Reviewerly/exHarmony huggingface dataset:
En upprepande slump eller ett andrafierande mönster? - En undersökning om strukturell diskriminering på grund av etnisk tillhörighet inom domstolsväsendet

Over the past decades, The Swedish National Council for Crime Prevention has conducted two studies showing that immigrants in Sweden and people with foreign backgrounds are overrepresented amongst crime suspects. As migration to Sweden increases these studies have received more attention. Nationalistic and social conservative parties are taking advantage of the situation, why the political climate has hardened; to such extent that it is now considered a threat to Sweden’s national security. This polarization can, to some degree, be seen within the Swedish judiciary. Previous research has evidenced structural discrimination against ethnic minorities in Swedish courts. In this study I therefore examine whether structural discrimination against ethnic minorities occurs in a selection of rape judgements and if so, how this occurs. A prerequisite for the occurrence of structural discrimination against ethnic minorities is however the creation of “the Other”, which at the same time entails defining “the Self”. The study is divided into two parts; in the first part I take inspiration from a discourse psychological approach and analyse my selection of judgements. Here I identify discourses sorted into different themes, that illustrate in what way the court creates “the Other” and portrays the “the Self”. The second part consists of a statistical analysis and I give an account of the choice of sanction and the length of sentence in the judgements where the Court of Appeal has adjudicated the case. I also make a comparison between defendants, which I have divided into three categories. This part is moreover preceded by a chapter where I, by applying a legal dogmatic method, give an account of the Swedish system of criminal sanctions and the applicable regulations in the Penal Code for determination of penalties. The aim is to examine whether it is possible to see any negative discrimination in practice, against people that have another ethnicity other than Swedish. The study shows that immigrants are sentenced to longer imprisonment sentences in comparison to ethnic Swedes. In the majority of these cases there is also an underlying discourse where the court creates “the Other”. Accordingly, this indicates the occurrence of structural discrimination because of ethnicity. Since the criminal acts and circumstances are not identical, it is not possible to say how the court would have adjudicated in a similar case, if the defendant would have been an ethnic Swede. However, a common denominator for these cases, where the defendant is an immigrant, is that they all have a foreign citizenship. This fact itself indicates a risk that ethnicity is consistently a factor taken into account when the court chooses a sanction, which cannot be explained just by stating that different circumstances occurred. (Less)
A Survey of Deep Learning Techniques in Natural Language Processing Applications

Language communication is a natural phenomenon that happens in humans but considered as hard for computer systems. Natural Language Processing is a branch of computer science that acts as a link between computers and natural communication languages. This helps machines to recognize, and analyze the commands given in human interaction languages and to process the commands. Data gets converted into more significant one if its context is understood deeply. When the data is understood in depth, text analysis and text mining become easier. Natural Language Processing plays a vital role in aid of human generated data comprehension. This result in grasping of the context-dependency of data as a logical consequence. With the emergence of Artificial Intelligence and Deep Learning that has redefined the data analysis tasks in a variety of domains; Natural Language Processing comes as a unanimous choice of tool in training computer systems. In this paper, we have reviewed the state-of-the-art methods available for Natural Language Processing and Deep Learning.
STUDENTS’ TARDINESS HABIT TO ATTEND THE CLASS AT THE STUDENTS OF STIE MUHAMMADIYAH MAMUJU

This article aims at providing a description of students’ tardiness habit to attend the class at the very students of STIE Muhammadiyah Mamuju. This research employed qualitative research. The participants constituted nine students, three lecturers, and three administrators. The instruments were involvement observation, in-depth interview sheet, focus group discussion sheet, and additional questionnaire. The data were transcribed, reduced, and analyzed descriptively.  It discovered that there were lots of students’ internal tardiness inhibitions and external tardiness inhibitions which impeded the students to be puctual to attend the lectures. Students’ tardiness shared profoundly negative impacts on themselves, lecturers, and other punctual students. It is eligible not to allow the tardy students to attend the class if they are late for 1 minute. However, tardiness policy for 15 minutes is given only for unavoidable lateness as long as there is a confirmation to the lecturers or even administrators via phone before the class. Corresponding author:  Hamzar Acha RH DOI: 10.24071/ijiet.2020.040213
Review:Developing a website analysis tool for vulnerability scanning and reporting

There are several software package security assurance tools offered that detects and report vulnerability in web application sites .The growth within the range and size of websites will increase the necessity for higher securing those websites. Manual testing and detection of web vulnerabilities will be terribly time overwhelming. machine-driven web Vulnerability Scanners (WVS) facilitate with the detection of vulnerabilities in web applications. Acunetix[1] is one in all the wide used vulnerability scanners. Acunetix is additionally straightforward to implement and to use. The scan results not solely give the small print of the vulnerabilities, however conjointly provide info concerning fixing the vulnerabilities. AcuSensor and AcuMonitor (technologies utilized by Acunetix) facilitate generate additional correct potential vulnerability results. One in all the needs of this paper is to orient current students of laptop security with victimization vulnerability scanners. Secondly, this paper provides a literature review associated with  security vulnerability scanners and also identifies a forms of vulnerabilities in internet application . This proposed work is going to be  feature deep neural network to enhance the accuracy of vulnerability scanner. These can facilitate the website designer and therefore the user to scan and secure the website with high accuracy.
Understanding distributed data &amp;#8211; a semantic web approach for data based analysis of NDT data in civil engineering

&amp;lt;p&amp;gt;In the field of non-destructive testing (NDT) in civil engineering, a large number of measurement data are collected. Although they serve as a basis for scientific analyses, there is still no uniform representation of the data. An analysis of various distributed data sets across different test objects is therefore only possible with high manual effort.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We present a system architecture for an integrated data management of distributed data sets based on Semantic Web technologies. The approach is essentially based on a mathematical model - the so-called ontology - which represents the knowledge of our domain NDT. The ontology developed by us is linked to data sources and thus describes the semantic meaning of the data. Furthermore, the ontology acts as a central concept for database access. Non-domain data sources can be easily integrated by linking them to the NDT construction ontology and are directly available for generic use in the sense of digitization. Based on an extensive literature research, we outline the possibilities that this offers for NDT in civil engineering, such as computer-aided sorting, analysis, recognition and explanation of relationships (explainable AI) for several million measurement data.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The expected benefits of this approach of knowledge representation and data access for the NDT community are an expansion of knowledge through data exchange in research (interoperability), the scientific exploitation of large existing data sources with data-based methods (such as image recognition, measurement uncertainty calculations, factor analysis, material characterization) and finally a simplified exchange of NDT data with engineering models and thus with the construction industry.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Ontologies are already the core of numerous intelligent systems such as building information modeling or research databases. This contribution gives an overview of the range of tools we are currently creating to communicate with them.&amp;lt;/p&amp;gt;
Heaton Park Dinosaur Safari

Join the Heaton Park dinosaur hunt and dino quiz download the lovexploring app to take part
CHALLENGE IN TECHNOLOGICAL INNOVATION

This article describes about the study based on document literature and documents review about the challenge facing in technological innovation. The writer has reviewed some reports and literarture relevance to this subject of the study. It is revealed that the challenge in technological innovation is to motivate youth to be interesting in study of Science, Technology, Engineering and Mathmatics (STEM). While the government is required to support the technology development in term of policy, financial and regulatory.
Mediational contents as propositional constituents

The objectives of the present paper are, firstly, to question the conception according to which propositional constituents are exhausted by the assignment of referential contents. Secondly, to argue that introducing the notion of mediational content is useful to provide a theory of meaning for expressions of a natural language. In order to achieve those objectives, I address the following issue: in what sense are mediational contents relevant to the determination of truth-conditions and to compose assertions?
An analysis of need and design of m-learning using scientific approach on electricity material in senior high school to stimulate higher order thinking skills

Abstract The purpose of this research is to create m-learning design can be used as learning supplement using scientific approach for stimulating students higher order thinking skill. This research used R and D method of ADDIE (Analyze, Design, Develop, Implementation, Evaluation), in this article limited to the design stage. The sample of need analysis consists of 67 Senior High School student and 14 Physics teacher in Lampung. The data of m-learning need is collected using a questionnaire and analyzed using quantitative descriptive analysis. Test design is carried out by the expert of physics (teacher and lecturer of physics). The result of this experiment are (1) scientific approach is not totally applied in physics learning in class yet. (2) lack of supportable learning media straightaway with K-13. (3) Teacher and student need supportable media matched with K-13 that is m-learning. M-learning design which uses a scientific approach for Electricity lesson has some characteristics such as interactive, having educative content, interactive module, presentation material, having electricity animation and videos, experiment simulation, summary, hyperlink to another sources, task, quiz, and discussion forum. The learning steps consist of observing, asking, trying, associating, and communicating. Synchronous learning activities are carried out for discussion forums, asynchronous for the other of it.
The Obstacle-Avoidance Path Planning for UAV Based on IOCAD

To plan the path for UAV flying in the complex, dense and irregular obstacles environment, this paper proposed an obstacle collision-avoidance detection model and designed an UAV path planning algorithm based on irregular obstacles collision-avoidance detection (IOCAD), which includes irregular obstacles pretreatment method. The proposed method uses the grid method to model the environment. Rough set theory and convexity filling are used to pretreat the obstacles, and the ray method is used to select the available points. The intersection detection and the distance detection are held for the obstacle to the flight path. The objective function minimizes the distance from the obstacle to the flight path to get planned paths. The simulation results show that the proposed method can effectively plan the paths with the constraints of the assumed environment and UAV performances. It is shown that the performance of the proposed method is sensitive to the grid length and safety distance. The optimized values for the grid length and safety distance are 0.5 km and 0.4 km respectively.
Object Detection System in Image Processing

An object detection system finds objects of the real world present either in a digital image or a video, where the object can belong to any class of objects namely humans, cars, etc. In order to detect an object in an image or a video the system needs to have a few components in order to complete the task of detecting an object, they are a model database, a feature detector, a hypothesiser and a hypothesiser verifier. This paper presents a review of the various techniques that are used to detect an object, localise an object, categorise an object, extract features, appearance information, and many more, in images and videos. The comments are drawn based on the studied literature and key issues are also identified relevant to the object detection. Information about the source codes and online datasets is provided to facilitate the new researcher in object detection area. An idea about the possible solution for the multi class object detection is also presented. This paper is suitable for theresearchers who are the beginners in this domain.
UIC-KORAIL Training Session 2020 on Railway Passenger Service based on IT Technology from 23 – 27 March 2020 in Seoul, Korea – UIC Communications

Register here: https://uic.org/events/uic-korail-training-session-2020 It is our great pleasure to invite you to the UIC-KORAIL Training Session 2020 on Railway Passenger Service based on IT…
MAP PROBABILISTIC DENSITY BASED SUBSPACE CLUSTERING FOR DIMENSIONALITY REDUCTION OF BIG DATA ANALYTICS

Density based subspace clustering algorithms focus on finding dense clusters of random shape and size. Most of the existing density based subspace clustering algorithms in the literature is less effective and accuracy while taking big dataset as input. In order to overcome such limitations, a MAP Probabilistic Density based Subspace Clustering (MAPPD-SC) Technique is introduced. The MAPPD-SC technique is designed for high dimensional data to improve the clustering accuracy and dimensionality reduction. Initially MAPPD-SC technique designs Map Probabilistic Density Based Subspace Clustering (MPDSC) algorithm with aim of grouping the similar data with higher accuracy and minimum time utilization. During big data clustering, the MAPPD-SC technique applies the maximum a posteriori (MAP) calculation with the goal of clustering more related data together and thereby forming optimal number of clusters with high accuracy. After completing clustering process, the MAPPD-SC technique designs Fusion Tree Data Storage Structure (FTDSS) with objective of storing clustered big data with reduced space complexity. The FTDSS only stores bits values of clustered data in its memory by using fusion tree concepts. This generated bit values of input clustered data takes minimal amount of memory space. From that, proposed MAPPD-SC technique reduces the dimensionality of big data for effective big data analytics. Experimental evaluation of MAPPD-SC technique is carried out on factors such as clustering accuracy, clustering time and false positive rate and space complexity with respect to number of climate data using El Nino Data Set.
PARALLEL AND LOAD BALANCING APPROACH FOR MINING FREQUENT PATTERN ON UNCERTAINGRAPHS USING SPARK FRAMEWORK

The decision making process is important for variety of real time applications. The uncertain graph isused in bio-informatics, social media, and data analytics process. This paper provides the problem of changes in subgraph mining using uncertain graphs. The probabilistic and semantic mining is applied for efficient mining. Thefrequent patterns are collected and solve using semantics. The P-Complete approximation is applied for evaluationof algorithm and give guarantee to achieve mining performance. A single uncertain graph is taken for probabilisticsemantics and accuracy can be achieved using devise computation method. The frequent patterns are devised andgenerated uncertain graph for computations. This algorithm provides better result and achieves efficient mining. Theunexpected results are removed by semantic and checkpoint is used for validation. The experiments results are testedin real time dataset and results are compared with various models.
LibGuides: Federal Government Shutdown: Home

Delaware Libraries are here to help you with needed information during the federal government shutdown.
A CONTRASTIVE ANALYSIS BETWEEN  ENGLISH AND INDONESIAN NEGATIONS: A CASE OF NEGATIVE MARKERS

This research is aimed at determining the similarities, dissimilarities, and possible difficulties faced by Indonesian and English speaking students as learning negations and also the recommendations to TEFL. The descriptive-qualitative method was used. The documentation technique was applied in collecting the data. To analyze the data, the researcher used a descriptive analysis. The results showed that there were six similarities and four dissimilarites between English and Indonesian negations. The six similarities were in rejection or denial with verbs, adjectives, nouns, adverbs, “No” followed by nouns, and incomplete or undone action. The four dissimilarities were in confixation, suffixation, short prohibition and strong objection. The possible difficultes faced by English speaking students was in confixation, while Indonesian students’ was in suffixation and strong objection. The dissimilarities make recommendations to TEFL teachers to design teaching materials of English grammar that enable students understand negations.
Citations in chemical engineering research: factors and their assessment

The study explores citation pattern of the 4112 articles in the field of chemical engineering published from 1974 to 2018 and indexed in Web of Science. Apart from good quality research, a number of other factors may be responsible for citing and not citing an article. The study has also tried to explore such factors. Only the top 500 articles with the most number of citations have been analysed in-depth. The countries like United States of America (USA), China, Germany, United Kingdom (UK), France, Canada, India, Japan, Spain, Russia and Brazil have the highest number of articles. The investigators calculated Pearson correlation between the number of keywords, pages, references and citations and it showed that there is no relationship between the number of keywords and number of citations. The number of pages and the number of references in a publication have a significant and positive impact on the number of citations.
援?궡 ?곸뼱援먯쑁?먯꽌 English Literacy愿???곌뎄?숉뼢 遺꾩꽍

The present study is aimed at investigating the previous research findings about Englsih Listeracy (EL) of Korean EFL learners. In the study, 93...
Saving the world on a shoestring: Utilising cohort diversity and enhanced technology to bridge the higher education expectation gap

Saving the World on a Shoestring: Utilising Cohort Diversity and Enhanced Technology to Bridge the Higher Education Expectation Gap Introduction. Education is at the heart of global development goals, catalysing advancement towards decreased poverty and inequality. This policy context has led to a heightened demand for higher education (HE), with universities expected to contribute to global productivity, growth and social equality through the development of human capital (OECD, 2018). To achieve these outcomes, and within a context of declining HE government funding, HE institutions must ensure students receive a holistic experience that prepares them for real world employment and achieves outcomes that are greater than the sum of its parts. Curriculum designs and assessment practices are therefore creating tensions between standardisation and measurability, and the development of creative and reflective learners (Biggs and Tang, 2011). Global research also indicates an indifference to student diversity which has intensified to hostility for credential-focused domestic students (Arkoudis et. al. 2018). This research indicates that, while student diversity exists, genuine inclusion does not (Boulton, 2019). Aims. Focused on developing multicultural competence to provide psychologically safe learning environments for all students, the three-staged intervention involved more than 5,700 business/accounting students. Methods. Utilising culturally responsive pedagogies and learning technologies, a cross-discipline and cross-university, targeted intervention (Zhang and Zhou, 2019) was prepared and actioned over a twelve-year period (2008-2019). Results. Utilising anonymous and voluntary survey responses and formal, university reported grading statistics, the intervention outcomes included: a significant reduction in hostility levels between diverse group members; student satisfaction ratings averaging 87% to 100%; a minimum cohort average one-grade increase in pre versus post peer review process assessment outcomes; and low, unit-based, failure rates (PG: 2-3%; UG: 4-8%). Discussion. The data indicates that adoption of a holistic and inclusive focus for intercultural team building and peer review, has achieved a sustainable and potentially ‘exportable’ resource for supporting, influencing, motivating and inspiring heterogeneous student cohorts, and their teachers, to learn together.
Evaluation of the Performance of Tiny YOLOv3 based Drone Detection System with Different Drone Datasets

There are increasing use of commercial drones everywhere. These drones are used for differentpurposes in different domains. A few of its uses are carrying goods, monitoring crowd, and providing security.Sometimes it may be used for capturing information from secured areas by trespassing. In our earlier work, toeradicate such security threats, we have analyzed the existing techniques for flying object detection andclassification and designed a robust system based on YOLO object detection algorithm. In this work, we evaluatedthe performance of Tiny YOLOv3 based drone detection system with different datasets of different sizes. Tomeasure the performance, we used different metrics. The arrived results proved the significant improvement ofTiny YOLOv3 in performance.