Reviewerly/exHarmony huggingface dataset:
Stealing Your Data from Compressed Machine Learning Models

Machine learning models have been widely deployed in many real-world tasks. When a non-expert data holder wants to use a third-party machine learning service for model training, it is critical to preserve the confidentiality of the training data. In this paper, we for the first time explore the potential privacy leakage in a scenario that a malicious ML provider offers data holder customized training code including model compression which is essential in practical deployment The provider is unable to access the training process hosted by the secured third party, but could inquire models when they are released in public. As a result, adversary can extract sensitive training data with high quality even from these deeply compressed models that are tailored for resource-limited devices. Our investigation shows that existing compressions like quantization, can serve as a defense against such an attack, by degrading the model accuracy and memorized data quality simultaneously. To overcome this defense, we take an initial attempt to design a simple but stealthy quantized correlation encoding attack flow from an adversary perspective. Three integrated components-data pre-processing, layer-wise data-weight correlation regularization, data-aware quantization, are developed accordingly. Extensive experimental results show that our framework can preserve the evasiveness and effectiveness of stealing data from compressed models.
Leveraging Structured Metadata for Improving Question Answering on the Web.

We show that leveraging metadata information from web pages can improve the performance of models for answer passage selection/reranking. We propose a neural passage selection model that leverages metadata information with a fine-grained encoding strategy, which learns the representation for metadata predicates in a hierarchical way. The models are evaluated on the MS MARCO (Nguyen et al., 2016) and Recipe-MARCO datasets. Results show that our models significantly outperform baseline models, which do not incorporate metadata. We also show that the fine-grained encoding’s advantage over other strategies for encoding the metadata.
Analisis Faktor Eksternal terhadap Perilaku Belajar Siswa SMA Patra Dharma Kota Balikpapan

&lt;p&gt;&lt;em&gt;This study aims to determine the effect of family environment and peer interaction on the learning behavior of XI SMA Patra Dharma Balikpapan students. Samples were obtained by means of random or random sampling techniques, with a sample of 95 students. How to collect data in this study by distributing questionnaires to class XI students of Patra Dharma High School students. To prove the hypothesis in this study by using t test and F test. The results of this study indicate that partially family environment, peer interaction affects the learning behavior of class XI students of Patra Dharma High School Balikpapan, this is shown by looking at the value of t count 2.223&amp;gt; t table 1,660 for family environment variables and t count 2,946&amp;gt; t table 1,660 for peer interaction. Whereas simultaneously the family environment, peer interaction affects the learning behavior of XI Patra Dharma Balikpapan class XI students, this is indicated by the calculated F value of 9.204 greater than Ftable = 3,098.&lt;/em&gt;&lt;/p&gt;
Comparing CGI, SSI, Flask, and Django

In this chapter, we will compare all the dynamic HTML page creation tools introduced so far. Each system has strengths and weaknesses and should be chosen with care. This will make it a lot easier to choose the system that fits your requirements.
A Geotemporal Clustering Model for COVID-19 Projection

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The Brain and Cognitive Processes

Our mental activity originates in the brain and is inseparable from its physico-chemical processes. So be it. However, this observation leaves open considerable problems, both for the empirical sciences (biology, chemistry, physics) and, from the more abstract point of view, for the relations between thought and its material roots.
Clinical prediction models for patients diagnosed with breast cancer: A systematic review

Background: Clinical prediction models provide insight in the probability of an event based on the combination of multiple predictor variables. Predicted probabilities may support clinical decision making. It is currently uncertain how many prediction models exist to support decision making in breast cancer care, which outcomes can be predicted, and which predictor variables are necessary to predict these outcomes. We aimed to systematically review prediction models that may be used to guide clinical decision making in patients who have been diagnosed with breast cancer.
Penerapan Algoritma Backpropagation Pada Pengenalan Tanda Nomor Kendaraan Bermotor Untuk Kartu Parkir Berbasis RFID

This research was conducted to improve a parking system's security using Radio Frequency Identification (RFID) technology to open parking barriers. To open the parking barriers, you must use an RFID card that has been registered to the system. There is no license plate checking on the parking system so that the RFID card can take other vehicles from the parking lot. Therefore, the RFID card needs to be linked with the license plate data using pattern recognition with an Artificial Neural Network. In this parking system, the backpropagation algorithm will be applied to identify the characters from the license plate's image captured with the camera. Information on parked vehicles can be seen through a web- based application that the administrator can only access. Also, this application can view the history of previously parked vehicles. Based on the calculation of accuracy using the confusion matrix, the backpropagation algorithm to identify the characters in this parking system has an accuracy value of 85.7%.
A Study on the Relationship between the Admission Motivation and Learning Status of Doctoral Students of Engineering

This study conducted an empirical study on the motivation, learning status and influencing factorsof engineering doctoral candidates in 9 doctoral authorized institutions in Guangdong Province. The resultsshowed that the primary motivation of the doctoral students in engineering was to enhance their scientificresearch ability and enhance their employment competitiveness. Different types of PhD students inengineering are divided according to the Education Range Theory. The research suggests that we shouldstrengthen the training of scientific research, consolidate the research foundation of students, improve theproportion of non-directional doctoral students, improve the award system, improve the training quality andteaching service, and improve the training quality of doctoral students in physical education.
Application of two-way narrative intervention in emergency department nurses under the novel coronavirus pneumonia epidemic

Objective: To investigate the difference in work stress between emergency department nurses and non-emergency department nurses under the novel coronavirus pneumonia epidemic, analyze the work pressure source in emergency department nurses, and propose two-way narrative nursing intervention Methods: The basic situation questionnaire form and the current domestic nurses work pressure source scale were used to investigate and evaluate the nurses in the emergency department and other general departments under the novel coronavirus pneumonia epidemic Two-way narrative method was taken for stepwise intervention of the emergency department nurses Results: It was found via investigation and evaluation that there was no statistically significant difference between the basic situation of emergency department nurses and non-emergency nurses (p0 05), while there was statistically significant difference in work pressure source (p0 05) After one month of narrative nursing intervention, there were no significant differences in work pressure source in terms of time distribution and workload, working environment, patient care, management and interpersonal relationship (p0 05) Conclusion: By two-way narrative intervention, it is possible to timely find and reduce the work pressure of nurses, thus providing a direction and basis for superiors work coordination and medical security in special departments under the novel coronavirus pneumonia epidemic
Perancangan Busana Streetwear Untuk Generasi Z Dengan Konsep Zero Waste Fashion Design

Abstract Fashion has become one of the media used by a person to express themselves towards society. Streetwear fashion is on the middle way towards becoming a fashion trend further looked up to by the majority of urban society, most especially generation z. However, in the current modern era, there are not many teenagers willing to explore local culture such as the use of traditional fabric to support their daily attire or as fashion. Products that tend to be monotonous make traditional fabric difficult to reach the younger community, especially regarding fashion. Aside from that, the retail fashion phenomenon also has a hand in the shift of traditional fabric, particularly woven lurik fabric. This research aims to create eco-friendly designs by using a zero waste fashion design technique, with the use of woven luric fabric implemented in street style. Aside from being an attempt to conserve traditional fabric towards the generation z, these designs have been able to compress the waste created in the production process to below 15%. Keywords: Generation Z, Lurik Woven Fabric, Streetwear, Zero Waste
The role of e-learning as a response to crises in reducing the spread of the coronavirus a study of the decisions of higher education and scientific research in the hashemite kingdom of Jordan

The study aimed to identify the role of e-learning in limiting the spread of the Coronavirus through the decisions of the Ministry Higher Education in the Hashemite Kingdom of Jordan The study consisted of 10 university presidents in Jordan The descriptive analytical approach was used in the study The arthematic means of e-learning came with a high degree of evaluation from the perspective of university presidents in the Hashemite Kingdom of Jordan, and this indicates the effectiveness of those methods in limiting the spread of the Coronavirus among students The application of these methods contributed to alleviating mixing among students, and this in turn helps in reducing the spread of the virus The results also showed that the preferred scenario among university presidents for the fundamental transformation that is related to the spread of the Coronavirus in terms of controlling and limiting it, is the application of the means and mechanisms of e-learning and the decisions and generalizations of the Ministry of Higher Education and Scientific Research in Jordan are an important stage in the recovery of Jordan and limiting the virus spread The reason for the confirmation of university presidents is linked to the positive results in the application of e-learning to reduce this phenomenon © 2020, Hampstead Psychological Associates All rights reserved
LibGuides: Internet of Things and Its Use in the Library Space: Home

This is a LibGuide on Internet of Things (IoT), which is specifically created for the students, researchers and professionals in the library field. General introduction to the topic.
LibGuides: LIbrary Basics: Library Catalog

This guide is intended as an overview to the finding resources within the library to help you get started!
Making Connections: ETDs, Academe, and the World of Work

In the dissertation process, graduate students ideally become practitioners in their field of study. They do not just absorb, analyze, and critique research as they do in their coursework; they join the community of scholars and scientists and carry out research. They become part of the disciplinary conversation. As professionals who interface with graduate students and their advisors, what are some roles that we can play to enhance the dissertation experience? In particular, what can we do that will assist our students in developing the best chance for a good job when they reach completion, whether that job is in academe or in the non-profit, government, or commercial sector? In this talk, Lippincott will focus on four areas in which we can provide graduate students with important 21 st century skills: Ability to employ digital tools and data management practices most utilized in their field of study Ability to make choices within the scholarly communications and intellectual property systems Ability to understand reputation management Ability to communicate research findings to the public Her presentation will also suggest how professionals who work with ETDs can accelerate change and offer practical suggestions for how institutions can provide better support in these areas for graduate students. Video:  https://youtu.be/TU6pg19itM0
A comparative study of search engines results using data mining and statistical analysis

Web search engines are keys to the immense treasure of information. Dependency on the search engines is increasing drastically for both personal and professional use. It has become essential for the users to understand the differences between the search engines in order to attain a higher satisfaction. There is a great assortment of search engines which offer various options to the web user. Thus, it is significant to evaluate and compare search engines in the quest of a single search engine that would satisfy all the needs of the user.
The Effects of College Education and Job Match on Activities to Change Jobs of College Graduates

본 연구는 대졸자의 대학교육과 직무일치가 이직 활동에 미치는 영향을 분석하였다. 연구 목적을 달성하기 위해서 노동시장의 격차를 고려하여 수도권 대학 졸업자와 비수도권 대학 졸업자를 구분하여 비교·분석을 실시하였다. 분석은 고용노동부와 한국고용정보원이 조사하고 있는 2018년 대졸자 직업이동 경로조사(2017GOMS) 자료를 활용하여 통제변인(개인배경), 대학교육, 직무일치 변인을 각각 선정하여 이항 로지스틱 회귀모형 분석을 실시하였다. 이에 본 연구의 분석결과는 다음과 같다. 첫째, 개인배경 변인 중 모든 분석 결과에서 비정규직이 정규직에 근무하는 대졸자보다 이직 활동을 할 확률이 더 높은 것으로 나타났으며, 직장만족도가 낮을수록 이직 활동을 할 확률이 더 높은 것으로 나타났다. 그리고 전체 대학 및 수도권 대졸자 분석 결과에서는 여성이 남성보다 이직 활동을 할 확률이 더 높은 것으로 나타났으며, 비수도권 대학 대졸자 분석 결과에서 성별은 통계적으로 유의미한 차이가 나타나지 않았다. 둘째, 대학교육 변인 중 모든 분석 결과에서 진로 및 취업 프로그램 참여 횟수가 많을수록 이직 활동을 할 확률이 더 높은 것으로 나타났다. 그리고 전체 대학 및 수도권 대졸자 분석 결과에서는 졸업 평점이 낮을수록 이직 활동을 할 확률이 더 높은 것으로 나타났으며, 비수도권 대학 대졸자 분석 결과에서 졸업 학점은 통계적으로 유의미한 차이가 나타나지 않았다. 셋째, 직무일치 요인 중 모든 분석 결과에서 현재 일자리 수준보다 과잉교육을 받았다고 판단한 대졸자가 적정교육 및 과소교육을 받았다고 판단한 대졸자보다 이직 활동을 할 확률이 더 높은 것으로 나타났다. 그리고 전체 대학 및 수도권 대졸자 분석 결과에서는 현재 일자리 수준보다 과잉기술을 습득하고 있다고 판단한 대졸자가 적정기술 및 과소기술을 습득하고 있다고 받았다고 판단한 대졸자보다 이직 활동을 할 확률이 더 높은 것으로 나타났으며, 비수도권 대학 대졸자 분석 결과에서 과잉기술은 통계적으로 유의미한 차이가 나타나지 않았다.The purpose of this study is to examine the effects of college education and job match congruence on activities to change jobs of college graduates. Because of the differences of labor market in regions, this study examined and compared two areas, the capital region and the not-capital region. The study analyzed the data, 2018 Graduates Occupational Mobility Survey(2017GOMS), collected by the Ministry of Employment and Labor and the Korean Employment Information Service. The factors are as follows: personal characteristic, college education, and job match. First, the analysis of all college graduates among the individual background variables showed that non-regular workers were more likely to change jobs than those who work full-time, and that the lower the job satisfaction, the more likely they were to change jobs. And all metropolitan college graduates analyses showed that women were more likely to change jobs than men, while non-metropolitan university graduates analyses showed no statistically significant difference in gender. Second, the analysis of all college graduates among university education variables showed that the more they participated in career and employment programs, the more likely they were to change jobs. And the analysis of university graduates in the entire university and metropolitan area showed that the lower the graduation grade, the more likely they were to move, and the analysis of college graduates in non-metropolitan areas showed no statistically significant difference. Third, among the factors of job role congruence, the analysis of all college graduates showed that college graduates who judged that they received excessive education were more likely to change jobs than those who judged that they had received proper and under-education than current job levels.
Improving Students' Speaking Skill Through Debate Technique (An Action Reserach At Grade X Of MAS Amaliyah Sunggal)

This research was aimed to find out the implementation of Debate Technique to improve students’ achievement in speaking skill. The subject of this research was at tengrade of MAS Amaliyah Sunggal in academic year 2019/2020. The research was conducted by using Classroom Action Research. The technique of analyzing data of thisresearch was using qualitative and quantitative data. The qualitative data were gained from observation sheet, interview. The quantitative data were taken from the tests such as: pretest and post-tests. The result of the analysis showed that the mean of the pretest was 64,516. The mean of the post-test in the first cycle was 73, 225. Then the mean of the posttest in the second cycle was 77,387. It showed that the implementation of debate technique could improve students’ achievement in speaking skill. The students’ were more active, creative, interactive, brave and confident in the learning activity. Therefore, it can beconcluded that the implementation of debate technique was effective to improve thestudents’ achievement in following the learning teaching process.
Postmodernity and proactive educational environment

We live in a time that is marked by the characteristics of a society that most modern researchers call postmodernity (Sarup, 1993). This trend, which emerged as an eclectic movement in aesthetics and philosophy, today manifests in all spheres of humanities and life - philosophy, psychology, sociology, ethnology, demography, etc.
Implementasi Dan Analisis Security Auditing Menggunakan Open Source Software Dengan Framework Stride

Abstrak Security Auditing merupakan sistem evaluasi terhadap perilaku jaringan untuk pengguna atau peralatan, dan kemudian memberikan petunjuk untuk mencegah terjadinya serangan. Penelitian ini bertujuan untuk menentukan risiko dari vulnerability dan threat pada vulnerability operating system (VulnOSv2) dan merupakan salah satu komponen untuk penyusunan Security Auditing System. Dengan digunakannya 10 walkthrough, dapat dilakukannya analisis perbandingan pada setiap tahapan dan juga penerapan tools secara cepat, tepat dan akurat. Simulasi yang dilakukan untuk menemukan vulnerability scanning dan attack pada walkthrough dengan menerapkan sebuah vulnerability operating system pada VirtualBox sebagai objek penelitian dan menggunakan open source software yaitu OpenVAS. Hasil analisis dari relasi antara data vulnerability dan threat berupa risiko secara kuantitatif dan kualitatif. Kemudian disusun dengan menggunakan attack tree yang dihubungkan berdsarkan Framework STRIDE untuk penyusunan Security Auditing system. Kata kunci : Security Auditing, Open Source, Tools, Klasifikasi, Attack Tree, Framework STRIDE Abstract Security Auditing is an evaluation system of the network behavior for the user or equipment, and then provides instructions to prevent the occurrence of an attack. The research aims to determine the risks of vulnerabilities and threats to operating system vulnerabilities (VulnOSv2) and denote as a component for the preparation of a security auditing system. With the use of 10 walkthroughs, comparative analysis can be done in Lot stages and also application of tools quickly, precisely and accurately. The simulation was done to find the scanning vulnerability and attack on the Walkthrough by implementing on operating system vulnerabilities on VirtualBox as an object research and using open source software called OpenVAS. The results of the relationship analysis between vulnerability and threat data are risk of quantitative and qualitative. Then compiled by using an attack tree associated with the STRIDE Framework for preparing the Security Auditing system. Keywords : Security Auditing, Open Source, Tools, Classification, Attack Tree, STRIDE Framework
Misogyny: a hate crime or a private affair? : A socio-cultural study of the intersection between hate crime legislation and men’s violence against women

Hate crime and men’s violence against women are two well-recognised and highly prioritised human rights phenomena in both international and local contexts. Yet, the idea of linking the two phenomen ...
Semi-supervised Lesion Detection via Image Restoration

Lesion detection is a critical task for medical image understanding. While the problem has been widely addressed in a supervised semantic segmentation manner, the problem clinically appears more similar to novelty detection with few or no annotations for the lesion. The reason is two-fold: 1) it is intuitively easier to collect large dataset from healthy individuals than that from a specific type of lesion individuals, 2) clinicians are generally interested in any abnormalities regardless of its type. This makes unsupervised methods more attractive solutions. Works such as AnoGAN and VAE with image restoration offer practical ways to localise lesions by training only on healthy data. However, for the same type of lesion, an obvious performance gap exists between unsupervised and supervised methods. In this work, we intend to provide supervision with a small number of lesion data to the unsupervised method with the aim to narrow the gap. The method is an extension of the unsupervised method of VAE with MAP-based image restoration. In more details, we train an U-Net on the few examples to predict the likelihood term and impose the supervision with annotated lesions such that the restoration only occurs for the lesion pixels. We train the unsupervised method on T2-weighted images of healthy individuals of Cam-CAN dataset and provide a small annotated dataset consisting of a few subjects from BraTS dataset, and test on an unseen subset of BraTS. With the addition of the few examples, the method shows an improvement over the unsupervised method while the gap with the supervised is narrowed but still exists. (Less)
Global Law Enforcement Software Market

Global Law Enforcement Software Market was valued at US$ 9.8Bn in 2019 and is expected to reach US$ 23.5Bn by 2027, at a CAGR of
Densely-Connected Transformer with Co-attentive Information for Matching Text Sequences

Sentence matching, which aims to capture the semantic relationship between two sequences, is a crucial problem in NLP research. It plays a vital role in various natural language tasks such as question answering, natural language inference and paraphrase identification. The state-of-the-art works utilize the interactive information of sentence pairs through adopting the general Compare-Aggregate framework and achieve promising results. In this study, we propose Densely connected Transformer to perform multiple matching processes with co-attentive information to enhance the interaction of sentence pairs in each matching process. Specifically, our model consists of multiple stacked matching blocks. Inside each block, we first employ a transformer encoder to obtain refined representations for two sequences, then we leverage multi-way co-attention mechanism or multi-head co-attention mechanism to perform word-level comparison between the two sequences, the original representations and aligned representations are fused to form the alignment information of this matching layer. We evaluate our proposed model on five well-studied sentence matching datasets and achieve highly competitive performance.