Reviewerly/exHarmony huggingface dataset:
Corruption in Sub-Saharan Africa - An Impediment to Economic Growth

Sub-Saharan Africa is faced with many challenges.It is a region bulging with resources but cursed with incredible political and economic greed.With a vast ethnic diversity and an often misconstrued cultural lifestyle, which puts the region on the marginalization line.From a historical context, the impact of colonialism has haplessly set the environment for low leadership standards.The background setting for Sub-Saharan Africa's economic underdevelopment is uninhibited corruption that exists within Sub-Saharan African societies.This institutional corruption takes a triangular causecultural, economic and political; each, together with so many other factors threaten Sub-Saharan Africa's socio-economic development.
Knowledge Discovery for Scalable Data Mining

The scalable diverse data and increasing levels of complexity in engineering and management science have given a boost to Data mining technology. The purpose of the proposed research is to evaluate the rule-based technique to develop solutions for analyzing customer Post Purchase behavior through kn
PENGEMBANGAN SISTEM PEMBELAJARAN BAHASA JEPANG BERBASIS ANDROID

In this study, the authors built a system for developing Japanese language learning based on Android. The expected benefits of this research are helping users to master Japanese. The method used in this study is the prototype method. The research begins by designing the Unified Modeling Language (UML) and Activity Diagrams. Then it is implemented into the Java Java programming language. Based on the results of the study, the author has succeeded in developing a Japanese language learning system at the elementary level to help elementary, middle and high school students and the Makassar community learn Japanese through the application. This application is designed to be easy to use for various ages. The results of this study were taken based on answers from 171 questionnaires conducted on students in the city of Makassar.
UTILIZATION OF EDUCATION MANAGEMENT INFORMATION IN DECISION MAKING

Purpose of Study: The undeniable fact that information at this time has been viewed as a very potential resource. Infor- mation is the only source needed by a leader of an educational institution. Information can be processed from other sources that are influenced by very complex organizations and owned computer devices.&#x0D; Methodology: Information processed using a computer can be used by an organizational leader and an individual with expertise as a means of communication and problem solving, as well as valuable information in the decision making the process.&#x0D; Results: In general from the results of research that researchers do indeed the combination of human resources and infor- mation technology applications that are tried to apply have been done. But this is not an easy matter, of course, depending on the focus of the development of management information systems individually sees the needs that are needed now.&#x0D; Implications/Applications: After studying and analyzing about the utilization of education management information sys- tem in decision making hence writer concludes that; first, decision making needs good information, second, irrelevant information will cause wrong judgment in making decision, third, the main basis of framework of information system utilization in taking decisions all information presented by the information system should be aimed at supporting certain phases of the decision-making process; fourth, the utilization framework of management information systems in decision making can also be used to assess an ongoing reporting system, fifth, decision making in education is an important part that should be done well by managers or other officials.
Suitability Analysis of Reservoir’s Location using GIS Based SPI Index (Case Study: Bodri Kuto Watershed)

Drought in some regencies of Central Java Province in 2015had disrupted the role of Central Java as a national rice buffer. Theimplementation of reservoir construction program is often constrained onland status issues so that construction implementation takes precedenceover locations that are state land. As directed by WMO to apply the SPImethod in monitoring the drought level worldwide, this study conductdrought index analysis point in Bodri Kuto Watershed using 25 rainfallstations. Drought distribution and drought-vulnerability mapping locationsare implemented by spatial interpolation. The result shows that the peak ofdrought occurred in 2006-2007 and 2015 with an average SPI value of -1.04 to 0.4 (dry - normal). The wet years occurred in 2001 and 2010-2011with an average SPI range of -0.72 to 2.93 (slightly dry - very wet). Theresult of the suitability assessment of the location of the existing andplanned reservoir shows that out of 33 reservoirs there is 6 reservoir (18%)which is highly suitable, 6 reservoirs (18%) ‘suitable’ while 21 otherreservoirs (64%) less suitable. The planned reservoir-construction programneeds to adjust the priority sequence of handling by considering suitabilityto drought-vulnerability locations in addition to criteria.
Investigation of the Blockchain’s Influence on Traditional Banking: Challenges and Opportunities

New technologies is constantly becoming more and more important for our dynamically changing society, and it occupy greater importance of nowadays' financial sector.This paper focuses on the investigation of the Blockchain and its impact on traditional banking in a qualitative way.The theoretical part of the research presents general overview, brief technical operating principles, main risks, and opportunities of the decentralized networking.The second part examines key properties, main limitations, pros and cons of the Blockchain as well as wider applicability in the financial sector based on experts' evaluation.The results of the expert evaluation provides core records about bank weaknesses and key aspects of the Blockchain influence for financial sector in conformity with 32 professionals.Findings of the research are very relevant while technologies are emerging enormously.Bank collaboration (and not the competition) with fintech is indispensable since both have strengths and weaknesses.However, new technologies, especially peer-to-peer computing, continually gains attention (positive or negative) from the researchers, media, and public.Methods used in the research are: scientific literature analysis, statistical data analysis, comparative analysis, and expert evaluation.
Research on the Function of Music in College Education

College students are the hope of national development and future. College education is an important position for college students to grow and grow up. Music is an indispensable artistic existence in College education. The cultivation of college students has become a problem that colleges and universities must face. Their new characteristics and ideas have brought new challenges to the education of colleges and universities. As the most active and energetic college students of the new generation, their training is not only related to their all-round development, but also directly affects the international competitiveness and development strength of countries in the 21st century. Therefore, it is an urgent and necessary direction to explore the new work of higher education. And music plays an extremely important role in shaping the personality charm of modern college students and their growth and success.
Analysis of Committee Selection Mechanism in Blockchain

The Committee Selection Mechanism can select multiple users of blockchain network to execute a consensus algorithm, such as PBFT. In order to guarantee two properties, the mathematical form of the mechanism is relatively limited. Further, if the mechanism is used in open network, it will bring about an increase in efficiency, but it will reduce the security and practicability of the blockchain network.
Reinforcement Learning Models for Abstractive Text Summarization

Abstractive text summarization is an active research topic in Natural Language Understanding. We live in a digital world where the information for every topic in Internet is increasing considerable, and users would benefit by generating summaries. Summaries are categorized in the following: summary generated through extractive methods and summary generated through abstractive methods. Abstractive methods are highly complex, due the fact that generates an abstract summary consisting of ideas or concepts listed in the documents but are repeated or interpreted with different words or phrases (models that are not restricted to selecting and rearranging phrases from the original documents). Most of today's tasks in Natural Language Processing (NLP) are performed with semi-supervised or supervised learning models. In this research we are looking to perform the text summarization using a new architecture that take advantage of Pre-trained models and Reinforcement Learning (RL). The goal of the research is to extend the summarization to multiple datasets at the time of training to generate summaries. The evaluation is performed on the CNN/Daily Mail, New York Times and Wikihow datasets.
Implementation of IoT System Using Blockchain With Authentication And Data Protection

Blockchain allows users and data providers to ensure authentication, authorization and data validity with proper multi-key exchange authentication for user identity and hash key for Blockchain so that the data is not just stored but also validated each time the user access. In this paper, we apply ZeroKnowledge proof to a Strong rooms using RFID Card reader and Camera module IoT systems to prove that a prover without disclosing information such as public key enhances the anonymity of Blockchain.
A Comparison of Techniques for Sentiment Classification of Film Reviews

We undertake the task of comparing lexicon-based sentiment classification of film reviews with machine learning approaches. We look at existing methodologies and attempt to emulate and improve on them using a 'given' lexicon and a bag-of-words approach. We also utilise syntactical information such as part-of-speech and dependency relations. We will show that a simple lexicon-based classification achieves good results however machine learning techniques prove to be the superior tool. We also show that more features do not necessarily deliver better performance as well as elaborate on three further enhancements not tested in this article.
A new phase retrieval algorithm with pure generalized three-step phase-shifting under matrix norm processing

Phase-shifting interferometry (PSI) is one of the most effective techniques in imaging a phase specimen, in which the phase retrieval is a basic and significant process. A new phase retrieval method based on the matrix norm algorithm in PSI is proposed in this paper. In this algorithm, the value of phase shift can be determined by three different matrix norms of the intensity difference between two phase-shifted interferograms, and then the phase can be retrieved. Neither the iterative calculation nor the extra measurements of other parameters are necessary on account of this algorithm which only requires three phase-shifted interferograms. The feasibility and accuracy of this algorithm are demonstrated by the simulated results. Experimentally, the generalized phase shift can be realized by a simple device which adjusting the angle of glass accurately. It is found that this algorithm has a good application prospect in the field of dynamic imaging.
Validating the Conceptual Framework with Exploratory Testing

The Small and Medium Enterprises (SMEs’) in the IT industry plays a major role towards the growth of country’s economy. SME makes a substantial contribution towards development of the country in the form of GDP and it is widely recognized around the world. SMEs are dependent on software to accomplish their objectives and maintain survivability and sustainability in their businesses, but they often face many challenges due to various factors. Most of the SME’s aim to produce valuable software in a short duration of time, and the traditional method of software development is not viable to provide satisfactory answer with regards to scope, time and resources they need and hence the quality of the product is not guaranteed. Though several approaches towards testing are available, adopting Exploratory testing has so far not been investigated in the context of SME, where software quality is often associated to business-critical values. In this research study, a conceptual framework using Exploratory Testing (ET) has been developed and it is validated by using Partial Least Square Structural Equation Modelling (PLS_SEM).
Hadamard Matrix Guided Online Hashing

Online image hashing has attracted increasing research attention recently, which receives large-scale data in a streaming manner to update the hash functions on-the-fly. Its key challenge lies in the difficulty of balancing the learning timeliness and model accuracy. To this end, most works follow a supervised setting, i.e., using class labels to boost the hashing performance, which defects in two aspects: First, strong constraints, e.g., orthogonal or similarity preserving, are used, which however are typically relaxed and lead to large accuracy drop. Second, large amounts of training batches are required to learn the up-to-date hash functions, which largely increase the learning complexity. To handle the above challenges, a novel supervised online hashing scheme termed Hadamard Matrix Guided Online Hashing (HMOH) is proposed in this paper. Our key innovation lies in introducing Hadamard matrix, which is an orthogonal binary matrix built via Sylvester method. In particular, to release the need of strong constraints, we regard each column of Hadamard matrix as the target code for each class label, which by nature satisfies several desired properties of hashing codes. To accelerate the online training, LSH is first adopted to align the lengths of target code and to-be-learned binary code. We then treat the learning of hash functions as a set of binary classification problems to fit the assigned target code. Finally, extensive experiments demonstrate the superior accuracy and efficiency of the proposed method over various state-of-the-art methods. Codes are available at https://github.com/lmbxmu/mycode.
In pursuit of good governance for the energy industry blockchain

This paper interprets the principles of good governance and corporate governance in the context of distributed ledger technologies, namely blockchain, analyzing specifically how these principles apply to a blockchain-enabled energy market. With blockchain, governance becomes decentralized and automated, creating a new, tech- nical bureaucracy. However, a programmed decision tree does not inevitably produce a digitized democracy and a functional marketplace. While blockchain governance decisions have been predominantly technical, they increasingly embroil legal, moral, cultural and even philosophical considerations. As a result, governance is increasingly recognized as a critical challenge in the future development of blockchain-enabled marketplaces. Future, multidisciplinary research by lawyers, engineers, political scientists and philosophers should venture further into develop- ing good governance principles for blockchain, focusing on equity and inclusion.
Data mining of the best spectral indices for geochemical anomalies of copper: A study in the northwestern Junggar region, Xinjiang

Abstract Hyperspectral remote sensing allows sampling at high temporal resolutions as well as rapid and non-destructive characterization of a wide range of mineralization, enabling identification of element content through spectral features. It provides data for prospecting in areas without sufficient geochemical data, and thus is of vital significance in prospecting for ores in such regions. However, approaches for remotely sensing elements are still lacking, particularly for element content. In this study, a level analysis of Cu content via spectral indices in the northwestern Junggar region, Xinjiang, was conducted. Based on four levels (0–100 ppm, 100–1000 ppm, 1000–10,000 ppm, and >10,000 ppm) of Cu content and corresponding spectral reflectance, simple and useful spectral indices for estimating Cu content at different levels were explored. The best wavelength domains for a given type of index were determined from four types of spectral indices by screening all combinations using correlation analysis. The coefficient of determination (R2) for Cu was calculated for all indices derived from the spectra of rock samples and was found to range from 0.02 to 0.75. With sensitive wavelengths and a significant correlation coefficient (R2 = 0.63, P
Construction for Searchable Encryption with Strong Security Guarantees

We present a construction for searchable symmetric encryption (SSE).We consider a wide range of attacks and hardness assumptions and fulfill the strongest security requirements.The "standard" privacy requirement against searchable encryption is message indistinguishability under an adaptively chosen keyword attack (IND-CKA2).We consider to protect the data and the keyword(s) together, i.e. privacy of the data is not considered as a separate problem (as the latter is typical in research papers).Beside the CKA model, we consider also the adaptively chosen trapdoor attack (CTA).Against active attacks (such as swapping attack) we add integrity protection for the (data, keyword) pair.By guaranteeing existential unforgeability (EU) for trapdoor keys we give protection against Keyword Guessing Attack (KGA).Attacks via searching for patterns in the database is prevented by randomized keyword encryption and trapdoor generation.Our construction is secure in the standard model of computation assuming bilinear groups with the widely used Symmetric eXternal Diffie Hellmann (SXDH) assumption.
Improving Students Speaking Ability Through Debate in The Classroom ( A Case Study for Students at Second Years Students’s of SMAN 3 Kota Bima in Academic Year 2017/2018)

This study aims to investigate the improvement of speaking ability through debate in the classroom and to investigate the students’s response toward the use of debate in teaching speaking at SMAN 3 kota Bima in academic year 2017/2018. In this study adopted experimental research design with method of collecting data used test and questionnaire, while technique for analysing data in this study based on quantities through data gained in the t-test formula. After analysing the data. It found the mean score of post-test by experimental research was higher than mean score of post-test by control research. Deviation score of post-test experimental class is 12 and control class is 5,93 and the square of deviation score of experimental class ≥ the square of deviation score of control class (1509 ≥ 287,87). It indicates that the treatment was succesful, more over significance value of the t-test also was higher than of the t-table (3,27 ≥ 2,021 = 95% and 3,27 ≥ 2,704 = 99%). The level of significance is 0,05% and 0,01% with degree of freedom (df) 58. It’s mean that Ha is accepted and Ho is refused. Not only research the treatment progress in experimental class and t-test in this study but also more response in using debate method in the classroom through questionnaire which have significant result 82,67% by respondents. This study concludes that debate method can improve students speaking ability in the classroom and has very positive response from students.
Proposal Hybrid CBC Encryption System to Protect E-mail Messages

Email is one of the most commonly utilized communication methods. The confidentiality, the integrity and the authenticity are always substantial in communication of the e-mail, mostly in the business utilize. However, these security goals can be ensured only when the cryptography is utilized. Cryptography is a procedure of changing unique data into a configuration with the end goal that it is just perused by the coveted beneficiary. It is utilized to shield data from other individuals for security purposes. Cryptography algorithms can be classified as symmetric and asymmetric methods. Symmetric methods can be classified as stream cipher and block cipher. There are different operation modes provided by the block cipher, these are Cipher Block Chaining (CBC), Output Feedback (OFB), Cipher Feedback (CFB) and Electronic Code Block (ECB). CBC used to complex the cryptographic systems, by using Initialization Vector (IV), Xoring, and encryption with specified key over chain of blocks, but CBC is vulnerable to chosen plaintext attack because the IV is static and vulnerable to chosen ciphertext attack because the encryption method with the key are static. This paper introduce a proposed E-mail messages encryption systems , the proposal based on modified CBC mode operation hybrid with some of techniques exploited in the encryption such as RADG, DNA, RNA and a suggested permutation methods. The proposed modifications applied on the CBC are generate IV randomly, generate key randomly, and propose encryption method, these modifications proposed to avoid the attacks that CBC is vulnerable to.
SemBleu: A Robust Metric for AMR Parsing Evaluation

Evaluating AMR parsing accuracy involves comparing pairs of AMR graphs. The major evaluation metric, SMATCH (Cai and Knight, 2013), searches for one-to-one mappings between the nodes of two AMRs with a greedy hill-climbing algorithm, which leads to search errors. We propose SEMBLEU, a robust metric that extends BLEU (Papineni et al., 2002) to AMRs. It does not suffer from search errors and considers non-local correspondences in addition to local ones. SEMBLEU is fully content-driven and punishes situations where a system's output does not preserve most information from the input. Preliminary experiments on both sentence and corpus levels show that SEMBLEU has slightly higher consistency with human judgments than SMATCH. Our code is available at http://github.com/freesunshine0316/sembleu.
Development of a Multi-Disciplinary Database of Cuneiform Tablets &amp;#x2013; an Improvement of 3D Models and Data Re-use

This contribution describes a digitized cuneiform tablet collection based on a complex database architecture that integrates several scientific domains of data obtained from various types of analyses. The system enables creating 3D enhanced digital models, coupling data from science and humanities to pose complex queries. Attention is also paid to the possibilities of re-use of the acquired data.
Fuzzy Logic Applied to Inflation Control in the Nigerian Economy

In this research work, a fuzzy logic system for inflation control in Nigerian economy is presented. The system consists of four (4) major components which include; the Knowledge base, the Fuzzification, the Inference engine and Defuzzification. Knowledge base were developed based on the discussion with the domain expert and observations of the Nigerian economy. Mamdani's fuzzy inference engine were used to infer data from the rules developed. This resulted in the establishment of some degrees of membership functions of input variables on the output. The methodology allows for High, Low, Yes and No to be applied in order to get the required result. Gaussian membership function was employed to evaluate the degree of participation of each input parameter and the defuzzification technique used in this work is Centriod of Area. Fuzzy logic system has been developed as an alternative to the traditional methods, in order to control inflation in the Nigerian economy.