Reviewerly/exHarmony huggingface dataset:
Legal Professional Privilege and Cybersecurity Breach in Context: A Comparative Law Analysis

Every company is undoubtedly under attack from hackers. Many companies have suffered data breaches resulting from cybersecurity. In Britain and the United States, the legal privilege strategy has been developed to shield companies after a cyber-attack from tortious liability. However, unlike in the United States, businesses in the British consumer market do not have to notify data subjects that cybercriminals have breached cybersecurity measures. Furthermore, compared to work product doctrine in American law, litigation privilege in British law is broad. It extends to prospective witnesses. On the other hand, work product privilege in American law is limited to documents. Hence, when a legal privilege strategy gets used against British plaintiffs, they are unfairly deprived of using pre-trial discovery procedures to access evidence essential to proving a data controller's tortious liability. Lawyers play a significant role in protecting against and responding to a data breach. In case a company finds itself amongst businesses that are suffering a breach, lawyers invariably become the critical members of the team to address the issues relating to the extent and nature of confidential information, contract implications with third parties, insurance coverage, regulatory enforcement actions, consumer and employee actions and shareholder litigation. These are issues that need a consultation with external counsel that have appropriate expertise in data security. The presence of in-house counsel will play a vital role in the general aftermath of a data breach. Parliament is supreme in the British constitutional law system. The issues identified by the current paper on the use of litigation privilege strategy by British companies as a cyber-risk management strategy can only get conclusively addressed by legislators. The study first recommends that the British Data Protection Act of 2018 gets amended to create a legal duty on businesses in the British consumer market to notify their clients when a cyber-attack leads to unlawful disclosure of stored private information. Second, the study recommends that the scope of litigation privilege in British law gets limited to documents using a statute.
Data Analysis and Visualization in Python for Polar Meteorological Data

The aim of this study is to analyze meteorological data obtained from the various expeditions made to the Indian stations in Antarctica over recent years and determine how significantly the weather has shown a marked change over the years. For any time series data analysis, there are two main goals: (a) the authors need to identify the nature of the phenomenon from the sequence of observations and (b) predict the future data. On account of these goals, the pattern in the time series data and its variability are to be accurately identified. This paper can then interpret and integrate the pattern established with its associated meteorological datasets collected in Antarctica. Using the data analytics knowledge the validity of interpretation for the given datasets a pattern has been identified, which could extrapolate the pattern towards prediction. To ease the time series data analysis, the authors developed online meteorological data analytic portal at NCPOR, Goa http://data.ncaor.gov.in/.
Improving Neural Network Accuracy and Calibration Under Distributional Shift with Prior Augmented Data

Neural networks have proven successful at learning from complex data distributions by acting as universal function approximators. However, neural networks are often overconfident in their predictions, which leads to inaccurate and miscalibrated probabilistic predictions. The problem of overconfidence becomes especially apparent in cases where the test-time data distribution differs from that which was seen during training. We propose a solution to this problem by seeking out regions in arbitrary feature space where the model is unjustifiably overconfident, and conditionally raising the entropy of those predictions towards that of the Bayesian prior on the distribution of the labels. Our method results in a better calibrated network and is agnostic to the underlying model structure, so it can be applied to any neural network which produces a probability density as an output. We demonstrate the effectiveness of our method and validate its performance on both classification and regression problems by applying it to the training of recent state-of-the-art neural network models.
The Effects of Extensive Reading Strategy to Improve Students’ Reading Comprehension

The goal in this research were (1) to identify that the extensive reading strategy improve the students’ reading comprehension at English Education Program of Dayanu Ikhsanuddin University Baubau or not, (2) to find out the students’ perception toward the use of extensive reading strategy in teaching reading. This research used quasi-experiment. The English students of Dayanu Ikhsanuddin university Baubau in academic year 2015/2016 who take Reading III course at fourth semester was the population of the research. This research used cluster sampling which consist of experimental and control group. The experimental group used extensive reading in teaching, whereas the control group used usual method in teaching the data in this research was collected by using reading comprehension test as pretest and posttest and questionnaire. The data has obtained by questionnaires and reading comprehension test analyzed by using SPSS 20 version. Based on the data analysis, it appears that the use of extensive reading strategy has effect to improve the students’ reading comprehension. Besides, the students’ perception towards the extensive reading activity was positive. Therefore, it can be concluded that extensive reading strategy effective to be used in improving the reading comprehension of students in the term of literal, inferential, and critical comprehension.
Anchor-free Small-scale Multispectral Pedestrian Detection.

Multispectral images consisting of aligned visual-optical (VIS) and thermal infrared (IR) image pairs are well-suited for practical applications like autonomous driving or visual surveillance. Such data can be used to increase the performance of pedestrian detection especially for weakly illuminated, small-scaled, or partially occluded instances. The current state-of-the-art is based on variants of Faster R-CNN and thus passes through two stages: a proposal generator network with handcrafted anchor boxes for object localization and a classification network for verifying the object category. In this paper we propose a method for effective and efficient multispectral fusion of the two modalities in an adapted single-stage anchor-free base architecture. We aim at learning pedestrian representations based on object center and scale rather than direct bounding box predictions. In this way, we can both simplify the network architecture and achieve higher detection performance, especially for pedestrians under occlusion or at low object resolution. In addition, we provide a study on well-suited multispectral data augmentation techniques that improve the commonly used augmentations. The results show our method's effectiveness in detecting small-scaled pedestrians. We achieve 5.68% log-average miss rate in comparison to the best current state-of-the-art of 7.49% (25% improvement) on the challenging KAIST Multispectral Pedestrian Detection Benchmark. Code: this https URL
An Adversarial Attack via Feature Contributive Regions

Recently, to deal with the vulnerability to generate examples of CNNs, there are many advanced algorithms that have been proposed. These algorithms focus on modifying global pixels directly with small perturbations, and some work involves modifying local pixels. However, the global attacks have the problem of perturbations’ redundancy and the local attacks are not effective. To overcome this challenge, we achieve a trade-off between the perturbation power and the number of perturbed pixels in this paper. The key idea is to find the feature contributive regions (FCRs) of the images. Furthermore, in order to create an adversarial example similar to the corresponding clean image as much as possible, we redefine a loss function as the objective function of the optimization in this paper and then using gradient descent optimization algorithm to find the efficient perturbations. Various experiments have been carried out on CIFAR-10 and ILSVRC2012 datasets, which show the excellence of this method, and in addition, the FCRs attack shows strong attack ability in both white-box and black-box settings.
"Domain Data Protocols" a key to your FAIR data

Research data management (RDM) has become a vital element to advance open science via data sharing and reuse. To improve RDM, research organisations (research funders, councils, universities, academies, institutes, etc.) increasingly require researchers to develop a Data Management Plan (DMP) for their project proposals or for research evaluations. While researchers and research projects usually recognise the benefits of better RDM, describing your standards, repositories, and data-policies in a DMP, most of the times in a non-committal way, is often considered a burden. Domain Data Protocols (DDP) are intended to make life easier for researchers as well as for research organisations demanding DMPs. They essentially give guidelines or directives for data management for a particular domain, agreed upon by a research community and/or the organisations demanding a DMP. The fact that communities collectively set the standards and guidelines for DMPs also means that there are great opportunities to increase the FAIRness of research data in these respective communities. Within EOSC-hub and the EOSC community at large, the use of Domain Data Protocols in Data Management Plans will boost the developments around FAIR data.
Fast Convex Relaxations using Graph Discretizations

Matching and partitioning problems are fundamentals of computer vision applications with examples in multilabel segmentation, stereo estimation and optical-flow computation. These tasks can be posed as non-convex energy minimization problems and solved near-globally optimal by recent convex lifting approaches. Yet, applying these techniques comes with a significant computational effort, reducing their feasibility in practical applications. We discuss spatial discretization of continuous partitioning problems into a graph structure, generalizing discretization onto a Cartesian grid. This setup allows us to faithfully work on super-pixel graphs constructed by SLIC or Cut-Pursuit, massively decreasing the computational effort for lifted partitioning problems compared to a Cartesian grid, while optimal energy values remain similar: The global matching is still solved near-globally optimal. We discuss this methodology in detail and show examples in multi-label segmentation by minimal partitions and stereo estimation, where we demonstrate that the proposed graph discretization can reduce runtime as well as memory consumption of convex relaxations of matching problems by up to a factor of 10.
Media-Communication in Modern Educational Sphere

The paper deals with problem of media-communication in educational sphere. We focused on the interdisciplinarity of media communication research, which is determined by comprehensive complicating effects of the individual and society, globalization processes and informational challenges of the modern era, such as the interpenetration of the physical world and cyberspace, the cognitive, interpersonal and social impact of information environments. Media communication is considered as the process associated with the dissemination by means of technical means between different groups and individuals of specially prepared messages of social and personal significance. We made the conclusion that the functions of media communication in educational sphere include: ideological and political influence on education, maintaining social community, organizing, informing, educating, communicating and entertaining. The specific content of media communication functions is determined by the specificity of the social, economic and cultural context of educational sphere in Russia, by radical changes the forms and methods of communication, cultural production and consumption, the sphere of economic, political and interpersonal relations, models of education.
Research guides: LibrarySearch Tips: Using Search Operators

A guide to the University of Toronto Libraries' LibrarySearch platform How to use search operators to improve your results
PKM memperbaiki alat-alat listrik rumah tangga pada masyarakat di Kecamatan Labakkang Kabupaten Pangkajene dan Kepulauan

Community service activities are carried out to the community of Pattallassang Village, Labakkang District, Pangkajene Regency and the Islands. This service is carried out in the form of training on maintenance and repair of household electrical appliances. The purpose of community service activities is to provide service to the community by providing training on: how to care for household electrical appliances in general, diagnose damage, and repair damage based on diganosa. The material provided in this training activity included: maintenance of household electrical appliances, repair of damage to household electrical appliances, operation of household electrical appliances, and installation of household electrical appliances. Implementation of community service regarding household electrical appliances went smoothly. Community service activities produce results; increased participant's knowledge of the benefits of maintaining electrical equipment, increased participant's knowledge of damage diagnoses, and increased participant's knowledge of correct household electrical appliances repairs.
Syllabus for Intellectual Property Course (Winter 2021)

This is a draft syllabus for the Intellectual Property course at Carleton University (Winter 2021).
Developing an interactive digital book to improve the technical drawing abilities of mechanical engineering students

ABSTRACT: The aim of this study was to develop an interactive digital book and assess the validity and effectiveness of it. A 4D development model was created consisting of four stages: a) define; b) design; c) develop; and d)disseminate. Product validity was confirmed by experts’ material in technical drawing (the material), as well as bymedia experts. The effectiveness of the product was assessed through a post-test control/experimental group design with two mechanical engineering student groups totalling 45 students. Data collection was done through observation, questionnaire and tests. Validation by experts of the material and media showed that the interactive digital book was very good and appropriate to use. It was also concluded that, in terms of product effectiveness, the use of the interactive digital book had a significant positive effect on student technical drawing ability. These findings showed that an interactive digital book could be used as one of the innovative learning media to improve students’ ability in technical drawing.Keywords: Interactive digital book, technical drawing ability, engineering student, 4D model
Sparse Pinball Twin Parametric Margin Support Vector Machine

The main purpose of this paper is to construct a twin parametric margin support vector machine combined an $\epsilon-$insensitive loss function for finding a pair of parametric margin hyperplanes that automatically adapts to the parametric noise with arbitrary shape to capture the data structure more accurately. We exhaustively test several UCI datasets demonstrates that our SPTPMSVM is noise insensitive, retains sparsity in most cases. Finally, we present the numerical experiment and compare our model with other models.
SISTEM PEMANTAUAN KETINGGIAN AIR SUNGAI DENGAN PENDEKATAN JARINGAN NIRKABEL

AbstractAlmost every rainy season, areas that are near watershed areas or watersheds. The area along the river has an important role in contributing and has a very high level of urgency to the occurrence of floods. Floods that often come suddenly cause huge losses, so people cannot be prepared to face flood disasters. So far the information system that has been built has been widely applied, but it has not maximally reduced the losses. To solve this problem, it is necessary to have a model or concept of a watershed monitoring information system that is fast and easily accessible online through a web application. In addition to some of the above, the concept of a communication system between the device point (node) to the center (server) along the river flow is made wirelessly using the ZigBee protocol. The results of the study are a wireless network based water level monitoring system that can be used as a basis for the next level of research.
Virtual Reality: Pro et Contra

The article is devoted to the study of the dual nature of virtuality as a sociocultural phenomenon, which enables the outlining of recommendations for ensuring the integrity of a holistic personality and its stability in a world subject to transformation. The study is based on the methodology of systemic and structural research; comparative induction method; principle of complementarity; method of participant observation. The effectiveness of the study is determined by the following conclusions: The dual nature of virtuality correlates with the dual nature of a human, who is both an actual biological organism functioning at the level of the information system and a potential social organism functioning at the level of the conceptual system; if the information system forms an orientation to the priority of the individual over the collective (egoism), then the conceptual system forms an orientation to the priority of the collective over the individual (altruism); in contrast to the information system, which restricts the entire diversity of the individual’s life to a reaction to the natural reflex, the conceptual system frees the individual from the dictate of the biological program through reflection; interaction with virtual reality can either fix the status of a passive consumer to an individual, whose consciousness as a correlate of an information system represents an ideal object for all kinds of manipulations, or initiate the birth of a creative person with a spiritual identity, which is acquired in the unity of information and conceptual systems; virtual reality as an integral component of the Global Internet, the actualization of which is determined solely by external actions from the side of the user (pressing a processor button, paying for the Internet, maintaining the equipment in working condition, etc.) acts as the simulacrum of an individual conceptual system, the updating of which is possible only through the inside of the conducted organization of the information system; the universal “simulator” providing the desired unity of information and conceptual systems is the art, which is due to the isomorphism of a human and the text of culture; if the true unity of the information and conceptual systems is the guarantor of the positive deviation of the individual, then the simulation of the desired unity through the external interaction of the individual and virtual reality generated by the Global Network inevitably becomes a source of negative deviation due to the fact that such virtual reality does not change anything in the biological substrate, saturating information system with additional information.
Procedurally Generated Self Overlapping Mazes in Virtual Reality.

A current research topic within virtual reality is to allow the user to move by natural walking in a virtual environment that exceeds the size of the tracking area. Multiple approaches to overlapping architecture dealing with this issue already exist, but they are either custom made for a specific tracking area size or require a tracking area too large to work efficiently for personal use. This paper proposes a method to make scalable overlapping architecture by procedural generation of tile-based mazes that seamlessly teleport the user using portals. We evaluated how the tile size of the overlapping maze affects the user’s spatial awareness of their physical position. 23 participants of Aalborg University students completed the Spatial Awareness Task of finding a tile that overlapped with their starting tile in a 3 \(\times \) 3, 4 \(\times \) 4, and 5 \(\times \) 5 tile maze. Between condition 3 \(\times \) 3 and 5 \(\times \) 5, and condition 4 \(\times \) 4 and 5 \(\times \) 5, participants were more confused in the 5 \(\times \) 5 tile maze compared to 3 \(\times \) 3 (p = .0015) and 4 \(\times \) 4 (p = .0295) tile mazes.
Insights on the Indian Ocean Tectonics and Geophysics Supported by GMT

This paper presented analyzed and summarized data on geological and geophysical settings about the tectonics and geological structure of the seafloor of the Indian Ocean by thematic visualization of the topographic, geophysical and geological data. The seafloor topography of the Indian Ocean is very complex which includes underwater hills, isolated mountains, underwater canyons, abyssal and accumulative plains, trenches. Complex geological settings explain seismic activity, repetitive earthquakes, and tsunami. Understanding and prognosis of the disastrous and catastrophic geological events is strongly based on correct data analysis, mod- elling and visualization. An important feature of this paper is mapping multi-source high-resolution data by GMT. Data include raster grids in NetCDF and GRD formats: ETOPO1, geologic and marine free-air gravity data, EGM96, age, spreading rates, and spreading asymmetry of the ocean crust by NOAA, total sediment thickness. Data were visualized by GMT modules to compare and analyze geophysical and geological settings of the Indian Ocean. Visualization reveled correlations between high bathymetric variations of the oceanic seafloor, distribution of main geological seafloor fabric: Southwest, Southeast, Mid and Carlsberg ridges. Tectonic maps were plotted to perform comparative analysis of several variables: crust age, spreading half rates (mm/yr), asymmetries in crustal accretion on conjugate ridge flanks (%), variations in the geopotential and gravimetric models. Being the warmest of the world’s ocean, Indian Ocean has specific climatic conditions (repetitive monsoons, tsunamis, cyclones and storms), complex geologic seafloor structure with triple junction and unique geographic settings. Presented paper contribut ed to the regional studies of the Indian Ocean.
Text-Independent Speaker Identification Using PCA-SVM Model

The Speaker identification system is widely applied in various fields to detect the identity of a person by detecting the sound signal energy released by a person and not driven by a particular text. The challenges are how to differentiate the voices characteristic of the speaker, such as intonation style, rhythm, the pattern of pronunciation, accent, and vocabulary. In this paper, a speaker identification system using Principal Component Analysis (PCA) and Support Vector Machine (SVM) is developed. Besides, the Mel Frequency Cepstral Coefficient (MFCC) is used as the feature extraction. The system is then evaluated using unseen noisy utterances with various signal-noise ratio (SNR). The evaluation is performed using a confusion matrix to calculate the accuracy, precision, and recall to determine the relevance of the output results on the system. Experimental results show that the developed system is quite robust. It is capable of identifying speakers with high performance, an accuracy of 88.97%, a precision of 91,87%, and a recall of 94,39%, for a low noise level with SNR of 15dB. The performance slowly decreases as the noise level increases. For a high noise level with SNR of up to 0dB, it is still able to recognize the unseen speakers with an average accuracy of 70.93%, precision of 74.68%, and recall of 83.51%.