Reviewerly/exHarmony huggingface dataset:
ZS4IE: A toolkit for Zero-Shot Information Extraction with simple Verbalizations

The current workflow for Information Extraction (IE) analysts involves the definition of the entities/relations of interest and a training corpus with annotated examples.In this demonstration we introduce a new workflow where the analyst directly verbalizes the entities/relations, which are then used by a Textual Entailment model to perform zero-shot IE.We present the design and implementation of a toolkit with a user interface, as well as experiments on four IE tasks that show that the system achieves very good performance at zero-shot learning using only 5-15 minutes per type of a user's effort.Our demonstration system is open-sourced at https:
Penerapan E-Modul Berbasis Digital Flipbook Untuk Menanggulangi Penyalahgunaan Narkoba Dan Kenakalan Remaja Di Desa Bedahlawak

At this time the development and association of the younger generation is very free. The development of technology and the era of free trade are supporting factors. In addition, the existence of social media makes everything easier to access and get. One of the negative impacts of this is the increase in juvenile delinquency, drug abuse and deviations committed by other teenagers. This community service activity is carried out by the academic community of KH University. A. wahab hasbullah aims to provide insight into knowledge for teenagers to always be vigilant and not fall into juvenile delinquency or drug abuse and others. The method used in this activity is socialization, as well as mentoring in the form of seminars for teenagers. The results of this activity help the younger generation to always be introspective and not fall into these negative things.&#x0D;
Quantum entanglement demonstrator for public engagement

The Networked Quantum Information Technologies (NQIT) hub was one of the quantum hubs of the first round of the United Kingdom’s flagship scheme, bringing together academia, industry, and government. The Optical Engineering and Quantum Photonics Group at the University of Southampton’s Optoelectronics Research Centre has developed an interactive demonstrator of a key device within NQIT to bring quantum photonics technologies to a wider audience. The system was exhibited at the 2017 UK Quantum Showcase in London to an audience of industry and government. It also featured as part of the Quantum City stand at the 2018 Cheltenham Science Festival, one of the United Kingdom’s leading annual science events.
Distance Learning at University Mastering Modern Technologies

The main goals of the education system are the formation of a versatile, creative personality with a high level of cognitive interest. At present, it is important for society to follow global information processes on the basis of their informational nature. Therefore, the attitude to the types and methods of Education began to change. Informatization of education and the use of information technologies in the educational process are becoming one of the most important issues in the education system. As you know, one of the biggest tasks of today is to master modern technologies. In the article, the authors give an overview of the history of distance learning of the educational process in universities due to the suppression of the epidemic around the world. According to international organizations, the views of Western scientists on online education were studied. In the process of Distance Learning, Microsoft has made sure that it is possible to increase the activity of students in a wide audience using various methods on the platforms «Teams», «Bandecam», «Canva Com», «LMS». When using the Microsoft Teams platform in the learning process, you can name its advantages and disadvantages. The university was able to use various methodological approaches to teaching using information technologies. The effectiveness of distance learning is determined and explained by the pedagogical meaning embedded in it. Distance learning technologies are designed to create an educational space that promotes students' self-determination by organizing elective courses, information work, and profile orientation.
Face Landmark Estimation-based De-identification System

Recent development in deep learning requires col- lecting and refining a great amount of data in various appli- cation areas since the performance of deep learning models strictly depends on the quality of datasets. Various types of datasets exist depending on the architecture or objective of the network. However, as the importance of personal privacy has recently increased, dataset de-identification has attracted increasing attention. What should be emphasized about the performance and privacy of deep learning is a controversial issue among many people. In this paper, we a method of de- identifying only important parts, not the entire bounding box of the face. An important part is the external information of the face. The proposed method is an efficient de-identification method because the loss of pixels is less than that of the bounding box. The external coordinates of the face used a landmark estimation method based on deep learning, which proved that de-identification is possible efficiently with experimental results.
A Study of Content-Based Recognition of Speech Utterance

Abstract: Automated voice recognition is a branch of algorithms and cognitive computing that tries to produce robots which can interact with other folks through speaking. Speaking is a data imply suggesting includes both verbal and psycholinguistic information in addition to paralinguistic data. Emotion is a good example of paralinguistic information transmitted in part through speech. Verbal interaction gets simpler because of the development of technologies that can comprehend paralinguistic information such as mood. In this Cnns circuits' usefulness in language research emotion identification was investigated. Spectrograms with a wide range of frequencies of audio samples remained employed as only a source characteristic for the internet infrastructure The circuits had been educated. to identify speaking patterns provided by performers when expressing a certain mood. We used English-language speech resources to validate and develop our technologies The information used for retraining was expanded by two levels in each database. As a result of this, the dropout strategy was employed to. The genderagnostic, language-agnostic CNN models, as per our findings, achieved the highest degree of accuracy, beat Consequences of elections in the literary, and equalled or even surpassed human performance on benchmark databases. Future study should test the capability of deep learning methods in voice emotion identification using real-life speech data. Keywords: Artificial intelligence, Machine Learning, Speech recognition, Convolutional neural network (CNN)
Correlational study of breast sonography and elastography with histopathology in patients with breast lump

The aim is to study the correlation of Breast Sonography and Elastography findings with histopathological diagnosis in patients with palpable breast lump. This was a prospective study. All patients fulfilling inclusion criteria in Krishna Hospital &amp; Medical Research Centre, Karad were included in the study which was conducted from December 2019 to July 2021. All patients with clinically palpable breast lump underwent breast ultrasound and breast elastography and were correlated with histopathological diagnosis. In the present study, conventional sonography had a sensitivity of 100%, specificity of 87.50%, PPV of 80% and NPV of 100% with overall accuracy of 91.67%. Elastography had a sensitivity of 100%, specificity of 90%, PPV of 83.3% and NPV of 100% with overall accuracy of 93.33%. From the present study I concluded that breast elastography when used along with conventional breast sonography can improve specificity of ultrasonography in differentiating benign and malignant lesions.
Special Issue “Applications of Artificial Intelligence Systems”

Artificial Intelligence, a term that was seen as an obscure subject, only to be studied by mathematicians or computer scientists, without much real-life application, less than 20 years ago, has become a pervasive term in our everyday life [...]
UJI STABILITAS pH DAN MORFOLOGI SEL DARAH MERAH UJI PADA LARUTAN ALSEVER DAN NaCl 0,9% DI UNIT DONOR DARAH PUSAT PMI

The background is generally the red blood cells tested are suspended and stored in Alsever's solution and 0.9% NaCl which is used in various immunohematological examinations to minimize the occurrence of transfusion reactions. During storage, red blood cells undergo changes, especially changes in pH and morphology. The purpose of this study was to determine the difference in pH stability and morphology of the tested red blood cells stored in Alsever's solution and 0.9% NaCl. The research method used is an experimental method by observing changes in pH and morphology of red blood cells that are stored in Alsever's solution and 0.9% NaCl on days 0.3,6,9,12, and 14. The results of this study are differences in pH stability. between those stored in Alsever's solution and 0.9% NaCl with the T-Test test, the p value = 0.00. The difference in the morphological stability of red blood cells tested between those stored in Alsever's solution and NaCl with the Mann Whitney test obtained p value = 0.037. The conclusion in this study is there was a difference between the pH stability and morphology of the tested red blood cells between those stored in Alsever's solution and 0.9% NaCl. That the pH of the tested red blood cells stored in Alsever's solution was stable until day 14 while in NaCl solution only up to day 9 and the morphology of the test red blood cells in Alsever's solution was stable until day 12 and in 0.9% NaCl solution was stable until day 6. Keywords: Alsever, Morphology, 0.9% NaCl, pH, Red Blood Cell Test..
Techno-Pedagogical Skills of Teacher Educators with Special Reference to E-Learning

Abstract: “The art of teaching is the art of assisting discovery.”- Mark Van Doren The term "techno-pedagogy skills" refers to the ability to use technology for pedagogical purposes as well as the ability to integrate technology into the classroom. It is a mixed or hybrid teaching method in which electronic resources or information and communication technology (ICT) are used in the learning process. These skills guide the teaching experience in an effective manner. Technical teaching skills are very much necessary for making the teaching process an enjoyable experience as it will significantly change the teacher's mode of interaction. While technical pedagogy is a boon in the teaching process, and circumstances such as the pandemic have increased the value or importance of these skills as virtual classes replace face-to-face classes, but the truth is that due to lack of knowledge about technical teaching skills, teachers are not using these skills correctly. There are so many reasons which are responsible for this condition. But in the present scenario the knowledge of teachers regarding techno-pedagogical knowledge demands focused attention as it is one of the basic or primary necessities in practicing the skills. This paper presents about the importance of techno-pedagogical skills of Teacher Educators with reference to elearning. Keywords: Techno-Pedagogical skills, Teacher Educators, E-learning
Reddit as a prediction tool for crypto-assets

Cryptocurrencies, such as Bitcoin and Ethereum, have recently become a conversation topic among the general population. This paper will explore the information available in Reddit regarding crypto assets. Unlike other social platforms, Reddit allows analyzing the general population sentiment while conveniently organizing information by topic. We study the benefit of sentiment variables derived from Reddit's crypto forums to forecast volatilities and returns. While volatility forecasts seem to benefit from Reddit sentiment variables consistently, results are not statistically different from a benchmark. In contrast, returns present mixed forecasting results but show statistical differences from the proposed benchmark. We also offer evidence that the Reddit variables gain importance in market-wide and asset-specific events.
Factors Contributing to Learners’ Lack of Self-Confidence in Speaking English

In English language learning, some learners face an issue promoting their speaking skills which is caused by the lack of self-confidence. As a response to this issue, this study is conducted to examine the factors contributing to learners’ lack of self-confidence in speaking English. This study employed a descriptive quantitative design. The data were collected from 147 students of SMAN 2 Lumajang using a questionnaire adapted from CSEFL (Confidence in Speaking English as a Foreign Language). The data were analyzed using descriptive statistical analysis. The findings showed that most of the learners possessed a moderate level of self-confidence, and ability was the most contributing factor to the lack of self-confidence for the majority of the learners. It was suggested that the teachers should create learning environments that promote learners’ self-confidence, for instance, by giving motivation and equal chance to speak in front of the class.
Synchronization of Lean Accounting Alert and Entrepreneurial Sustainability among Micro Firms in Nigeria during Pandemic and Catastrophe: Using Confirmatory Factor Analysis

This study focused on the synchronization of lean accounting alert and entrepreneurial sustainability in micro firms in Nigeria during pandemic and catastrophe era.The time horizon cross-sectional survey was adopted with time frame of 2020-2021 to experiment the alertness of lean accounting by professional accountants.Hence, from the 1875, only 370 were selected because they deem fit for the transformational change on lean adoption.The multi-stage cluster sampling technique was introduced in liaison with systematic sampling techniques to select the appropriate respondents.The instrument was administered, only 354 were credibly retrieved.The instrument was validated on face and content validity, while the internal consistency of the test retest was determined by using Cronbach Alpha coefficient with elimination of error and defect(α =0.888), elimination of waste (α=0.874) and product sustainability (α=0.921).To ascertain the principal component from the threshold the KMO and Bartlett's test were introduced for the sample adequacy and appropriateness of sphericity respectively.The Pearson Product Moment Correlation was utilized for analysis of the two hypotheses with SPSS version IBM 25.From the findings, lean accounting alert influenceproduct sustainability.Based on the findings and conclusion, this study contributes to the knowledge that the practices and process of lean improvement, lean culture and lean thinking are major alertness to improve product sustainability in the micro firms in Nigeria.It could be recommended that elimination of waste, error and defect should be practice with lean process on lean thinking, lean culture and lean improvement.
Mitigating Risk in Financial Industry by Analyzing Social-Media with Machine Learning Technology

A large amount of data is available on Twitter that can be used to manage different types of risks in financial institutions. This paper shows how machine learning algorithms can be applied to analyze large unstructured data and train a model to make a future prediction on tweets to categorize them by risk type and use sentiment analysis to understand the risk type. This model reads each tweet and categorizes them by risk using a specified dictionary and adds sentiment analysis to show the risk type seen in each tweet. Logistic regression used in this research helped to formulate the prediction model. Twitter data from 2019 was used to train and test a supervised machine learning algorithm and once the model started predicting tweets efficiently, it was used to predict twitter data from 2022 in our experimental research. Our experiment confirmed that Twitter data can be used to manage risk with the right type of modeling using machine learning techniques.
A STUDY ON SUSTAINABILITY DEVELOPMENT GOAL INDICATORS FOLLOWED BY NIFTY-FIFTY LISTED COMPANIES IN NSE

The purpose of this study is to determine the relationship between the SDGs and companies. The Objective of this study to find the relationship between the SDGs and Companies, Sustainability Reporting and Verification of Adherence to GRI Indicators. This study relies on secondary data (Annual Reports, Sustainability Reports, NVG Principles). The study includes Nifty Fifty Companies. The research focuses on the theoretical framework of the SDGs, the GRI Indicators, and NVG Principles of these firms. Further, Scoring Methodology was utilized to collect data for the investigation. Then comes Descriptive Analysis of 17 SDGs, Reporting Practices, and EES Distribution. Chi-Square tests was used as statistical tests. The hypothesis was validated using the Chi-Square test, which revealed that there is relationship between the Economic and Environmental Components and their reporting. However, Social Component proved that there is no association between Social Component and its reporting. KEYWORDS: Sustainable Development Goals, Global Reporting Index, NVG Principles, NSE Listed, Scoring Methodology.
Multi-Task Learning Using Gradient Balance and Clipping with an Application in Joint Disparity Estimation and Semantic Segmentation

In this paper, we propose a novel multi-task learning (MTL) strategy from the gradient optimization view which enables automatically learning the optimal gradient from different tasks. In contrast with current multi-task learning methods which rely on careful network architecture adjustment or elaborate loss functions optimization, the proposed gradient-based MTL is simple and flexible. Specifically, we introduce a multi-task stochastic gradient descent optimization (MTSGD) to learn task-specific and shared representation in the deep neural network. In MTSGD, we decompose the total gradient into multiple task-specific sub-gradients and find the optimal sub-gradient via gradient balance and clipping operations. In this way, the learned network can satisfy the performance of specific task optimization while maintaining the shared representation. We take the joint learning of semantic segmentation and disparity estimation tasks as the exemplar to verify the effectiveness of the proposed method. Extensive experimental results on a large-scale dataset show that our proposed algorithm is superior to the baseline methods by a large margin. Meanwhile, we perform a series of ablation studies to have a deep analysis of gradient descent for MTL.
Pengembangan Keterampilan Santri melalui Pelatihan Desain Grafis di Syarif Hidayatullah Cyber Pesantren

Pesantren is a place to learn about religious knowledge, in the modern era students not only master religious knowledge but other skills must be mastered such as graphic design. These skills and abilities will be needed by students in the future, therefore one solution in helping these problems is the holding of graphic design training aimed at new students of Syarif Hidayatullah Cyber ​​Islamic Boarding School. The graphic design training activities carried out were focused on twibbon design training using Corel Draw X7. The implementation stage is the delivery of material, practice, and the last evaluation. The results achieved during the training can be seen from the enthusiasm of the students in participating in the training.
Low-light Instrument Image Enhancement Method Based on Illumination Estimation

The captured low-light instrument images suffer from poor visibility caused by low brightness, blurry details, and noise. These images need to be pre-processed to get high-quality images. Low-light image enhancement isabout improving the visibility of the low-light image. Previous image enhancement approaches have improvedthe quality of the low-light image and achieved some results. However, these methods suffer from the problemof heavy computational burden, and the enhanced images have a noise that shows poor visually pleasing results. In this paper, we present a low-light instrument image enhancement approach based on illuminationestimation to solve these problems simultaneously. YOLOv4 is used to detect the instrument image, which can reduce time consumption. The detection section is cropped as the input image for enhancing an image.The illumination of each pixel is estimated by finding the maximum value in RGB channels. Moreover, adesigned optimization function and Gamma correction are employed to optimize the illumination image as thefinal illumination image. Finally, a bilateral filter is introduced to remove noise. Experiments on the low-lightinstrument image are present to demonstrate the effectiveness of the proposed method and its superiority overthe state-of-the-art methods.
EFFECT OF BANKS MERGER AND ACQUISITION ON THE NIGERIA’S ECONOMIC GROWTH: A COMPARATIVE ANALYSIS OF PRE AND POST PERFORMANCE

Business combination over mergers and acquisitions (M&amp;As) have become global phenomenon to achieve economies of scale and higher productivity. This study examined effect of banks’ mergers and acquisitions on Nigeria’s economic growth prior to and after merger sessions. The study made use of secondary data obtained from Central Bank of Nigeria (CBN) Statistical Bulletin covering the period 1990–2004 for Pre-M&amp;As and 2005–2019 for Post-M&amp;As totaling 30 years. Descriptive statistics and ordinary least square regression were employed for data analysis. The results indicated that in the Pre-M&amp;As era, bank’s capital base, credit granted to the private sector and bank spread positively enhanced economic growth howbeit; bank's gross credit adversely affected GDP. Findings also revealed that Post-M&amp;As era contradicted Pre-M&amp;As period, with all variables showing insignificant and unexpected relationship with economic growth, except credit granted to the private sector. This indicates that banks’ M&amp;As has not positively and adequately impacted on Nigeria’s economic growth during period under consideration. As a result, the study recommends that banks’ regulatory and supervisory framework should be strengthened and healthy competition should be promoted.
Experimental image dataset for validation of the noise-induced bias that affects Digital Image Correlation

The present article shares with the scientific community several image sets used for experimentally validating the noise-induced bias on different Digital Image Correlation (DIC) formulations, as reported in Baldi et al. [1]. These sets are provided with a description of the experimental setup used for image acquisition. The basic idea is to acquire a series of images obtained by rigidly translating the target, where incremental displacement is of the order of a small fraction of a pixel. This condition requires a high-precision control of the target position through the tests. Moreover, the noise content of each image set is modulated using a statistical approach that uncouples the intensity field from the standard deviation. Lastly, the images are acquired with different exposure conditions to analyze the gray tone gradient effect on noise-induced bias.