Reviewerly/exHarmony huggingface dataset:
Metallogenic inception of the Arabian-Nubian Shield: Daero Paulos porphyry copper prospect, Eritrea

The Daero Paulos porphyry copper prospect, in the Asmara region of the central Eritrean highlands, is part of the Nakfa tectono-stratigraphic terrane, which, along with four other major and several minor terranes that constitute the Neoproterozoic Arabian-Nubian Shield, is characterized by juvenile, intra-oceanic island-arc crust. Alteration and mineralization at Daero Paulos occupy a north-northeast-trending corridor of multiphase, rhyolitic to dacitic intrusions emplaced into mafic and intermediate volcanic and subvolcanic rocks and derivative volcaniclastic strata. New U-Pb geochronological data for the volcanic rocks in the region confirm a >860-Ma age for the Neoproterozoic (Tonian) host sequence. The porphyry copper alteration evolved from early epidote-chlorite-albite through sericite-chlorite to late quartz-sericite. Local advanced argillic alteration is the erosional remnant of the lithocap that formerly dominated the shallow parts of the Daero Paulos system. A post-mineralization, Alaskan-type pyroxenite-gabbro body intruded the porphyry copper corridor, and is interpreted as the feeder for mafic dikes along the periphery of the porphyry copper system. Re-Os ages of 881.0 ± 5.5 and 864.2 ± 3.6 Ma for molybdenite from veinlets at Daero Paulos constrain an early Tonian timing for porphyry copper formation during early opening of the Mozambique Ocean after Rodinian supercontinent break-up. The ages also imply a rapid transition from initial rifting to the start of subduction and consequent establishment of an intra-oceanic island arc in what is now the Nakfa terrane. The molybdenite ages show that Daero Paulos is currently the oldest dated mineralization in the Arabian-Nubian Shield, and ~60–200 and, possibly, ~250 m.yr. older than porphyry copper mineralization elsewhere in the Shield. However, volcanogenic massive sulfide (VMS) mineralization could have been forming at broadly the same time, albeit not genetically associated with Daero Paulos. Preservation of such shallowly formed Neoproterozoic mineralization is mainly attributed to burial beneath thick post-amalgamation volcano-sedimentary basinal cover, collision-generated thrust sheets, and later Phanerozoic strata.
Offline Navigation (Homing) of Aerial Vehicles (Quadcopters) in GPS Denied Environments

This paper focuses on offline navigation in quadcopters (Return-to-Home), autonomously in GPS Denied Areas or in cases that the aircraft loses GPS Signal by using the Haversine’s Great circle formula to calculate distance and direction. The internal sensors are used to estimate offsets for distance and direction. A control system modification is proposed, resulting in a high success rate with the several tests using a quadcopter with a Pixhawk flight controller, equipped with PX4FLOW.
Search and Rescue Robot with a 4 Flipper Mechanism

Safety, Security and Rescue Robotics also known as Search and Rescue (SAR) robotics is the emerging field in robotics. There are many challenges and research domains in this field. This paper aims in the design and implementation of the robust flipper based Search and Rescue robot for high mobility and modularity challenges. Robots are not as agile as humans while moving on uneven terrains after the disaster has occurred. The designed rescue robot has the capability to move on any rough uneven terrain with ease. Modularity, mobility, and robustness are the key factors that are taken into consideration for designing this rescue robot with the flipper mechanism to move effectively and efficiently in all the harsh environments. The robot is totally designed in Solidworks CAD tool. The robot was tested in an artificially created disaster scenario considering all the parameters like step fields, sand, gravel, and rough terrains.
Evaluation of Error Probability of Classification Based on the Analysis of the Bayes Code

Suppose that we have two training sequences generated by parametrized distributions ${P_{\theta _1^{\ast}}}$ and ${P_{\theta _2^{\ast}}}$, where $\theta _1^{\ast}$ and $\theta _2^{\ast}$ are unknown. Given training sequences, we study the problem of classifying whether a test sequence was generated according to ${P_{\theta _1^{\ast}}}$ or ${P_{\theta _2^{\ast}}}$. This problem can be thought of as a hypothesis testing problem and the weighted sum of type-I and type-II error probabilities is analyzed. To prove the results, we utilize the analysis of the codeword lengths of the Bayes code. It is shown that upper and lower bounds of the probability of error are characterized by the terms containing the Chernoff information, the dimension of a parameter space, and the ratio of the length between the training sequences and the test sequence. Further, we generalize the part of the preceding results to multiple hypotheses setup.
IVP-LDL: Label Distribution Learning via Preservation of Information Volumes

Traditional learning methods solve classification problems with training stage, and exploit the intrinsic relationships between available training instances and binary class labels. Label distribution learning aims to learn the models that ideally depict the connection between instances and probabilistic labels, which can be used to predicate the label distributions of further instances. Existing methods mainly focus on independent learning of predication models, and adaptive learning models are still desired for complicated scenarios. In this work, a novel approach to label distribution learning is proposed, and unfolded generator is adopted to produce class-specific samples of each class. As a consequence, the original problem can be solved with convenient accomplishment, and parallel computing is applicable for extension. Furthermore, information volumes of each instance is adopted to predicate the ideal probabilistic labels, which is approximately preserved with summation of information volumes associated with different classes. Experimental results on various real-world data sets demonstrate that, the proposed method is able to achieve fascinating performance compared with existing methods.
“UD-ETR Based Restoration &amp; CNN Approach for Underwater Object Detection from Multimedia Data”

In this paper, the work has been done in the field of underwater world, which includes restoration of the obtained images and then the detection of objects. The identification of the objects is performed in order to check the presence of items in the video and to unequivocally find a particular object. This is the area of interest for researchers because of the presence of various species under water. The images which are taken in the water lacks some factors such as: non-uniform lighting, low contrast, turbid water etc. which leads to the generation of improper outputs. These issues give rise to the involvement of restoration technique, which is a fundamental technique used for removing some severe abnormalities from the obtained images such as: low contrast, blurring etc. The proposed algorithm UD-ETR (UDCP based Energy Transmission Restoration) is used to restore the green channel images. It contains multiple stages of restoration which ultimately gives final restored image. Further, CNN (Convolutional Neural Network) is used for detecting the fish from the restored image. This algorithm is implemented using the MATLAB tool and the efficiency obtained shows its capability.
Analyzing Ensemble Methods for Software Fault Prediction

Prediction of software faults using different machine learning techniques has been reported earlier by many researchers. However, these individual techniques suffered from performance problems as the software fault dataset changes. In the last few years, ensemble-based approaches gained popularity in the software fault prediction because of their improved performance over the single-fault prediction techniques. Motivated by this reason, an experimental study is performed on ensemble methods for predicting whether a software contains fault or not. The study includes random forest, bagging, random subspace, and boosting as ensemble methods, and decision trees, logistic regression, and k-nearest neighbors as base learning algorithms for the ensembles. The experiments are conducted on 15 software fault datasets corresponding to the Eclipse project and PROMISE Software Engineering repository. We evaluated the results using precision, accuracy, recall, and ROC-AUC score. Additionally, we performed the Friedman statistical test to see whether the performance difference of ensemble methods is statistically significant or not. We also performed the Wilcoxon signed-rank test for the paired samples to check which of the two techniques have performance differences.
Sequence Obfuscation to Thwart Pattern Matching Attacks

Suppose we are given a large number of sequences on a given alphabet, and an adversary is interested in identifying (de-anonymizing) a specific target sequence based on its patterns. Our goal is to thwart such an adversary by obfuscating the target sequences by applying artificial (but small) distortions to its values. A key point here is that we would like to make no assumptions about the statistical model of such sequences. This is in contrast to existing literature where assumptions (e.g., Markov chains) are made regarding such sequences to obtain privacy guarantees. We relate this problem to a set of combinatorial questions on sequence construction based on which we are able to obtain provable guarantees. This problem is relevant to important privacy applications: from fingerprinting webpages visited by users through anonymous communication systems to linking communicating parties on messaging applications to inferring activities of users of IoT devices.
Improved efficiency for covering codes matching the sphere-covering bound

A covering code is a subset C ⊆ {0, 1} <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> with the property that any z E {0, 1} <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> is close to some c E C in Hamming distance. For every c, δ > 0, we show a construction of a family of codes with relative covering radius δ+ε and rate 1-H(δ) with block length at most exp(O((1/c) log(1/c))) for every c> 0. This improves upon a folklore construction which only guaranteed codes of block length exp(1/ε <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ). The main idea behind this proof is to find a distribution on codes with relatively small support such that most of these codes have good covering properties.
Semi-Supervised Machine Learning for Spacecraft Anomaly Detection &amp; Diagnosis

This paper describes Anomaly Detection via Topological-feature Map (ADTM), a data-driven approach to Integrated System Health Management (ISHM) for monitoring the health of spacecraft and space habitats. Developed for NASA Ames Research Center, ADTM leverages proven artificial intelligence techniques for rapidly detecting and diagnosing anomalies in near real-time. ADTM combines Self-Organizing Maps (SOMs) as the basis for modeling system behavior with supervised machine learning techniques for localizing detected anomalies. A SOM is a two-layer artificial neural network (ANN) that produces a low-dimensional representation of the training samples. Once trained on normal system behavior, SOMs are adept at detecting behavior previously not encountered in the training data. Upon detecting anomalous behavior, ADTM uses a supervised classification approach to determine a subset of measurands that characterize the anomaly. This allows it to localize faults and thereby provide extra insight. We demonstrate the effectiveness of our approach on telemetry data collected from a lab-stationed CubeSat (the “LabSat”) connected to software that gave us the ability to trigger several real hardware faults. We include an analysis and discussion of ADTM's performance on several of these fault cases. We conclude with a brief discussion of future work, which contains investigation of a hierarchical SOM-architecture as well as a Case-Based Reasoning module for further assisting astronauts in diagnosis and remediation activities.
Entropy of a Quantum Channel: Definition, Properties, and Application

The von Neumann entropy is a central concept in physics and information theory, having a number of compelling physical interpretations. There is a certain perspective that the most fundamental notion in quantum mechanics is that of a quantum channel, as quantum states, unitary evolutions, measurements, and discarding of quantum systems can each be regarded as certain kinds of quantum channels. Thus, an important goal is to define a consistent and meaningful notion of the entropy of a quantum channel. Motivated by the fact that the entropy of a state ρ can be formulated as the difference of the number of physical qubits and the “relative entropy distance” between ρ and the maximally mixed state, here we define the entropy of a channel N as the difference of the number of physical qubits of the channel output with the “relative entropy distance” between N and the completely depolarizing channel. We establish that this definition satisfies all of the axioms, recently put forward in [Dour, IEEE Trans. Inf. Theory 65, 5880 (2019)], required for a channel entropy function. The task of quantum channel merging, in which the goal is for the receiver to merge his share of the channel with the environment's share, gives a compelling operational interpretation of the entropy of a channel. We define Rényi and min-entropies of a channel and establish that they satisfy the axioms required for a channel entropy function. Among other results, we also establish that a smoothed version of the min-entropy of a channel satisfies the asymptotic equipartition property.
Universal superposition codes: capacity regions of compound quantum broadcast channel with confidential messages

We derive universal codes for transmission of broadcast and confidential messages over classical- quantum-quantum and fully quantum channels. These codes are robust to channel uncertainties considered in the compound model. To construct these codes we generalize random codes for transmission of public messages, to derive a universal superposition coding for the compound quantum broadcast channel. As an application, we give a multi-letter characterization of regions corresponding to capacity of the compound quantum broadcast channel for transmitting broadcast and confidential messages simultaneously. This is done for two types of broadcast messages, one called public and the other common.
Value Function Dynamic Estimation in Reinforcement Learning based on Data Adequacy

In recent years, reinforcement learning has played an important role in the study of decision problem in computer games. To solve the problem of how to better estimate the value function with limited computational resources, this paper proposes a dynamic estimation method of value function based on data adequacy. In consideration of the varying complexity of each state in the MDP model, we propose a dynamic value function estimation method which is different from the fixed value function estimation method in traditional methods. Based on the PigChase challenge of the Malmo project launched by Microsoft in 2017, we compare the new method with the existing techniques. Experimental results show that the performance of the proposed algorithm is better than traditional algorithms.
The Effects of Gender and the Presence of Third-Party Humans on Telepresence Camera Height Preferences

With the rise of immersive virtual reality and telepresence, it is important to understand the factors that contribute to creating an optimal user experience. In particular, there are divergent recommendations for setting camera heights in virtual contexts that facilitate telepresence. Therefore, we conducted a 2x2 mixed-design experiment with 93 college students asking them to select their preferred camera height when varying camera placement (overhead, chest) and the presence of human avatars (present, not present). We found that while camera placement did not have a significant effect of preferred camera height, the presence of avatars (increased height preference) and gender (women preferred lower heights) were significant. Our results provide evidence that factors within a virtual environment and individual differences influence users’ preferences of camera height. Thus, systems designed for immersive virtual reality and telepresence should customize camera height based on these factors.
Dealing with Disinformation: Evaluating the Case for Amendment of Section 230 of the Communications Decency Act

Recent revelations surrounding Russian interference in the 2016 US presidential election and the role that "fake news" may have played in shaping voter preferences have sparked a broad conversation on how to combat the spread and influence of disinformation online. Emerging from this conversation has been a number of proposals that seek to pass legislation or promulgate regulations that would make it more difficult for disinformation to flow through the Web. To that end, these interventions will confront the long-standing legal protections provided by Section 230 of the Communications Decency Act of 1996 (CDA 230), a key legal provision which broadly shields platforms from legal liability for the actions of third-party users of their services. The present-day debates on how to address "fake news" will join the legacy of efforts to reform or eliminate the shield provided by CDA 230. This chapter seeks to address three questions given this historical background. First, would modifications to CDA 230 pave the way to an effective response to the challenges posed by disinformation online? Second, if so, should such modifications be made? Finally, how should such modifications be crafted?
Co-Design in Libraries

In order to optimise a needs analysis for digital infrastructure in the Digital Humanities, participatory development concepts are presented and compared with regard to their potential suitability. Since the use of co-design seems to be suitable due to its high degree of participation and its open organisational structure, a checklist for projects in academic libraries was developed, which is presented in addition to a toolkit and a case study. Based on the case study it is shown how a detailed requirements analysis and a design concept for a project-specific working environment for researchers could be created in a one-day interdisciplinary workshop with the help of co-design elements. The activities used, such as customer journey mapping or a stakeholder analysis created with the help of LEGO bricks, led to new perspectives in the collaboration between users and librarians.
Algebraic manipulation detection codes via highly nonlinear functions

In this paper, we study the relationship between algebraic manipulation detection (AMD) codes and highly nonlinear functions. As applications, on one hand, a generic construction for systematic AMD codes is introduced based on highly nonlinear functions. Systematic AMD codes with new parameters can be generated from known highly nonlinear functions. Especially, several infinite classes of optimal systematic AMD codes, some with asymptotically optimal tag size, can be constructed. On the other hand, systematic AMD codes are used to construct highly nonlinear functions. The known construction by Cramer et al. (2008) for systematic AMD codes turns out to be based on a special kind of functions with high nonlinearity.
No-Reference Quality Assessment for Realistic Distorted Images by Color Moment and Texture Features

In real applications, images captured by cameras are easily affected by various distortion types, such as noise, blur, blockiness, and so forth. The complicated distortion existing in realistic distorted images is the major challenge to accurately predict their perceptual quality. In this work, we propose a novel and effective general-purpose No-Reference (NR) quality assessment method for realistic distorted images by Color Moment and Log-Gabor Layer. In the proposed method, we firstly convert the input image into HSV color space. Then, we extract the chromatic features namely color moment, which can capture the color degradations effectively. Meanwhile, considering the different sensitivities of the HVS to texture and non-texture regions, we divide the image into four layers by log-Gabor filter and extract the texture features in each layer. Quantitative experiments on two realistic distorted image datasets prove the validity of our method and its advantageous predicting image quality over the state-of-the-art models.
Shot Boundary Detection Based on HSV Color Model

In this paper, the traditional algorithm of shot boundary detection based on histogram difference is introduced briefly. Based on this, a video shot boundary detection algorithm based on HSV color model is proposed. The method firstly detects the shot hard cut based on the weighted color histogram difference curve, then performs the shot gradual transition detection according to the image local average pixel value characteristic curve. Finally, two partial detection results are fused, and all the shot transitions of the video can be obtained. Experimental result shows that the method has a higher recall and precision.
Exploring the opportunity for a hybrid methodology in project management: a focus group approach

Abstract Nowadays, project-based work is no longer a challenge for a today company. Optimizing the workforce, better managing the results, delivering in time, quality and budget (the triple constrains [1]) are just a few of the advantages. Still, to re-organize an entire company into a project-based organization requires a lot of efforts and energy across its departments and teams. However, some companies step forward and change the project management methodologies multiple times. That brings another wave of changes, stress and reorganizations combined with a complex organizational phenomenon, which requires far more effort than just to replace the current tools and technologies with new ones [2]. Thus, the main purpose of this paper is to reflect and present the results of the workshop called “Going Agile – the journey”, which was held on Project Management Forum 2019, a Conference organized inside of Continental Automotive Romania for all project managers working in the company. Based on the focus group technique there was identified the main struggles associated with the adoption of Agile methodology within Automotive Industry, the similarities with the plan-driven methodologies and willingness to advance the agility in company’s daily working life.