Reviewerly/exHarmony huggingface dataset:
Good Governance, Public Finance, National Security and Economic Growth in Nigeria: A Discursive Explorational Approach

Nigeria is poorly ranked on the global scale of governance indicators (Fashagba and Oshewolo, 2014).The country is currently facing a host of complex security challenges such as violent insurgency, herdsmen hazard, piracy, kidnapping for ransom, attacks on oil infrastructure, organized crime and religious extremists.These threats typically involve irregular forces and are largely societal based.According to Omodia (2012), failure of governance is core to the socio-economic and political development challenges confronting Nigeria and the spate of violence that threatens national security.Security implies protection from danger or other conditions that threaten human life and property.It is in practice to anchor the security of life and property within the sphere of human rights under International Law (Cletus, 2014).Such human rights include Liberty and Security of the person, protection against slavery and servitude, protection against arbitrary arrest and detention.According to the Clarification of United Nations Development Program (UNDP, 2006), the state obligation to respect, protect and fulfill human right is a bench mark for security within any given entity.Governance means the manner in which power is exercised by governments in the management and distribution of a country"s social and economic resources (Ogundiya, 2011).The nature and manner of this distribution makes governance a bad or good one.To Hyden and Agborsangaya (2011), governance is defined as the management of public territory in which state and non-state actors come together to make policy decisions affecting the security and welfare of the citizens.The emerging cases of insecurity in Nigeria are traceable to rebellious groups like Boko Haram and Herdsmen from the North, Niger Delta Militants from the South-South and MASUB from the East.The emergence of Boko Haram and herdsmen insurgents in Nigeria have not only paralyzed the already bastardized economy but threaten our corporate national existence.According to Edeh and Ugwueze (2014), Boko Haram is currently reinforcing the economic comatose of the Northern Nigeria and therefore impoverishing the people the more and making life unbearable for both the indigenes and non-indigenes who perpetually live in fear thereby re-echoing indigenes insecurity situation and forcing many out of the region.
Do long-term foreign currency sovereign credit ratings positively affect bond and equity market efficiency in Africa

This study investigates the weak-form efficiency of long-term foreign currency denominated bonds and stocks in incorporating long-term foreign currency sovereign credit rating announcements in 19 African countries over the period of 1994 to 2014. The results of Ljung-Box Q autocorrelation, runs and variance ratio tests find that sovereign credit ratings do not significantly impact bond market efficiency. In contrast, stock markets show evidence of weak form efficiency implying that long-term sovereign credit ratings positively affect equities market efficiency in Africa.
Newly-Coined Words and Emoticons Dictionary Construction for Social Data Sentiment Analysis

In the co mposition of social networks and social networks services, most of articles are written with writer's personal ideas and emotions within 200 words.Social networks services produce social b ig data and provide vast volumes of data.Social big data has various types of text -centric data, photos, music and videos, and informal data.It is difficult to deal with social big data, sin ce it has rapid changes and volume growth.But, analysis of social big data may accept the online market trust agreement and establish national policies to support the marketing and strategy formulation of the co mpany for marketing and strategy establishment.This paper proposes a new social big data analysis system that uses new-coined words and emoticons for social big data analysis.In this paper, we also construct a new dictionary of emoticons to improve the accuracy of big data analysis related to the public opinion, and to improve the accuracy of emot ional analysis using the existing emotional dictionaries and the newly constructed new emoticons and emoticon dict ionaries at the analysis stage.Especially, the accuracy of social big data analysis could be imp roved by quantifying and analyzing emot ional level about emoticons and new-coined words.This research built a dictionary of emoticons, and used the Naver open dictionary for newly-co ined words.But, newly-coined words that were not included in the Naver open dictionary are added to proposed newly-coined words database.
Pattern Discovering for Ontology Based Activity Recognition in Multi-resident Homes

Activity recognition is one of the preliminary steps in designing and implementing assistive services in smart homes. Such services help identify abnormality or automate events generated while occupants do as well as intend to do their desired Activities of Daily Living (ADLs) inside a smart home environment. However, most existing systems are applied for single-resident homes. Multiple people living together create additional complexity in modeling numbers of overlapping and concurrent activities. In this paper, we introduce a hybrid mechanism between ontology-based and unsupervised machine learning strategies in creating activity models used for activity recognition in the context of multi-resident homes. Comparing to related data-driven approaches, the proposed technique is technically and practically scalable to real-world scenarios due to fast training time and easy implementation. An average activity recognition rate of 95.83% on CASAS Spring dataset was achieved and the average recognition run time per operation was measured as 12.86 mili-seconds.
SMART ATTENDANCE APPLICATION -‘SOLUTION TO PHOTO ATTACKS PROBLEM’

Face recognition is one of the most necessary application of image analysis and has gained significant attention.It has seen wider use in recent times on mobile solutions.Analysis within the field of automatic face platform and in different sorts of technology has been conducted since the 1960s, but it's generally used as an access management.This study is to propose an answer to the matter of security system and might be compared to different photograph attacks in face recognition system by finding pattern in eyes (closed or open) to differentiate system.Recently, it's conjointly became widespread as a difference between a true external body and a photograph.
LIBYA: Budget 2021

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 58, Issue 6 p. 23480B-23481B Policy and Practice LIBYA: Budget 2021 First published: 17 August 2021 https://doi.org/10.1111/j.1467-6346.2021.10114.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume58, Issue6August 2021Pages 23480B-23481B RelatedInformation
Determinants of Innovation across Nigeria Enterprises: Does Size and Region Matter?

Will the ally of size and region (Location) serve a catalyzing ingredient for innovation across enterprises in Nigeria?Interestingly, many enterprises have since deemed it fit to make effort to advance in their operation because their level of innovativeness today might be identified with as the least tomorrow given the level of general widespread extension recorded among other competitors.Hence, the study seeks to address the determinants of innovation across Nigeria enterprises given the interplay of a firms size and region (location) using the Probit regression estimation method in examining the Nigeria Enterprise Survey Data for 2,676 enterprises for the year 2014.Evidence from the study reveals that a firm's region (location) and size significantly influence the firm's innovativeness in their deals of doing business at 0.05 (5%) significant level.Therefore, the study recommends the establishment of inter-link infrastructures that cut across region of the economy in order to facilitate their ability to take up innovative challenges and also the promotion of credit facility scheme (in form of venture capital fund) to help promote the activities of infant firms and existing enterprises, limitations and the further research areas are discussed.
Computational Efficient Method for Denoising of Salt and Pepper Noise for Image Enhancement

Digital Image processing is basically a computer-algorithm which is used to enhance the quality of image to understand the feature of image and exact the meaningful features information from image. Image processing has wider range of algorithms to be applied to the input image and can escape the difficulty as the signal distortion and add noise in input image at the time of processing of images. Noises affect the image visualization and degraded the image quality, sometimes chaotic variation in value of pixel intensity, lighting effect or because of poor contrast, image can’t be used directly because many time interest feature information not received as output that’s one reason image processing is significant for removal of noise from images, so noise removal is becomes trending field in image processing. Median filter method is one of most popular method to eradicate the effect of noise from image and it enhances the image quality to take meaningful feature easily from image. In this paper removing of noise using median filter to enhance the image quality is discussed, also the importance and applications of enhancement technique are covered. Parameter PSNR and MSE is also used to analysis the image quality along with the visualization of image. Simulation results show that Median filter gives good outcome for salt &amp; pepper noise as compare to other filtering method. MATLAB software is used as simulation tool.
Reviews

Deep learning for computer vision: Image classification, object detection, and face recognition in Python, by Jason Brownlee, 2020, Machine Learning Mastery, 563 p., US$0 (eBook). Illustrated Seismic Processing: Volume 1: Imaging, by Stephen J. Hill and Andreas Rüger, ISBN 978-1-560-80361-4, 2019, Society of Exploration Geophysicists, 330 p., US$39 (members), US$72 (nonmembers). Geology: A Very Short Introduction, by Jan Zalasiewicz, ISBN 978-0-198-80445-1, 2018, Oxford University Press, 168 p., US$11.95 (print).
PI, REVISITED

An attempt is made to show how an important mathematical constant (namely Π ), in use for ages, is evaluated computers are used, no doubt, but what is the philosophy behind the program created to carry out the evaluation (to any specified degree of accuracy). The discussion focuses on what exactly is (or are) the cornerstone(s) of such programs.
Use of a Clear Sky Index to Evaluate Solar and Cloud NWP Forecasts

&amp;lt;p&amp;gt;Forecasting cloud accurately is still a challenge in numerical weather prediction (NWP) models. Detailed qualitative evaluation of such forecasts is needed in order to improve the forecasts. Cloud cover is often used for the evaluation but it is not a good metric due to inconsistency in methods for assessing the cloud cover. Global horizontal irradiance (GHI), also referred to as &amp;amp;#8220;global radiation&amp;amp;#8221;, provides an objective and quantitative measure for evaluating cloud forecasts during daytime.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Non-dimensional indices for solar energy resource assessment have been developed in recent years and decades that are very useful. One such index&amp;lt;br&amp;gt;is the clear sky index (CSI), which is the GHI divided by the theoretical GHI during clear sky conditions (e.g. [1,2]). We use the theoretical GHI clear sky model of [3,4], which includes coefficients that account for variable integrated atmospheric water vapour, aerosols and ozone. We have used binned CSI data computed using HARMONIE-AROME NWP forecast data and observations to identify model deficiencies in cloud and to evaluate new model physics options and settings. Sample results include the identification of consistent negative GHI biases under the thickest clouds and positive biases under Stratocumulus clouds. Such results help to pin-point deficiencies in the HARMONIE-AROME NWP model.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;br&amp;gt;[1] Perez, R.; Ineichen, P.; Seals, R.; Zelenka, A. Making full use of the clearness index for parameterizing hourly insolation conditions. Sol. Energy 1990, 45, 111&amp;amp;#8211;114.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;[2] Skartveit, A.; Olseth, J.A.; Tuft, M.E. An hourly diffuse fraction model with correction for variability and surface albedo. Sol. Energy 1998, 63, 173&amp;amp;#8211;183.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;[3] Savij&amp;amp;#228;rvi, H. Fast radiation parameterization schemes for mesoscale and short-range forecast models. J. Appl. Meteorol. 1990, 437&amp;amp;#8211;447.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;[4] Gleeson, E.; Nielsen, K.P.; Toll, V.; Rontu, L.; Whelan, E. Shortwave Radiation Experiments in HARMONIE. Tests of the cloud inhomogeneity factor and a new cloud liquid optical property scheme compared to observations. ALADIN-HIRLAM Newsl. 2015, 5, 92&amp;amp;#8211;106.&amp;lt;/p&amp;gt;
A case study of the link between artificial intelligence and knowledge creation in an emerging technology in China

In Chapter 11, Søberg (2020) explores the development of advanced technical capabilities, in a Chinese firm working in the emerging industry of artificial intelligence, specifically visual recognition and surveillance systems. Using theories from knowledge management, the analysis reveals the essential engagement of customers in new product development, and why their knowledge is needed due to the unclear description of market needs. Hence, this chapter suggests that a pre-linguistic embodiment of tacit knowledge can be found in field tests and prototypes, during knowledge creation. Moreover, that they can be useful tools for externalisation of knowledge for the further development of advanced technical knowledge.
How can Blockchain ecosystems serve SMEs?

Blockchain applications for industrial use present distinct opportunities to SMEs. The chapter aims to identify potential benefits blockchain uptake could bring to SMEs as well as foreseeable challenges that could hinder small businesses from reaping the benefits of blockchain adoption. Findings from the OECD country cases studies on “Blockchain for SMEs and Entrepreneurs” in Israel and Italy provide an in-depth analysis of the characteristics and trends of country-specific blockchain ecosystems and industrial use cases. The chapter also provides an overview of blockchain-related policy and regulation trends as well as policy examples aimed at increasing awareness and supporting blockchain innovation activities beyond financial services.
MOTIVATION AND CAREER DEVELOPMENT AS KEY FACTORS IN THE UKRAINIAN POLICE

Nowadays the issues of being police officer, protection of order and feeling of power are up to the day in our everyday life.Motivating police personnel can be complicated.Supervisors must work hard to ensure officers perform their duties efficiently and effectively.Many factors can negatively affect productivity and cause officers to become complacent, doing the bare minimum necessary.The difficult nature of crime fighting can cause officers to become cynical toward the population as a whole and develop an «us-versus-them» view [3].A negative attitude in police work can lead to feelings of inconsequentiality toward law enforcement goals and either slow or stop internal motivation.Officers who begin their careers with an attitude of «saving the world» can become jaded toward that goal after years of witnessing the worst in people.Constantly observing the aftermath of violent crimes, like robbery, rape,
Research on Effective Teaching Strategies of Basketball General Course for Physical Education Majors in Colleges and Universities in China

Through the methods of literature review, expert interview and field investigation, this paper analyzes the effective teaching and promotion strategies of basketball general course for physical education major in Colleges and universities in China. It is believed that the main problems in the effective teaching of basketball general course of physical education major in China are cognitive bias in effective teaching, ignoring the effectiveness of teaching process, and dissimilation of effective teaching orientation In the problem, this paper puts forward the specific strategies to improve the effective teaching of general basketball course of physical education major in Colleges and universities, that is to correctly understand the effective teaching, pay attention to the effective teaching process, and establish the effective teaching goal orientation, so as to provide enlightenment for peer researchers to explore effective teaching together, and provide reference for peer workers to better understand effective teaching and improve effective teaching efficiency.
Real Time Linguistic Analysis using Natural Language Processing

There are plenty of analysis done on linguistic communication process to develop and improve systems that square measure a lot of human, which will perceive easy directions. There are many research organizations working on different projects of NLP. This paper can function as the premise of connecting likeminded folks primarily based upon their thoughts, their interests the ideas they share. In an exceedingly layman’s language this is able to work on a true time basis, currently primarily based upon the user response linguistic communication process Techniques are enforced and in real time thoughts are matched with someone of vertical having interests and thoughts just like ours so, it might operate like connecting us with a world of our own. This paper aims at providing associate surroundings wherever like individuals move with individuals of their kind in order that they speak solely purposeful and zilch out of context by developing a Natural Language Processing based Linguistic Analysis system.
Bitcoin Mining to Reduce the Renewable Curtailment: A Case Study of CAISO

High energy intensity is an enduring problem for the cryptocurrencies, especially for those based on Proof-of-Work like Bitcoin. Energy demand not only comprises the largest share of the operation cost of Bitcoin mining, but also poses a considerable hindrance to the climate agenda. The present paper explores how renewable energy generation can be availed to address these challenges. The need to curtail excess production of renewable energy to maintain the balance between supply and demand and thereby avoid negative electricity prices opens possibilities for deploying renewables to meet bitcoin energy demand. Situating the Bitcoin mining machines at the generation side of solar and wind is an attractive solution to mitigate both the curtailment problem and the energy intensity problem. Here we present a case study on the California Independent System Operator (CAISO), analyzing the profitability of such a solution. Using 2018 historical data, our simulation reveals that the CAISO system will earn 5.6~48.1 million dollars net profit by selling Bitcoin without holding it. These mining machines will also absorb 50.8%~79.9% of the curtailed energy. The probability making a profit in terms of volatile bitcoin price and mining difficulty is positively correlated with the capacity factor of the mining machines. However, there is a tradeoff between the curtailment usage rate and the capacity factor of the machines. To consume more curtailed energy, the system will need to deploy more mining machines and become more sensitive to the volatility of the bitcoin price and hash rate.
SOCIAL MEDIA: IMPACT ON THE LANGUAGE TRAINING

In the globalized world, when people who have grown up with personal computers are often called digital generation, understating of foreign languages is a prerequisite for successful employment in the labor market and effective business collaboration.The use of various social networking tools has influenced students' everyday life, and language learning is no exception.Popular social media, such as Facebook, Pinterest and YouTube, offer educators the ways to reinvigorate the classroom climate in higher education institution.Without any doubt, social media provide opportunities for students to develop digital skills, multiliteracy practices, to interact in and through the target language, to improve their pragmatic and linguistic proficiency.
Foreword

Weak productive capacities penalize structurally weak and vulnerable economies, including many landlocked developing countries. This penalty is aggravated by the coronavirus disease pandemic, and the global economic crisis that has accompanied it, wreaking havoc on the production structures, trading relationships and domestic livelihoods of these countries. The deep economic shock is compounding mounting damage from climate change, steep drops in international commodity prices and declining trust in global solidarity, threatening to erase the development gains of the last decades. New pathways for building economic resilience and addressing the root cause of vulnerabilities in these countries are desperately needed.
Cognition of a Robotic Manipulator Using the Q-Learning Based Situation-Operator Model

In this article, we have applied cognition on robot using Q-learning based situation operator model. The situation operator model takes the initial situation of the mobile robot and applies a set of operators in order to move the robot to the destination. The initial situation of the mobile robot is defined by a set of characteristics inferred by the sensor inputs. The Situation-Operator Model (SOM) model comprises of a planning and learning module which uses certain heuristics for learning through the mobile robot and a knowledge base which stored the experiences of the mobile robot. The control and learning of the robot is done using q-learning. A camera sensor and an ultrasonic sensor were used as the sensory inputs for the mobile robot. These sensory inputs are used to define the initial situation, which is then used in the learning module to apply the valid operator. The results obtained by the proposed method were compared to the result obtained by Reinforcement-Based Artificial Neural Network for path planning.
A SURVEY OF ADVANCED DEEP MACHINE LEARNING TECHNIQUES IN EMERGENCY HEALTH CARE USING MEDICAL HEALTH RECORDS

The quantity of digital information contained in electronic health records has increased dramatically during the last ten years (EHR).Numerous researchers have discovered that these records may be used for a variety of other purposes as well, including applications in clinical informatics.Additionally, within the same time period, significant advancements in the area of deep learning have been made by the machine learning community.Using EHR data, we examine the existing research on applying deep learning to clinical activities.In this article we will discuss various deep learning techniques used for the classification of electronic health records.