Reviewerly/exHarmony huggingface dataset:
MEDICAL SENTIMENT ANALYSIS BASED ON SOFT VOTING ENSEMBLE ALGORITHM

Digital information is continuously generated from various sources such as social media, user reviews for services. The processing of this written information to extract user opinions is critical for developing customer satisfaction. In particular, medical services may be improved with customer feedbacks if the user opinions or sentiments are inferred from user reviews. There is an ongoing effort to develop automated software systems to evaluate these customer reviews. Machine Learning (ML) algorithms combined with Natural Language Processing (NLP) techniques are used to assess customer feedbacks. There are many studies related to English language in the literature to evaluate sentiments of user reviews. However, Turkish language needs research and it has abundant search opportunities in terms of sentiment classification. This work develops a soft voting ensemble (SVE) algorithm that combines predictions of Logistic Regression (LR), Random Forest (RF) and Decision Tree (DT) to analyze a newly collected medical review data. The accuracies of sentiment classifications of LR, RF and DT are 90.68%, 89.03% and 85.41%. The sentiment classification accuracy of SVE, combination of three algorithms, is 91.12%. The obtained results are promising for an automated Turkish medical sentiment identification algorithm.
Novel Noise Filter Techniques and Dynamic Ensemble Selection for Classification

Background: Ensemble selection is one of the most researched topics for ensemble learning. Researchers have been attracted to selecting a subset of base classifiers that may perform more helpful than the whole ensemble system classifiers. Dynamic Ensemble Selection (DES) is one of the most effective techniques in classification problems. DES systems obtain to select the most appropriate classifiers from the candidate classifier pool. Ensemble models that balance diversity and accuracy in the training process improve performance than the whole classifiers. Objective: In this paper, the novel techniques are proposed by combining Noise Filter (NF) and Dynamic Ensemble System (DES) to have better predictive accuracy. In other words, a noise filter and DES make the data cleaner and DES improve the performance of classification. Methods: The proposed NF-DES model had been demonstrated on twelve datasets, especially has three credit scoring datasets and a performance measure accuracy. Results: The results show that our proposed model has better than other models. Conclusion: The novel noise filer and dynamic ensemble learning with aim to improve the classification ability are presented. To improve performance of classification, noise filter with dynamic ensemble learning makes the noise data toward the correct class. Then, novel dynamic ensemble learning choose the appropriate subset classifiers in the pool of base classifiers.
A Proposed Architecture to Suspect and Trace Criminal Activity Using Surveillance Cameras

In these recent innovative advances give the chance to utilize a lot of sight information from video content. Hence, this process can be applied to the recognition and the need to guarantee a short reaction time to detect potential crime and follow the character. In this paper, we try to present an architecture and workflow that empowers multi-modular information accumulation and computerizes the discovery of crime-related activities. We have used the existing surveillance camera set up for the observation of criminal activity and follow the personality. The proposed system will suspects the crime activities in run time from the real-world data.
SHORT TEXT TOPIC MODELING WITH EMPIRICAL LEARNING

In the present modern digital era, use of social media has been increasing exponentially.People have started using short text for expressing their thoughts.Social media websites like Twitter, Facebook are generating vast amount of short text at every second that reveals good knowledge of real time information.Extensive research is going on to discover knowledge from it.Short text is very sparse and ambiguous; hence there is a big challenge to find latent topics from it.This can be resolved by using unsupervised machine learning approach referred as topic modeling.This paper covers various topic modeling methods like Latent Dirichlet Allocation (LDA), Non-negative Matrix Factorization (NMF), and Semantics-assisted Non-negative Matrix Factorization (SeaNMF) and their comparative analysis.These three methods have been tested on ABCNews headline dataset, results have been analyzed using average Normalized Google Distance (NGD) score; which is 67.88%, 58.60%, 59.32% for SeaNMF, NMF and LDA respectively.The quantitative result shows that more meaningful and semantically similar words are clustered under each topic by SeaNMF model.
ANALISIS FORENSIK UNTUK MENDETEKSI KEASLIAN CITRA DIGITAL MENGGUNAKAN METODE NIST

Currently, the changes in image quality resulting a low-resolution images, faded colors, and so on. This condition potentially attract irresponsible parties to take advantage of the situation for certain purposes. Nowadays, it is very easy for people to manipulate, change, or delete the original information from a digital image thus cause the authenticity and integrity of the image to be doubted. This study is conducted in a specific objective to prove the authenticity of a digital evidence for analysis by providing detailed illustrations of the role of Digital Forensics in accordance with applicable legal regulations in Indonesia using the NIST workflow. The research flow begins with uncovering the background of the problem, collecting data, making scenarios, applying the NIST method, and making conclusions. The illustration used in the scenario is a video inserted into a digital evidence. The video used in this research is the Cyanide Coffee Case with the suspect Wayan Mirna Salihin, happened in August 16, 2016 which was uploaded by Kompas TV channel on Youtube. The NIST analysis phases used several tools: Exiftools, Forevid, and Video Cleaner. The result indicates that all phases in the NIST method are correlated to each other. The result is specifically very clear in the collection phase. The discovery of hidden information causes the examination and analysis process to be more complex especially the extraction process of digital evidence in the form of images. Indeed, the use of various tools are more helpful in disclosing the existing information. This information can be seen from the results of metadata, hash value, and image sharpness from the analyzed digital evidence.
Dataset on the deposits of the semi-circular rampart around the former Viking settlement Hedeby and its vicinity

Soils and sediments are able to preserve traces of human activity in the form of morphological, geochemical and geophysical properties of materials. Thanks to that the study of these materials may provide valuable information about the formation and functioning of archaeological sites. Materials transported for earthwork construction and their configuration preserve important information on the past landscape development, the anthropogenic transformation of the landscape as well as the process of the fortification formation. The UNESCO heritage site Hedeby was one of the most significant proto-towns in Northern Europe and an important trading center in the Viking Age. The town was surrounded by the semi-circular fortification rampart connected to the Danevirke, the Danish fortification system. Due to its dimensions (maximum height 10 m) and good preservation state, the semi-circular rampart is one of the most prominent features of the area. In this article the data on the physico-chemical analysis of the materials from the cores along a coring transect across the semi-circular rampart are presented. The following properties were determined: pH, weight percentage of gravel, charcoal, artefacts, and bones, loss on ignition, magnetic susceptibility, grain size distribution ≤2 mm, elemental concentrations. The data is valuable for geoarchaeological analysis of the landscape transformation and the earthwork construction at Hedeby including the reconstruction of the process and the techniques used in the Viking Age. Data on the buried soil found underneath the rampart deposits might provide insight into the surface soils characteristics prior to the rampart construction.
Assessment of Banded Iron Formations around Gouap Area as Potential High-Grade Iron Ore (Nyong Serie, Congo Craton - South Cameroon)

The Gouap area is found in the southern part of Cameroon and belongs to the Nyong Series situated NW corner of the Ntem Complex. The assessment of banded iron formations (BIFs) in this area is carried out through rock sampling survey. Samples were analyzed by inductively coupled plasma mass spectrometry (ICP-MS) combined with instrumental neutron activation analysis (INAA) technologies to completely characterize the rocks. The studied banded iron formations show microband texture and granoblastic microstructure. The mineral assemblage indicates that they undergone the metamorphism of greenschist facies conditions. The chemical composition of the Gouap iron formations shows that the major components (99.43%) that are Fe 2 O 3 and SiO 2 indicate the purity of the chemical precipitates . The Gouap iron deposits fall into the group of oxide facies with magnetite as dominant mineral and the most diagnostic fingerprints of the source metals are Ni, Cr and Cu. The Gouap iron deposit displays some light terrigenous input in its geochemistry implying that it belongs to the Algoma- type and indicates that iron formations were deposited in an environment devoid of siliciclastic detrital input. The Gouap BIFs derived from Precambrian mature quartz arenite and Fe-sand that were deposited in an Oceanic Island-arc Margin (ARC) setting under oxic conditions with slow sedimentation accompanied with minor input of anoxic conditions with fast sedimentation. This constitutes a new result for de iron deposits in Cameroon. The overall data of Gouap iron deposits pointing to hydrothermal and Red Sea hydrothermal deposits (RS). They exhibit Low- temperature hydrothermal fluids (< 0.1%) and Seawater, indicating that mixing of seawater and less amount (< 0.1%) of low-temperature hydrothermal fluids (< 200°C) might have occurred during their deposition. Some samples have values that reflect between 1 to 5% of a high-temperature hydrothermal fluid input suggesting that the Gouap iron formations were deposited close to the distal position. The high concentration of Fe 2 O 3(T) in the Gouap iron deposit (average = 63.73 wt%) shows that it has a very interesting potential for exploitation and this iron contents can be classified as high- grade or medium- grade iron ores by global standards, and it fall within the acceptable levels for commercial ores. Gouap BIFs host high- grade siliceous ore with magnetite being the predominant mineral. This also constitutes a new result for the iron deposit in Cameroon.
Controlling 2D Artificial Data Mixtures Overlap

Clustering methods are used for identifying groups of similar objects considered as homogenous set. Unfortunately, analytic performance evaluation of clustering methods is a difficult task because of their ad-hoc nature. In this paper, we propose a new test case generator of artificial data for 2 dimensional Gaussian mixtures. The proposed generator has two interesting advantages: the first one is its ability to produce simulated mixture for any number of components, while the second one resides in the fact that it formally quantifies the overlap rate which allows us to add some complexity to the data. Clustering algorithms and validity indices behavior is also analyzed by changing the overlap rate between clusters.
Ongoing education of math teachers and PISA quality assessment: from professional competence to the mathematical literacy of schoolchildren

The quality of education is a key factor in the social development of the individual, society, and the state. This article is aimed at identifying the theoretical essence of the concept, the “quality of education” in the context of the international PISA comparative study and the ongoing education of math teachers as a factor in the development of students’ mathematical literacy. The diagnostics for interviewing and questioning teachers, students and parents revealed problems and difficulties in teaching and studying mathematics. A key tool was context analysis of the GGTU Center for teachers’ professional development activities. The Ongoing Education Program “Schoolchildren Practical Math Literacy Formation” presented in the article and the author’s teaching manual “Life as a Math Plot” reveal their practical focus on the development of math teachers’ professional subject competence, on schoolchildren’s math literacy development, and, as a result, a general improvement in the quality of education according to the PISA results.
CHALLENGES AND OPPORTUNITIES OF DISTANCE LEARNING DURING COVID-19 IN UAE

The COVID-19 pandemic has affected educational systems not just in UAE, but globally as well, where the total number of 1.725 billion students had been affected by the closure of schools and higher education institutions on April 15, 2020. Due to the characteristics of educational settings in UAE, it has recommended and further adopted the use of distance learning programs and open educational application and platforms that support affected students and families. For educational practices and distance learning in areas that are affected with COVID-19 predicaments, urgently required teaching students in many ways with technology and online platforms under the umbrella of “distance learning” or “remote teaching”. The present research paper endeavor to explore the alternative solutions recommend imparting essential knowledge about COVID-19, its details guidelines, and how educational practices is affected in the areas, such as, UAE. Explore how it can respond to future challenges. The research paper further reviews the present practices in the curriculum and make it more responsive to the learning experiences outside needs of the students to take the responsibility for their learning even beyond the conventional classrooms.
A Study on Online Learning Management System: Implementation of Edmodo-Based Blended English Learning Method

Industrial Revolution 4.0 makes rapid changes in every aspect of a human’s life. One of them is the teaching and learning English which has been affected by technology. It is supported by the fact that English is the number one language used globally. Therefore, Education 4.0 emerges in facing Industrial Revolution 4.0 to increase the education level. By this, it is expected that higher education becomes more reachable than before and a tendency which leads to more international standardized higher education institutions. In these rapid changes, there are two challenges faced by students in higher education institutions: English proficiency and culture transition. Thus, the State Islamic Institute of Ponorogo, as one of developing State Islamic Institutes in Indonesia starts to implement a blended learning system in every course as the solution. The lecturers use a variety of learning management system, including Edmodo. This study used quantitative and qualitative analysis on assessing the effectiveness of Edmodo implementation from the students’ point of view as well as determining the progress, learning engagement, as well as the students’ performance overall. The results showed that Edmodo facilitates student-centered and anytime-anywhere learning. It was also found that it makes the English course administration easier. Moreover, students asked in this study had a favorable opinion toward learning English via Edmodo. However, some disadvantages English and technical problems of using Edmodo in teaching and learning were also discussed in this study.
STUDENTS’ ATTITUDE TOWARDS USING WHATSAPP FOR EDUCATIONAL ACTIVITIES AT FEDERAL UNIVERSITY DUTSIN-MA, KATSINA STATE, NIGERIA

Social networking sites have been so popular among students in Nigerian universities and other parts of the world. They use them for different purposes, patterns and modes. WhatsApp is one of them. It’s a free messenger application that works across multiple platforms like iPhone and android phones. This universal application is being used widely among undergraduate students. They use it to send multimedia messages like photos, videos, audios and documents or simple text messages. It’s clear that class groups created on WhatsApp are used as medium for teaching and learning. This comes in form of communicating with students by nurturing a kind of social atmosphere in the class. It helps in framing dialogue and collaboration between the students and their teachers. This research is a descriptive survey designs. The sample size comprised of 101 undergraduate and postgraduate students who were randomly selected from the different stratified levels of clustered departments. They were derived from the seven faculties of the university. The Research developed and used questionnaire as the study’s instrument. Three (3) research questions guided this study; while the analytical tools were descriptive statistics in form of mean and standard deviation. Other tools employed were t-test and ANOVA by using SPSS version 23. Overall, findings demonstrated high level of attitude towards WhatsApp among the students. It also showed how the students use the application in various modes. The general findings confirmed that WhatsApp is being used as an academic tool for both teaching and learning in Federal University Dutsin-Ma.
An End-to-End Secured Email System using Base64 Algorithm

In this present days, email system has turned out to be the broadly way to exchange information from one person to the other.Traditional email system is a one layer authentication system that is secured by username and password which are not enough to ascertain security.The email is connected through many routers and mail servers on its way to the recipient by becoming vulnerable to both physical as well as virtual eavesdropping by unauthorised person.This leaves a digital papers trail thereby more privacy and confidentiality of sensitive information is required.Encryption is of prime importance when confidential data is transmitted over the network.The system is developed to allow users to encrypt information before it is transmitted over the network.Base64 Algorithm was used for encryption and decryption of the information.This system runs on any device which works on windows operating system platform.The developed system secures the sensitive information sent through email by providing a secure, fast, and strong encryption which makes the mail very difficult for an attacker to interpret while in transmission thus making it resistant to forms of attacks.The various uses of this system in real life and its functionality are explained in this paper.
Портал научной библиотеки как элемент единого цифрового пространства научных знаний

The article considers the functions of the scientific and thematic portal as an element of a common information space. The portal structure includes actual book and magazine catalogs, ready-made electronic databases, libraries of external and internal scientific and information resources, analytical and educational sections. The authors considered the principles of development of a single information space and their compliance with the principles of the new library website, highlighted the development priorities and determined plans for the future.
Methodological issues of education monitoring and evaluation

This research explores the opportunities of monitoring education. The research presents the monitoring as the general methodological basis of education management structure. The research also reveals the aspects of educational approach description or concept of the educational approach. The strategic analysis of an educational or training program is done. The function of monitoring as a necessary theoretical and methodological background to evaluation work is shown here. The research indicates the essence of evaluation as a main strategy of the training program. It showed the evaluation work as applied and strategic ways to examine the added -value and acknowledge the impact of educational or training methods. It shows the evaluation as a strategic analysis to inform practice and assess impact. The research also reveals the monitoring as a deeper level of analysis explores the added value of programs to inform future work and establishes a written record of practice. A separate supervising function of monitoring which practices addition and necessary theoretical and methodological background to evaluation work is shown here.
Library Support for Distance Learning at Colorado Christian University

CCU) is a four-year liberal arts school founded in 1914 as Denver Bible Institute.Its student population currently exceeds 8,400 students (about 3,500 FTE), enrolled in one of two colleges: the on-campus/in-seat College of Undergraduate Studies (CUS-50+ degree programs) and the College of Adult and Graduate Studies (CAGS-80+ degree programs), which offers classes at extension centers and online.The CAGS programs currently represent about 75% of the enrollment.The Clifton Fowler
SANDFOX Project Optimizing the Relationship Between the User Interface and Artificial Intelligence to Improve Energy Management in Smart Buildings

This paper deals with energy efficiency in buildings in order to mitigate the climate change. Buildings are the highest source of energy consumption worldwide. However, a large part of this energy is wasted, mainly due to poor buildings management. Therefore, being accurately informed about consumptions and detecting anomalies are essential steps to overcome this problem.Currently, some software exist to typically record, store, archive, and visualize big data such as the ones of a building, a campus, or a city. Yet, they do not provide Artificial Intelligence (AI) able to automatically analyze the streaming data to detect anomalies and send alerts, as well as adapted reports to the different stakeholders.The system designed in the sandfox project has for objective to fill this gap. To improve the energy management, an innovative system should aim at visualizing the streaming data, editing reports, and detecting anomalies, for different stakeholders, such as policy makers, energy managers, researchers, technical staff or end-users of these buildings.The paper presents the User-Centred Design approach that was used to collect the required needs from different stakeholders. The developed AI system is called sandman (semi-Supervised ANomaly Detection with Multi-AgeNt systems). It processes data in a time constrained manner to detect anomalies as early as possible. sandman is based on the paradigm of self-adaptive multi-agent systems.The results show the robustness of the AI regarding the detection of noisy data, of different types of anomalies, and the scaling.
Post-Quantum Authentication Schemes

Many authentication methods have been proposed to authenticate GNSS and SBAS civil signals in response to signal interference threats. These proposed methods utilize contemporary cryptographic standards. However, quantum computing poses a threat to currently existing authentication schemes that may render them insecure. Thus, it is vital to implement authentication methods that are quantum resistant to protect GNSS and SBAS signals well into the future. This paper briefly discusses the impact of quantum computing on contemporary cryptographic standards. A review of the post-quantum digital signature authentication schemes from the NIST post-quantum cryptography standardization competition is presented. Schemes that are applicable to GNSS and SBAS authentication are then identified. Next, a brief introduction to multivariate cryptography is presented. The paper concludes with a discussion on how the post-quantum schemes can used to authenticate GNSS and SBAS data.