Reviewerly/exHarmony huggingface dataset:
A Conceptual Model for the E-Commerce Application Recommendation Framework using Exploratory Search

The users helped by the search engine for online transactions in e-commerce; nonetheless, there is still a lack of search interest from the user and online shopping intentions.To boost the user's search for product recommendations, use a search engine for the quest but not for purchasing purposes.Existing frameworks have some significant problems in the recommendation technology, such as new product problems, fewer evaluation problems, a vast amount of data, etc.Many e-commerce applications lack a better search experience like an Exploratory search system.This research work aims to create a conceptual model for recommendation systems using exploratory search, to study the behavior of users and the efficacy of exploratory search in terms of the quality of the search results produced.Several machine learning algorithms are used in this research to classify e-commerce products and evaluate the performance of these algorithms.The full-text search mechanism is used to implement an exploratory search system.The exploratory search system is evaluated by three criteria called to look up, learn and investigate.After the experiments and evaluation, it is observed that AdaBoost over decision tree performs better than the other classification algorithms implemented.The exploratory search system satisfies the three requirements that are lookup learn and investigate during the search process.Contributions to this work are to build a conceptual model for the recommendation system through the dataset of user events and finding the implementation of an exploratory search mechanism in an e-commerce application.
AI Based Vision for Blind People

Science and technology always attempt to make human life easier. The people who are having complete blindness or low vision face many difficulties. Blindness can occur because of many reasons including disease, injury or other conditions that limit vision. The purpose of this project is to develop an aid for the blind or the visually impaired people. In this project, we design and implement a smart device which helps the blind. The scene around the person will be captured by using a camera and the objects in the scene will be identified. The earphones will give a voice output describing the identified objects. Not every text content is present in a Braille language so, an effort has also made to convert a text content into an audio format for the visually impaired person. The architecture of the system includes the processor Raspberry Pi, Pi camera, headset and a power supply.The processor collects the frames of the surroundings and convert it to voice output.Softwares like Putty, Python 3.5 and Tensorflow will be used to develop the project.Manual testing will be performed for testing the hardware components used in the system.Whereas, for software testing automated testing will be performed to check the working of the overall software contents.
Single particle entanglement as a tool for generating quantum random numbers

In this work we present a proof-of-concept of a photonic quantum random number generation scheme based on the entanglement between two internal degrees of freedom of single photons. The quantum correlations between momentum and polarization at the single photon level are verified by a Bell test in the CHSH form. The violation of this inequality not only ensures the entanglement, but also provides an estimation of the minimum entropy of the generated sequence. This allows to optimize the application of randomness extractor to obtain an unbiased sequence of random numbers.
Quantifying uncertainty in machine learning models

We'll see why and how it is very important to compute uncertainty in inferential statistics and predictive machine learning models.1) Deep dive in random forestRandom Forest gives us naturally an estimation of the distribution for each sample thanks to the bagging technic.2) Generalisation for regressionThe quantile loss is useful to compute prediction intervals for every regression model. It is however a computationally costly. Certain loss like cosh can help against this con.3) What about classificationIn classification, probability is a measure of the uncertainty... but does every models give us good probabilities ? Let plot some reliability curve to check if we need to calibrate the output with a sigmoid a an isotonic regression !
Towards Building a Computerized System for Modelling Advanced HCC Tumors, in Order to Assist Their Minimum Invasive Surgical Treatment

Hepatocellular Carcinoma (HCC) is the most frequent form of liver cancer, being the fourth leading cause of cancer-related death worldwide. The curative treatment in most cases is the tumor removal from the body (surgery), but more than 70% of HCC patients have advanced tumors and cannot be treated with such procedures. Alternative laparoscopic surgical treatments, such as high dosage radiation-brachytherapy (HDR-BT) or inside-tumor drug release (IDR), are currently researching for tumor size reduction. Our target is to develop computerized methods for assisting the medical robot used in such treatments, to make them safer and more efficient. We build an accurate 3D model of the HCC anatomical context, based on Computed Tomography (CT) images acquired before surgery, putting into evidence the HCC tumor, its position within the liver and the most important blood vessels connected to it. We also highlight, in real time, during surgery, the 2D slice corresponding to the transducer position. In this article, we describe the corresponding software system, focusing on the segmentation and 3D reconstruction techniques, assessed through specific experiments.
Investigação do efeito do material do curso on-line na capacidade de redação dos alunos de inglês como língua estrangeira

The paper aimed to investigate the effect of using online course material on EFL students’ writing ability has conducted. The focus of the study is mainly to discover the writing attitudes and learning problems among students. The study employs a methodological triangulation whereby both qualitative and quantitative methods will be used. The study incorporated three stages. First, the foundation survey and the pretest were regulated to all the samples. Next, in the four-week treatment stage, understudies were obliged to do the two errands in class. The main research tools used in the study are the Students’ Survey Questionnaires and the interview questions. 20 English school majors in a rookie composing class took an interest in the study. The significant discoveries show that understudies made noteworthy change in equivalent word use in the controlled tests and still kept up that learning two months after they finished the web learning units. It was concluded from the correlation of the pretest and posttest papers that the students increased their general composition quality and execution in the utilization of synonymous descriptive words. The students had the capacity impel a few examples for the target expressions of 25 equivalent words with different degrees of achievement. By and large, the exactness rate of incitement was more than 50%.
PENINGKATAN MINAT DAN HASIL BELAJAR TEMATIK DENGAN MENGGUNAKAN MEDIA GAMBAR SISWAKELASI SDIT NURUL IKHLAS PADANG

This study aims to describe the interests and learning outcomes of students by using picture media in learning theme 1 of subtheme 3 in class I SDIT Nurul Ikhlas Padang ". This type of research is Classroom Action Research. The instrument for data collection was obtained through observation of students' interest sheets, teacher observation sheets and learning achievement tests. The results of the study are the first through the use of media interest pictures and student learning outcomes have increased, which can be seen in the observation sheet that has been filled out by the observer teacher where in the first cycle the acquisition of student learning outcomes has increased namely the average value in the first cycle 57 with mastery learning 71% increased to 72.72 in the second cycle with 88% completeness. The conclusion of this research is that through media images can increase student interest and learning outcomes.
Intelligent chatbot assistant: A study of integration with VOIP and Artificial Intelligence

Development and research on Artificial Intelligence have increased during recent years, and the field of medicine is not excluded as a target audience for this top modern technology. Despite new re ...
Underwather shearography – consideratons and first results

Shearography is an optical measurement technique based on the interference between two laterally displaced images of the region of interest. Due to its quasi-equal-path configuration, shearography is robust enough for applications outside the laboratory. In fact, shearography has been successfully used for nondestructive testing in composite materials mainly in the aerospace, boating and, more recently, in the oil and gas industries. There are several demands in the oil and gas industry for nondestructive testing on subsea metallic elements coated with composite materials to prevent or mitigate the effects of corrosion. The present work deals with the underwater shearography for nondestructive testing in metal parts coated with composite materials. The paper begins with considerations about the propagation of light in underwater environments and a discussion on the elements that disturb the measurements with shearography such as changes in wavelength, absorption, dispersion, distortions caused by refraction in the air-glass-water interfaces among others. The different loading possibilities to reveal defects in the tested elements are analyzed: by pressure loading, thermal loading by radiation and thermal loading by induction. Exploratory experiments carried out inside water tanks involving the three loading techniques are presented and discussed. The results are compared and the combinations that led to the best results are emphasized. Finally, future works that involve a fully immersed system for underwater shearogaphy are briefly announced.
Innovating with Language AI

Understanding human language in real world scenarios involves not just natural language processing but also speech, vision, knowledge graphs, user modeling, and other AI techniques. Doing this at Google scale involves planetary-scale cloud computing as well as tiny-scale edge computing. I'll share a behind-the-scenes look at how Google uses Language AI to power its billion-user products, and discuss some of the newer approaches we are developing to make sense of human language. I'll end with our vision to democratize AI and how you can use Google AI in your own work.
Exploring awareness and factors facilitating diffusion, adoption and use of social media in teaching, learning and research by faculty members in Ahmadu Bello University, Zaria

This paper focused on Exploring Awareness and Factors Facilitating Diffusion, Adoption and Use of Social Media in Teaching, Learning and Research (TLR) by Faculty Members in Ahmadu Bello University, Zaria. The objectives of this paper are: To identify the types social media faculty members of Ahmadu Bello University, Zaria, are aware of and to identify factors that facilitate the diffusion, adoption and use of social media in TLR by faculty members in Ahmadu Bello University, Zaria. The researchers used single case study research design for this study. The population of this study comprised all the faculty members including staff in training in the 12 faculties of ABU, Zaria with a total number of One thousand nine hundred and fifty nine (1, 959). The researchers selected participants purposefully who must have had life experiences with using social media in Teaching, Learning, Research. Thus, the researchers used this criterion to select 12 faculty members for the interview, one from each faculty. The researcher employed interview as the instrument for collecting data. The researcher adopted the thematic process of data analysis. It was found out that Faculty members were aware of two types of social media: Everyday life Social Media and Scholarly Social Media. Factors that facilitate the diffusion of social media for TLR are: being technologically savvy (curiosity), social media as a tool for interactions, social media as a tool for collaboration and Interactions among faculty members. Factors that facilitate Adoption of social media for TLR by the faculty members are academic network, official academic gathering, and family members. Factors that facilitate the Use of social media by the faculty members are social media benefit, ease of use and Exposure of faculty members abroad (training) etc. It was concluded that Faculty members in Ahmadu Bello University, Zaria were aware of scholarly social media and everyday life social media. They indicated that diffusion, adoption and use of social media for teaching, learning and research depend on some factors. These factors included curiosity, Academic connectivity like academic colleagues, online forums, students etc. It was recommended that University management should mount training programmes aimed at creating awareness on the academic implication of the two social media types and how best to apply in Teaching, Learning, Research. Training programmes in the form of workshops, conferences and symposium etc. would ensure increased awareness and encourage best practice and Faculty members should endeavor to acquire technology savvy skills as it will help in upstanding social media technologies which will improve Teaching, Learning and Research in the University.
Logics of Preference when There Is No Best

Well-behaved preferences (e.g., total pre-orders) are a cornerstone of several areas in artificial intelligence, from knowledge representation, where preferences typically encode likelihood comparisons, to both game and decision theories, where preferences typically encode utility comparisons. Yet weaker (e.g., cyclical) structures of comparison have proven important in a number of areas, from argumentation theory to tournaments and social choice theory. In this paper we provide logical foundations for reasoning about this type of preference structures where no obvious best elements may exist. Concretely, we compare and axiomatize a number of ways in which the concepts of maximality and optimality can be generalized in this general class of preferences. We thereby expand the scope of the long-standing tradition of the logical analysis of preference.
Hierarchical and Unsupervised Graph Representation Learning with Loukas’s Coarsening

We propose a novel algorithm for unsupervised graph representation learning with attributed graphs. It combines three advantages addressing some current limitations of the literature: (i) The model is inductive: it can embed new graphs without re-training in the presence of new data; (ii) The method takes into account both micro-structures and macro-structures by looking at the attributed graphs at different scales; (iii) The model is end-to-end differentiable: it is a building block that can be plugged into deep learning pipelines and allows for back-propagation. We show that combining a coarsening method having strong theoretical guarantees with mutual information maximization suffices to produce high quality embeddings. We evaluate them on classification tasks with common benchmarks of the literature. We show that our algorithm is competitive with state of the art among unsupervised graph representation learning methods.
Educational Content Management In Information And Learning Environments

The article discusses a new entity for Russian and world educational practice - the diversity of information and educational content and the problem of managing it. We consider the following as a methodology that underlies the study of issues related to the description of models for managing content diversity in information and educational environments: a competency-based approach, well developed in Russian pedagogy; a praxeological approach, less popular, but most adequately consistent with the modern theory of practical-centrism; infological approach, which is only gaining recognition of the pedagogical community in connection with the formation and rapid development of information educational technologies. The article focuses on highlighting the development strategies for the management of the diversity of educational content in the education system that is characteristic of the information society: orientation to the development of ways to obtain relevant knowledge as an attribute of quality of life; diversification of the semantics of the term “education”; reorientation of standardized functional preparation for a paradigm based on the construction of a personalized educational trajectory; the evolution of knowledge into one of the sources of value; formation of education as a defining tool for education and socialization of migrants. It is proposed to use information and educational environments as a tool for managing educational content. Some Russian educational platforms that implement the principles of content management in educational practice are presented.
PSYCHOSOCIAL AND MENTAL HEALTH ASPECTS IN THE FACE OF SOCIAL DISTANCE DUE TO THE COVID-19 PANDEMIC

Introduction: SARS-CoV-2 causes the disease known as COVID-19. One of the most effective ways to control the pandemic is social distancing, which directly affects people's psychosocial and mental health conditions. Thus, the objective of this article was to discuss measures on how to deal with these aspects in the face of social distancing. Outline: Reflection article based on scientific literature, as well as documents from the Brazilian Ministry of Health and the World Health Organization, conducted with a time filter of the last 5 years. Results: It is common, with social isolation, that people harbor negative feelings and emotions. Talking, reading, and watching are ways of improving the situation. Children spend more time at home, needing measures that can better subsidize these moments; the elderly become more anxious, angry, stressed, agitated, requiring more dialogue; and health professionals are more susceptible to these demands due to being at the frontline of facing the pandemic. Implications: Reinforce the importance of distancing and give support to the subjects. Therefore, a remote call center can be created, as well as training professionals to better deal with this personal situation and with other individuals.
ANALISIS PERBANDINGAN ALGORITMA KRIPTOGRAFI METODE DATA ENCRYPTION STANDARD DENGAN METODE ADVANCED ENCRYPTION SYSTEM : STUDI KASUS PADA PT. ONE STANDARD GROUP PTE LTD

The security system within a company is the top priority, one of its application is in web media, where it exist various confidential information in it, such as user information on the company PT. One Standard Group PTE LTD must be kept confidential not to fall into unauthorized parties, therefore a security system to address the information security is needed. The security system of modern symmetric key cryptography algorithms is considered to be able to overcome these problems which are generally divided into two, namely Data Encryption Standard (DES) dan Advanced Encryption System (AES). From the two algorithms, the author makes comparisons to obtain a more efficient algorithm in terms of security and times. The method that the author used in this research is Extreme Programming Research Methodology, with a qualitative methodological analysis technique, and in data collection author uses direct observation and literature study. The system that the author created applies additional security for user information which will be directly stored with the AES method and the DES method and the system will display the processing time of both. The conclusion that the author can achieve from this thesis is AES method cryptographic algorithms are more secure than the DES method because the AES method has double protection, but from the time aspect efficiency, the DES method cryptographic algorithms are more efficient.Keyword: Data Security, Cryptographic, AES, DES
Synchronizing Artificial Intelligence tools with DNA profiling for efficacious Recruitmentin Military Services

Artificial Intelligence permeates in almost every facet of life. In today’s scenario it is making its mark in various functions of the organization. It has also found its importance in HR related activities such as talent acquisition for organizations with respect to the requirements of it using various AI tools. This is made possible due to intelligent filtering tools used upon Big Data. DNA profiling is area of future technological necessity, which generates a complete characteristic chart of a person. This when combined with other information can be of great use in Acquisition process in certain areas. Military and Defense related services have lots of medical and other physiological consideration of candidates involved. There is huge amount of tax payers’ money which is used up by the Government for checking the medical and physical traits of several candidates for the job purposes. We propose a technique which may help in analysis of physical traits of the candidates preemptively which may help to reduce the expenditure of checkups and other recruitment processes. This technique would be to synchronize the DNA profiling with Artificial Intelligence tools for to preemptively filter out the candidates with required physical considerations for the specific job area which is Military/ Defense related job acquisition process. Further experimental proof done in targeted manner is the justification for the hypothesis.
Opportunities and Challenges for Procurement in Big Data and Artificial Intelligence

There are many emerging technologies that are being used and their potentials are being tested in the real world. The paper addresses about how different areas of procurement are getting impacted with AI and big data. Change is inevitable and requires adapting to the changing environment similar to the world of procurement changing at a very rapid rate. During early stages of digitization, a clear view about the potentials of the technology was known, but procurement being so complex, it had always been that sector which did not adapt to the emerging technology. Slowly and steadily even procurement is seen as a sector that could make use of digitalization in order to leverage procurement functions. Procurement is no longer just restricted to the buying and selling and has a strategic role in order to lower the costs and ultimately resulting into more profit for the company. Globalization has taken a toll and as the industriesare increasing rapidly.The entire purchase to pay and source to pay can be managed in a single module and no physical purchase orders and invoices need to be sent to the vendors.This not only saves time but also the efficiency and productivity increase triple folds.
Apache OpenWhisk – Open Source Project

Marek speaking: “Most of my 20+ year IT career has been with server-side Java. It started with Sun Microsystems’ Java when it was a new language used mostly in web page applets in 1995-97. Back in 1996 I started my Java adventure by writing one of the first server-side Java systems creating Web Forums dedicated to the Disaster Recovery in NTT in Japan. Since then plenty of new and old systems were built or migrated to server-side Java and eventually to the cloud.
Points Worth Repeating: Best Blogs of 2019 and Tips for 2020

Looking back over our posts from 2019, we found five that deserved a second look. Among the most popular articles published last year, some focus on ...
Evolution of SSL/TLS Indicators and Warnings in Web Browsers (Transcript of Discussion)

I would like to start my talk with a short thought experiment.