Miracle-dz/UniFAR-FTUs huggingface dataset:
Propagation Channel Models for Next-Generation Wireless Communications Systems

SUMMARY As new systems and applications are introduced for nextgeneration wireless systems, the propagation channels in which they operate need to be characterized. This paper discusses propagation channels for four types of next-generation systems: (i) distributed Multiple-Input Multiple-Output (MIMO) and Cooperative MultiPoint (CoMP) systems, which require the characterization of correlation between channels from a mobile station to different base stations or access points; (ii) device-todevice communications, where propagation channels are characterized by strong mobility at both link ends (e.g., in vehicle-to-vehicle communications), and/or significant impact of moving shadowing objects; (iii) fulldimensional MIMO, where antenna arrays extend in both the horizontal and vertical dimension, so that azimuthal and elevation dispersion characteristics of the channel become relevant, and (iv) millimeter wave Wireless Local Area Network (WLAN) and cellular communication systems, where the high carrier frequency leads to a change (compared to microwave communications) concerning which propagation processes are dominant. For each of these areas, we give an overview of measurements and models for key channel properties. A discussion of open issues and possible future
The DNS-Based Authentication of Named Entities (DANE) Transport Layer Security (TLS) Protocol: TLSA

Encrypted communication on the Internet often uses Transport Layer Security (TLS), which depends on third parties to certify the keys used. This document improves on that situation by enabling the administrators of domain names to specify the keys used in that domain's TLS servers. This requires matching improvements in TLS client software, but no change in TLS server software. [STANDARDS- TRACK]
Liberating usability testing

ions Many methods can be used to investigate a person’s use of an artifact. If we say that the person’s actual experience of using an artifact at the time of using it is the object of study, then most methods have abstractions or distances away from this object of study. In a survey or questionnaire, the respondent is involved in a reflective process; that is, they are thinking about an event (their use of the artifact) that occurred in the past in a different situation. So there are abstractions in the dimensions of time and place. There is an abstraction in the primary focus of the study in that it is the questionnaire, not the artifact. And there is an abstraction in the cognitive framework in that the respondent is not relating to their own framework, but to the questionnaire designer’s. Table 1 lists these abstractions and also outlines the abstractions in other methods which are typically used to evaluate usability. In a similar way to questionnaires, the typical application of interviewing does not deal directly with a person’s actual thinking, feeling, and actions when using an artifact. Two other common methods used in usability evaluations—heuristic evaluations and cognitive walkthroughs—are also distanced from the core focus of the inquiry but are less likely to spill into reification because they do not pretend otherwise. We might expect that the anthropological approach, which has the studying of behavior within context as a distinguishing characteristic, would highlight the mechanism of inquiry within experience. However, people using this approach have their research sensibilities attuned to the complex and fascinating socio-environmental contexts of use [5], not to the precision of a person’s actual experience of using an artifact. Usability testing, however, aims a direct inquiry into the experience of using an artifact while the artifact is being used. From the user’s point of view, they simply relate to their own thinking and experience at the time of using the thing. As consumers with generations of shopping practice, we might also see this inquiry as an everyday type of thing. It is perhaps this marvellous simliBeRAtinG Usability Testing Questionnaire Interviewing heuristic evaluation Cognitive walkthrough usability testing Time No No Yes Yes Yes Place No No No No No Artifact (as primary focus) No No No Yes Yes user Yes Yes No No Yes user’s cognitive framework No Yes No No Yes table 1: Inquiring into the actual use of an artifact: are these methods typically done to the conditions of use? Phil Carter | Auckland University of Technology | phil.carter@aut.ac. nz
Under the supervision of

Dark energy is one of the mysteries of modern science. It is unlike any known form of matter or energy and has been detected so far only by its gravitational effect of repulsion. Owing to its effects being discernible only at very very large distance scales, dark energy was only detected at the turn of the last century when technology had advanced enough to observe a greater part of the universe in finer detail. The aim of the report is to gain a better understanding of the mysterious dark energy. To this end, both theoretical methods and observational evidence are studied. Three lines of evidence, namely, the redshift data of type Ia supernovae, estimates of the age of the universe by various methods, and the anisotropies in the cosmic background radiation, build the case for existence of dark energy. The supernova data indicate that the expansion of the universe is accelerating. The ages of the oldest star clusters in the universe indicate that the universe is older than previously thought to be. The anisotropies in the cosmic microwave background radiation suggest that the universe is globally spatially flat. If one agrees that the dynamics of the geometry of the universe is dictated by its energy-momentum content through Einstein’s general theory of relativity, then all these independent observations lead to the amazing conclusion that the amount of energy in the universe that is presently accounted for by matter and radiation is not enough to explain these phenomena. One of the best and simplest explanations for dark energy is the cosmological constant. While it does not answer all questions, it certainly does manage to explain the observations. The following report examines in some detail the dark energy problem and the candidacy of the cosmological constant as the right theory of dark
Automatic Imaging System With Decision Support for Inspection of Pigmented Skin Lesions and Melanoma Diagnosis

In this paper, we describe an automatic system for inspection of pigmented skin lesions and melanoma diagnosis, which supports images of skin lesions acquired using a conventional (consumer level) digital camera. More importantly, our system includes a decision support component, which combines the outcome of the image classification with context knowledge such as skin type, age, gender, and affected body part. This allows the estimation of the personal risk of melanoma, so as to add confidence to the classification. We found that our system classified images with an accuracy of 86%, with a sensitivity of 94%, and specificity of 68%. The addition of context knowledge was indeed able to point to images that were erroneously classified as benign, albeit not to all of them.
Reduced-Complexity Iterative Receiver for Improving the IEEE 802.15.7 Convolutional-Coded Color Shift Keying Mode

In this letter, we conceive novel symbol-based color-shift keying (CSK)-aided concatenated coding schemes, which provide attractive performance gains over the comparable bit-based systems. Quantitatively, our 4 CSK-aided and 16 CSK-aided symbol-based concatenated systems require 0.8 and 0.45 dB lower SNR than the equivalent bit-based schemes. In terms of decoding complexity, the 4 CSK-aided and 16 CSK-aided systems reduce the decoding complexity by 67% and 33%, respectively. We have also analyzed the convergence behavior of our system with the aid of non-binary extrinsic information transfer charts adapted for symbol-based iterative CSK-assisted systems.
Downward propagation of zonal mean zonal wind anomalies from the stratosphere to the troposphere: Model and reanalysis

The connection between the Arctic Oscillation and the stratosphere is investigated on intra-annual timescales. Both the National Centers for Environmental Prediction reanalysis data and a general circulation model simulation are used. In the winter half year November–April the dominant variability in the stratosphere in middle and high latitudes has the form of downward propagation of zonal mean zonal wind anomalies. The strength of the anomalies decays below 10 hPa, but often the anomalies reach the surface. The time for the propagation from 10 hPa to the surface is ∼15 days. When positive anomalies reach the surface, the phase of the Arctic Oscillation tends to be positive. The stratospheric variability and the downward propagation is found to be driven by the vertical component of the Eliassen-Palm flux. This flux propagates from the lower troposphere to the tropopause on a timescale of 5 days. Model and reanalysis compare well in the structure of the stratospheric variability and the connection between the stratosphere and troposphere. However, the strength of the stratospheric variability is ∼25% weaker in the model.
Data aggregation approach to multisensor radar imaging

By integrating two developed optimization methods for optimal data aggregation modifications can also be proposed that involve a priori calibration information both on the systems' resolution and relative noise levels in the acquired images. In view of this, some previously developed fusion schemes, in which the weights /spl pi//sub m/ were proposed to be selected proportionally to the width of the PSF and signal-to-noise ratio (i.e. inversely proportional to the relative noise intensities) could be referred to as suboptimal versions of the developed regularization-based aggregation approach.
Dissolution of salt deposits by brine density flow

The origin of collapse structures and breccias that vertically penetrate or occur within impermeable evaporites has never really been understood. The density of the brine that develops as salt deposits are dissolved can generate continuous gravitational brine movement. If the source of the dissolving water is artesian, or continuous, a flow cycle is developed in which the salt itself supplies the density gradient that becomes the vehicle of its own dissolution. The Delaware Basin in western Texas and southeastern New Mexico provides a particularly good example of how brine density flow can produce dissolution chambers that collapse to form breccias. The potential for dissolution by brine flow is an inherent property of partly exhumed evaporites and may constitute a risk factor in the storage of radioactive waste in evaporite deposits.
A Simple and Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization

This paper studies the stochastic optimization for decentralized nonconvex-strongly-concave minimax problem. We propose a simple and eﬃcient algorithm, called Decentralized Recursive-gradient descEnt Ascent Method ( DREAM ), which achieves the best-known theoretical guarantee for ﬁnding the ǫ -stationary point of the primal function. For the online setting, the proposed method requires O ( κ 3 ǫ − 3 ) stochastic ﬁrst-order oracle (SFO) calls and O
Statistical framework for model-based image retrieval in medical applications

Recently, research in the field of content-based image retrieval has attracted a lot of attention. Nevertheless, most existing methods cannot be easily applied to medical image databases, as global image descriptions based on color, texture, or shape do not supply sufficient semantics for medical applications. The concept for content-based image retrieval in medical applications (IRMA) is therefore based on the separation of the following processing steps: categorization of the entire image; registration with respect to proto- types; extraction and query-dependent selection of local features; hierarchical blob representation including object identification; and finally, image retrieval. Within the first step of processing, images are classified according to image modality, body orientation, ana- tomic region, and biological system. The statistical classifier for the anatomic region is based on Gaussian kernel densities within a probabilistic framework for multiobject recognition. Special empha- sis is placed on invariance, employing a probabilistic model of vari- ability based on tangent distance and an image distortion model. The performance of the classifier is evaluated using a set of 1617 radiographs from daily routine, where the error rate of 8.0% in this six-class problem is an excellent result, taking into account the dif- ficulty of the task. The computed posterior probabilities are further- more used in the subsequent steps of the retrieval process. © 2003
Recognition of Mammal Genera on Camera-Trap Images Using Multi-layer Robust Principal Component Analysis and Mixture Neural Networks

The segmentation and classification of animals from camera-trap images is a difficult task due to the conditions under which the images are taken. This work presents a method for recognizing mammal genera from camera-trap images. Our method uses Multi-Layer Robust Principal Component Analysis (RPCA) for segmenting, Convolutional Neural Networks (CNNs) for extracting features, Least Absolute Shrinkage and Selection Operator (LASSO) for selecting features, and Artificial Neural Networks (ANNs) or Support Vector Machines (SVM) for classifying mammal genera present in the Colombian forest. Our classification method mixes the features of several CNNs. We evaluated our method with the camera-trap images from the Instituto de Investigación de Recursos Biológicos Alexander von Humboldt. We obtained an accuracy of 92.65% classifying 8 mammal genera and a False Positive (FP) class, using automatic-segmented images. On the other hand, we reached 90.32% of accuracy classifying 10 mammal genera, using ground-truth images only. Unlike all previous works, we confront the animal segmentation and genera classification on the camera-trap framework. This method shows a new approach toward a fully-automatic detection of animals from camera-trap images.
Empowerment or concealed compliance?: A review of literature on mobile ICT solutions for patient empowerment

Healthcare systems are under pressure because of demographic changes and increased demand. Patient empowerment is seen as a powerful approach to cope with this pressure. Information technology is used in various forms to promote patient empowerment, and carries a perceived potential. We did a systematic review of literature in order to find out how information technology is used to enable empowerment. We found that most of the solutions are in reality promoting a compliance model and not an empowerment model. We discuss some possible reasons, and promote the untapped potential of a new generation of solutions.
Work Role Similarity and Work Familiarity between Members: A Tripartite View of Social Identity towards Knowledge Contribution in Organizations

Knowledge sharing within an organization allows it to develop a competitive advantage over its rivals. However, sustaining and motivating members of knowledge sharing groups to contribute knowledge is a challenge for many organizations. To address this problem, organizations have implemented new knowledge sharing tools such as Wikis to facilitate knowledge contribution, although these have had varying success possibly due to the importance of social identity in knowledge sharing behavior. This study examines how similarity in work roles and work familiarity between members affect various dimensions of social identity they individually perceive, and in turn, affect knowledge contribution. Field data gathered from a knowledge intensive organization provide evidence that similarity in work roles and work familiarity have a strong influence on social identity, which in turn affects knowledge contribution.
On Weighted Envy-Freeness in Indivisible Item Allocation

In this paper, we introduce and analyze new envy-based fairness concepts for agents with weights: these weights regulate their mutual envy in a situation where indivisible goods are allocated to the agents. We propose two variants of envy-freeness up to one item for the weighted setting: in the strong variant, the envy can be eliminated by removing an item from the envied agent's bundle, whereas in the weak variant, envy can be eliminated by either removing an item from the envied agent's bundle or by replicating an item from the envied agent's bundle in the envying agent's bundle. We prove that for additive valuations, a strongly weighted envy-free allocation up to one item always exists and can be efficiently computed by means of a weight-based picking sequence. For two agents, we can also efficiently achieve strong weighted envy-freeness up to one item in conjunction with Pareto optimality using a weighted version of the classic adjusted winner algorithm. In addition, we show that an allocation that maximizes the weighted Nash social welfare always satisfies weak weighted envy-freeness up to one item, but may fail to satisfy the strong version of this property.
The Penn Discourse Treebank 2.0 Annotation Manual

This report contains the guidelines for the annotation of discourse relations in the Penn Discourse Treebank (http://www.seas.upenn.edu/~pdtb), PDTB. Discourse relations in the PDTB are annotated in a bottom up fashion, and capture both lexically realized relations as well as implicit relations. Guidelines in this report are provided for all aspects of the annotation, including annotation explicit discourse connectives, implicit relations, arguments of relations, senses of relations, and the attribution of relations and their arguments. The report also provides descriptions of the annotation format representation.
Jump Gaussian Process Model for Estimating Piecewise Continuous Regression Functions

This paper presents a Gaussian process (GP) model for estimating piecewise continuous regression functions. In many scientiﬁc and engineering applications of regression analysis, the underlying regression functions are often piecewise continuous in that data follow different continuous regression models for diﬀerent input regions with discontinuities across regions. However, many conventional GP regression approaches are not designed for piece-wise regression analysis. There are piecewise GP models to use explicit domain partitioning and pose independent GP models over partitioned regions. They are not ﬂexible enough to model real datasets where data domains are divided by complex and curvy jump boundaries. We propose a new GP modeling approach to estimate an unknown piecewise continuous regression function. The new GP model seeks a local GP estimate of an unknown regression function at each test location, using local data neighboring the test location. Considering the possibilities of the local data being from diﬀerent regions, the proposed approach partitions the local data into pieces by a local data partitioning function. It uses only the local data likely from the same region as the test location for the regression estimate. Since we do not know which local data points come from the relevant region, we propose a data-driven approach to split and subset local data by a local partitioning function. We discuss several modeling choices of the local data partitioning function, including a locally linear function and a locally polynomial function. We also investigate an optimization problem to jointly optimize the partitioning function and other covariance parameters using a likelihood maximization criterion. Several advantages of using the proposed approach over the conventional GP and piecewise GP modeling approaches are shown by various simulated experiments and real data studies.
A Large-Scale Study of Phishing PDF Documents

Phishing PDFs are malicious PDF documents that do not embed malware but trick victims into visiting malicious web pages leading to password theft or drive-by downloads. While recent reports indicate a surge of phishing PDFs, prior works have largely neglected this new threat, positioning phishing PDFs as accessories distributed via email phishing campaigns. This paper challenges this belief and presents the first systematic and comprehensive study centered on phishing PDFs. Starting from a real-world dataset, we first identify 44 phishing PDF campaigns via clustering and characterize them by looking at their volumetric, temporal, and visual features. Among these, we identify three large campaigns covering 89% of the dataset, exhibiting significantly different volumetric and temporal properties compared to classical email phishing, and relying on web UI elements as visual baits. Finally, we look at the distribution vectors and show that phishing PDFs are not only distributed via attachments but also via SEO attacks, placing phishing PDFs outside the email distribution ecosystem. Thispaper also assesses the usefulness of the VirusTotal scoring system, showing that phishing PDFs are ranked considerably low, creating a blind spot for organizations. While URL blocklists can help to prevent victims from visiting the attack web pages, PDF documents seem not subjected to any form of content-based filtering or detection.
A principle for resilient sharing of distributed resources

A technique is described which permits distributed resources to be shared (services to be offered) in a resilient manner. The essence of the technique is to a priori declare one of the server hosts primary and the others backups. Any of the servers can perform the primary duties. Thus the role of primary can migrate around the set of servers. The concept of n-host resiliency is introduced and the error detection and recovery schemes for two-host resiliency are presented. The single primary, multiple backup technique for resource sharing is shown to have minimal delay. In the general case, this is superior to multiple primary techniques.
Building an overlay for wireless mesh network

The research and development of the wireless mesh networks (WMNs) now still popular. P2P was an old technique, but it is coming back for building an virtual overlay network on top of physical network. Open Chord as varian of Chord is a tool based on distributed hash table that can be used to build overlay. In swarm intelligence presented the particle swarm optimization (PSO) algorithm. One application of the algorithm named Sensor PSO for square area sensor network. We had modified this application for free rectangle area network. In this paper we report a study how to build an overlay network based on Open Chord. The objective of our study is to use overlay network to efficiently find the resources currently available in the WMNs. Our application firstly read the output of SensorPSO for building an underlay network, then built a virtual overlay on top of the underlay. The virtual overlay network resulted can be used for routing simulation.