Reviewerly/exHarmony huggingface dataset:
Analysis of the Silaba Method in Beginning Reading Activities for Class 1 at Banjarsari 01 Public Elementary School

Background: Beginning reading is one of the most basic skills for students and as a tool to find out the meaning that has been learned in learning at school, beginning reading is one of the activity programs specifically designed for students who have just entered elementary school. The silaba method is a syllable method that presents words into syllables and then assembles syllables into words with the aim that students who are unable to read words can read words.&#x0D; Purpose: This study aims to determine whether the silaba method can improve the beginning reading activities of grade 1 students at SDN Banjarsari 01.&#x0D; Design and methods: This research uses a qualitative descriptive method, which is a qualitative descriptive method. The approach used in this study is a qualitative approach. This research was conducted at Banjarsari 01 Elementary School, Banjarsari Village, Ciawi District, Bogor Regency. The instrument used in this study was an interview guide instrument. The technique used in this study was a data collection technique, which in this study used data collection in the form of observation, interviews and documentation, the data analysis technique used in this study is an interactive data analysis technique in conducting data analysis with a model according to Milles and Huberman.&#x0D; Results: The results of this study indicate that the silaba method is a suitable method to be applied in beginning reading activities because it greatly facilitates students in reading skills for grade 1 students at SDN Banjarsari 01”. This silaba method also facilitates teachers in learning activities. The media needed by the teacher in this silaba method is quite simple and also easily understood by all students. Beginning reading for grade 1 students using the silaba method meets the indicator criteria for the achievement of students' reading activities.
Assessing the Conformity to ISO27001 Security Policy of Information Systems Policies of Universities in the SADC Region

It is very important for universities to devise strategies for realising their mandate and one of those strategies is to leverage on information systems for improved service efficiency and realising business goals.This is bearing in mind that organisational strategies determine which information systems to implement, and which policies guide the use of the Information Systems.Universities these days rely heavily on ICT resources for the core teaching and research activities.The need for clear IS policies and procedures are therefore needed for universities to be successful in their mandate.A lot of universities these days spend time and resources creating their business processes, strategies and policies and passing it through their different structures for approval.However, there is no clear evidence that the policies are visible to the intended audience.This paper therefore investigates the online visibility of IS policies of Southern African public universities in 15 countries in Southern African Development Community (SADC).Region and the conformity to ISO27001 standards of the IS policies.These universities are selected from those with membership of the Southern African Regional Universities Association (SARUA).
BearCare Rechargeable Walnut Wearable Smart Thermometers

Biomedical Safety & Standards 53(15):p 110-111, September 01, 2023. | DOI: 10.1097/01.BMSAS.0000947168.44572.15
Study on development model and governance strategy of informal phenomenon in typical countries of sub-Saharan Africa

Informality is a typical feature of sub-Saharan African countries.It not only provides income and living conditions for low-income groups, but also restricts the sustainable development of national economy and living environment to a large extent.Under the concept of building a community of shared future for mankind, research on governance around informality is of great significance for reconfiguring the development environment of contemporary countries and cities in sub-Saharan Africa.According to the differences in the main causes of informal development in sub-Saharan African countries, this paper selects four typical countries, Ghana, Kenya, South Africa and Zimbabwe, to analyze the development process and main characteristics of informal development.Finally, based on the perspective of the "Belt and Road" Initiative, this paper puts forward corresponding governance strategies for the informality of sub-Saharan Africa from three aspects: the joint construction of overseas industrial parks between China and Africa, the planning cooperation between China and Africa, and the private assistance provided by China to Africa, so as to deepen China-Africa cooperative relations and promote the building of a community with a shared future for mankind.
Measuring Student Behavioral Engagement using Histogram of Actions

In this paper, we propose a novel technique for measuring behavioral engagement through students' actions recognition. The proposed approach recognizes student actions then predicts the student behavioral engagement level. For student action recognition, we use human skeletons to model student postures and upper body movements. To learn the dynamics of student upper body, a 3D-CNN model is used. The trained 3D-CNN model is used to recognize actions within every 2minute video segment then these actions are used to build a histogram of actions which encodes the student actions and their frequencies. This histogram is utilized as an input to SVM classifier to classify whether the student is engaged or disengaged. To evaluate the proposed framework, we build a dataset consisting of 1414 2-minute video segments annotated with 13 actions and 112 video segments annotated with two engagement levels. Experimental results indicate that student actions can be recognized with top 1 accuracy 83.63% and the proposed framework can capture the average engagement of the class.
Improving Myanmar Image Caption Generation Using NASNetLarge and Bi-directional LSTM

The main objective of this paper is to improve the automatic Myanmar captions by learning the contents of images using NASNetLarge and Bi-LSTM model. Describing the contents of an image is a complex task for machine without human intervention. Computer Vision and Natural Language Processing are widely used to tackle this problem. This paper proposed a deep learning-based Myanmar image captioning system which used a NASNetLarge feature extraction model of CNN as an encoder and a deep Recurrent Neural Network (RNN) with Bi-directional Long Short-Term Memory (LSTM) as a decoder. For corpus construction, we created and annotated the Myanmar image captions corpus (consists of over 40k Myanmar sentences), which is based on Flickr8k dataset. Furthermore, two different types of segmentations such as word segmentation level and syllable segmentation level are studied in text preprocessing step. In this work, the proposed Bi-directional LSTM model is compared with LSTM, GRU as well as the baseline model. Experiments on the updated dataset is presented that all of our models using syllable segmentation give higher and comparable BLEU scores than word segmentation for Myanmar image captioning system. NASNetLarge with Bi-directional LSTM model using syllable segmentation approach achieved the highest BLEU-4 score 40.05% which is 12.5% better than word segmentation in this work and 15.67% BLEU-4 score better than our previous work.
FEATURE SELECTION FOR ARABIC MISPRONUNCIATION DETECTION BASED ON SEQUENTIAL FLOATING FORWARD SELECTION AND DATA MINING CLASSIFIERS

Feature selection process is used to reduce the feature vector length and identify thediscriminative features. Many acoustic-phonetic features including Mel-Frequency CepstralCoefficient (MFCC), Energy, Pitch, Zero-crossing, spectrum were tested individually for Arabicmispronunciation detection using three classifiers; Random Forest, Bayesian classifier, and BaggedSupport Vector Machine (SVM). The results for Bagged SVM were better than the other twoclassifiers. Top three individual features with highest accuracies were identified for each isolatedArabic consonant. To validate the results, a modified form of Sequential Floating Forward Selection(SFFS) process was used. Results showed that MFCC along with its first and second derivatives,energy, spectrum, and zero-crossing were the most suitable acoustic features for Arabicmispronunciation detection system. The proposed approach provided an average accuracy of 94.9%which was better than the previous best 92.95% for Arabic consonants.
IDENTIFYING COMPLEMENTARY CORNER DETECTORS FOR CORRECT IMAGE PIXELS CLASSIFICATION

Classification of digital image content is mainly done by identifying low level imagefeatures such as corners and edges. The literature shows variety of algorithms for the identification ofcorner and non-corner pixels, important for objects’ identification and image segmentation. However,all of these algorithms produce different results for same data and therefore, suitable for limitedapplications. This paper proposes a hybrid solution of combining complementary corner detectionalgorithms to improve image pixels’ classification. This has been done by identifying the bestdetection algorithm for corner points with small and large angles and producing a hybrid algorithm bycombining the latter two. Results have shown that Harris detector combined with Global and LocalCurvature Points (GLC) improved the detection rate by 28% in synthetic images, but 50% in realimages whereas, the combination of Shi’s detection algorithm with GLC enhanced the detection rateby 25.9% in synthetic images and 123% in real images, showing a significant improvement.
ANEXPOSITIONANALYSIS OF FACIAL EXPRESSION RECOGNITION TECHNIQUES

This studycompared the technique such as Gabor-wavelet filter banks and LocalBinary Patterns (LBP) that were commonly used for facial expression recognition.Broad experimentalphases were designed to analyze the accuracy and efficiency of each state of art techniques regardingfacial expression recognition. A close analysis of the Receiver Operating Characteristics (ROC) andoverall accuracy of the results for well-known facial databasesrevealedthat the LBPbased extraction offacial expression features was the most efficient and effective technique.
AN AVERAGE-BASED APPROACH FOR INITIAL CENTROID SELECTION IN KMEANS ALGORITHM

The underlying research work was focused on one of the standard k-means issue ofinitial centroid selection. An average based approach was used for avoiding random clusterinitialization. The experiments of this study showed that the results obtained with proposed methodwere better and consistent. It was concluded that the proposed method had less classification error,reduced total number of iterations and took less execution time than random initialization method.
CAN MULTIPLE MODELS IMPROVE BAYESIAN'S PERFORMANCE? AN INVESTIGATION USING MCNEMAR'S TEST

Machine learning algorithms have been widely used for classification purposes in a number of research domains; however, very few researches paid any attention to statistically validate the performance of these algorithms for different data. This paper attempted to study the Naïve Bayes algorithm’s performance for dataset of different sizes. Furthermore, a known theory has also been investigated, that building multiple models such as Bagging, Boosting and Stacking tend to improve a classifier’s performance. The analysis has been performed using McNemar’s test; a well known nonparametric statistical test in the medical analysis domain. Results showed that not all ensemble methods work as expected and therefore, needs to be selected carefully. Moreover, the use of McNemar’s test appeared to be simple, but gave statistically valid results.
INFORMATION COMMUNICATION TECHNOLOGIES FOR IRRIGATION MANAGEMENT SYSTEMS: AN EMPIRICAL INVESTIGATION

With the advancement in information communication technology ICT and its introduction in the field of agriculture, thecommunity has to shift from conventional ways to technology oriented solutions. In this paper, a mapping study researchtechnique was adopted to identify evidences related to irrigation systems developed for efficient use of water. The studyfindings showed that proposed solutions were quite advance, expensive and were largely used by agriculture scientistrather than farmers. Therefore, simple and efficient ICT tools were required to address farmers’ requirements andadoption of such solutions to be evaluated in real environments. In case of Pakistan, situation was not very different dueto low digital literacy rate. Therefore, proposed smart solutions for irrigation require thorough evaluation by farmers.
SELECTION OF DISCRIMINATIVE FEATURES FOR ARABIC PHONEME’S MISPRONUNCIATION DETECTION

Pronunciation training is an important part of Computer Assisted Pronunciation Training (CAPT) systems. Mispronunciation detection systems recognized pronunciation mistakes from user’s speech and provided them feedback about their pronunciation. Acoustic phonetic features plays a vital role in speech classification based applications. This research work investigated the suitability of various acoustic features: pitch, energy, spectrum flux, zero-crossing, Entropy and MelFrequency Cepstral Coefficients (MFCCs). Sequential Forward Selection (SFS) was used to find out most suitable acoustic features from the computed feature set. This study used K-Nearest Neighbors (K-NN) classifier was used to detect the pronunciation mistakes from Arabic phonemes. This research selected the set of most discriminative acoustic features for each phoneme. K-NN achieved accuracy of 92.15% for mispronunciation detection of Arabic Phonemes
The digital twin application of the installation for electrochemical water activation in the educational process

The issues of developing a digital twin of an installation for the electrochemical activation of water using the Trace Mode 6 SCADA system are considered. Keywords digital twin, electrochemical activation of water, control object, regulation, automation, transfer function, education
The cinematography of the novel “Sasha, hello!” Dmitry Danilov

The implementation of aspects of literary cinematography in Dmitry Danilov’s novel “Sasha, hello!”, which was analyzed using contextual, structuralist methods, the method of holistic analysis of a literary text, is considered. For the analysis, the concepts of “literary cinematography”, “audiovisuality”, “edit”, “plot”, “chronotope”, “eye” and “look”, “image of the author”, “reader-viewer” are used, the specifics of cinema as a fact of culture. It is substantiated that literary and cinematic codes are intertwined within the framework of this work. The specificity of the implementation of the principle of audiovisuality in the text is considered. It is revealed that the text is built according to the assembly principle. To construct the plot, the writer uses, among other things, emphatically cinematic plot. At the same time, the emphasized visibility of history, the orientation towards the creation of visible spaces allows the writer to create a specific absurdist narrative. The use of the vocabulary of the “Kino” group and the inclusion of the image of the author in the form of a conditional director-screenwriter transform the very status of a literary text. This makes it possible to present a literary work as an analogue of a motion picture, while actualizing the interactive moment, including the reader-viewer in the unfolding of the text. The materials of the study and its conclusions can be used not only to analyze other works by D. Danilov, but also in the analysis of modern domestic and world literature in the context of literary cinematography and the relationship between literature and cinema.
The Needs Analysis in Developing Trig-GO App For Trigonometry Learning: A Qualitative Approach

The rapid development in the world of technology and communication has contributed directly to the teaching and learning process in schools.Therefore, a paradigm shift towards learning methods in the education system needs to be implemented to meet the educational aims of the 21st century.This is due to the current methods of delivery in teaching and learning are still conventional.Therefore, this study aims to develop Trig-GO apps for mathematics in secondary schools by focusing on the topic of trigonometry.The development process of this application is guided by the model of Dick, Carey and Carey.This paper describes the design and development of Trig-GO apps prototype based on Design and Development Research (DDR) methods and approaches.The findings of the study indicated that a prototype of the Trig-GO application has been developed.The results of the development of the application prototype were evaluated through qualitative methods.The data was obtained from five experienced teachers and six students via observations, interviews and document analysis.Therefore, the results of the analysis showed that the Trig-GO application prototype developed need improvement.Thus, this also will give impact to the quality and production of the application prototype.It is expected to assist students in solving trigonometry questions at the highest level.The development of this prototype application is intended to assist teachers in providing teaching aids that can be used in the teaching of trigonometry through a digital approach.
Deposit Money Banks and Corporate Social Responsibility in Nigeria: Sectoral Patterns and Trends

This study examines trends and patterns of Deposit Money Banks’ Corporate Social Responsibility (CSR) to various socio-economic sectors in Nigeria. Using a dataset of 10 years, 2004-2014, and based on simple descriptive analysis, the study demonstrates that DMBs in Nigeria spend more on social empowerment than in more productive areas that would better the livelihood of the citizenry. DMBs’ preferences for social sectors are largely informed by their drive to protect their interest defined in terms of profit. However, lack of a policy guiding and regulating CSR activities generally in Nigeria is responsible for DMBs biased CSR activities and for lack of diversification. The study, therefore, recommends that Nigeria should design a CSR policy framework as a guiding principle for all CSR activities in the country. It is only through this that the corporate world would be tamed to invest their CSR in more productive sectors that would better the livelihood of their host communities and the country at large.
Efficient Mobile Sequential Recommendation Using Backward Path Growth

The goal of mobile sequential suggestion is to give a taxi driver a route that connects a number of pick-up locations so that they are more likely to pick up clients while spending less money on gas.In essence, a significant barrier is this problem's tremendous difficulty of the computation..In this research, we offer a unique dynamic programming-based strategy with two distinct stages-offline pre-processing as well as online search-to tackle the mobile sequential recommendation issue.From a list of pick-up spots, various candidate sequences are pre-calculated in the offline step.Based on the cost function's noted iterative feature, a backward incremental sequence creation technique is suggested.In order to efficiently minimize the search space for candidate sequences, an incremental pruning approach is simultaneously applied during the sequence generating process.The produced possible sequences are also subjected to a batch trimming technique to exclude some subpar sequences of a specified length.At the online stage, our technique can effectively select the best driving route for an empty taxi from the left candidate sequences because the pruning efficacy increases as the sequence length increases.Moreover, our approach can deal with the issue of finding the best route when there is a destination limitation or a maximum cruise distance.Experimental findings on actual and artificial data sets demonstrate that our strategy outperforms state-of-the-art approaches in regards of both pruning ability and efficiency.Hence, in practical applications, our strategies may be used to successfully handle the issue of mobile sequential recommendation with several pick-up places.
Voting algorithm into CBIR: a review

Collectiveness is becoming nowadays the trend and the ubiquitous notion available in almost recent introduced informatics smart systems like: collective intelligence tied to bio-inspired solutions and reactive multi-agent systems. In the context of collectiveness and collective decision-making, voting algorithm is an important alternative helping to achieve better accuracy and performance. As any other scientific field, CBIR has taken profit of many recently introduced techniques and methods including voting algorithm. In this paper, we talk about voting algorithm into CBIR through quoting its different utilisation with various operations and sub-operations over the different CBIR components such as ranking, re-ranking, feature extraction and representation, feature selection, clustering and classification. Although that the algorithm is the same in its processing mode, the different utilisation contexts lead to different versions especially regarding the considered resources and targets. The paper, presented as a review, allows then collecting and organising the different works adopting voting algorithm, with its different versions, into CBIR field, and discussing the performance and the efficiency of the algorithm in the different considered contexts.
Performance Analysis of Encryption Capabilities of ARM-based Single Board Microcomputers

In the few years since the Raspberry Pi was released in 2012, countless microcomputers based on the ARM architecture have been introduced.Their small size, high performance relative to their power consumption, and the ability to run the popular Linux operating system make them ideal for a wide range of tasks. Information security is an area of particular importance. Different encryption and encoding algorithms play an important role in almost all areas of information security. However, these algorithms are very computationally intensive, so it is important to investigate which microcomputers can be used for these tasks, and under which trade-offs. The performance of ten different microcomputers is investigated and presented for the application of common symmetric and public-key encryption and decryption, digest creation and message authentication protocols, such as RSA, AES, HMAC, MD5, SHA. Reliable encryption requires the generation of reliable (pseudo)random numbers (Cryptographically Secure Random Numbers, CSRN), and microcomputers based on ARM SoCs usually have hardware implemented (pseudo)random number generators. The applicability of the random number generat er generators. The applicability of the random number generators of different microcomputers are investigated and presented; test methoods are described , and recommendations are made.