Reviewerly/exHarmony huggingface dataset:
Analysis of Impossible Differential on LowMC Block Cipher

Impossible differential attack is one of the strongest methods of cryptanalysis on block ciphers. In block ciphers based on SPN (substitution permutation network), the only layer that resists the difference is the nonlinear layer. Obviously, paying attention to the features of nonlinear layer is important for the sake of preventing statistical attacks, such as the differential attack. Therefore, this layers’ features regarding attack tolerance should be carefully investigated. The existence of such a nonlinear layer with the required features and applying it in the entire length of the block can lead to more resistance against differential attacks. Over the past few years, a new set of block ciphers based on SPN has been introduced, in which the nonlinear layer is applied only to a particular part of the state. In this paper, a general framework for finding the   characteristics of the impossible difference in this type of new block cipher is presented. Contrary to the previous miss-in-the-middle methods, which are used to find the impossible differences, the method       presented in this article is independent of the feature of linear layer of the algorithm and allows the attacker to systematically find the effective impossible differential even in cryptographic algorithms with highly complex linear layer. In order to demonstrate the efficiency of the proposed method, the family of LowMC ciphers that use bitwise linear layer are examined in this paper and based on this framework some           impossible differential characteristics are proposed for some versions of reduced LowMCs. This proposed impossible differential characteristics can be easily applied in key-recovery attacks based on the framework presented in this paper. As an example, we show that based on the impossible difference characteristic    obtained for 63 rounds of the LowMC (128,128,2,128), a key-recovery attack is applied to the 64-round of this algorithm. In proposed attack, the complexity of memory is 289, the complexity of the time is 2123.7, and the complexity of the data is equal to 2123.1 of the chosen plain text.
Sentiment Detection from Speech Recognition Output

Emotion and sentiment detection from text have been one of the first text analysis applications. Practical use includes human-computer interaction, media content discovery and applications for monitoring the quality of customer service calls. In this paper we perform a review of established and novel features for text analysis, combine them with the latest deep learning algorithms and evaluate the proposed models for the needs of sentiment detection for monitoring of the customer satisfaction from support calls. The issues we address are robustness to the low ASR recognition rate, the variable length of the text queries, and the case of highly imbalanced data sets. The proposed approaches are shown to significantly outperform the accuracy of the baseline algorithms.
Download FFmpeg Audacity in 2021 (How to Install & Update)

FFmpeg audacity is an order line apparatus that changes over sound or video groups. FFmpeg can likewise capture and encode progressively from different ...
THE LINGUISTIC POWER OF PERSONAL DRIVE IN THE GREATEST SHOWMAN

Politeness has become quickly to understand that can make things worse by wrong responding to the interlocutors. It has the strategy to show the power and treat the interlocutors. Besides, a movie that raised politeness entitled The Greatest Showman won a Golden Globes award for best original, which can have to categorize as something new. Thus, the researcher chose politeness strategies as a topic because of movie drama rarely thoughts about politeness.The aim of this research uses to find out what are the types of politeness strategies that constructed by the personal drive to motivate others and what are the factors that trigger the personal drive-in using politeness strategies to encourage others. This research used a qualitative approach to answer the research questions. The qualitative approach was chosen as the methodology to analyze the data findings because it is the most appropriate method to answer the research questions of the study. This research uses the politeness strategy leading the factor of language and power as the data which are spoken by the personal drive in The Greatest Showman movie. The study shows that four types of politeness strategies Brown and Levinson (1987) constructed by the personal drive to motivate the others, it also shows that factors of language and power Fairclough (1989) trigger politeness strategies due.
Video Stalling Decision Method

Effectively improving the competitiveness of ISP has always been a hot topic in the field of communication research. Video as the main body of network traffic, providing video users with high satisfaction network services can enhance the user experience, and thus effectively improve the competitiveness of ISP. Some user behaviours will affect the detection of the stalling event. Therefore, this paper proposes a video stalling decision model based on the video stalling detection method based on HTTPS. The model mainly models the IP source, packet length, packet type, and basic information of the packet data. In the case of the unsolved HTTPS protocol, it can use the limited information to identify the user behaviour and perform the stalling detection, thereby reducing the misjudgement rate of the stalling detection.
Security Measures Against SQL Injection Attacks

Most technical web applications have been using the SQL standard in recent years. These Web applications transmit a structured query language to the database through SQL. Values are returned from the database using queries or parameters in web applications as per user requests. The results returned are displayed in certain formats to the user or administrator, depending on the programme architecture. However, malicious code entered by the attacker in web applications can be used to exploit SQL queries dynamically created. SQL is injected with the user's malicious code during the process. In other words, it is possible to retrieve the information by inserting malicious SQL commands in areas where data such as window address bars or access controls can be entered. This detail is not freely accessible and proprietary. By incorporating new and related dimensions to the SQL injection situation, the attacker will access other information in the database. Through running any commands on the database server, an attacker may harm the programme or server. An example and review of a SQL injection attack on a web application built on MSSQL-ASP.NET is discussed in this article. In addition, protection precautions and recommendations for solutions against browser-based web apps security vulnerabilities are listed.
LibGuides: Graduate Study and Research: Research: A Process and a Practice

How to use the library resources in planning, researching, writing, and finishing a course paper, thesis, dissertation, and similar projects. research guides, materials, and process
LibGuides: Diversity in STEM Education: Background Information

This Library Guide contains resources for students interested in Diversity in STEM education (Science, Technology, Engineering, and Mathematics)
Cognitive Argumentation and the Selection Task

Author(s): Dietz, Emmanuelle; Kakas, Antonis | Abstract: This paper presents a study of the selection task based on Cognitive Argumentation (CA), a computational framework for dialectic argumentation-based reasoning. CA is built from a theoretical framework of argumentation in AI which is then grounded via cognitive principles from Cognitive Science. The aim is to understand the selection task variations by studying how argumentative reasoning is suitably flexible to uniformly capture the differences among the individuals' selections, the canonical groups and the shifts within the different contexts in which the experiment is carried out. Our approach is assessed with respect to the developed criteria within the meta-analysis of Ragni and Johnson-Laird in 2018.
RANCANG BANGUN SISTEM INFORMASI PENGHITUNG PENGUNJUNG OTOMATIS BERBASIS INTERNET OF THINGS

The increase in the number of visitors creates a new problem, namely the full capacity of the venue when the number of visitors is not proportional to the standard capacity of the available building. Calculating the number of visitors to shopping centers can provide information to managers to optimize locations and evaluate the attractiveness of several shopping centers. Regional managers can analyze and monitor the status of a crowd center. Because of these problems, an automatic system is needed to count the number of visitors passing through the door at the same time. In this study, the parameter used is the detection of passing objects. The researchers used the HC-SR04 infrared sensor to count the number of people who passed the infrared sensor on the door. The results of this study state that the systems and tools that have been built can work well, with evidence that the tools can store data and the system can display the data
형태음운론을 도입한 음운 교육 내용 연구

The purpose of this study is to elucidate the proper status and the right perspective of morphophonology in Korean grammar education, and to define what knowledge students should be provided with in morphophonology education. Morphophonology should be taught to expand language awareness and to pay attention to language changes. To this end, students should be presented with the following knowledge. Firstly, phonological processes occur at the boundaries of morphemes. Secondly, there are phonological phenomena in which grammatical information of words should be considered. Thirdly, phonological processes occur differently depending on the speaker''s perception of the word composition. Fourthly, the current word forms are the result of a long use of words. For the proper application of these knowledges, morphology education must precede phonology education, syllable education must be implemented, and teachers should be free from normative point of view in terms of educational philosophy when teaching phonology.
On the Number of Circuits in Regular Matroids (with Connections to Lattices and Codes)

We show that for any regular matroid on m elements and $\alpha \geq 1$, the number of $\alpha$-minimum circuits, or circuits whose size is at most an $\alpha$-multiple of the minimum size of a circuit in the matroid, is bounded by $m^{O(\alpha^2)}.$ This generalizes a result of Karger for the number of $\alpha$-minimum cuts in a graph. As a consequence, we obtain similar bounds on the number of $\alpha$-shortest vectors in totally unimodular lattices and on the number of $\alpha$-minimum weight code words in regular codes.
Los Angeles Reading Corpus of Individual Differences: Pilot distribution and analysis

Author(s): Harris, Jesse; Rich, Stephanie | Abstract: We introduce the LARC-ID, a pilot corpus of eye-movements obtained from subjects reading texts from a range of genres. Materials were presented in multiple paragraphs on the screen to more closely match naturalistic reading environments. Readers were encouraged to read for comprehension and enjoyment, engaging in various kinds of comprehension questions, including an open-ended reflection at the end of each text. Subjects also participated in a battery of individual difference measures, including those known to predict reading behavior in controlled experimental contexts, e.g., Rapid Automatized Naming (RAN; Denckla a Rudel, 1976), the author recognition (ART; Stanovich a West, 1989), and reading span (RSpan; Daneman a Carpenter, 1980) tasks. In addition to describing the central properties of the text and relationships between tasks in the battery, we present a sample analysis exploring how intrinsic lexical characteristics (length, frequency, and morphological complexity) interact with selected individual difference measures. The analysis provides the very first glimpse into what we hope will become a useful resource for reading researchers and educators. The entire corpus is freely available for unrestricted use.
Blockchain Technology: Chat Application

Blockchain is a method of storing data that makes it extremely difficult, if not impossible, to edit, hack, or update the system. As time passes, blockchain technology becomes more popular, and blockchain-based applications, also known as DApps, which will be used in this article, are becoming more widely recognised. We will construct a chat application based on a decentralised network in this article to eliminate its absolute reliance on centralised players. On a peer-to-peer network like Ethereum, the actual message and data will be kept. To offer decentralised storage and efficient lookup, we will employ a blockchain and distributed hash table (DHT). which will describe what we will do, which is a trendy issue among academics and trades. Except for the fact that DApps are important, we currently have a limited grasp of DApps and nature. To close the data gap, this paper presents a file for the most comprehensive blockchain-based DApps analysis to date, which includes 995 Ethereum DApps data and 29,846,075 dealings logs above them. We usually do a descriptive investigation of Dapp preferences, characterise patterns of how Dapps use good contracts to gain access to fundamental blockchain, and evaluate the results issues with the post and misuse of DApps In support of the findings, we propose a large number of Results for DApp users to choose the best DApps. Dapp developers must work harder in order to create more efficient DApps, and vendors must likewise support them.
Performance Evaluation of Adaptive Neuro-Fuzzy Inference System (ANFIS) In Predicting New Students (Case Study : UBP Karawang)

The process of admitting new students is an annual routine activity that occurs in a university. This activity is the starting point of the process of searching for prospective new students who meet the criteria expected by the college. One of the colleges that holds new student admissions every year is Buana Perjuangan University, Karawang. There have been several studies that have been conducted on predictions of new students by other researchers, but the results have not been very satisfying, especially problems with the level of accuracy and error. Research on ANFIS studies to predict new students as a solution to the problem of accuracy. This study uses two ANFIS models, namely Backpropagation and Hybrid techniques. The application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) model in the predictions of new students at Buana Perjuangan University, Karawang was successful. Based on the results of training, the Backpropagation technique has an error rate of 0.0394 and the Hybrid technique has an error rate of 0.0662. Based on the predictive accuracy value that has been done, the Backpropagation technique has an accuracy of 4.8 for the value of Mean Absolute Deviation (MAD) and 0.156364623 for the value of Mean Absolute Percentage Error (MAPE). Meanwhile, based on the Mean Absolute Deviation (MAD) value, the Backpropagation technique has a value of 0.5 and 0.09516671 for the Mean Absolute Percentage Error (MAPE) value. So it can be concluded that the Hybrid technique has a better level of accuracy than the Backpropation technique in predicting the number of new students at the University of Buana Perjuangan Karawang
Google Bert- Multiple Choice Question Generation on Ontology Base

Data mining is the ability to identify useful information from raw data and process the useful information in a separate list. The process of extracting useful information from big data source is known as ontology. In current days the semantic web is becoming a more trending topic for a lot of new research inventions. Multiple Choice Question Generation is one of the hot topics which are becoming a challenge for semantic web developers. By using this ontology model, a lot of researchers try to proposed MCQ item generation by giving sample phrases or sentences, or paragraphs for the system and try to generate the MCQ automatically based on those phrases. Hence in this proposed paper, we try to design an MCQ item generation system and we try to label that system as OntoQue. The proposed application is evaluated and tested using Deep Learning NLP pre-trained model like Google BERT, through which we can able to extract the MCQ generation for a summary. In the primitive methods, we try to use Long Short-Term Memory (LSTM) networks in order to learn order dependence in a sequence manner, but this is failed to achieve 100 % accuracy in training bulk amount of data and there is also a problem in LSTM like vanishing gradient problem through which some quantity of data vanishes while training the machine. For testing the proposed application we try to use the Stanford question answering dataset, in which the data set combines more than 1one lakh questions in SQuAD1.1 with over fifty five thousand unanswerable questions written adversarial by crowd workers to look similar to answerable ones. The proposed model can accurately train with this dataset and this can try to generate the desired result for any type of text summary which we try to enter for the system.
Research Liaisons: the next layer of Facilitation

Research productivity has been greatly enhanced by Research Computing Facilitation teams to help researchers maximize their use of advanced cyberinfrastructure. However, researchers have more technology needs than just advanced cyberinfrastructure, such as data management and instrument device support. To address this, the Academic Engagement team in Michigan Medicine added Research Liaisons as another layer of human support on top of the Facilitation team.
Large-Scale Quantitative Evaluation of Dialogue Agents’ Response Strategies against Offensive Users

As voice assistants and dialogue agents grow in popularity, so does the abuse they receive. We conducted a large-scale quantitative evaluation of the effectiveness of 4 response types (avoidance, why, empathetic, and counter), and 2 additional factors (using a redirect or a voluntarily provided name) that have not been tested by prior work. We measured their direct effectiveness on real users in-the-wild by the re-offense ratio, length of conversation after the initial response, and number of turns until the next re-offense. Our experiments confirm prior lab studies in showing that empathetic responses perform better than generic avoidance responses as well as counter responses. We show that dialogue agents should almost always guide offensive users to a new topic through the use of redirects and use the user’s name if provided. As compared to a baseline avoidance strategy employed by commercial agents, our best strategy is able to reduce the re-offense ratio from 92% to 43%.
Methods for studying the library fund: state and development

The socio-historical factors in the development of methods for studying the library fund through the prism of the formation of the conceptual and scientific-theoretical apparatus of fund science, as well as the process of improving the methodology of library science research are characterized. The formation of these methods is analyzed in connection with the development of the theory and methodology of fund science as an integral part of library science in the context of the transformation of the forms of library activity, the expansion of new methods of organizing and methods of analyzing the library fund, due to the emergence of information and digital technologies.
Variational Problems and the Calculus

The origin of the calculus of variations and the problems of the catenary and the brachistochrone.
Gated Extra Memory Recurrent Unit for Learning Video Representations

Convolutional recurrent neural networks (ConvRNNs) are widely used for spatiotemporal modeling tasks including video frame prediction. A major drawback of existing ConvRNNs is the amount of computing and memory resources, which can hinder practical applications on embedded devices. Thus, to reduce them, we propose 1) a new gated architecture of the recurrent unit with temporal memory and 2) the replacement of computationally demanding convolution with a more light-weight Hadamard product. Adopting such constraints can degrade the performance, but we show that the proposed model produces better results with reduced computation and memory. Quantitative evaluation with the Moving MNIST dataset shows that the overall performance of video frame prediction is improved by 13% in terms of MSE and by 3% in terms of SSIM without increasing the number of parameters and their multiplications, compared with the conventional ConvLSTM baseline. Further, applying the Hadamard product replacement outperforms the baseline MSE by 5%, while reducing the number of parameters by 14% and the number of multiplications by 25%.
Professional Deformations of Bailiffs with Different Professional Efficiency

The study purpose is to identify and describe the professional deformations types of bailiffs with different professional efficiency. Research methods are questionnaires and multivariate statistical analysis methods. The study used the author’s questionnaire for assessing the professional deformation types and work performance subjective assessment by law enforcement officers. The study involved 277 federal bailiffs service employees of the Arkhangelsk region. The bailiffs are characterized by a high level of such professional deformations as overcontrol, conservatism and authoritarianism. By means of a two-stage cluster analysis, all employees are divided into three groups according to the professional performance level (low, medium and high) according to their subjective assessment. Bailiffs with a low professional performance level are distinguished by a higher professional aggression, behavioral transfer, conservatism and learned helplessness level. Authority, overcontrol, and anxiety do not have statistically significant differences in groups, which may be due to their positive impact on employee performance.
Anti-phishing with google extension 3H1M using blacklist algorithm / Muhammad Hafiz Ramli … [et al.]

The advancement of technologies has rapidly risen for the past few years, which brings a lot of benefits especially to the users. However, the developments have also contributed many security issues, where security attacks have also become more advanced. Phishing is one of the security attacks that describe spoof emails or websites to trick users into exposing their personal or any confidential information. Hence, this project develops a solution, 3H1M extension, to help in mitigating the phishing issues when browsing the Internet. This extension will compare the visited website URL with the blacklisted website lists in the database to identify the validity of the website. If the user is visiting a malicious website, a pop-up message will be displayed on the screen and the user will be directed to the search engine page. A comparison is made between a web browser implemented with and without the 3H1M extension. It can be observed that the extension is able to help the users to distinguish between the real and malicious websites.
Gesture Controlled Robot For Human Detection

It is very important to locate survivors from collapsed buildings so that rescue operations can be arranged. Many lives are lost due to lack of competent systems to detect people in these collapsed buildings at the right time. So here we have designed a hand gesture controlled robot which is capable of detecting humans under these collapsed building parts. The proposed work can be used to access specific locations that are not humanly possible, and detect those humans trapped under the rubble of collapsed buildings. This information is then used to notify the rescue team to take adequate measures and initiate rescue operations accordingly.