Reviewerly/exHarmony huggingface dataset:
Conditional BRUNO : a neural process for exchangeable labelled data

We present a neural process that models exchangeable sequences of high-dimensional complex observations conditionally on a set of labels or tags. Our model combines the expressiveness of deep neural networks with the data-efficiency of Gaussian processes, resulting in a probabilistic model for which the posterior distribution is easy to evaluate and sample from, and the computational complexity scales linearly with the number of observations. The advantages of the proposed architecture are demonstrated on a challenging few-shot view reconstruction task which requires generalisation from short sequences of viewpoints.
Cognitive mapping of the public's risk perception based on gender and age in Saudi Arabia

Background: Humans process their lifetime experiences internally as mental images that constitute their cognitive maps, which they employ to recall and assess important features in their relative contexts. This study aims to develop a cognitive map of the public's risk perception based on gender and age in the unique Saudi cultural context. Methods: Data were collected using a self-administered survey measuring the public's perceived risk of nine common life hazards. Differences in gender (bivariate analysis) and age (correlation analysis) over each domain were presented. Cognitive mapping was developed. Results: Of the 317 participants, there were 211 (67.6%) females and 101 (32.4%) males with 32.5 ± 10.7 years as the mean and standard deviation of their age. A series of regression models showed that males had a better perception on the knowledge and control domain compared to females about the hazard of nuclear reactors (β = −0.2, adjusted P
Rate Adaptive Congestion Control Using Lookup Table Scheme to Enhance Quality of Experience

In recent years video communication has occupied a large percentage of Internet traffic and the trend is expected to increase. Many services are offered via the Internet use video content to reach millions of users. Real time video services in the Internet are mostly done by using User Datagram Protocol (UDP). UDP is preferable because it is fast, but has a weakness of not supporting congestion control mechanisms; hence it usually floods the channel it is using causing congestion which then leads to packet loss, excessive delay and jitter. To support good quality of experience (QoE), packet loss, delay and jitter must be kept at accepted values. This paper presents part of an ongoing MSc. research work whose aim is to develop a rate adaptive congestion control scheme using a lookup table. The scheme use Real Time Transport Protocol (RTP) and RTP Control Protocol (RTCP) to provide end to end network transport service which is not provided by UDP and control service. The proposed congestion control scheme comprises of two components:- a lookup table and congestion control equation. The lookup table is created at the beginning of sender’s application and keeps a record of fraction loss and Inter Packet Gap (IPG), which is the interval in time between sending packets. Upon receiving a report the lookup table is searched to see if there is a match for the report’s fraction loss value and returns, the appropriate IPG value. If there is no match a congestion control equation is used to compute a new IPG value, which is then added to the lookup table and used for rate adjustment. Simulation of the proposed work was done using NS3, where by the Quality of Service (Qos) parameter which affect the Quality of Experience (QoE) such as delay and jitter were observed. Elvavid, a video quality evaluation tool is used to measure the quality of video by using Peak Signal Noise Ratio (PSNR) and Mean Opinion Score (MOS) measurements.
An Efficient Public Auditing Method with Periodic Verification for Data Integrity in Cloud

With the huge development in cloud computing services, cloud storage becomes an important service for individuals and organization, with the capabilities of on-demand outsourcing application. After outsourcing the data, owner has no physical control over remotely present data. To verify the data integrity, several efficient cryptographic techniques related to provable data possession (PDP) were proposed to check the remote data integrity without downloading it from the cloud storage server. In this paper, with the knowledge of interactive PDP protocol, we propose an efficient public auditing method based on probabilistic queries and periodic verification to improve the performance of audit service. The method reduces the leakage of the data by public auditing and reduces the computational and communication cost of audit services by selecting the secured parameter. Our experimental result shows it incurs less communication cost.
Research Guides: Virtual Reality at UAB Libraries: VR Comment Form

This guide is intended to serve as a source of general information about the virtual reality tools and related services provided by the UAB Libraries. Virtual reality tools and services are intended to support UAB Libraries mission and that of the Univers
A Novel Negative Sample Generating Method for Knowledge Graph Embedding

In order to extract relation and reason efficiently in knowledge graphs, entities and relations are encoded into a continuous low-dimensional semantic space. In the negative samples generating stage, most knowledge graphs embedding methods pay more attention to replace head or tail entities for high-efficient training, and seldom to replace relations. These negative sample Generating methods contribute little for relation prediction. In this paper, we propose a new negative triplet generating method. Compared to those methods which replace only the entities such as TransE, TransH and TransR, the proposed method replaces both the entities and the relations in appropriate proportions. Experimental results on several classical data sets such as WN18 and FB15K show that the proposed method significantly outperforms original methods in the accuracy of the relation link prediction with little impact on the entity link prediction. According to the experimental results, we also find that the ability of the relation link prediction increases and the ability of the entity link prediction decreases when the proportion of the relations replacement probability increases.
Perbedaan Kemampuan Bahasa Anak Usia Prasekolah Antara Riwayat Diasuh Orang Tua dengan Riwayat Diasuh Selain Orang Tua

Introduction: The ability of language to communicate with others is also a combination of everything related to motor skills, psychology, and protection. Preschool age is the stage that occurs when children aged 3 to 6 years. In everyday life not all parenting is done by parents but also taken care of by parents. Test the language of children with the DDST (Denver Developmental Screening Test) test. Objectives: 1) study the language development of preschoolers raised by their own parents. 2) learn the language development of preschool preschoolers cared for by parents. 3) Comparing the differences in the language skills of preschoolers raised with parents Research Methods: the method used is descriptive comparative. Responding to 53 children, in the election using simple random sampling technique. Data collection using DDST (Denver Developmental Screening Test) sheet. Data analysis using Mann Whitney Test. Research Results: Based on the results of the Mann Whitney Test obtained P-value 0.004 <0.05. With a significant difference of opinion between children's language skills are taken care of by parents and a summary is taken care of other than parents. Parents take care of parents better than preschool parents. Conclusion: There is a significant difference between children's language skills raised by parents and a summary of care for other than parents.
Aspects of Swiss financial regulation

New technologies based on blockchain or DLTs such as cryptocurrencies, DAOs and decentralised applications changed and created a new deal in the regulatory framework. In this context, the question is not whether these technologies and the businesses they trigger impact financial regulation, but rather how they impact it and how regulators perceived them so far. Some may consider these technologies as a playground for start-ups only constrained into a Sandbox where regulators look out to them from the corner of their eyes. But most of the regulators have been forced to recognise that a specific evolution is here standing. From Switzerland to European institutions and international organisations, each major actor of the financial markets is now handling the same question, as to how to integrate the blockchain in the regulatory landscape. If blockchains really means decentralisation and distribution, how and where does regulators’ jurisdiction begins? Where is the tie-point of the regulation in that case? Did Switzerland develop the same approach? The author will first analyse the general considerations that one may take into account when approaching a regulation in this field, compared to what has been done in Switzerland, to finally make his own proposal as to how to handle the Swiss regulation by offering a 4-steps approach.
ITS4S3: A Video Quality Dataset With Unrepeated Videos, Camera Impairments, and Public Safety Scenarios

This technical memorandum provides technical details for the video quality subjective experiment its4s3. This experiment includes 594 videos, each 4 seconds in duration. The experiment consists of six sessions, each portraying a different public safety scenario. The goals of this experiment are to demonstrate a wide range of quality responses from digital video cameras; to present video sequences suitable for first responder tasks; to begin to understand the video quality difference between video used as evidence and video used for situational awareness; and to collect data from a more representational sampling of people than is usually possible, by conducting the experiment at a large meeting venue. The its4s3 dataset is intended to train no-reference (NR) video quality metrics. The dataset is freely available for research and development purposes.
Classroom Techniques Used By Tutors In TeachingSpeaking At Saturday English Gathering Program: ACase Study Of Muhammadiyah University Of Surakarta

This research aimed to describe: (1) the classroom techniques in teachingspeaking by the tutors of Saturday English Gathering (SEGA) of UMS, (2) thepurposes of using the techniques, and (3) the roles of the tutors and students. Thesubjects were the tutors at SEGA and the objects were the techniques used by thetutors. The type of this research was descriptive qualitative. The data collectiontechniques were observation, interview and documentation. Technique ofanalyzing qualitative data consisted of data reduction, data display, andconclusion or verification. The result showed three techniques used by the tutorsat SEGA, five purposes, three teachers roles and three students roles. Thetechniques were monolog presentation, dialogue, and discussion. The purposes ofusing the techniques for the students were: (1) to speak up more bravely, (2)improve students’ fluency, (3) drill speaking skill, (4) know more about grammar;and (5) know more vocabularies. The roles of tutors were explainer, facilitator,and commentator. The roles of students namely: the planner of their own learningprocess; learners were the member of the group; learners learned from teachers,students, and teaching sources.
All Types of Large Earthquakes Produce Prompt Gravity Signals

New observations of recently discovered gravity perturbations that precede seismic waves have the potential to improve earthquake early-warning systems in California and other tectonic settings.
Perspectives of a distributed future: aspects of criminal law

Virtual currency, or cryptocurrency, has become an important payment medium. Bitcoin is such a cryptocurrency and due to its importance, it is the primary focus of this chapter. It shall be discussed – from a Swiss criminal law perspective – which criminal offences may be committed with regard to this cryptocurrency, and which criminal law provisions may come into play in order to sanction the criminal behaviour. Some procedural aspects shall also be addressed – still based on the Swiss legal system as well as the relevant points of reference for the extra-/territorial jurisdiction under Swiss criminal law, which is an important aspect in particular with regard to the virtual nature of a cryptocurrency. Prosecution of offenders whose criminal behaviour involves bitcoins is limited in that bitcoins may not be the objects of any offence whose constituent elements require the presence of a movable good, since bitcoins have no physical equivalent in the form of coins or banknotes. ‘Theft’ of bitcoins is inconceivable under Swiss criminal law. But bitcoins fall within the scope of provisions related to data or with financial assets: therefore, offences committed in relation to bitcoins are prosecutable. However, current enforcement takes place barely by analogy and legal provisions will have to be developed to more adequately encompass bitcoin related offences. It is important to note that selling and purchasing bitcoins, as well as other activities relating to bitcoin trading platforms used for transferring funds or bitcoins, fall within the scope of the Anti-Money Laundering Act. We conclude, in sum, that virtual currencies do not evolve in a legal void, but it might become necessary to develop criminal law in order to capture more precisely the virtual nature and distinctive properties of cryptocurrencies. But, on the other hand, we observe that the actual lack of legal protection is precisely a consequence of the deliberate departure of bitcoin users away from government involvement towards a less regulated and less protected world, one that bitcoin users seem to seek. Asking than for an enhanced protection by criminal law would somehow be a paradox, as criminal law is the instrument of the monopolized public authority ‘par excellence’.
Proposta de nomenclatura de cor para pesquisa de impressos históricos

This paper fits in the research methodology of the investigation of a historical printing technique, chromolithography, and its commercial application in Brazil between 1876 and 1919.In the course of the research the necessity of adoption of a specific color nomenclature was identified, attending its objectives: color identification, characterization and differentiation.Color nomenclatures contemporary to the study period (mid XIX century to early XX century) were researched, until the adoption of a descriptive, logical and comprehensive system based on Munsell Color System, Universal Color Language and on the terminology proposed by ISCC-NBS.This proposal includes the execution of a chromatic reference scale, exemplifying its practical use in this research.
REVIEW OF METRICS EXTRACTION TOOL USING UML

In the present consequence, whole world depends on software. It is a cost effective way is essential because all countries depend on complex computer based systems. So it is a big challenge of the developers and researchers to adopt latest technologies which convert a highly complex system design into a simple design. Intended for this purpose, developers inspire the design and construction of computer-based systems by using reusable software which is called as component. A component can be deployed, as they possess the qualities such as reusability, stability, proper communication, modularity, testability, and complexity. The reusable components on integration interoperate with each other resulting in an operational application which is developed with minimum effort and low maintenance cost. We used Component Based Software Development (CBSD) process, which is based on the basic concepts of Object Orientated Techniques where Unified Modelling Language (UML) shows an important role. Different quality factors of a component are measured with the help of metrics, and there are number of metrics proposed for components. In this paper we proposed a methodology of static metrics for integration of software components, complexity metrics for UML Component-based System Specification (CBSS) and interface complexity metrics in a component assembly. These metrics are derived using UML artifacts. We derived these metrics by developing a tool named “CAME” (Component Assembly Metrics Extractor) in NetBeans which parses through the XMI file (XML Meta Data Interchange) generated by UML tool and produces different component metrics through graphic user interface. These metrics will help the software developer in making the system more stable, better and efficient.
Influence of School Operational Assistance Fund (BOS) Management on the Student Grade Advancement in Fatuleu State High School 1, Kupang District

This study aims to analyze the influence of School Operational Assistance (BOS) funds management on the Grade Advancement rate of the underprivileged students in SMA I Fatuleu (Fatuleu State High School 1), Fatuleu District, Kupang Regency, NTT Province.This research is a descriptive correlational study, using a quantitative approach.The location of this research was Fatuleu State High School 1, located in Fatuleu District, Kupang Regency.The sampling method used in this study was a probability sampling method with a simple random sampling technique.The collected data were processed using a computer with the following stages of analysis; (1) Univariate Analysis; (2) Bivariate Analysis; (3) Multivariate Analysis.Research result exhibited simultaneously a significant influence between Organizing, Planning and Monitoring and Evaluation on the timeliness of the Grade Advancement Rate of Underprivileged Students in Fatuleu State High School 1; there is a significant influence between planning variables on the timeliness of the Grade Advancement Rate of Underprivileged Students in Fatuleu State High School 1; there is a significant influence between the Organizing variables on the timeliness of the Grade Advancement Rate of Underprivileged Students in Fatuleu State High School 1; there is no significant influence between the monitoring and evaluation variables on the timeliness of the Grade Advancement Rate of Underprivileged Students in Fatuleu State High School 1.
The effect of word embeddings and domain specific long-range contextual information on a Recurrent Neural Network Language Model

This work explores the effect of input text representation on the performance of a Long Short-Term Memory Recurrent Neural Network Language Model (LSTM RNNLM). Due to a problem with vanishing gradients during LSTM RNNLM training, they cannot capture long-range context information. Long-range context information often encapsulates details about the text application domain. Word embedding vectors capture similarity and semantic context information in their structure. Additional context can be captured by socio-situational setting information, topics, named entities and parts-of-speech tags. This work uses a character LSTM RNNLM as a control in experiments to determine the effect different types of input text representation have on the perplexity of an LSTM RNNLM in terms of a percentage increase or decrease in the value. Adding socio- situational information to a character LSTM RNNLM results in a 0.1 % reduction in perplexity in comparison to that of the control model. When the character embeddings are swapped with word2vec embeddings a reduction in perplexity of 2.77 % is obtained. Adding context information such as socio-situational information to the word embedded model should also result in a perplexity reduction. However, this is not the case, as the addition of socio-situational information to a word embedded model results in a 5.79 % perplexity increase in comparison to the word2vec only model. This trend of an increase in perplexity is observed in further experiments where other types of context information are added to a word embedded model. The largest increase in perplexity is obtained when word embeddings and topics are applied giving a perplexity increase of 7.55 %. This increase in perplexity is due to the addition of more data (context information) to the input text. More data means more words (unique or otherwise) that are being concatenated together as a representation of the input. This results in a larger and sparser input that not only takes longer to train but has less useful information captured on average resulting in models with a higher perplexity. A better method of text representation that will reduce the size of the input while still capturing the necessary semantic information implicit in word embeddings will be adding the vectors together instead of concatenating them.
Experience of Studying Innovative Behavior of Youth in Russia

Transformations in society need to raise the level of their economic consciousness. The problem is that the level of innovation remains low. The article presents the description of the innovative economic behaviour study. A survey was done on students from different courses. The experiment was aimed at studying the group interaction factors in the formation of innovative behaviour. We proceeded from the proposition that innovativeness is a derivative of individual creativity and external factors, in particular, the factor of group interaction. We assume that factors of group interaction are more important for the development of innovative economic behavior. The case study have a several stages. First, the level of individual creativity and innovativeness was studied. Then the subjects received a task during the week. The results showed that the level of individual creativity is not a sufficient condition for the manifestation of innovative behaviour. Group factors play an important role in it as well. More importantly for team work is intra-group cognitive and social processes. In addition, the results of the case study, suggest that innovation is a skill that can be developed.
Optimal Resampling for Learning Small Models.

Models often need to be constrained to a certain size for them to be considered interpretable. For example, a decision tree of depth 5 is much easier to understand than one of depth 50. Limiting model size, however, often reduces accuracy. We suggest a practical technique that minimizes this trade-off between interpretability and classification accuracy. This enables an arbitrary learning algorithm to produce highly accurate small-sized models. Our technique identifies the training data distribution to learn from that leads to the highest accuracy for a model of a given size. We represent the training distribution as a combination of sampling schemes. Each scheme is defined by a parameterized probability mass function applied to the segmentation produced by a decision tree. An Infinite Mixture Model with Beta components is used to represent a combination of such schemes. The mixture model parameters are learned using Bayesian Optimization. Under simplistic assumptions, we would need to optimize for $O(d)$ variables for a distribution over a $d$-dimensional input space, which is cumbersome for most real-world data. However, we show that our technique significantly reduces this number to a \emph{fixed set of eight variables} at the cost of relatively cheap preprocessing. The proposed technique is flexible: it is \emph{model-agnostic}, i.e., it may be applied to the learning algorithm for any model family, and it admits a general notion of model size. We demonstrate its effectiveness using multiple real-world datasets to construct decision trees, linear probability models and gradient boosted models with different sizes. We observe significant improvements in the F1-score in most instances, exceeding an improvement of $100\%$ in some cases.
Do you click and collect your on-line shopping?: Interview with Louise Saunders

It's a growing trend to shop on-line and then click the option to pick up your goods in-store. Dr Louise Grimmer from UTas looks at why we do it and what's in it for us and for the retailers.