Reviewerly/exHarmony huggingface dataset:
Exploring the Knowledge Embedded in Class Visualizations and Their Application in Dataset and Extreme Model Compression

Artificial neural networks are efficient learning algorithms that are considered to be universal approximators for solving numerous real-world problems in areas such as computer vision, language processing, or reinforcement learning. To approximate any given function, neural networks train a large number of parameters—up to millions, or even billions in some cases. The large number of parameters and hidden layers in neural networks make them hard to interpret, which is why they are often referred to as black boxes. In the quest to make artificial neural networks interpretable in the field of computer vision, feature visualization stands out as one of the most developed and promising research directions. While feature visualizations are a valuable tool to gain insights about the underlying function learned by the network, they are still considered to be simple visual aids requiring human interpretation. In this paper, we propose that feature visualizations—class visualizations in particular—are analogous to mental imagery in humans, resembling the experience of seeing or perceiving the actual training data. Therefore, we propose that class visualizations contain embedded knowledge that can be exploited in a more automated manner. We present a series of experiments that shed light on the nature of class visualizations and demonstrate that class visualizations can be considered a conceptual compression of the data used to train the underlying model. Finally, we show that class visualizations can be regarded as convolutional filters and experimentally show their potential for extreme model compression purposes.
A Generic System for Processing Insurance

Insurance companies are regularly provided with health check reports by the buyers of insurance. Different forms of printed lab reports/health check reports have to be digitized for each value of captured parameters. Optical Character Recognition (OCR), is used to convert the images of handwritten, typed, printed text or any kind of scanned documents into machine-encoded text in order to digitize the values from the report. Conversion to this standard set of digital values will benefit in automating a lot of backend approval process. we collect the reports from the user and read the values from the report and scrutinize the values. Based on the values with the company’s standard set, the scrutinization is done and it is then visualized using any visualization tool. The result is presented to the user so that the user can get an idea whether he/she is eligible for insurance claim. The foremost objective of this paper is making the insurance backend approval process a lot easier and a quick response to the buyers.
Construction and Practice of a New Experimental Teaching System for Undergraduate Chemistry Specialty based on the Cultivation of Innovative Ability

Curriculum system is the carrier of talent training.In order to better cultivate top-notch innovative talents, according to the characteristics and development tendency of chemistry discipline, a new experimental curriculum
USING COMBINATORIAL MAPS FOR ALGORITHMS ON GRAPHS

The aim of this paper is to come back to a data structure representation of graph by permutations. This originated in the years 1960-1970 by contributions due to J. Edmonds [7], A. Jacques [11], W. Tutte [22] in order to consider the embedding of a graph in a surface as a combinatorial object. Some algebraic developments where suggested in [4] and [12]. It was also used for implementation in different situation, like planarity testing by H. de Fraysseix and P. Rosenstiehl [6], computer vision by G. Damiand and A. Dupas [5] or formal proofs by G. Gonthier [9].
LHC experiments and their Open Data

The CERN laboratory has released a new open data policy for the LHC experiments.Although this policy focuses on the common strategy for the release of research-quality data, it strengthens all aspects of open data, and reaffirms the commitment of all the LHC experiments towards open science.In this presentation we give a summary on the status of the open data efforts from each of the large LHC experiments as well as their plans and strategies under the new policy.
Design of low-power CMOS VLSI circuits using multi-objective optimization in genetic algorithms

This paper presents a design CAD tool for automated design of digital CMOS VLSI circuits. In order to fit the circuit performance into desired specifications, a multi-objective optimization approach based on genetic algorithms (GA) is proposed and the transistor sizes are calculated based on the analytical equations describing the behavior of the circuit. The optimization algorithm is developed in MATLAB and the performance of the designed circuit is verified using HSPICE simulations based on 0.18µm CMOS technology parameters. Different digital integrated circuits were successfully designed and verified using the proposed design tool. It is also shown in this paper that, the design results obtained from the proposed algorithm in MATLAB, have a very good agreement with the obtained circuit simulation results in HSPICE.
Witwatersrand composite paleoplacers

Background. The Witwatersrand gold province located in South Africa is the richest in the world. The Witwatersrand deposits are composite, where osmirids and diamonds are mined along with gold, silver and uranium. The genesis of the Witwatersrand deposits is controversial. Most local geologists support the hypothesis of the presence of paleoplacer deposits with subsequent metamorphic transformation of ore-bearing conglomerates. In addition, there are aeolian, hydrothermal-sedimentary, hydrothermal-sedimentary-metamorphic and magmatic models of ore formation. Aim. To establish the genesis of the Witwatersrand deposits. Materials and methods. Analysis of published literature and factual data. Results. Osmirids and diamonds are mined along with gold, silver and uranium from the composite Witwatersrand deposits. Such a set of useful components is not known in any of the deposits of magmatic or hydrothermal genesis. Considering the confinement of useful components to conglomerates, the detrital nature of most of the gold grains and the presence of various accompanying minerals in the heavy fraction, characteristic of igneous rocks of felsic, basic and ultrabasic composition, the hypothesis of the primary alluvial nature of the deposits of the Witwatersrand province looks the most reasonable. Conclusions . The factual material indicates an alluvial origin of the Witwatersrand deposits with subsequent metamorphic transformation of ore-bearing reefs. The primary alluvial formation of ore-bearing conglomerates is indicated by the confinement of gold and uranium to channel facies with a tendency to accumulate in the basal horizons of the reefs, the presence of rounded gold particles bearing the traces of transportation in alluvial flows, as well as a set of minerals in the heavy fraction of concentrate, characteristic of placers.
Efficient image retrieval using multi neural hash codes and bloom filters

This paper aims to deliver an efficient and modified approach for image retrieval using multiple neural hash codes and limiting the number of queries using bloom filters by identifying false positives beforehand. Traditional approaches involving neural networks for image retrieval tasks tend to use higher layers for feature extraction. But it has been seen that the activations of lower layers have proven to be more effective in a number of scenarios. In our approach, we have leveraged the use of local deep convolutional neural networks which combines the powers of both the features of lower and higher layers for creating feature maps which are then compressed using PCA and fed to a bloom filter after binary sequencing using a modified multi k-means approach. The feature maps obtained are further used in the image retrieval process in a hierarchical coarse-to-fine manner by first comparing the images in the higher layers for semantically similar images and then gradually moving towards the lower layers searching for structural similarities. While searching, the neural hashes for the query image are again calculated and queried in the bloom filter which tells us whether the query image is absent in the set or maybe present. If the bloom filter doesn't necessarily rule out the query, then it goes into the image retrieval process. This approach can be particularly helpful in cases where the image store is distributed since the approach supports parallel querying.
E-LEARNING TRAINING ACTIVITIES FOR LECTURERS

This E-Learning workshop aims to improve lecturers' mastery in utilizing one of the E-Learning platforms, namely Edmodo. This is done as a means for lecturers to carry out teaching and learning activities without being limited by time and place. From the whole series of activities in this training program, several conclusions can be drawn that Edmodo can be used as an alternative to E-Learning learning media that is easy to use and apply to the campus environment.
Sistem Pintu Otomatis Menggunakan E-KTP Berbasis Internet of Things (IoT) pada Kamar Hotel

The system of opening and closing the hotel room doors is already using RFID but its use is still not optimal because the card used is very expensive and the card used can only be one card for each room, so if the card is lost, you have to re-enter the card id. Therefore, digital electronic technology systems and devices are needed to make it easier to open the door and close the hotel room so that it can facilitate the hotel security system with automatic locks. This system and device uses an E-KTP and an Internet of Thing (IoT)-based Keypad and which functions to control the device using a NodeMCU while for a card reader with an RFID engine. The research method uses a model, namely with a prototype model for making systems and automatic room door locking system tools. The results and conclusions of the manufacture of hotel room automatic door locking systems and devices using an Internet of Thing (IoT)-based E-KTP equipped with a message LCD and keypad as a door opening solution if the RFID machine does not work. The security of hotel guests who stay is more guaranteed and can also make it easier for guests and hotel staff with an automatic hotel room door lock system. The results of the user's assessment of the work of a series of systems and tools to open and lock this automatic hotel room door are very good with a value of 88.7%.
Views of University Administrators on Online Education During the Epidemic Period

The human resources unit in universities has planned training for academicians and directors. With the transition to distance education during the pandemic peri-od, face-to-face training has started to take place online. With this study, online training was planned for the administrators in the administrative department of universities. The opinions of the managers about online training are critical. Man-agers’ views were consulted on the effectiveness of online training. In this study, a qualitative research method was used to reach detailed results. The study group of the research con-sists of 18 administrators in the administrative department of the Institute of Legislation and Comparative Law under the Government of the Russian Federation, Peoples’ Friendship University of Russia and Russian New University. The application was carried out in the ‘online manager development programme’ for 3 weeks in the 2020–2021 fall semester. In order to access the data of this study, the interview form developed by the researchers was used as a data collection tool. While preparing the interview questions developed by the re-searcher, the opinions of four experts in the field were taken and the questions were finalized. Con-tent analysis was used in the analysis of the data. The find-ings obtained as a result of the research are given in detail in the findings and re-sults section.
Cloud Computing Environment

Cloud computing is an on demand availability of cloud system resources such as data storage and computing power without direct active management by the user.The word cloud is used as a metaphor for internet and a standardized cloud like shape was used to denote a network on schematic's.[1] Cloud is about where you compute, not how you compute.Here, we will discuss about difference between and On-premises and Cloud-based computing, Scalability, server storage with cloud service providers, data security, maintenance in terms of infrastructure as well as cost efficiency.It is described as the delivery of on-demand services over the internet works on "pay-as-you-go" basis.Cloud computing has two type of models: •Service model: infrastructure as a service platform as a service software as a service Cloud computing service models are hassle-free.The most popular cloud computing models AWS, Microsoft's azure, Google cloud platform are as discussed below.SLAs, instances, container, Kubernetes, Regions, storage are all important factors also discussed in this paper.How cloud providers provide services over the cloud and what are the importance of those services in the modern day infrastructure.The data usage has been discussed providing a large dependency in processing the programs.The future introduction is also mentioned giving new research aspects to the field of cloud computing.Keyword: Explanation of various types of cloud services provided, types of cloud being discussed, market value regarding cloud computing is mentioned, various cloud providers as well as organizations running on cloud is explained, service model is discussed with various storage properties, scalability, containers and kubernetes are briefly explained, Future of cloud is being discussed. INTRODUCTION:"Cloud is about how you do computing, not where you do computing."This well-known phrase is typically depicted by Paul Moritz, CEO of VMware.Cloud computing acts like a power plant, in which we don't know how the power is generated, we are just plugging into the systems and using that power and paying bills., this could also be an example of Electricity-as-a-service (Eaas).In the year 2006, Amazon Web Services launched life changing scenario: EC2 (Elastic compute cloud) and S3 (simple storage services) , EC2 ,acting as a virtual system with its own CPU as well as RAM, the operating system is also present which could be administered by the user with IP address available for further networking.
Adding Proof Calculi to Epistemic Logics with Structured Knowledge

Dynamic Epistemic Logic (DEL) is used in the analysis of a wide class of application scenarios involving multi-agents systems with local perceptions of information and knowledge. In its classical form, the knowledge of epistemic states is represented by sets of propositions. However, the complexity of the current systems, requires other richer structures, than sets of propositions, to represent knowledge on their epistemic states. Algebras, graphs or distributions are examples of useful structures for this end. Based on this observation, we introduced a parametric method to build dynamic epistemic logics on-demand, taking as parameter the specific knowledge representation framework (e.g., propositional, equational or even a modal logic) that better fits the problems in hand. In order to use the built logics in practices, tools support is needed. Based on this, we extended our previous method with a parametric construction of complete proof calculi. The complexity of the model checking and satisfiability problems for the achieved logics are provided.
UNDERWATER RESTAURANT BUILDING (TYPICAL STUDY: UNDER RESTAURANT BUILDING, SOUTHERN NORWAY)

The underwater building is a building that has its uniqueness where this building in terms of its location is below the surface of the water, besides that this building has its uniqueness from the shape of the building, for example in a typical study of an underwater restaurant located in Southern Norway called restaurant Under This building was chosen because it is an underwater building and has its uniqueness in the building. Research on underwater buildings is carried out to find out what applications are used and what concepts are used in underwater buildings. For the data processing method using a comparative method where this research method is an analytical variable from the results of the combination between data from the theory of architectural elements and the principles of water. And produce a variable to analyze underwater buildings such as shape, space, color, and texture or material.
Linguistic Analysis, Ethical Practice, and Quality Assurance in Anonymizing Recordings of Spoken Language for Deposit in Digital Archives

This report considers linguistic analyses as matters of ethical practice and quality assurance in the anonymization of recordings of spoken language for deposit in a digital language archive. Ethically, researchers must be committed to protecting the identities of primary data providers. Accordingly, conducting pragmatic analyses before initiating technical anonymization procedures can aid in determining exactly what discourse, in what contexts, might constitute identifying information in need of anonymization. Qualitatively, one of the main goals of language documentation is to preserve as much primary data as possible for future research. Accordingly, conducting phonotactic analyses with the help of computer software can aid in determining precise chronometer readings for each tonal insertion to excise as little primary data as possible during anonymizations. These findings warrant further research on anonymization protocols in digital language archive projects.
Implementasi Data Mining Menggunakan Algoritma Apriori Pada Penjualan Suku Cadang Motor

This research was carried out to simplify or assist Candra Motor workshop owners in managing data and archives of motorcycle parts sales by applying a data mining a priori algorithm method. Data mining is an operation that uses a particular technique or method to look for different patterns or shapes in a selected data. Sales data for a year with the number of 15 items selected using the priori algorithm method. A priori algorithm is an algorithm for taking data with associative rules (association rule) to determine the associative relationship of an item combination. In a priori algorithm, it is determined frequent itemset-1, frequent itemset-2, and frequent itemset-3 so that the association rules can be obtained from previously selected data. To obtain the frequent itemset, each selected data must meet the minimum support and minimum confidence requirements. In this study using minimum support ? 7 or 0.583 and minimum confidence of 90%. So that some rules of association were obtained, where the calculation of the search for association rules manually and using WEKA software obtained the same results.By fulfilling the minimum support and minimum confidence requirements, the most sold spare parts are inner tube, Yamaha oil and MPX oil.
The Early Childhood Education Teachers’ Needs of Being Able to Teach English Well

English should be introduced and taught to early childhood in a fun way. Early childhood education teachers are required to have the ability to teach English in a good and fun way. The purpose of this study is to explore the needs of being able to teach English well for the early childhood education teacher (ECET). The survey technique was conducted with 56 respondents from the ECE teachers. The survey was conducted via google form with 15 questions. The result showed that 55% of the respondents gave priority of developing instructional media and materials in the expected training. Meanwhile as many as 33% of expected training was emphasized on teaching technique as the first prominent. The only 12% who considered motivation training was very principle. All trainings they were expecting the needs of designing training concept such as duration, facilitator, methodology, material, media, and setting of places were fully considered
Finding Facial Expression Patterns on Videos based on Smile and Eyes-Open Confidence Values

Facial expression recognition is one of the types of non-verbal communication that is not only commons for human but also plays an essential role in everyday lives. The development of science and technology allows the machine to automatically detect human facial expressions based on images and videos. Numerous facial expression detection methods have been proposed in the literature. This paper presents a method to find three basic facial expressions (neutral, happy, and angry) from two parameter values: smile and eyes-open. The analysis involves a preprocessing step using a combination of pre-designed proprietary algorithm and Luxand library. Firstly, the parameters were mapped into two-dimensional space and then grouped into three clusters using K-means, a popular heuristic clustering method. Secondly, more than 50,000 frames for each video were experimented using the proprietary research data. The result shows that the proposed method successfully performed a simple video analysis of facial expressions.
The quality of higher education during the Covid-19 pandemic and the prospects for post-secondary education

The COVID-19 pandemic, which spread widely around the world at the beginning of 2020 and continues to this day, has seriously affected the field of higher education. In a short time, it forced to change the traditional form of education to distance learning. Most of the world’s universities were not ready for this: neither technically nor conceptually. As a result, there is widespread criticism of online education, the quality of training is declining, the negative consequences of covid education are being actualized. At the same time, researchers are looking for new vectors of development, studying the mistakes of the past, realizing that the pandemic did not have a special impact, but only aggravated the problems already existing in the education system. In this regard, a study was conducted in Kazakhstan, the purpose of which was to study the quality of higher education during the pandemic through the eyes of students, their preferences and proposals for reforming higher education. As part of this study, a sociological survey was conducted that covered a thousand students from different regions of the Republic of Kazakhstan. This study will complement the ideas about the prospects of higher education after the pandemic, and the results will be useful for teachers of higher educational institutions, philosophers of education and anyone interested in the problems of higher education. Key words: philosophy of education, pandemic, higher education, quality of education, distance education, post-secondary education.