Reviewerly/exHarmony huggingface dataset:
Cultural Congruence of Websites: Conscious, Unconscious, or Coincidental? – The Case of Honda Cars

Introduction. This paper analyses the cross-cultural website design strategy of a division of a single multinational company, namely Honda Cars.Method. We conducted a content analysis of sixty-one Honda Cars websites, each targeted at a different country.Analysis. We perform t-tests and compute Pearson correlations to verify and quantify the cultural convergence of the Honda Cars websites. We use novel regression analyses to explain the deviations between the culture reflected in the websites and the culture of the country the sites are targeted at.Results. We find that the sites of Honda Cars are by and large culturally congruent – for all the dimensions of national culture originally proposed by Hofstede and Hall. The templates that some regional offices of Honda Cars provided to their branches thus do not appear to have overly constrained local developers in creating a culturally sensitive site. Finally, the sites show a higher degree of localisation when the Internet penetration in the country is high and a lower localisation degree when the country has an extreme score on a specific cultural dimension.Conclusions. Our results suggest that the observed cultural congruence is partly deliberate and partly accidental.
A Study on the Impact of Satisfaction with Public Libraries on Using and Recommending Intention

As the South Korean government has recently announced its intention to implement a three-year policy on building additional libraries and complex community centers as the community-based everyday life SOC project, society has shed new light on libraries as public service institutions. Accordingly, this study was conducted to determine the factors affecting resident satisfaction with public libraries, intention to use, and intention to recommend public libraries, for use as basic data to increase resident satisfaction and use of public libraries in South Korea. To this end, we conducted a survey on residents who have experience with using 13 public libraries designated as regional representative libraries in South Korea. The surveyed data was verified with structural equation using AMOS. The results were as follows. First, all factors, such as material, facility, staff, program, and service, except location and space, had a significant effect on resident satisfaction with public libraries. Second, it was found that satisfaction had a significant effect on intention to use and intention to recommend. The results of this study may contribute to qualitatively improving public library services by reflecting the changing needs of users, as well as social trends at the working level of libraries in the South Korean society. URL:  http://ijkcdt.net/xml/24907/24907.pdf
Deep Neural Network Optimization for Handwritten Text Recognition

These days a large number of handwritten documents are available in scanned images. The aim of Handwritten Text Recognition (HTR) is to transcribe the offline document images by a computer through the use of deep neural networks. Even though hybrid architectures, designed for this purpose are gaining popularity, we aim to further optimize the prescribed models by changing the hyperparameters associated with the number of convolutional neural network layers on the overall accuracy. We explore the implementation of hybrid architectures and show that mainly the depth of the network plays a noteworthy role in improving the accuracy of the trained model.
Controlling CRISPR Through Law: Legal Regimes as Precautionary Principles

Since its advent in 2012, CRISPR has spawned a cottage industry of bioethics literature. One principal criticism of the technology is its virtually instant widespread adoption prior to deliberative bodies conducting a meaningful ethical review of its harms and benefits — a violation, to some, of bioethics’ ‘‘precautionary principle.’’ This view poorly considers, however, the role that the law can play — and does, in fact, play — in policing the introduction of ethically problematic uses of the technology. This Perspective recounts these legal regimes, including regulatory agencies and premarket approval, tort law and deterrence, patents and ethical licenses, funding agencies and review boards, as well as local politics. Identifying these legal regimes and connecting them to the precautionary principle should be instructive for bioethicists and policy makers who wish to conduct ethical reviews of new applications of CRISPR prior to their introduction.
Measurable and Deployable Security

Security measurement helps identify deployment gaps and present extremely valuable research opportunities. However, such research is often deemed as not novelty by academia. I will first share my research journey designing and producing a high-precision tool CryptoGuard for scanning cryptographic vulnerabilities in large Java projects. That work led us to publish two benchmarks used for systematically assessing state-of-the-art academic and commercial solutions, as well as help Oracle Labs integrate our detection in their routine scanning.
Study on the Quality Requirements and Training System of College Student Cadres in the New Era

The difference between student cadres and ordinary students is that they have three layers of identities: students, managers, and coordinators. Therefore, training and improving the quality of student cadres not only help to improve their own qualities, but also helps counselors to do good student work. In this regard, this article expounds on the current qualities and surviving problems that college student cadres should possess, as well as the main problems in the current cultivation of college student cadres, and on this basis, puts forward several training program suggestions.
Best Computer For Unity Development

Game design and development raise stock in the market with more people venturing into this territory, with a need to leave ones mark and produce a game ...
Research Guides: Off-Campus Library and Interlibrary Loan Services: Home

This LibGuide outlines the policies and procedures for off-campus students, faculty & staff utilizing the services and resources of the Shapiro Library.
Strengthening Women’s Participation in the Traditional Enterprises of sub-Saharan Africa: The Role of Corporate Social Responsibility Initiatives in Niger Delta, Nigeria

The purpose of this paper is to critically examine the multinational oil companies (MOCs) corporate social responsibility (CSR) initiatives in Nigeria. Its special focus is to investigate the impact of the global memorandum of understanding (GMoU) on development of rural women’s traditional enterprises in the Niger Delta region. A total of 2400 women were sampled across the region. Results from the use of a combined propensity score matching and logit model indicate that the GMoU model of the CSR has recorded significant success in supporting farming and fishing transformation generally; but has also undermined those initiatives that focused on empowering rural women in traditional enterprises, due to the cultural and traditional context in the region. This causes both direct harm to women and their children, and wider costs to African economies. It implies that if the GMoU interventions are not targeted to raise women’s economic status and to deter aggression, invariably they may contribute towards reducing the participation of women in economic, political and social development and, by extension, dampen efforts in deterring poverty and achieving the sustainable development goals (SDGs) in sub-Saharan Africa.
Research Guides: Off-Campus Library and Interlibrary Loan Services: Borrowing Shapiro Library Materials

This LibGuide outlines the policies and procedures for off-campus students, faculty & staff utilizing the services and resources of the Shapiro Library.
Application to Predict The Number of Applicants for New Students With a Time Series Model

Problems that will be faced by higher education institutions, especially in the phase of new student admissions. Careful planning and strategies are needed in dealing with the process of admission of new students. The data for planning can be obtained using the forecasting method. The time series forecasting model is used to get forecasting data. Forecasting data is used for the decision making process. The data of new student admissions obtained is 3-period data (2017 - 2019). The data obtained is stationary. Because the data is stationary, the data does not need differentiation. The data obtained also has a sufficient correlation value, and has a loop on the 7th lag. Before making an application, a test is performed to find a time series model that is suitable for admission data. The tested models are the ARIMA model and the AutoRegression model. In testing the forecast timespan, the ARIMA model gets a smaller error value in almost all tests. In the Cross-validation method, the ARIMA Model also gets a smaller RMSECV or MAECV value than the AR model. The ARIMA model was chosen to be implemented into the application. The auto_arima algorithm is used so that applications can adapt to different data. The ARIMA model is implemented into a prediction application using the Python programming language. Application development uses Django as a web-based web application framework. Bootstrap is used to create application interfaces.
Blue Valley Libraries: The Rise of Industry: Project

Choose a prompt and research historical and contemporary events surrounding the chosen issue.
Criminological Analysis of the Crime concerning Organ Trafficking

While organ transplantation is increasingly used as a medical treatment, the main factor limiting its application remains the lack of available organs. In general, the kidney is the most commonly transplanted organ, being a life-saving solution for patients with end-stage renal failure . Living donors can donate a kidney anda part of the liver. Equally, heart and liver transplantation is frequently practiced. Other organs such as the lungs, pancreas and small intestine can also be transplanted. And it should also be taken into consideration that new types of organ transplants are being worked on. It should be mentioned that all organs can be donated after death.
A complex question answering system based on knowledge Graph in Terahertz Domain

At present, the terahertz Q&A system can only answer simple single entity questions, so it is difficult for people to retrieve and obtain effective information. In order to deal with diversified questions in Terahertz field and realize the function of complex questions in Terahertz field, a multi-entity question answering model is proposed in this paper. To deal with complex problems in terahertz field, this paper proposes a multi-round Q&A method for multi-entity recognition, and adds entity discrimination to improve the accuracy of named entity recognition. The method in this paper achieves the F1 value of 68.24% in CCKS2019CKBQA test set and F1 value of 85.33% in Terahertz data set. The method in this paper implements complex questions in the Terahertz domain.
The DataFrame API

In this chapter, we will be having a look at the DataFrame API, which is the core API that we will use with .NET for Apache Spark. Apache Spark has a couple of different APIs, the Resilient Distributed Dataset (RDD) and DataFrame APIs, for processing. We will cover what the APIs are and why the RDD API is not available in .NET and that it is fine; the DataFrame API gives us everything we need.
Research Guides: Off-Campus Library and Interlibrary Loan Services: Using the Shapiro Library's Electronic Resources/Databases

This LibGuide outlines the policies and procedures for off-campus students, faculty & staff utilizing the services and resources of the Shapiro Library.
SIBINAS (Sistem Informasi Bina Skripsi) (Studi Kasus: Prodi Sistem Informasi UIN Raden Fatah Palembang)

The main problem in this research is college student difficulties in the process of undergraduate thesis such as document, find out which titles were accepted, find out who the supervisor professor and examiner lecturers are, along with undergraduate thesis scheduling. The purpose of this research is to facilitate the activities of the undergraduate thesis coaching process in universities which in this case the case object of research is information systems study program of UIN Raden Fatah Palembang. This research uses a spiral software development methodology. This spiral methodology has advantaged that users can understand the information system well and guarantee the information system properly in accordance with user requests, this is because users can observe and participate in evaluating the information system during its development.
Interventions Recommendation: Professionals' Observations Analysis in Special Needs Education.

We present a new task in educational NLP, recommend the best interventions to help special needs education professionals to work with students with different disabilities. We use the professionals’ observations of the students together with the students diagnosis and other chosen interventions to predict the best interventions for Chilean special needs students.
Exploiting Vulnerabilities in Deep Neural Networks: Adversarial and Fault-Injection Attacks

From tiny pacemaker chips to aircraft collision avoidance systems, the state-of-the-art Cyber-Physical Systems (CPS) have increasingly started to rely on Deep Neural Networks (DNNs). However, as concluded in various studies, DNNs are highly susceptible to security threats, including adversarial attacks. In this paper, we first discuss different vulnerabilities that can be exploited for generating security attacks for neural network-based systems. We then provide an overview of existing adversarial and fault-injection-based attacks on DNNs. We also present a brief analysis to highlight different challenges in the practical implementation of adversarial attacks. Finally, we also discuss various prospective ways to develop robust DNN-based systems that are resilient to adversarial and fault-injection attacks.
Quantum Circuit Synthesis Using Projective Simulation

Quantum Computing has been evolving in the last years. Although nowadays quantum algorithms performance has shown superior to their classical counterparts, quantum decoherence and additional auxiliary qubits needed for error tolerance routines have been huge barriers for quantum algorithms efficient use.These restrictions lead us to search for ways to minimize algorithms costs, i.e the number of quantum logical gates and the depth of the circuit. For this, quantum circuit synthesis and quantum circuit optimization techniques are explored.We studied the viability of using Projective Simulation, a reinforcement learning technique, to tackle the problem of quantum circuit synthesis. The agent had the task of creating quantum circuits up to 5 qubits. Our simulations demonstrated that the agent had a good performance but its capacity for learning new circuits decreased as the number of qubits increased.
Design and Implementations of Spherical Robot Hardware Level

In this paper, development of the mobile platform for the spherical robot is considered. A three-omni-wheeled mobile robot was selected as a driving mechanism. The actuators of the mobile robot are DC motors with a transistor bridge circuit as a driver. The results of testing motors for determining linearity of the system are presented as well as a closed-loop speed control system for each motor is implemented. The paper presents a description of the architecture of hardware level and related software.
Using linguistic features to predict the response process complexity associated with answering clinical MCQs

© 2021 The Authors. Published by Association for Computational Linguistics . This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://aclanthology.org/2021.bea-1.23
문제중심학습 기반 STEAM 현장체험학습 프로그램이 초등과학 영재의 과학 탐구 능력, 창의적 문제해결력 및 과학적 태도에 미치는 영향

In this study, a problem-centered learning based STEAM field experience learning program was developed and the effects of applying it were investigated. The program was composed of 8 sessions by using problem-centered learning education method and integrating STEAM elements between disciplines. The contents of program are as follow. In the step of sharing problems and making a problem-solving plan, they understood the various examples and meanings of endangered species, explored the project activities, and made an inquiry plan. In the search and re-exploration phase, a smart device was used to investigate the appearance, habitat environment and cause of extinction for Clithon retropictus, and a site inquiry plan was established for each group. Then, they moved to the field to explore brackish-headed gallops and discuss ways to protect endangered species. In the step of creating a solution, a web-based report was produced as the final product using smart devices based on the results of the inquiry. In the presentation and evaluation stage, the produced web-based report was used to present each group, conduct mutual evaluation, and organize project activities. The developed program was applied to 6th grade 29 students enrolled in the J University Gifted Education Center. In order to find out the effectiveness of the program, tests of science process skill, creative problem-solving ability, and scientific attitude were conducted before and after of program learning, and the results were statistically analyzed by t-test. In addition, a STEAM program satisfaction test was conducted after project in order to find out the satisfaction of the class. As a result of application of the program, the results were significantly improved in openness, criticism, and creativity among the sub-factors of creative problem-solving ability and scientific attitude. Satisfaction with the STEAM program was also high, but no significant result was found in science process skill. Therefore, the program of this study could be influenced on improvement of creative problem-solving ability and scientific attitude of gifted students in elementary science.
Performance Evaluation of Video Compression Using Different Wavelets and Tensors for Multimedia Applications

The main objective will be the exploitation of the redundancies in the image to reduce the requirement of number of bits required to represent a particular original image which should remain less significant and also should be irrelevant to human visual system. With the limited bandwidth, the compression process should enable us to store and as well as transmit the video signal in the effective manner. JPEG2000, MPEG, AVC, H.264, H.265, lossy or lossless are the some of the algorithms available in the market which are based on these compression standards. Discrete Wavelet Transform(DWT) has remained as popular algorithm for video compression. We have discussed different wavelets such as Symlet, Haar, Biorthogonal, Daubechies in this paper, along with tensors decomposition were used to compare the performance analysis of the video compression for multimedia applications. Four different wavelet based compression methods like SPIHT-3D, STW & EZW, SPIHT-3D and SPIHT were used to verify the base layer with 2 enhancement layers and are considered to be the best among all. We used different input video formats like WMV, AVI and MPEG to compared the wavelets and used the parameters like compression ratio, Retained energy and Peak Signal to Noise ratio to observe the output in MATLAB.
Detection of Phishing E-Mails: A Learning-Based Approach

Cyberspace has become an integral part of our life. We use cyberspace for various purposes like sharing information, interaction, business activities, in discussions, to express our opinions on forums and storing confidential data. But at the same time, in the recent years, cyber attacks have been increased rapidly, and it has become a major concern to the most of the organizations and networks. Specifically, spear phishing is the most commonly used attack vector to breach the security, and it has caused severe damage to the target network such as stealing login credentials, credit card numbers, and delivery of malware. So phishing E-Mail has imposed severe challenges to the cyber security. In fact, E-Mail phishing has become a major concern and complex threat to the organizations and networks. It is possible for attackers to achieve their goal by just collecting a small amount of information about a target. Through this paper, we have proposed a phishing E-Mail detection method. This paper includes feature extraction from E-mail, building a dataset and a classification module consisting of linear SVM, multinomial Naive Bayes and logistic regression classifiers. And our experimental observations proved that logistic regression classifier performs better, and it gives an accuracy of 99%.
Linear Regression on Internet Banking Adoption Dataset Using WEKA

Data mining or knowledge discovery in the database (KDD) is an excellent process to find out valuable information from a large collection of data. Data mining has successfully been used in different fields such as medical, marketing, banking, business, weather forecasting, etc. For the banking industry, data mining, its importance, and its techniques are vital because it helps to extract useful information from a large amount of historical data which enable to make useful decisions. Data mining is very useful for banking sector for better acquiring and targeting new customers and helps to analyze customers and their transaction behaviors. In the recent era, a new technology that has achieved considerable attention, especially among banks, is internet banking. Its large scope of applications, its advantages brings an immoderate change in a common human's life. Linear regression is one of the most commonly used and applied data mining techniques. Linear regression is really a very fast and simple regression algorithm and can give the best performance if the output variable of your data is a linear grouping of your inputs. In this paper, the linear regression is applied on internet banking adoption dataset in order to compute the weights or coefficients of linear expression and provides the predicted class value. The analysis here is done with the help of WEKA tool for data mining.
Faster and louder

Sébastien Erard’s most famous invention for the piano was the double-escapement action, which allows the pianist to rapidly repeat a given note without completely releasing the key, thus rendering the key and the hammer totally independent from each other. This action revolutionised the design of piano mechanisms and had a profound impact on music written for the instrument. Far from being an isolated discovery from the 1820s, Sébastien’s invention was the culmination of a lifetime of searching for ways to make the piano more responsive to the musician’s touch, all the while maintaining a powerful tone.
A abstratização de evidenciais no português brasileiro, no espanhol dominicano e no italiano

This article presents the result of an investigation on the development of more abstracted microconstructions based on predicative lexical evidential structured with the prototypical dicendi verb. Three Romance languages ​​were contrasted: Brazilian Portuguese (BP) ( dizer ), Spanish (ESP) ( decir ) and Italian (IT) ( dire ). The evidential semantic domain concerns the source of the enunciated knowledge (Aikhenvald 2004; Casseb-Galvao 2001) and its coding can occur by lexical and/or procedural elements. The main hypothesis involves the recognition that across languages more prototypical lexical uses originate processes of constructional changes of abstract evidentials, with grammatical or discursive meanings, as [ diski ], in PB, ( decir ), in ESP and si dice che , in IT.