations. We are able to achieve near-perfect accuracy with one of our models using limited data, while the other model requires more extensive data to achieve stable accuracy.
An Efficient Relay Selection Method Based on ANN Channel Estimation Technique for Amplify and Forward Relay in Cooperative Networks

Owing to high degree of flexibility, Artificial Neural Networks (ANN) can be used to model nonlinear channel estimation phenomenon.An ANN-based channel estimation technique and relay selection scheme was proposed as an alternate to Fuzzy Logic Controller (FLC) based channel estimation system.ANN's learning property is fully exploited to decipher the deteriorated symbols through extreme faded networks.Similar to FLC channel estimation techniques, this technique is found to be more effective in increasing bandwidth.Simulated results for Multi-input Multi-output (MIMO) of 2×2 and 4×4 using Additive White Gaussian Noise (AWGN) and Rayleigh channel in terms of quantity (Mbps) compared with Signal to Noise Ratio (SNR) over a choice of 0 to 30 dB.This illustrates the effectiveness of the knowledge proficiency of ANNs is 92.19% of AWGN and 94.62% of Rayleigh whereas for FLC is 70.34% of AWGN and 75.51% of Rayleigh channel.
SagTree: Towards efficient mutation in evolutionary circuit approximation

Approximate circuits that trade the chip area for the quality of results play a key role in the development of energy-aware systems. Designing complex approximate circuits is, however, a very difficult and computationally demanding process. Evolutionary approximation—in particular, the method of Cartesian Genetic Programming (CGP)—currently represents one of the most successful approaches for automated circuit approximation. In this paper, we thoroughly investigate mutation operators for CGP with respect to the performance of circuit approximation. We design a novel dedicated operator that combines the classical single active gene mutation with a node deactivation operation (eliminating a part of the circuit forming a tree from an active gate). We show that our new operator significantly outperforms other operators on a wide class of approximation problems (such as 16 bit multipliers and dividers) and thus improves the performance of the state-of-the-art approximation techniques. Our results are grounded on a rigorous statistical evaluation including 39 approximation scenarios and 14,000 runs.
Limited Installation Ranges of Silt Curtain in Ocean and River Hydrodynamic Environment

Youn, S.; Jung, B., and Lee, S., 2021. Limited installation ranges of silt curtain in ocean and river hydrodynamic environment. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 106–110. Coconut Creek (Florida), ISSN 0749-0208. A silt curtain is a flexible ocean structure and is applied to control the diffusion of suspended sediment and pollution materials in the whole world. Specially, the silt curtain is the rational method to control the diffusion of suspended sediment and pollution materials in most ocean construction fields in Republic of Korea. However, this flexible ocean structure has the limitation to install and to maintain in rough hydrodynamic condition due to wave, tidal current, and wind. In this study, the limitation of installation range of silt curtain in countries, where have the rule of installation guide of silt curtain, were reviewed to decide available installation of silt curtain. Designing methods of silt curtain were also reviewed. The applied designing methods in this study were studied in ‘Research to increase the effectiveness of silt curtain (2018)’. To check designing methods, various wave, tidal current, and wind conditions were applied based on designing methods. When tidal current and wave height are over the specific wave height and the speed of tidal current, no more installation of silt curtain was available to use from the result of this study. According to the result, the installation range of silt curtain due to hydrodynamic forces in Republic of Korea is required for safety and protection of ocean environment around maritime area.
mTransDial: Multilingual Dataset for Transport Domain Dialog Systems (Poster)

Task oriented virtual assistants or dialogue systems are being popular for different domains such as restaurant booking, weather update, flight booking etc. The efforts are supported by availability of large scale annotated conversational datasets for such domains. However, the same is not true for transport domain dialogue systems. Moreover, for such systems to be useful, they should be able to handle natural queries submitted by users. For countries like India where most of the people communicate in regional languages, it is important to have such systems support the regional languages. The existing datasets for transport domain are mostly monolingual in nature and support only English language. For countries like India, where people tend to speak multiple languages and have code-mixed conversations the existing systems and the datasets won’t be of much use. To the best of our knowledge, there is no multilingual code-mixed dataset available for designing public transport related conversation systems. In this paper, we propose a code-mixed English-Hindi dataset to accelerate the development of transport domain conversational systems suitable for countries like India. Our dataset has multiple intents like: route finding, bus/train/cab finding, nearby place search, traffic alert queries, out of domain queries. We also provide initial baseline results for user intent identification using existing state of the art models on our dataset and a prototype to show the usability of the work.
Evaluating Conversational Question Generation: CoffeeBot

Asking questions is an important way of showing interest in peopleand learning more about them. We deployed a social robot, Coffee-Bot, capable of asking personalized conversational questions basedon topics mentioned by the user over time. We describe our evalua-tion setup and results of our pilot study. Our initial results, basedon interactions with seven participants, indicate a high level of en-joyment among participants and provided us with useful feedbackon the CoffeeBot experience for a future long-term study.
Meaningful Transparency At EPA: A Framework for Rationalizing Approaches to Promote Open Science and Data Sharing for Evidence-Based Policymaking

In modern society, transparency about how government agencies operate facilitates accountability and oversight, thereby encouraging not just effective governance but also public trust in agency decisions. Within the scientific enterprise, transparency supports new knowledge creation as well as the use of scientific research in policy decisions.While the Environmental Protection Agency (EPA) has taken significant steps to operate transparently throughout its history, like most federal agencies, more work is needed for EPA to develop a holistic approach for applying transparency throughout agency activities. With the growing prevalence of the open-science and open-data movements, policymakers must give further attention to how EPA can and should advance as the agency plans for the future.Recognizing the array of laws, policies, and priorities implemented by EPA to take into consideration, this paper considers the extent to which EPA makes information accessible and useful. Whether scientific evidence for a scientific community or open data for the broad American public, EPA has an ever-evolving information-management role.This report presents a landscape summary of the various policies implemented by EPA, covering science-integrity, data-quality, and information-management policies as well as a discussion of EPA efforts to improve access to both EPA-funded research and non-EPA-funded research used in policy decisions. This report also applies government-wide initiatives and new mandates forevidence-based policymaking to EPA. This report offers a conceptual framework for applying EPA’s existing policies related to transparency to examine how policymakers might consider further modifications to the agency’s transparency approaches in the coming years. The frameworkdescribes how different types of transparency affect stages of evidence building and use at EPA.
Evaluation Of E-Learning Based On Nau (Nielsen'S Attributes Of Usability) According To Students

STMIK Sumedang is one of the high schools that provides e-learning. As many access, there were several problems. After scrutinized, the problem is more inclined to usability, then in this research will be conducted evaluation of the usability of STMIK Sumedang e-Learning. Usability is an aspect of the quality of software that needs to be tested and is a perspective of non-functional needs that have the most important benchmarks and the most fundamental factors in the application, as this perspective can determine the success or failure of an application when used by its users. Nielsen's Attributes of Usability (NAU) is one of the methods of measuring the Usability aspects of an application and will be used in this research. The usability variables to be evaluated are learnability, efficiency, memorability, errors, and user Satisfaction's, with a significance level of 0.1 (10%), respondents amounting to 743 and sample size 111 (df = 109). Overall from a range of values is not very good – excellent, assessment aspects of usability towards STMIK Sumedang e-learning average assessed enough by the user (students) in fulfilling the usability aspects according to Nielsen's Model. It is hoped that suggestions for improvement/recommendation of this evaluation can be considered as guidance in the framework of application development process.
Explaining by Removing: A Unified Framework for Model Explanation

Researchers have proposed a wide variety of model explanation approaches, but it remains unclear how most methods are related or when one method is preferable to another. We establish a new class of methods, removal-based explanations, that are based on the principle of simulating feature removal to quantify each feature's influence. These methods vary in several respects, so we develop a framework that characterizes each method along three dimensions: 1) how the method removes features, 2) what model behavior the method explains, and 3) how the method summarizes each feature's influence. Our framework unifies 25 existing methods, including several of the most widely used approaches (SHAP, LIME, Meaningful Perturbations, permutation tests). This new class of explanation methods has rich connections that we examine using tools that have been largely overlooked by the explainability literature. To anchor removal-based explanations in cognitive psychology, we show that feature removal is a simple application of subtractive counterfactual reasoning. Ideas from cooperative game theory shed light on the relationships and trade-offs among different methods, and we derive conditions under which all removal-based explanations have information-theoretic interpretations. Through this analysis, we develop a unified framework that helps practitioners better understand model explanation tools, and that offers a strong theoretical foundation upon which future explainability research can build.
Multi-Objective Artificial Bee Colony Algorithm for Parameter-Free Neighborhood-Based Clustering

Although various clustering algorithms have been proposed, most of them cannot handle arbitrarily shaped clusters with varying density and depend on the user-defined parameters which are hard to set. In this paper, to address these issues, the authors propose an automatic neighborhood-based clustering approach using an extended multi-objective artificial bee colony (NBC-MOABC) algorithm. In this approach, the ABC algorithm is used as a parameter tuning tool for the NBC algorithm. NBC-MOABC is parameter-free and uses a density-based solution encoding scheme. Furthermore, solution search equations of the standard ABC are modified in NBC-MOABC, and a mutation operator is used to better explore the search space. For evaluation, two objectives, based on density concepts, have been defined to replace the conventional validity indices, which may fail in the case of arbitrarily shaped clusters. Experimental results demonstrate the superiority of the proposed approach over seven clustering methods.
EFFECTIVE TOOLS FOR ORGANIZING EDUCATIONAL ACTIVITIES IN THE NEW REALITIES

Introduction. The introduction substantiates the problems of modern educational practice, the relevance of improving legislation in education, and the search for new approaches and tools for organizing educational activities. Materials and methods. Theoretical and empirical research methods are employed to corroborate the consolidation of the concept of education at the national level; identify the goals, objectives, and directions of modern educational work with children; and reveal effective tools for organizing educational activities in the regional general education system. Results. A set of measures has been implemented at the institutional level to test an exemplary educational program, and conditions have been created for the successful development and implementation of working programs. Conclusions. The main lines for the analysis of the educational program implementation results, methods of obtaining information, evaluation criteria, and key issues that determine the prospects for the educational system development are determined. Keywords: education, risks, directions of educational activity, an exemplary program of education, a set of measures at the federal, regional and institutional levels for the development of the system of educational work with students