Reviewerly/exHarmony huggingface dataset:
European Cybersecurity Perspectives

2018 is a difficult year to summarize for Infosec. After the initial flurry of activity around Spectre and Meltdown in the beginning of January, we ended the year with global supply chain concerns brought about by the Super Micro story. Throughout the year we saw the geopolitical dilemmas of 2018 manifest in cyber security issues. Technology giants like Facebook and Google had a security reckoning. However in pure scariness the medical data breaches of MyHeritage (DNA) and MyFitnessPal (health) rank higher. The Starwood Marriot Hotel breach made every travelling executive nervous for the rest of the year, but probably not as nervous as the incident of CEO Fraud at Pathe. In an effort to alleviate some of that impact we are proud to publish the 6th European Cyber Security Perspectives (ECSP) report. The 2019 issue is filled with great articles from our partners ranging from government, universities and private companies. Special thanks goes out to all the partners who have submitted an article for the 6th edition of the ECSP. Also huge hugs to first time authors from de Piratenpartij, de Volksbank, Leiden University, University of Illinois, Hack in the Box and QuSoft. If IoT was the buzzword in 2017 then Artificial Intelligence (AI) was most definitely in 2018. AI and security seem to be intertwined and that is why you will find several articles about AI in this issue. This year the organization of Hack in the Box created a challenge which you can find at the bottom of the centerfold. There are great prizes involved so make sure to try your luck.
Spatio-Temporal Action Localization in a Weakly Supervised Setting

Enabling computational systems with the ability to localize actions in video-based content has manifold applications. Traditionally, such a problem is approached in a fully-supervised setting where video-clips with complete frame-by-frame annotations around the actions of interest are provided for training. However, the data requirements needed to achieve adequate generalization in this setting is prohibitive. In this work, we circumvent this issue by casting the problem in a weakly supervised setting, i.e., by considering videos as labelled `sets' of unlabelled video segments. Firstly, we apply unsupervised segmentation to take advantage of the elementary structure of each video. Subsequently, a convolutional neural network is used to extract RGB features from the resulting video segments. Finally, Multiple Instance Learning (MIL) is employed to predict labels at the video segment level, thus inherently performing spatio-temporal action detection. In contrast to previous work, we make use of a different MIL formulation in which the label of each video segment is continuous rather then discrete, making the resulting optimization function tractable. Additionally, we utilize a set splitting technique for regularization. Experimental results considering multiple performance indicators on the UCF-Sports data-set support the effectiveness of our approach.
Unblocking Blockchain Potentials

The goal of this paper is to research and present the current developments and future prospects of the blockchain technology throughout economy. Since it was introduced within the Bitcoin, blockchain became a buzzword repeated everywhere, often a proposition of panacea for the global problems. However, in the meantime the world of cryptocurrencies experienced a typical boom-bust cycle which many left wandering if blockchain technology was anything more than a hype. This paper aims to establish a brief overview of the possible implementations of distributed ledger (blockchain) technology in the context of the fast growing information society: blockchain may be the essential tool in the economy based upon Internet-of-things, new mobile connectivity standards and big(ger) data.
Entanglement classification via integer partitions

In [M. Walter et al., Science 340, 1205, 7 June (2013)], they gave a sufficient condition for genuinely entangled pure states and discussed SLOCC classification via polytopes and the eigenvalues of the single-particle states. In this paper, for $4n$ qubits, we show the invariance of algebraic multiplicities (AMs) and geometric multiplicities (GMs) of eigenvalues and the invariance of sizes of Jordan blocks (JBs) of the coefficient matrices under SLOCC. We explore properties of spectra, eigenvectors, generalized eigenvectors, standard Jordan normal forms (SJNFs), and Jordan chains of the coefficient matrices. The properties and invariance permit a reduction of SLOCC classification of $4n$ qubits to integer partitions (in number theory) of the number $2^{2n}-k$ and the AMs.
Baseline Monitoring of Elemental Contamination Levels in Soil Samples in Elebele Community, Bayelsa State, Nigeria

This study evaluated the physico-chemical properties of the soil and water in Elebele Community in Ogbia Local Government Area of Bayelsa State, Nigeria. Standard sampling and analytical methods were employed. The predominant soils of the region are mainly sandy-loam and clayey-loamy. The soil physico-chemical properties were in good status as they were not toxic. Soil particle size distribution (sand silt and clay) was observed as follows: sand content ranged between 50.6%-86.2% with a mean of 64.5% at the surface soil while the subsurface soil ranged between 35%-80.2% with a mean of 60.2%. Silt on the other hand ranged between 7.8%-36% and a mean of 25.1% at the surface and ranged between 12.8-49.6% and mean of 25.4% at the subsurface while clay ranged between 3.4%-16% and mean of 9.4% at the surface and also ranged between 7%-16% and mean value of the soil. However, the soil physical properties were relativity good for sustainability. Also, the metals studied were detected in all the sites. Generally the concentrations of the metals were highest at the top soils. This is expected since the top soil is the point of contact. The metal levels in all the sites were significantly higher than the levels observed in the control sites. Sources of heavy metals in soils like inorganic fertilizers and pesticides need to be controlled.
Organization of career support and development by means of building an individual educational trajectory

The current stage of socio-economic development of Russia is characterized by intensive changes in the field of interaction between the labor sphere and the education system. In terms of the organization of career support and development as a structural unit of the pedagogical process aimed at the development of the function of self-realization of the individual, we consider the situation of self-realization as a complex multilateral phenomenon, causing the result of the assimilation of material and personal development. A prerequisite for the development of educational trajectories is the developed and implemented in practice monitoring system, which is based on the following principles: purposefulness, continuity, integrity and diversity, consistency of actions of its subjects, targeting and publicity of the extracted information. A necessary condition for the development of educational trajectories is continuity, which provides: the unity of goals and objectives of the educational process; the content and methods of work of the teacher and students at all stages of their development; common understanding of the development laws, which reveal the relationship of learning, education and personal development. Analysis of the forms of joint activities of different educational institutions found that multi-level integrated training of specialists is carried out on the basis of the interaction of different types of professional educational institutions that retain legal independence, and meaningful one – on the basis of successive curricula and optimization of the content of academic disciplines. There are a number of problems that are being slowly solved: training of professional personnel lags behind the pace of structural adjustment of high-tech industries, there is a “washing out” of high-tech expensive specialties, the demand of national production is significantly ahead of the supply of educational institutions in terms of volumes and structure of personnel training, etc.
Economics of Entrepreneurship Activities of Muslim Youth Corpers In Kano State, Nigeria.

The majority of Nigerians live on less than $1.90 per day, which clearly reflects Nigeria’s high level of poverty. Sadly, the younger generation is being severely affected by this adverse situation. With the population of youth being approximately sixty eight million however, the country could reduce the level of poverty by further promoting youth engagement in entrepreneurship.The promotion of entrepreneurship could make a positive impact and encourage economic growth and development. This white paper is an attempt to investigate the economics of entrepreneurial activities of Muslim youth corps members in Kano state. Its focus is as follows:Identify various entrepreneurial activities by the Youth Corp Members.Examine the factors determining their participation in entrepreneurship activities.Suggest solutions to identified constraints of entrepreneurial activities.A multistage sampling technique was used to select sixty respondents among corps members and primary data was collected with structured questionnaires. The data was analyzed using descriptive and inferential statistics. The results revealed that more than 80% of the respondents were between 20-30 years of age.  The majority of the respondents were male and 90%  were non-native, while 40% engaged in entrepreneurship.The inferential statistics showed that age, level of parents’ education, stipends received and membership of an association, determined participation in entrepreneurial activity. The study therefore recommends awareness creation on the importance of skill acquisition and implementation for income generation among the youth, as well as enactment and implementation of appropriate governmental policies to boost entrepreneurship of economic growth.
Robust Model Selection for Finite Mixture of Regression Models Through Trimming

In this article, we introduce a new variable selection technique through trimming for finite mixture of regression models. Compared to the traditional variable selection techniques, the new method is robust and not sensitive to outliers. The estimation algorithm is introduced and numerical studies are conducted to examine the finite sample performance of the proposed procedure and to compare it with other existing methods.
Redesigning the isolation room for schizophrenia patients after a partial remission stage

In rethinking and formulating the design or redesigning the isolation room or schizophrenia patient's bedroom in in the details of the spatial elements in this research will focus on the shape and color of the cell wall elements or the bedroom of schizophrenic patients. Further research of the meaning of space for humans and to recommend specific design of the space is expected to help minimize the negative behavior of schizophrenic patients condition. This research will identify whatever the effect and the trigger on how the wall element in terms of shape and color can intervene to the behavior of schizophrenic patients. Architecture and human behavior are for humanity. By using descriptive qualitative research methods based on behavioral research in an architectural perspective, direct observation, in-depth interviews untill interviews with psychiatrists and also discussing these results with the theory that became the objective background for the assessment of spatial parameters. Emphasizes on the simple architectural products to be tested directly with a scale of 1: 1 using architectural fabrication techniques, redesigning of the isolation room of catatonic paranoid schizophrenia patients after a partial remission stage which led to the formulation of a new design of simple architectural products of this research will be one of the beginning for the development on the multidisciplinary science for the advancement of human science in the future. The analysis of the spatial behavior of the patient will be mapped and taken into absolute consideration for designing architectural wall products for schizophrenic patients with the age over 15 years.
PENGGUNAAN MEDIA PEMBELAJARAN BAHASA INGGRIS DI SD YPK YOKA BARU KOTA JAYAPURA, PAPUA

Teaching English as a foreign language in Indonesia is challenging. The purpose of this program is to overcome several of the many challenges in teaching English, that is the use of teaching media. Conducted in SD YPPK Yoka Baru, Jayapura, the method used is participation which involves students from English Department, FKIP Uncen. The activities include preparing, designing, and demonstating the teaching media. The result shows that using teaching media is effective to improve the students’ motivation in learning English.Keywords: teaching english, the teaching media, student, Jayapura
Integration of airborne (SkyTEM) and ground (Dias) large-volume electrical survey data for delineation of new deposits

Summary The study is a result of integrated interpretation of SkyTEM data collected in 2017 and Dias ground data, collected in 2018 as a follow-up survey. The integrated interpretation is a result of collaboration between Aurora Minerals Group of Kazakhstan and Canadian-based Promiseland exploration, Ltd. Analysis and inversions of SkyTEM data resulted in successful discovery of a new gold-bearing deposit with Au contents up to 10 g/t as well as delineation of four new areas with potential for gold-bearing mineralization, which were further followed up by Dias ground 3D DC/IP surveys. The main challenges in the application of electrical methods were low contents of sulphides in mineralized zones, which result in weak EM anomalies, which however yield high apparent chargeability values (not detectable directly by airborne surveys). Another challenges were presence of highly conductive overburden, limiting penetration of airborne EM sygnal as well as extremely large ground data-sets due to 3D multi-electrode configurations. The challenges were met by using state of the art 3D inversions of ground DC/IP data run on a dedicated server, which resulted in 7 new drill-targets subject to upcoming 2019 drilling operations.
P-ODN: Prototype based Open Deep Network for Open Set Recognition

Most of the existing recognition algorithms are proposed for closed set scenarios, where all categories are known beforehand. However, in practice, recognition is essentially an open set problem. There are categories we know called "knowns", and there are more we do not know called "unknowns". Enumerating all categories beforehand is never possible, consequently it is infeasible to prepare sufficient training samples for those unknowns. Applying closed set recognition methods will naturally lead to unseen-category errors. To address this problem, we propose the prototype based Open Deep Network (P-ODN) for open set recognition tasks. Specifically, we introduce prototype learning into open set recognition. Prototypes and prototype radiuses are trained jointly to guide a CNN network to derive more discriminative features. Then P-ODN detects the unknowns by applying a multi-class triplet thresholding method based on the distance metric between features and prototypes. Manual labeling the unknowns which are detected in the previous process as new categories. Predictors for new categories are added to the classification layer to "open" the deep neural networks to incorporate new categories dynamically. The weights of new predictors are initialized exquisitely by applying a distances based algorithm to transfer the learned knowledge. Consequently, this initialization method speed up the fine-tuning process and reduce the samples needed to train new predictors. Extensive experiments show that P-ODN can effectively detect unknowns and needs only few samples with human intervention to recognize a new category. In the real world scenarios, our method achieves state-of-the-art performance on the UCF11, UCF50, UCF101 and HMDB51 datasets.
Creating Lightweight Object Detectors with Model Compression for Deployment on Edge Devices

To achieve lightweight object detectors for deployment on the edge devices, an effective model compression pipeline is proposed in this paper. The compression pipeline consists of automatic channel pruning for the backbone, fixed channel deletion for the branch layers and knowledge distillation for the guidance learning. As results, the Resnet50-v1d is auto-pruned and fine-tuned on ImageNet to attain a compact base model as the backbone of object detector. Then, lightweight object detectors are implemented with proposed compression pipeline. For instance, the SSD-300 with model size=16.3MB, FLOPS=2.31G, and mAP=71.2 is created, revealing a better result than SSD-300-MobileNet.
LibGuides: Qualtrics Training: About Qualtrics

Qualtrics is a simple web-based survey tool that provides the opportunity to conduct online survey research, evaluations, and many other data collection activities..
Alleviating the translation-ambiguity disadvantage: Using a placeholder to signal an upcoming translation

Translation-ambiguous words are words with two or more translations across languages. These words are remembered less accurately and at slower rates than words with only one translation (so-called translation-unambiguous words; e.g., Eddington & Tokowicz, 2013; Tokowicz & Kroll, 2007). Previous research has investigated different training methods that could reduce the translation-ambiguity disadvantage. Degani et al. (2014) found that presenting multiple translations in the same session improves retention of translation ambiguous words compared to training translations in different sessions. The current study explores the effects of informing second language learners that a word has multiple translations, and that the second one will be presented later in vocabulary training. We predicted that the use of a placeholder will produce similar accuracy results as training both translations in the same session, however, this is only observed when participants’ individual differences are considered.
A Latent Variational Framework for Stochastic Optimization

This paper provides a unifying theoretical framework for stochastic optimization algorithms by means of a latent stochastic variational problem. Using techniques from stochastic control, the solution to the variational problem is shown to be equivalent to that of a Forward Backward Stochastic Differential Equation (FBSDE). By solving these equations, we recover a variety of existing adaptive stochastic gradient descent methods. This framework establishes a direct connection between stochastic optimization algorithms and a secondary Bayesian inference problem on gradients, where a prior measure on noisy gradient observations determines the resulting algorithm.
The Formation of Core Qualities of Teachers in Higher Vocational Colleges Under Big Data

With the advent of big data era, network technology has gradually infiltrated into higher vocational education teaching work.In the context of big data, in the face of online open teaching resources, the role of teachers is faced with unprecedented challenges.Teachers should follow the development trend of big data, use data information technology to promote modern teaching mode, and realize The Times demand of data-driven teaching practice.In this regard, teachers in higher vocational colleges should follow the trend of The Times, update their inherent concepts, and use data technology to improve their big data literacy so as to better serve the teaching work.Based on the connotation of core quality of teachers in higher vocational colleges, this paper puts forward the basic requirements for core quality of teachers in the new era, so as to carry out targeted training and improve their professional knowledge and skills and data processing skills.
A Generalized Construction of Codebook Asymptotically Meeting the Welch Bound

In this letter, as a generalization of Luo et al.'s constructions, a construction of codebook, which meets the Welch bound asymptotically, is proposed. The parameters of codebook presented in this paper are new in some cases.
PERUBAHAN PROGRESIF DALAM PEMBELAJARAN PAI BERBASIS TEKNOLOGI INFORMASI DAN KOMUNIKASI

This article explains about PAI learning by utilizing information and communication technology (ICT). PAI learning in Indonesia needs to be integrated with ICT, because it can open various avenues for teachers to more easily convey material and learners can also more easily understand. Illustrations which in the past were only made by teachers by drawing manually and made with paper, have now changed with the presence of a variety of good hardware and software. Learning by utilizing ICT can change the paradigm and teaching and learning process, both from the teacher and students.The progressive changes can be felt together, provided that all education providers support by providing various types of facilities
UNGKAPAN BUDAYA DALAM KARYA SASTRA REMAJA: ASPEK-ASPEK KARAKTER REMAJA AMERIKA DALAM PRADA AND PREJUDICE KARYA MANDY HUBBARD

Culture-bound words has become potential issues in understanding texts due to their specific connotation and implication in the language expressing the culture. Since language is not merely a classification of a set of general and universal concepts, but more importantly that each language articulates or organizes the world differently, then concepts may be distinctly encapsulated in different languages. Culture involves aspects of intellects and arts in a society. Elements of culture in a society involves customs, beliefs, lifestyle, attitude, social organization and habits and arts in the given society.The topic of the study is cultural-bound expressions in literary works as a product of a culture. The study focuses on cultural-bound expressions in young adult literature (YAL). YAL is chosen as the object of study for its phenomenal growth and development since late 20th century and early 21st century. The study chooses Mandy Hubbard’s Prada and Prejudice (2009) as the data source due to the wide range aspects of American culture being presented in the work. The study found that the cultural bound expressions are found in various environments, including family, school, peer group and society. The study also discusses the ideas of freedom and individual rights, responsibility, morality and pragmatism as the underlying notions of the expressed cultural concepts being expressed in the character of the work. The study is expected to contribute to better cultural understanding of American teenage culture as expressed in young adult literature. young adult literature, American values , cultural bound expressions
한국 대학생들의 요약하기 능력 부족에 관한 질적 연구

The main purpose of this paper is to examine the reasons for the gap between Korean college students’ lack of summarizing ability and achievement...
Illumination enhanced face Recognition for smart access system

Principle Component Analysis (PCA) is a widely used technique in the field of face recognition. Any system will have its own pros and cons. One of the disadvantages of PCAis its bonding with the light variation. By focusing on this issue, an improved algorithm is proposed by combining PCA with the Fast Fourier Transofrm-2. This solution is thenapplied to a real time environment which provides the smart access to the house. The user interface is provided using the Android application installed on the user’s smart phone.The communication between the smart access system and the application can happen remotely. The mechanical door lock is controlled using the system which can receive andtransmit the command