Reviewerly/exHarmony huggingface dataset:
Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers

A discriminatively trained neural net classifier can fit the training data perfectly if all information about its input other than class membership has been discarded prior to the output layer. Surprisingly, past research has discovered that some extraneous visual detail remains in the logit vector. This finding is based on inversion techniques that map deep embeddings back to images. We explore this phenomenon further using a novel synthesis of methods, yielding a feedforward inversion model that produces remarkably high fidelity reconstructions, qualitatively superior to those of past efforts. When applied to an adversarially robust classifier model, the reconstructions contain sufficient local detail and global structure that they might be confused with the original image in a quick glance, and the object category can clearly be gleaned from the reconstruction. Our approach is based on BigGAN (Brock, 2019), with conditioning on logits instead of one-hot class labels. We use our reconstruction model as a tool for exploring the nature of representations, including: the influence of model architecture and training objectives (specifically robust losses), the forms of invariance that networks achieve, representational differences between correctly and incorrectly classified images, and the effects of manipulating logits and images. We believe that our method can inspire future investigations into the nature of information flow in a neural net and can provide diagnostics for improving discriminative models.
Blockchain Consensus Algorithms: Study and Challenges

Blockchain is defined as a distributed and decentralized database of public and private ledger of all transactions or digital assets that have been executed and shared among different parties. The transactions in the distributed ledger are validated by agreement by many participants in the system and this is possible only through consensus algorithms. Consensus algorithms make sure that all the distributed nodes in the decentralized network must come to an agreement on the states of certain records and data. It also plays a major role in achieving reliability and developing consensus between different peers in the network. The consensus algorithms can be categorized into two groups: Proof based and Voting based. Proof based algorithms ensure that the node performing enough proof would mine a new block to the chain and get the rewards among all the nodes in the network whereas the Voting based consensus algorithms make sure that the nodes participating in the network are known and adjustable so that they are able to transfer and receive the messages for verifying a new block. Different algorithms fall under both the categories. Since consensus algorithms play a vital role in deciding the safety as well as efficiency of blockchain, selecting the correct algorithm for blockchain applications becomes an important factor. In this chapter the basics of blockchain starting from introduction to consensus algorithms, their importance to blockchain, principles and characteristics are discussed along with the working of different consensus algorithms and their comparisons. The chapter also focuses on the research challenges in this subdomain of blockchain technology.
New Book Format of the XXI Century - Electronic Textbooks

The rapid informatization process of the education system has created both the opportunities and the need for the use of e-books in education. E-books allow students to actively participate in the learning process, to personalize their learning, to gain new knowledge and to evaluate their own abilities. The e-textbook also enriches traditional forms of learning, encompassing a large amount of teaching and learning materials and stimulating the development of new teaching methods. In our opinion, it is time to switch to electronic and interactive formats in the development of electronic aids and textbooks in universities. One of the leading directions in the use of information and communication technologies today is the effective use of computers in educational activities. The main issue in implementing this activity is the selection of e-learning resources that will improve the quality of education.
Application and Practice of Computer Network Technology in Online Business Japanese Teaching

Abstract In recent years, the process of global integration has gradually accelerated. The relationship between countries have been close, and the interactions have continued to increase. Our country is close to Japan, and our relationship is getting closer. As a developed country, Japan’s culture, economy, politics, the country’s development experience, and reform measures are all worth learning [1]. Nowadays, the two countries often hold activities related to cultural exchanges between China and Japan, and more and more people in our country choose to travel and study in Japan. At the political level, there are also many policies aiming to strengthen the interaction. Therefore, cultivating people mastering Japanese is very important for the development of our country. Among all categories of Japanese, business Japanese is the most critical to mutual communication. Then, it is very necessary to continuously improve business Japanese teaching. Computer network technology is also a relatively well developed technology, and its development has prompted the emergence of convenient online business Japanese teaching. It is an innovative reform for business Japanese teaching, breaking through the traditional teaching methods and models. It is conducive to the sustainable development of business Japanese teaching and cultivates practical business Japanese talents.
Information technologies in education: application of stream technologies

The article deals with using stream learning information technology in the context of teaching students of humanitarian specialties. The authors consider the theoretical views of researchers on the stream learning features, the presentation of educational material using video materials, which is a didactic tool that increases the level of perception and understanding of teaching information. Based on the students’ survey, the authors have revealed their attitude to using the stream learning method, creating and using educational videos by teachers, as well as types of educational activities where it is advisable to use stream technologies in the educational process. The article considers also the advantages and disadvantages of using stream technologies in the educational process. The authors consider various types of videos, the possibilities of their use in the educational process, requirements for their preparation, recommendations for use, and options for combining with other multimedia.
Forecast Analysis of Gross Regional Domestic Product based on the Linear Regression Algorithm Technique

Statistical data are indispensable for macro-economic planning activities such as the Gross Regional Domestic Product (GRDP) where data can determine the economic development strategies and policies that have been adopted and can be continued in the future. This study draws on quantitative data sources from the Regional Statistical Agency of Jakarta for the period 2017-2019, the subject of the Gross Regional Domestic Product based on current business prices. The aim of this research is to test and predict the level of accuracy of GRDP at current prices based on business fields using the Linear Regression method supported by Rapid Miner software. The results show that the validated Linear Regression algorithm with K-Fold values from 2 to 10 with the sampling type linear sampling and shuffled sampling can be used and implemented with the smallest Root Mean Square Error value of IDR 9,977,431 at k = 10 for the sampling.
Development of postgraduate school’s digital library as a repository of digital collections

Abstract The development of information and communication technology offers advantages for library management. The ease of access to the internet makes it easy for us to access the library’s digital collection without any time and space limitations. Currently, many digital libraries have been developed in various universities to complement the existence of conventional libraries. This digital library’s presence can be a solution for traditional libraries to overcome existing limitations and constraints. This current study discusses how Universitas Negeri Semarang’s postgraduate school digital library is developed. The waterfall method and was used to guide systems development. This paper outlines how the digital library is used to give a portrait to the users of some features offered.
Improving Performance by Genetically Optimizing Support Vector Machine to Detect Code Smells

Code smell occurrence is a common phenomenon when functionalities of complex systems are subjected to frequent changes. They are design anomalies that prevent future alterations, lead to errors, and make software frail. Appropriate refactoring is employed to treat them, but the first challenge in this process is identifying and detecting code smells. Despite the excellent performance of available tools, their limitations prevent developers from their adoption. Machine learning is employed to eliminate the limitations of tools and classify source code stinking with smells. In this study, the support vector machine in four different kernel settings can detect six variations of code smells. To improve performance, SVM is optimised by tuning its hyperparameters using a genetic algorithm. A genetic algorithm eliminates the need for an expert to determine the best value for hyperparameters and tests an extensive range of values that is impossible with the grid search. Accuracies are compared before and after tuning hyperparameters of the support vector classifier. Results show hikes in accuracy for all cases, with a maximum value of 40%. SVM with RBF kernel performed best among others and had the highest accuracy, up to 97.5%.
Development of a tracer study system for graduates of the Integrated Science Department, Universitas Negeri Semarang

Abstract Tracer study is a mechanism implemented by universities to track graduates to measure the relationship between educational goals and processes with the current condition of graduates. In addition, the results of the tracer study are also used as an assessment for higher education accreditation. For this reason, Department of Integrated Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang has developed a website-based integrated tracer study system. The system development method used is the Waterfall Model which consists of Requirement Analysis, Design, Development, and Testing. From the results of testing conducted by information systems experts, the system being developed is very feasible both in terms of functionality and usability. The website-based online system can handle graduate data management, able to provide all information about graduates and an overview to the Departmental Council regarding the competitiveness of graduates in the world of work. It is hoped that the tracer study system that has been developed can be continued to see how the competitiveness of graduates in improving department management.
An Novel Hand Gesture System for ASL using Kinet Sensor based Images

The prime goal of this study is to perform resolution enhancement using experimental analysis.The framework presents hand image resolution enhancement techniques based on multi scale decomposition and edge preservation smoothing.The proposed technique Dual Tree complex wavelet transform (DT-CWT) and edge preservation smoothing (EPS) algorithm images are decomposed into different sub bands and interpolated, after which sub bands are reconstructed to achieve the enhanced image.The study outcome of this phase is studied with respect to PSNR and RMSE for all the letters of ASL.
Optimal Composition of Services for Intelligent Systems Using TOPSIS

Service-oriented architecture is a widely accepted service used for supporting consolidation and integration functions under an enterprise system which are complex in nature but with an intelligent framework which helps in integrating the services in an optimistic and dynamic manner for getting the task done. For any service-oriented architecture-based application, its services are the main components, as it requires service compositions for answering various requests. There exist many possible service compositions for completing a task. To find an optimum composition from those dynamically present during run time is another crucial aspect for the success of this architecture. The present research elaborated a novel idea for optimal composition of services in SOA or any other service-based system. This paper covers a case study along with the outcomes of the experiment which indicates the efficiency and validity of the proposed technique.
Capability of Vetiver (Vetiveria Zizanioides), Guinea Grass (Panicum Maximum) and Organic Manures to Remove Total Hydrocarbon and Heavy Metals from Crude Oil Contaminated Soil in Port Harcourt

In a field study conducted at the Teaching and Research Farm of Rivers State University PortHarcourt, Nigeria, to examine the ability of vetiver and guinea grasses amended with organic manures in remediation of crude oil polluted soil; soil polluted with Bonny light crude oil at 0 and 2% v/w was subjected to a remediation processes using vetiver (Vetiveria zizanioides) and Guinea grass (Panicum maximum) amended with organic manures for a period of twelve months. Two weeks after pollution, poultry and rabbit manures were applied at 0, 10, 20 and 30 tons per hectare respectively. Vetiver and guinea grasses were planted two weeks later. It was fitted in factorial split plots randomized block design. Results of the study revealed that remediation of the soil with grasses degraded the Total hydrocarbon content (THC) to 23 and 21.2% for vetiver and guinea grass respectively, while the quantity of heavy metals removed from the soil were 28.4% and 25.9% for iron, 37.3 and 32.8% for zinc, 35.8 and 30.8% for lead (Pb) and 23.1 and 38.5% cadmium for vetiver and guinea grass respectively. Amendment of the soil with 30 tons’ /ha organic manures increased the quantity of THC degraded to 70.6% and 67.9% for vetiver and guinea grass respectively while the concentration/quantity of heavy metals removed from the soil increased to 58.4 and 54.7% for Fe, 66.9 and 65.1% for Zn, 69.4 and 66.6% for Pb and 80.8 and 71.2%, in Cd for vetiver and guinea grass respectively. The quantity and concentration of THC and heavy metals degraded in the soil was higher in vetiver than guinea grass plots and in vetiver amended with poultry manure than in guinea grass amended with rabbit manure. There was a significant (P&lt;0.05) difference in uptake of THC and heavy metals in plant tissues between vetiver and guinea grass. Vetiver accumulated more of the contaminants in their tissues than guinea grass. Amendment of the soil with organic manures reduced the uptake of the contaminants (THC and heavy metals) from the plant tissues. Generally, both grasses have the capability to remediate crude oil contaminated soil. Augmentation of the two grasses with organic manures enhanced their capability.
Composing Normalizing Flows for Inverse Problems

Given an inverse problem with a normalizing flow prior, we wish to estimate the distribution of the underlying signal conditioned on the observations. We approach this problem as a task of conditional inference on the pre-trained unconditional flow model. We first establish that this is computationally hard for a large class of flow models. Motivated by this, we propose a framework for approximate inference that estimates the target conditional as a composition of two flow models. This formulation leads to a stable variational inference training procedure that avoids adversarial training. Our method is evaluated on a variety of inverse problems and is shown to produce high-quality samples with uncertainty quantification. We further demonstrate that our approach can be amortized for zero-shot inference.
Innovative pedagogical practices in higher education of the XXI century (aspects of public administration)

This article is an overview. The research highlight’s objective and subjective preconditions of the process of modernization of professional and ideological-methodological training of a modern specialist, respectively, changes in the dynamics and content lines of modern historical progress. The content of innovative tendencies of the university education system in Ukraine and the urgency of the problem of teacher tutor training are indicated. The general and distinctive features of tendencies of development of innovative pedagogical practices in higher school abroad in the direction of professional training of teachers (the USA, Poland, and China) are allocated. The relevance of theoretical coverage of innovative pedagogical practices in higher education is due to the peculiarities of their development in modern conditions in Ukraine and abroad. Modernization of the higher education system today requires the study and comprehensive analysis of this issue. Theoretical basis: scientific articles of domestic and foreign scientists on the problems of innovative pedagogical practices in higher education.
Assessment of Academic Utilization of Online Information Resources by Undergraduate Students in University of Nigeria, Nsukka

ABSTRACT The research was undertaken to determine the academic utilization of online information resources by undergraduate students in the University of Nigeria, Nsukka. The objectives of the study were to identify the online information resources used by the students; academic purposes for their use, extent of their academic use, problems as well as strategies for improving the utilization of the online information resources by undergraduate students. Descriptive survey was used as the design of this study. The study was carried out in Nsukka, Enugu State in the South Eastern Geopolitical zone of Nigeria. The population of the study is made up of 25,657 students of the University of Nigeria, Nsukka. Six research questions were set to guide the study. The instrument for data collection is UOIRSQ (Utilization of Online Information Resources by Students’ Questionnaire) which was formulated in accordance with the research question. Since the research design is descriptive, likewise, descriptive method of data analysis was used in answering the research questions. The major findings were that out of many online information resources available, only few of them are used by undergraduate students. Wikipedia Online Encyclopaedia, Google Books and Punch/Vanguard are highly used. Problems and strategies for improving on the problems were given. Some of the recommendations made for enhancing the academic utilization of online information resources by students in the university include: providing more online training facilities to undergraduates in order to equip them on how to use online information resources; constantly upgrading the server’s bandwidth to ensure maximum service or faster navigation; providing and given to the students improved access to computer systems, preferably laptops, and also teaching them advanced searching skills through organisation of workshops and seminars by the library and university.  URL:  http://ijkcdt.net/xml/11661/11661.pdf
New direction of Library Service Innovation Based on mobile Internet

Abstract The main application device of mobile Internet is mobile smart phone. There is no doubt that smart phones have opened a new era for our lives. Electronic reading mode has become the main way for young people to read journals[1]. A lot of electronic reading software has also appeared. In order to effectively improve the national cultural quality, the library service innovation using mobile Internet technology has become a new research direction. Many schools have joined the research. This paper briefly analyzes the characteristics of mobile Internet. This paper puts forward the innovation of mobile Internet and library service. This paper also puts forward the innovative construction of University Library and mobile Internet.
Fake Review Detection Using Hybrid Ensemble Learning

Hegde, Sindhu Raj Rai, Raghu Sunitha Hiremath, P. G. Gangisetty, ShankarOpinion spam on online restaurant review sites are a major problem as the reviews influence the users’ choice to visit or not to a restaurant. In this paper, we address the problem of detecting genuine and fake reviews in restaurant online reviews. We propose a fake review detection technique comprising data preprocessing, detection and ensemble learning that learns the reviews and their features to filter out the fake reviews. Initially, we preprocess to obtain the refined reviews and employ two independent classifiers using deep machine learning and feature-based machine learning techniques for detection. These classifiers tackle the problem in two aspects, i.e., the deep machine learning model learns the word distributions and the feature-based machine learning model extracts the relevant features from the reviews. Finally, a hybrid ensemble model from the two classifiers are built to detect the genuine and fake reviews. The experimental analysis of the proposed approach on Yelp datasets outperforms the existing state-of-the-art methods.
Social networks and education: the increase in student learning efficiency and the search for means of control

The total informatization of a society leads to the wide popularization of social networks. A growing number of people in the world can use social networks with any device, which simplifies and improves the process of online communication. Social networks provide an opportunity for free, cheap, simple, and direct contact with the student audience. They help enter discussions, explore new topics, acquire and maintain new knowledge and skills, assess one’s work and the work of one’s colleagues, and think critically. The article considers the features of social networks and analyzes their capabilities (main advantages) in student education. The analysis of possibilities and readiness of university professors and students to involve social networks in the educational process is carried out. A SWOTanalysis of the involvement of social networks in the educational process is given. The benefits and limitations of IT in the educational process for different categories of users are considered. Tools and examples of using social networks are presented. The article also considers the ways of organizing control and analysis of student progress using social services and networks.
Discovering Second Language Acquisition in Higher Education in Dealing with Industrial Revolution 4.0 Challenges

Industrial revolution 4.0 is an era where information technology regards as a human life base. This era will also disrupt various human activities, including the fields of science, technology, and art, without exception in the field of education. Industrial Revolution 4.0, which is an expansion of the digital world to various sectors, must be prepared with manifold approaches to accommodate our next generations to be able to keep up with the current era. Several skills need to be prepared, one of which is the mastery of English from an early age (Second Language Acquisition), also a more innovative learning system in higher education such as adjusting the learning curriculum and increasing students' ability in mastering English as second language acquisition.