Reviewerly/exHarmony huggingface dataset:
Macroeconomic determinants of balance of payments performance in selected African countries

Abstract Most African countries are open and are still opening up for international trade such that they are signatories to various trade agreements such as the Economic Partnership Agreement (EPA) with the EU, and Forum on China-Africa Cooperation (FOCAC), among others. However, these countries face a common persistent balance of payment deficit challenges, but the existing literature investigates this problem at specific country levels. Meanwhile, African countries are also rapidly transitioning towards economic integration with the establishment of the African Continental Free Trade Area (AFCFTA) to deepen intra-Africa trade. Therefore, for unionized policy proposition purposes, this study seeks to investigate the determinants of the balance of payments performance of African countries as a group based on panel data from 1990 to 2020 for 33 of these countries. For robustness checks, the system-GMM, the Random, and Fixed effects models are employed for estimating the determinants of BOP chosen based chiefly on the MABOP theory. The results show that domestic income, trade openness, and the broad money supply are the critical determinants of BOP performance in Africa. Further, the findings do not confirm the domestic income growth-BOP performance trade-off hypothesis, and an inverted U-shape rather than J-curve phenomenon is observed for Africa relative to the exchange rate. Based on the findings, the study recommends inter-alia that, African countries pursue value-creation-oriented investment, import substitution industrialization, as well as zero central bank budgetary financing policies to improve their BOP performances.
Wireless Communication Network Security System Based on Big Data Information Transmission Technology

This paper establishes a unified perception information transmission model for the difference in the number of cognitive radio users in wireless communication network systems. The model can effectively improve the utilization of spectrum resources. At the same time, this paper introduces a cyclic delay full diversity sensing information coding transmission scheme for the security risks of wireless communication networks. We established a system simulation model to compare performance under different correlation coefficients. The study found that the total interference intensity in the cyclic delay diversity system is lower than that of the frequency division duplex and time division duplex. Its antijamming attack capability also becomes stronger accordingly.
Standardisation of Logistics Customer Service

Purpose: This paper is devoted to the standardisation of customer service in the logistics services market.Its first part focuses on various aspects of defining and optimising buyer service.Next, the focus turns to the benefits and barriers of service standardisation, and at the end of the text, the focus turns to logistics buyer service, understood as the ability of a company's logistics system to meet customer expectations in such categories as lead time, certainty and security of transactions, communication with the customer, and efficiency and convenience of service.The authors have made a comprehensive analysis of customer service as a business process.They have focused on the ways in which customer service is perceived and the factors determining its level.They then evaluated the advantages of standardising logistics service, without ignoring the limitations of implementing this process.Design/Methodology/Approach: The paper uses the method of descriptive characteristics of market phenomena and processes.The professional literature on customer service standardisation was comprehensively searched.Findings: The results of the analyses are of both cognitive and pragmatic value, especially in the context of undertaking work towards the development and implementation of a standardised logistics strategy for customer service.Originality/Value: Standardisation of the customer service process allows for a quicker response to customer preferences, and also makes it possible to design the process in such a way that it has a positive impact on the company's operations and becomes a source of its competitive advantage.Among the many benefits of standardising logistics customer service are increased customer satisfaction, lower staff management costs and a systematic drive to improve the quality of customer service.
Information Needs Matrix as a Tool for Improvement of Customer Service Process in a Manufacturing Company – A Case Study

Purpose:The aim of the paper is to present the concept and analyse the possibility of using the matrix of information needs as a tool improving the process of customer service.Moreover, the paper presents the procedure of its implementation and use on the example of a production company from the furniture industry operating in Poland.Design/Methodology/Approach: The paper uses the concept of case study.It presents the essence of the matrix of information needs as a tool to improve communication between departments in the company.The procedure of implementing this tool in a production company was also presented.Additionally, the paper is based on the analysis of literature concerning information needs and logistics customer service in companies.Findings: The result of the work is an information needs matrix as a tool for improving the effectiveness of the customer service process in a company.The procedure of preparation and implementation of such a matrix was presented on the example of a production company operating on the furniture market in Poland.Other results include the identification of challenges and problems in the implementation process of the information needs matrix.Originality/Value: The described matrix of information needs is a very important tool for improving the effectiveness of communication between departments involved in the customer service process.In this manner, the implementation of the matrix contributes to the improvement of the efficiency of the whole service process.The matrix should be based on a detailed analysis of the information needs of each participant in the process and take into account the specificity of the company.
EDMODO AS ONLINE ASSESSMENT TOOL: TO IMPROVE EFL STUDENTS’ READING COMPREHENSION

The study's objective was to examine if using Edmodo as an online assessment tool can improve students’ reading comprehension of recount text in e-learning. E-learning is considered an effective way to facilitate a better learning experience for students, especially in the assessment aspect. Formative assessment is a critical component of education that enable teachers and students to evaluate and improve their performance. Pre-experimental research with one group pre-test and post-test was applied in this study. The participants in the study were 36 tenth-grade senior high students in Krian, East Java. The instrument was pre and post-test consisting of objective and subjective tests. A paired sample t-test in SPSS 25 was used to analyze the data. The confidence interval of the difference used is 0.05. Therefore, the null hypothesis (Ho) is rejected and the alternative hypothesis (Ha) is accepted if the value of Sig. (2-tailed) is less than 0.05. The result shows that online formative assessment through Edmodo can improve students’ reading comprehension skills. It is clear that Edmodo can serve as a prominent online assessment tool for students to assist them in improving their reading comprehension skills in e-learning. It is recommended teachers should continue to look for alternative platforms to conduct online assessments for e-learning to keep up with modern technological developments.&#x0D; &#x0D; &#x0D;
Research on Front-end of ASV System Based on Mel Spectrum in Noise Scenario

Mel Spectrum is an engineered audio feature that simulates human perception and has been successfully used in various speech and audio applications, making it a versatile frame-level feature. Nevertheless, the Mel Spectrum still needs further improvement. This paper proposes a frontend architecture for ASV systems based on deep neural networks (DNNs) and an improved Mel spectrum. Our architecture retains the simplicity and interpretability based on the characteristics of the Mel spectrum while providing noise immunity and cross-domain robustness. In this paper, we use the output of the studied acoustic feature extractor as the input to the ECAP A- TDNN and complete the training of an ECAPA-TDNN model for 1211 speaker identifications based on the VoxCeleb1-dev dataset. An automatic speaker verification (ASV) system was constructed using a model as a speaker embedding extractor. The experimental results show that the two ASV systems containing the improved Mel spectrum proposed in this paper show significant improvements compared to the ASV systems containing MFCCs in both intra-domain and cross-domain scenarios. On VoxCeleb1-dev and VoxMovies, the EER of the ASV system containing the improved Mel spectrum features––Mel-MACs achieves an improvement of 4.34% and 19.81 % compared to the ASV system containing FBanks and MFCCs, respectively.
Partial Information Decomposition via Deficiency for Multivariate Gaussians

Bivariate partial information decompositions (PIDs) characterize how the information in a "message" random variable is decomposed between two "constituent" random variables in terms of unique, redundant and synergistic information components. These components are a function of the joint distribution of the three variables, and are typically defined using an optimization over the space of all possible joint distributions. This makes it computationally challenging to compute PIDs in practice and restricts their use to low-dimensional random vectors. To ease this burden, we consider the case of jointly Gaussian random vectors in this paper. This case was previously examined by Barrett (2015), who showed that certain operationally well-motivated PIDs reduce to a closed form expression for scalar messages. Here, we show that Barrett's result does not extend to vector messages in general, and characterize the set of multivariate Gaussian distributions that reduce to closed-form. Then, for all other multivariate Gaussian distributions, we propose a convex optimization framework for approximately computing a specific PID definition based on the statistical concept of deficiency. Using simplifying assumptions specific to the Gaussian case, we provide an efficient algorithm to approximately compute the bivariate PID for multivariate Gaussian variables with tens or even hundreds of dimensions. We also theoretically and empirically justify the goodness of this approximation.
Improving Uyghur ASR systems with decoders using morpheme-based language models

Uyghur is a minority language, and its resources for Automatic Speech Recognition (ASR) research are always insufficient. THUYG-20 is currently the only open-sourced dataset of Uyghur speeches. State-of-the-art results of its clean and noiseless speech test task haven't been updated since the first release, which shows a big gap in the development of ASR between mainstream languages and Uyghur. In this paper, we try to bridge the gap by ultimately optimizing the ASR systems, and by developing a morpheme-based decoder, MLDG-Decoder (Morpheme Lattice Dynamically Generating Decoder for Uyghur DNN-HMM systems), which has long been missing. We have open-sourced the decoder. The MLDG-Decoder employs an algorithm, named as "on-the-fly composition with FEBABOS", to allow the back-off states and transitions to play the role of a relay station in on-the-fly composition. The algorithm empowers the dynamically generated graph to constrain the morpheme sequences in the lattices as effectively as the static and fully composed graph does when a 4-Gram morpheme-based Language Model (LM) is used. We have trained deeper and wider neural network acoustic models, and experimented with three kinds of decoding schemes. The experimental results show that the decoding based on the static and fully composed graph reduces state-of-the-art Word Error Rate (WER) on the clean and noiseless speech test task in THUYG-20 to 14.24%. The MLDG-Decoder reduces the WER to 14.54% while keeping the memory consumption reasonable. Based on the open-sourced MLDG-Decoder, readers can easily reproduce the experimental results in this paper.
A Bayesian Motivated Two-Sample Test Based on Kernel Density Estimates

A new nonparametric test of equality of two densities is investigated. The test statistic is an average of log-Bayes factors, each of which is constructed from a kernel density estimate. Prior densities for the bandwidths of the kernel estimates are required, and it is shown how to choose priors so that the log-Bayes factors can be calculated exactly. Critical values of the test statistic are determined by a permutation distribution, conditional on the data. An attractive property of the methodology is that a critical value of 0 leads to a test for which both type I and II error probabilities tend to 0 as sample sizes tend to ∞. Existing results on Kullback-Leibler loss of kernel estimates are crucial to obtaining these asymptotic results, and also imply that the proposed test works best with heavy-tailed kernels. Finite sample characteristics of the test are studied via simulation, and extensions to multivariate data are straightforward, as illustrated by an application to bivariate connectionist data.
Evaluation of Talent Training Model Taking into Account the Knowledge Recognition Algorithm of Multiple Constraint Models

In the current talent model analysis, the phenomenon occurs such as serious errors, low efficiency, and poor accuracy. Based on this, a talent training model evaluation method is proposed based on multi-constraint model knowledge recognition algorithm. The knowledge recognition algorithm of the multiple constraint model is used to establish a talent training mode evaluation based on the knowledge recognition algorithm of the multiple constraint model, and the mode weight value is used to adjust the connection weights of the knowledge recognition algorithm of the multiple constraint model. The proposed knowledge recognition algorithm of the multiple constraint model is used to analyze the data index weights of the medical professional talent model in detail, to establish the appraisal model of the talent training. The model can effectively complete the evaluation and analysis of the comprehensive ability of medical professional talents. When using the classifier for training, 76% of the data feature dimensions can be selected for dimension reduction, so as to improve the imbalance problem under the training sample. The characteristics of the various constraint models designed in this paper can be tested by using the classifier. Finally, the experimental analysis results show that the application of the knowledge recognition algorithm of the multiple constraint model to the training mode of medical professionals can significantly enhance the accuracy of evaluation. It has certain reference significance in personnel training.
Fine-grained Web Service Trust Detection: A Joint Method of Machine Learning and Blockchain

Current website defacement detection methods often ignore security and credibility in the detection process. Furthermore, with the gradual development of dynamic websites, false positives and underreports of website defacement have periodically occurred. Therefore, to enhance the credibility of website defacement detection and reduce the false-positive rate and the false-negative rate of website defacement, this paper proposes a fine-grained trust detection scheme called WebTD, that combines machine learning and blockchain. WebTD consists of two parts: an analysis layer and a verification layer. The analysis layer is the key to improving the success rate of website defacement detection. This layer mainly uses the naive Bayes (NB) algorithm to decouple and segment different types of web page content, and then preprocess the segmented data to establish a complete analysis model. Second, the verification layer is the key to establishing a credible detection mechanism. WebTD develops a new blockchain model and proposes a multi-value verification algorithm to achieve a multilayer detection mechanism for the blockchain. In addition, to quickly locate and repair the defaced data of the website, the Merkle tree (MT) algorithm is used to calculate the preprocessed data. Finally, we evaluate WebTD against two state-of-the-art research schemes. The experimental results and the security analysis show that WebTD not only establishes a credible web service detection mechanism but also keeps the detection success rate above 98%, which can effectively ensure the integrity of the website.
FANET Experiment: Real-Time Surveillance Applications Connected to Image Processing System

The major goal of this paper is to use image enhancement techniques for enhancing and extracting data in FANET applications to improve the efficiency of surveillance. The proposed conceptual system design can improve the likelihood of FANET operations in oil pipeline surveillance, and sports and media coverage with the ultimate goal of providing efficient services to those who are interested. The system architecture model is based on current scientific principles and developing technologies. A FANET, which is capable of gathering image data from video-enabled drones, and an image processing system that permits data collection and analysis are the two primary components of the system. Based on the image processing technique, a proof of concept for efficient data extraction and enhancement in FANET situations and possible services is illustrated
The Influence of Service Innovation, University Reputation on Student Satisfaction: Academic Culture as a Mediator at Universitas Khairun

Education is one of the driving forces for progress in the global community, one of which is through the emergence of innovations. With innovations in various fields of science and knowledge, changes have emerged that can positively impact people's lives. Higher Education, as one of the places of development of science, is a very appropriate place to develop innovations, both in the technological and social fields. On the other hand, changes in people's mindsets and behaviors demand changes in higher education institutions. The rapid development of science, supported by technological advances, demands changes in education and teaching patterns, including in higher education. With information disclosure and existing social and technological changes, science can develop further and more rapidly if the education system can adjust to the changes. This study used a survey method with the distribution of questionnaires. The population of the study was students of Khairun University. Sample takers with non-probability sampling method, by convenience sampling. The analysis method used in this study used Smart PLSVersion 3.0 The results showed that out of 10 hypotheses, five hypotheses were accepted, and five hypotheses were rejected.
Harnessing The Internet for Inclusive Development: Evidence from Spatial Panel Data Analysis in Indonesia

Technology utilization is often considered one of the main drivers promoting inclusive development. As a form of technology utilization, whether using the internet can promote inclusive development has been a concern for researchers and policymakers. Considering geographical connectivity characteristics, we examine the effects of internet penetration on inclusive development by applying spatial econometric models and using data from 34 provinces in Indonesia from 2015 to 2020. This study reveals that encouraging the internet penetration can significantly improves the inclusive development in a province. However, the increase of internet penetration leads to the decrease of inclusive development in neighboring provinces. The digital divide among provinces in Indonesia can be attributed to this phenomenon. This study also indicates a strong positive spatial correlation of inclusive development. Our findings point to the need for policies to promote people's use of the internet to achieve more benefits from development, balance the digital development to reduce the harmful effects of the digital divide, and consider the spatial aspects when making policies to promote inclusive development.
Pengembangan Video Pembelajaran Berbasis ICARE (Introduction, Connection, Application, Reflection, dan Extension) untuk Meningkatkan Hasil Belajar Siswa Kelas VIII di SMP N 2 Sungai Tarab

This study departs from student learning at school, namely the lack of awareness of students in participating in mathematics learning and the lack of student involvement in learning. The various characteristics of students make many students who do not understand the material from learning mathematics. When learning online, students only receive learning through LKPD, without explanation by the teacher. Students prefer the material in mathematics learning they can see and they visit. The purpose of this research is to produce a valid, practical, and effective ICARE-based learning video. This study uses development research methods. This research consists of 3 stages, namely the definition stage, the design stage, and the development stage. The definition stage is carried out to define the needs in the learning process and collect various information related to the product to be developed. Furthermore, the design stage aims to design learning videos. The last stage of development is to develop learning videos that have been designed that are valid, practical, and effective. The results showed that the designed learning video was valid with a validation result of 78.45%. Then the ICARE-based learning videos have been practically used with the practical results of 16 students of class VIII SMP N 2 Sungai Tarab amounting to 61.175%. In addition, ICARE-based learning videos have been effectively used based on students' responses to learning, namely students where the percentage is 81.4%. Student learning outcomes increased with the N-Gain category of 0.67% with sufficient criteria.
Developing Audio Visual Media in Teaching Recount Texts for the Tenth Grade Students of Madrasah Aliyah

This study aims to develop audio-visual media in learning recount text for grade 10 MAN and to find out the level of validity of the media that has been developed. The lack of available media and students' disinterest in the learning process, which makes them less engaged in class, are the driving forces behind the development of learning media audio-visual. This research uses development research using 4D models. This research was conducted in three stages, namely 1) definition which consists of front-end analysis, student analysis, material analysis, and concept analysis. 2) design which consists of making draft storyboards and editing media. 3) development, namely the stage to get validation from experts. The results of this study indicate that the learning media was developed in the recount text material got an average score of 86.5% with very valid criteria. This means that this product is worthy of being tested to become a learning video in recount texts material.