Reviewerly/exHarmony huggingface dataset:
CSL Net: Convoluted SE and LSTM Blocks Based Network for Automatic Image Annotation

Due to advancement of multimedia technology, availability and usage of image and video data is enormous. For indexing and retrieving those data, there is a need for an efficient technique. Now, Automatic keyword generation for images is a focussed research which has lot of attractions. In general, conventional auto annotation methods having lesser performance over deep learning methods. The annotation is transformed as captioning in deep learning models. In this paper, we propose a new model CSL Net (CSLN) as a combination of convoluted squeeze and excitation block with Bi-LSTM blocks to predict tags for images. The proposed model is evaluated using the various benchmark datasets like CIFAR10, Corel5K, ESPGame and IAPRTC12. It is observed that, the proposed work yields better results compared to that of the existing methods in term of precision, recall and accuracy.
A Dutch Dataset for Cross-lingual Multi-label Toxicity Detection

Multi-label toxicity detection is highly prominent, with many research groups, companies, and individuals engaging with it through shared tasks and dedicated venues.This paper describes a cross-lingual approach to annotating multi-label text classification on a newly developed Dutch language dataset, using a model trained on English data.We present an ensemble model of one Transformer model and an LSTM using Multilingual embeddings.The combination of multilingual embeddings and the Transformer model improves performance in a cross-lingual setting.
Multi-Level Refinement Feature Pyramid Network for Scale Imbalance Object Detection

Object detection becomes a challenge due to diversity of object scales. In general, modern object detectors use feature pyramid to learn multi-scale representation for better results. However, current versions of feature pyramid are insufficient to handle the scale imbalance, as it is inefficient to integrate the semantic information across different scales. In this paper, we reformulate the feature pyramid construction as a feature reconfiguration process. Finally, we propose a novel detection network, Multi-level Refinement Feature pyramid Network (MRFPN), to combine the high-level features (i.e., semantic information), middle-level feature and low-level feature (i.e., boundary information), in a highly-nonlinear yet efficient manner. In particular, a novel contextual features module (chain parallel pooling) is proposed, which consists of global attention and local reconfigurations. It efficiently gathers task-oriented contextual features across different scales and spatial locations (i.e., lightweight local reconfiguration and global attention). To evaluate significance of proposed model, we designed and trained a robust end-to-end single stage detector called MRFDet by assimilating it into a conventional SSD model, and it achieved better detection performance compared to most recent single-stage objects detectors. In particular, MRFDet achieves an AP of 45.2 with MS-COCO and an improvement in the map of 4.5% with VOC compared to conventional SSD. We are releasing the source code for our proposed model MRFDet, to facilitate the research community.
Chatbot for Information Service of New Student Admission Using Multinomial Naïve Bayes Classification and TF-IDF Weighting

New student admission is a process where prospective students need the information to decide which higher education institution they will enroll.Live chat on the institution website is one of the reliable information sources to find information about the institution.Most higher education institutions have their website but not every single of them has implemented a live chat feature on the website.Live chat requires humans to answer website visitors' questions.However, there are limitations in humans to always be able to respond and provide answers accurately.A chatbot is a machine learning implementation that can be applied to overcome these limitations.Natural Language Processing (NLP) concept can help chatbots translate human language and help the computer understand what humans mean in their language.The machine learning model that is used for classification is Multinomial Naïve Bayes with the help of term weighting using TF-IDF.With the classification model, prospective students' questions can be classified based on their intents, but the model needs labeled questions as the training data.Chatbot with quality training data set and 24/7 service availability makes prospective students' questions can be answered quickly anytime and anywhere.In this research, 1.330 questions were gathered as training data and grouped into 17 intents.More than 90% of questions predicted correctly using K-Fold Cross Validation, but only 65% when the chatbot is tested by website visitors due to less clean and less complete training data set that obviously can be improved in the future.
Perception and Use of OPAC by Users in Academic Libraries in Kwara State, Nigeria

Background of the study: The study investigated the use and perception of Online Public Catalogue (OPAC) by users in academic libraries in Kwara State, Nigeria.&#x0D; Purpose: The study adopted descriptive survey research method were a total number of 203 questionnaires were distributed amongst library users in both selected academic libraries. A simple random sampling technique was used for this study.&#x0D; Method: The descriptive analysis was used to analyze the collected data using frequency counts and simple percentages.&#x0D; Findings: The study revealed that majority of the respondents is aware of the existence and availability of OPAC. Although a very small percent of respondents in Unilorin and Kwara State Polytechnic got their awareness of OPAC through the library. The study also revealed that an average percent of respondents in both institutions can make use of the library OPAC effectively. Based on user’s perception of OPAC, the findings show that majority of respondents highly acknowledge OPAC, well perceived and more preferred to card catalogue. A high percent of respondents admitted that the library OPAC enable them to locate materials quickly on the shelf. However, most of the respondents showed that they are facing some challenges which include poor network services, power failure, poor assistance from the library staff etc.&#x0D; Conclusion: The researchers recommend that the library should create more awareness and effective user education for students on the use of OPAC at various levels to ensure maximum utilization of the library resources.
Mineral resource modelling using an unequal sampling pattern: An improved practice based on factorization techniques

This work addresses the problem of geostatistical simulation of cross-correlated variables by factorization approaches in the case when the sampling pattern is unequal. A solution is presented, based on a Co-Gibbs sampler algorithm, by which the missing values can be imputed. In this algorithm, a heterotopic simple cokriging approach is introduced to take into account the cross-dependency of the undersampled variable with the secondary variable that is more available over the entire region. A real gold deposit is employed to test the algorithm. The imputation results are compared with other Gibbs sampler techniques for which simple cokriging and simple kriging are used. The results show that heterotopic simple cokriging outperforms the other two techniques. The imputed values are then employed for the purpose of resource estimation by using principal component analysis (PCA) as a factorization technique, and the output compared with traditional factorization approaches where the heterotopic part of the data is removed. Comparison of the results of these two techniques shows that the latter leads to substantial losses of important information in the case of an unequal sampling pattern, while the former is capable of reproducing better recovery functions.
Adaptive Multi-Grained Buffer Management for Database Systems

The traditional page-grained buffer manager in database systems has a low hit ratio when only a few tuples within a page are frequently accessed. To handle this issue, this paper proposes a new buffering scheme called the AMG-Buffer (Adaptive Multi-Grained Buffer). AMG-Buffer proposes to use two page buffers and a tuple buffer to organize the whole buffer. In this way, the AMG-Buffer can hold more hot tuples than a single page-grained buffer. Further, we notice that the tuple buffer may cause additional read I/Os when writing dirty tuples into disks. Thus, we introduce a new metric named clustering rate to quantify the hot-tuple rate in a page. The use of the tuple buffer is determined by the clustering rate, allowing the AMG-Buffer to adapt to different workloads. We conduct experiments on various workloads to compare the AMG-Buffer with several existing schemes, including LRU, LIRS, CFLRU, CFDC, and MG-Buffer. The results show that AMG-Buffer can significantly improve the hit ratio and reduce I/Os compared to its competitors. Moreover, the AMG-Buffer achieves the best performance on a dynamic workload as well as on a large data set, suggesting its adaptivity and scalability to changing workloads.
Building Quality Management System For Student Vocational Training Based On Technological Approach

Building a quality management system for training students is aimed at enhancing the training of highly qualified professionals able to work effectively in line with national and international standards, and committed to obtain greater professional development in a knowledge-based economy.Subject to a certain environment, the concept "quality of education" can refer to some endeavors to fulfil the highest quality requirements, the ideal to strive for in academic education, compliance with established educational standards, goals, mission of university and educational programs, the ability of an organization to constantly improve and enhance the educational process.The authors review technological approach applied in the education system and quality management system built thereunder for vocational training of students.Management ensures the quality of vocational training of students through the integration of many components.The system for managing the quality of student training based on technological approach is a constructive means of implementing pedagogical ideas, educational programs, teaching technologies and streamlining the process of student vocational training.Technological approach is considered as a specially organized interaction of all educational agents, aimed at achieving certain learning outcomes.Quality management of student vocational training based on the technological approach embraces diagnostic and operational presentation of expected learning outcomes; diagnostic tools to evaluate the current state and forecast trends in the nearest development (monitoring) of the system; a set of technologies; building of an optimal training model for given specific conditions; feedback mechanism.
Soil quality and metal distribution around stone quarries within Abeokuta, Southwest, Nigeria

Quarrying activities are explored to extract a variety of materials deposited underneath the earth surface. These activities however can potentially impact negatively on soil quality and cause elemental pollution. This study assessed soil quality and distribution of metals in soils around four quarrying sites (PAPA, S&amp;D, TCity and Mile 8) within Abeokuta, Ogun State, Nigeria. Thirty six topsoil samples were collected at distances from quarry gates in September 2019 and analyzed using standard methods. Soil quality and metal concentrations were compared with reference and standards and the degrees of soil contamination assessed using relevant indices. Soil quality reduced with distance from the quarry gates. Similarly, metal concentrations had strong and significant (P=0.05) negative relationships with distance and were higher in soil samples compared to the reference. Moderate contaminations for all metals were observed in soils collected close to the quarry gates soils from the results of the contamination factor index (Cf). However, the results of ecological risk index (Ei) showed that the metal loads in soils currently do not pose any ecological risk.&#x0D; Keywords: Quarry, Soil quality, Metal distribution, Soil contamination, Potential ecological risk
Development of Virtual Lab Media to Improve Student’s Critical Thinking Ability

This study aims to generate media Virtual Lab on the basis of electrical materials that meet the criteria are valid instructional media, practical, and effective .The population in this study was the Airport Electrical Engineering class class XVII semester I, while the research subjects of the validity trial were Unimed physics lecturers and the subjects of the implementation of Virtual Lab learning media were the Airport Electrical Engineering class XVII, totaling 24 people and the Airport Electrical Engineering level III and XIV.46 people .The procedure for developing Media Virtual Lab using the Research and Development Method initiated by Borg and Gall which consisted of research and information collecting, planning, developing preliminary forms of product, preliminary field testing, main product revision, main field testing, operational product revision, operational field testing, final product revision, and dissemination and implementation.The instruments used in this research are validity questionnaires to see the validity of the Virtual Lab media , lecturer and student response questionnaires to see the practicality of Virtual Lab media on basic electrical materials and pretest and posttest instruments to see the effectiveness of Virtual Lab Media .From the research results, it can be concluded that the Virtual Lab Media Development with an average value of 78.76% for media validation results while 78.86% for material expert validation results, both of which are categorized as quite valid and can be used but minor revisions.Practical response of Virtual Lab Media by lecturers with an average value of 86.1% which is categorized as very practical, while by students 82.94% for small groups and 77.33% for large groups which are quite practical.The effectiveness of Media Virtual Lab shows N-Gain with a value of 0.61 which is considered effective on basic electrical materials .
Automatic Modulation Recognition Method Based on Hybrid Model of Convolutional Neural Networks and Gated Recurrent Units

With the application of various wireless communication technologies, the electromagnetic environment has become more complex, and the recognition of signal modulation has become increasingly difficult.In this paper, a hybrid model based on deep learning, which aims to quickly classify received modulated signals and help to plan spectrum resources, is proposed.The model is designed by considering the characteristics of convolutional neural networks (CNNs), global average pooling (GAP), gate recurrent units (GRUs), and other structures.Firstly, signal spatial features are extracted by convolution using a CNN, the dimension of the highdimensional feature map is reduced by GAP, then the signal temporal correlation is extracted using GRUs.Finally, modulation modes are classified in the softmax layer to classify and recognize the modulation modes of the received signal.Experimental results show that the average recognition rate of the model was 60.64% and the maximum recognition rate was 90%.The proposed method not only improves the recognition performance but also enhances the interpretability of the network.
Real-Time Detection of Cook Assistant Overalls Based on Embedded Reasoning

Currently, the target detection based on convolutional neural network plays an important role in image recognition, speech recognition and other fields. However, the current network model features a complex structure, a huge number of parameters and resources. These conditions make it difficult to apply in embedded devices with limited computational capabilities and extreme sensitivity to power consumption. In this regard, the application scenarios of deep learning are limited. This paper proposes a real-time detection scheme for cook assistant overalls based on the Hi3559A embedded processor. With YOLOv3 as the benchmark network, this scheme fully mobilizes the hardware acceleration resources through the network model optimization and the parallel processing technology of the processor, and improves the network reasoning speed, so that the embedded device can complete the task of real-time detection on the local device. The experimental results show that through the purposeful cropping, segmentation and in-depth optimization of the neural network according to the specific processor, the neural network can recognize the image accurately. In an application environment where the power consumption is only 5.5 W, the recognition speed of the neural network on the embedded end is increased to about 28 frames (the design requirement was to achieve a recognition speed of 25 frames or more), so that the optimized network can be effectively applied in the back kitchen overalls identification scene.
Study on the Ability Improvement of Diplomatic Etiquette of Naval College Cadets

To improve the diplomatic etiquette ability of naval college cadets, this article develops study on several forms to improve methods of naval diplomatic etiquette.Firstly, this article introduces the basic meaning of naval diplomatic etiquette.Afterward, it analyzes eight aspects of diplomatic etiquette ability of naval college cadets, including promoting the Chinese culture, improving the understanding of communication, reforming the existing international naval diplomatic etiquette, and so on.Finally, this article discusses the ways to improve the diplomatic etiquette ability of the cadets, including how to strengthen the theoretical foundation of naval diplomacy etiquette, learn the foreign languages, equipment and customs in advance, and reinforce the practical exercise.The conclusion herein can be used as a reference for improving diplomatic etiquette training for naval colleges.
Role of Eye Tracking in Human Computer Interaction

With the invention of computers arises the need of an interface for users and interacting with a computer has become a natural practice. For all the opportunities a machine can bring, it is now a limiting factor for humans and their interaction with machines. This has given rise to a significant amount of research in the area of human computer interaction to make it more intuitive, simpler, and efficient. Human interaction with computers is no longer confined to printers and keyboards. Traditional input devices give way to natural inputs like voice, gestures, and visual computing using eye tracking. This paper provides useful insights in understanding the use of eye gaze tracking technology for human-machine interaction. A case study was conducted with 15 participants to analyze eye movements on an educational website. Visual attention was measured using eye gaze fixations data and heat maps were utilized to illustrate the results.
Problem Of Goal Setting As Condition For Advanced Development

Successful organization of the modern educational process is stipulated by the solution of the "parentstudent -teacher" interaction problem.In the traditional context of using the words "education" and "upbringing", education is understood as the process of intellectual saturation of a person who possesses certain educational competencies being literacy, reading, etc., which enable to judge its content.Education implies the process of assimilating certain cultural and social norms enabling to talk about the formal side of personality development.The semantic factor in the education and upbringing processes in the "parent-student-teacher" system is goal setting, which contributes to a new meaningful interpretation of advanced development in education.Advanced development in education is the development focused not so much on the past and present, but on the future, on anticipating and forming students' knowledge, the ability to work with uncertainty, with the prospects for the future.In the context of the newly emerging trends like digitalization and technologization of education processes, when education is narrowed down to learning, the education and upbringing distance themselves from each other.Education gets stuck on teaching and wastes its sense-forming principle being an activity aimed to create an image of a person.At this new level of their entity, the student drops out of the traditional system "parentstudent-teacher", and the communicative continuum is transformed.Goal setting being a factor in the "parent-student-teacher" system, can contribute to a new meaningful interpretation of advanced development in education.
PEMANFAATAN METODE IMPRESIF TERHADAP PROSES PENGEMBANGAN KARAKTER SISWA

Teaching literature during a pandemic can be an alternative in developing character in students. This research is important to do to see the convergence of performances that are usually watched once, but due to digitalization, it is now easier for viewers to enjoy the performance. This study reveals the role and function of virtual drama staging in character building in children during the pandemic. The research data source is the recording of the virtual performance of Theater Comma entitled "Pandemi" by N. Riantiarno. The approach used is descriptive qualitative. And the method used is descriptive qualitative method. This study uses an objective (approachstructural).The findings found several values of character strengthening, namely religious, honest, responsible, and social care. These four values can be seen from the dialogue between actors to the attitude of the actors in responding to the pandemic. Based on the values of character education found, it shows that virtual performances are able to become a relevant literary medium for planting character education in the distance learning period. Keywords: Teaching Literature, Virtual Performances, Character Education, Structural, Theater Comma
K-Nearest Neighbour and Dynamic Time Warping for Online Signature Verification

Online signatures are one of the most commonly used biometrics. Several verification systems and public databases were presented in this field. This paper presents a combination of knearest neighbor and dynamic time warping algorithms as a verification system using the recently published DeepSignDB database. Our algorithm was applied on both finger and stylus input signatures which represent both office and mobile scenarios. The system was first tested on the development set of the database. It achieved an error rate of 6.04% for the stylus input signatures, 5.20% for the finger input signatures, and 6.00% for a combination of both types. The system was also applied to the evaluation set of the database and achieved very promising results, especially for finger input signatures.