Miracle-dz/UniFAR-FTUs huggingface dataset:
Complex networks and decentralized search algorithms

The study of complex networks has emerged over the past several years as a theme spanning many disciplines, ranging from mathematics and computer science to the social and biological sciences. A significant amount of recent work in this area has focused on the development of random graph models that capture some of the qualitative properties observed in large-scale network data; such models have the potential to help us reason, at a general level, about the ways in which real-world networks are organized. We survey one particular line of network research, concerned with small-world phenomena and decentralized search algorithms, that illustrates this style of analysis. We begin by describing awell-known experiment that provided the first empirical basis for the �six degrees of separation� phenomenon in social networks; wethen discuss some probabilistic network models motivated by this work, illustrating how these models lead to novel algorithmic and graph-theoretic questions, and how they are supported by recent empirical studies of large social networks.
Congestion control with dynamic threshold adaptation and cross-layer response for tcp over IEEE 80.11 wireless networks

Wireless technologies provide mobile access and enable rapid and cost-effective network deployment. But a wireless link is generally accompanied by high interference, transmission errors and a varying latency. The erratic packet losses usually lead to a curbing of the flow of segments on the TCP connection, and thus limit TCP performance. This paper presents a threshold control mechanism with cross-layer response approach for improving TCP Vegas performance in IEEE 802.11 wireless networks. By making slight modifications to the legacy IEEE 802.11 MAC and TCP, the numerical results reveal that the proposed scheme provides a significant improvement in TCP performance under IEEE 802.11 wireless environments.
An Adaptive Spatial Subdivision of the Object Space for Fast Collision Detection of Animating Rigid Bodies

Collision detection tests between objects dominate run time simulation of rigid body animation. Traditionally, hierarchical bounding box tests are used to minimize collision detection time. But the bounding boxes do not take shapes of the objects into account which results in a large number of collision detection tests. We propose an adaptive spatial subdivision of the object space based on Oct-tree structure to rectify this problem. We also present a technique for efficiently updating this structure periodically during the simulation.
Enhancing personal interaction through the web interface in online shopping

At present, most e-commerce websites are low in social presence. Thus in contrast with traditional face-to-face business settings, they are difficult to satisfy online consumers’ social needs for interacting with other humans. Following this perspective, a significant number of literature calls for a need to improve e-commerce web sites’ social presence in addition to the well-recognized aspects of perceived usefulness and perceived ease of use. In this study, the author finds that within the context of an e-commerce web site selling electronic products (mobile phone), the adoption of interface design features of socially rich text and picture (enabling imaginary interaction with other humans) and virtual community (providing means for actual interaction with other humans) is an efficient way of increasing social presence. Results, however, also suggests that social presence per se is not significant in predicting online purchase intention. Even so, e-vendors may also benefit from offering high level of personal interaction on their e-commerce web sites as socially rich text and picture and virtual community have influential impacts on trust and perceived value, the two important predicators of purchase intention found in this study. Further analysis of the reasons behind are conducted and implications of these findings for theory and practice are discussed.
Influence of Topography and Management Practices on Nitrogen Content of Soils Formed in Biotite-Granite Parent Material on the Jos Plateau, Nigeria

Nitrogen is a macro nutrient that is essential to crop growth and production. One of the major constraints to sustainable crop production on the Jos Plateau is soil fertility. The availability of nitrogen and other essential plant nutrients in the soil is a key indicator of soil fertility. The content of nitrogen in soils is affected by a number of factors such as drainage, texture and slope steepness. This study was conducted on one of the important parent materials on the Jos Plateau, biotite-granite, taking into account the influence of topography and management practices by farmers. The result showed that the nitrogen content of the soils were quite low. The surface soils had a range of 0.021-0.140% with mean of 0.065%. The slope facets had means of 0.058%, 0.042%, 0.069% and 0.103% respectively for the upper foot slope, middle foot slope, lower foot slope and depression. The higher content of nitrogen in the depression was strongly correlated (r =0.694) with organic matter. The result for the profile pits revealed that soils in the upper foot slope and depression had higher contents at the surface (0.105% and 0.140%) while the middle foot slope had the lowest. The profile pits with and without application of burnt municipal waste had 0.150% and 0.090% respectively at the surface. T-test gave a value of 0.001 for nitrogen 0.01 to 0.001 for other soil properties indicating strong differences in the means International Journal of Scientific and Research Publications, Volume 8, Issue 9, September 2018 320 ISSN 2250-3153 http://dx.doi. org/10.29322/IJSRP.8. 9.2018. p8144 www.ijsrp. org for the two treatments. Crop rotation, planting of cover crops and mixed farming were suggested as management practices that could be used to increase nitrogen content of the soils.
Squinted SAR focusing for improving automatic radar sounder data analysis and enhancement

ABSTRACT Radar sounder (RS) instruments are providing a huge amount of subsurface data. In order to support the study of this data, several automatic methods have been recently proposed. So far, the development of such methods mostly focused on publicly available radargrams (standard products), which are generated from raw data in order to obtain high visual quality images. The possibility to exploit raw processing to derive additional information for automatic analyses has not yet been considered. In order to fill this gap, in this paper, we show that by properly tuning raw signal processing it is possible to automatically obtain additional a priori information on subsurface targets. Such information can be used to potentially improve the results of further automatic analyses and/or address problems that cannot be easily solved automatically using only standard products. In particular, we propose four measurements obtained using squinted synthetic aperture radar focusing that provide useful physical information about subsurface features. Moreover, in order to prove the effectiveness of the proposed approach, a novel preprocessing method for automatic layer detection techniques based on the concepts developed in this paper is presented and validated. All the examples reported in the paper use real planetary RS data acquired by the SHAllow RADar instrument on Mars.
Adaptive enumeration of implicit surfaces with a(cid:14)ne arithmetic

We discuss adaptive enumeration and rendering methods for implicit surfaces, using octrees computed with a(cid:14)ne arithmetic, a new tool for range analysis. A(cid:14)ne arithmetic is similar to standard interval arithmetic, but takes into account correlations between operands and sub-formulas, generally providing much tighter bounds for the computed quantities. The resulting octrees are accordingly much smaller, and the rendering faster. We also describe applications of a(cid:14)ne arithmetic to intersection and ray tracing of implicit surfaces.
Blind Audio Source Separation by

Blind Audio Source Separation Vincent Y.F. Tan (SID) Signal Processing Laboratory, Cambridge University Engineering Department, Cambridge, CB2 1PZ, UK In this project, the problem of blind separation of underdetermined mixtures of audio sources is considered. The sources have to be sparsely represented on a given basis or dictionary. They are assumed to follow a Student t distribution in the transformed domain. A Bayesian approach using Gibbs Sampling is employed to estimate the sources in the transformed domain. The performance resulting from the use of various transform methods is compared. A central theme of this project is sparsity and how this relates to separation quality and noise reduction. The orthonormal bases that will be considered include the Discrete Cosine Transform, the Modified Discrete Cosine Transform, two Discrete Wavelet Transforms and a basis obtained using the Wavelet Packet Best Basis Algorithm. The overcomplete dictionaries that will be used include the Hybrid Transform and the Short-Time Discrete Cosine Transform. These transforms were chosen because of their varying abilities to provide sparse representations of different classes of audio signals. The numerical results show that if the signal is sparse in the transformed domain, the separation results are better. Sparsity is measured using the normalized L1 norm. Various measures of separation quality, including the Source to Distortion Ratio will be used. In general, the Modified Discrete Cosine Transform is a good representation for audio signals with more tonals than transients. The Discrete Wavelets provide a sparser representation for audio signals with more transients than tonals. Due to its adaptive nature, the Wavelet Packet Best Basis Algorithm finds a basis that provides a sparse representation for all the classes of signals that were tested. Finally, contrary to our initial expectations, the overcomplete dictionaries failed to provide a significant improvement in separation quality. We propose an explanation for this observation.
Catch Me If You Can: Financial Misconduct around Corporate Headquarters Relocations

We find that misreporting activities and aggressive earnings management positively associate with the probability of headquarters relocation, after controlling for economic factors and high dimensional fixed effects. Firms with higher probability of conducting financial fraud are more likely to move to a location where the regional SEC office has less intense scrutiny against local firms, and such firms tend to provide no explicit reason for relocations. Moreover, using shocks to local SEC enforcement intensity, we find that the probability of headquarters relocation increases after the shock for firms with higher likelihood of financial misconduct. Finally, a propensity matching estimation shows that relocated firms are more likely to continue conducting fraud and restate previously reported earnings than firms that do not relocate. However, they are not more likely to be caught by either regulators or shareholders. Our results provide new evidence on the fraudulent motives for headquarters relocations and suggest that the intensity of local SEC scrutiny has a direct impact on firm’s financial misconduct and location decisions.
Full-Text version Title : Efficient Biometric and Password Based Mutual Authentication for Consumer USB Mass Storage Devices

A Universal Serial Bus (USB) Mass Storage Device (MSD), often termed a USB flash drive, is ubiquitously used to store important information in unencrypted binary format. This low cost consumer device is incredibly popular due to its size, large storage capacity and relatively high transfer speed. However, if the device is lost or stolen an unauthorized person can easily retrieve all the information. Therefore, it is advantageous in many applications to provide security protection so that only authorized users can access the stored information. In order to provide security protection for a USB MSD, this paper proposes a session key agreement protocol after secure user authentication. The main aim of this protocol is to establish session key negotiation through which all the information retrieved, stored and transferred to the USB MSD is encrypted. This paper not only contributes an efficient protocol, but also does not suffer from the forgery attack and the password guessing attack as compared to other protocols in the literature. This paper analyses the security of the proposed protocol through a formal analysis which proves that the information is stored confidentially and is protected offering strong resilience to relevant security attacks. The computational cost and communication cost of the proposed scheme is analyzed and compared to related work to show that the proposed scheme has an improved tradeoff for computational cost, communication cost and security.
Detection and attribution of long-term climatic and hydrological trends in the Cathedral Peak catchments.

It has become accepted that global change is a considerable threat to vulnerable environments such as mountains. Various studies highlight the importance of change detection in long term climatic and hydrological data in understanding the catchment responses to various environmental changes. Long term trend detection of rainfall, temperature and streamflow has shown to be of practical importance to water resources management and planning. More especially in mountainous regions which have highly variable microclimates and are vulnerable to climate change impacts. In mountainous regions, the lack of data as a result of sparse observation networks often leads to a poor understanding of the climatic systems and amplifies the degree of uncertainty in trend detection. Given this need, the area of interest to this study was the intensively monitored Cathedral Peak catchments which are representative of the uKhahlamba Drakensberg region where a significant amount of water is generated for the KwaZulu-Natal and Gauteng provinces. In this context, the aim of the study was to detect trends in the historical hydroclimatic data of the Cathedral Peak catchments and gain understanding about the causes of change. To accurately detect and attribute the hydroclimatic trends in rainfall, temperature and streamflow the study was carried out using three methods. The first method investigated the data for historical trends (1948 - 2000), followed by a comparative analysis which investigated the differences between the historical and current records (2012 – 2015). The third method was an attribution study which investigated the influence of rainfall and land use to determine which of the two considered factors contributed as the cause of change. The Mann-Kendall and Sen’s slope estimator non-parametric tests were used to detect trends in the data and determine magnitude of the trends detected while the Mann-Whitney test was used to detect the difference between the historical and current records. The results across all times scales showed a few statistically significant trends in rainfall. However, the majority of the rainfall analyses showed no statistically significant trends with the expectation of a decline autumn rainfall detected in the seasonal analysis. The comparative analysis showed a few significant differences indicating increased rainfall between the historical and current period. The short current record was seen to have restrained the ability to detected definite differences in the rainfall. The significant positive trends detected in the historical temperature records and the comparative analysis provided more evidence of an increase in the temperature between the historical and current period. Furthermore, the positive trends found in the daily maximum and average temperatures were consistent with those from previous studies, which can be used to establish that there has been a general increase in the temperature between 1955 and 2000. Significant negative trends were detected in both the historical streamflow and the…
A numerical study of 3D frequency-domain elastic full-waveform inversion

We have developed a 3D elastic full-waveform inversion (FWI) algorithm with forward modeling and inversion performed in the frequency domain. The Helmholtz equation is solved with a second-order finite-difference method using an iterative solver equipped with an efficient complex-shifted incomplete LU-based preconditioner. The inversion is based on the minimization of the data misfit functional and a total variation regularization for the unknown model parameters. We implement the Gauss-Newton method as the optimization engine for the inversions. The codes are parallelized with a message passing interface based on the number of shots and receivers. We examine the performance of this elastic FWI algorithm and workflow on synthetic examples including surface seismic and vertical seismic profile configurations. With various initial models, we manage to obtain high-quality velocity images for 3D earth models.
Panel on "Past and Future of Computer Science Theory" (Discussion Paper)

The twenty-ninth edition of the SEBD (Italian Symposium on Advanced Database Systems), held on 5-9 September 2021 in Pizzo (Calabria Region, Italy), included a joint seminar on “Reminiscence of TIDB 1981” with invited talks given by some of the participants to the Advanced Seminar on Theoretical Issues in Databases (TIDB), which took place in the same region exactly forty years earlier. The joint seminar was concluded by a Panel on “The Past and the Future of Computer Science Theory” with the participation of four distinguished computer science theorists (Ronald Fagin, Georg Gottlob, Christos Papadimitriou and Moshe Vardi), who were interviewed by Giorgio Ausiello, Maurizio Lenzerini, Luigi Palopoli, Domenico Saccà and Francesco Scarcello. This paper reports the summaries of the four interviews.
A Gesture Processing Framework for Multimodal Interaction in Virtual Reality

This article presents a gesture detection and analysis framework for modelling multimodal interactions. It is particulary designed for its use in Virtual Reality (VR) applications and contains an abstraction layer for different sensor hardware. Using the framework, gestures are described by their characteristic spatio-temporal features which are on the lowest level calculated by simple predefined detector modules or nodes. These nodes can be connected by a data routing mechanism to perform more elaborate evaluation functions, therewith establishing complex detector nets. Typical problems that arise from the time-dependent invalidation of multimodal utterances under immersive conditions lead to the development of pre-evaluation concepts that as well support their integration into scene graph based systems to support traversal-type access. Examples of realized interactions illustrate applications which make use of the described concepts. CR Categories: D.2. 2 [Software Engineering]: Design Tools and Techniques User interfaces; H.5. 2 [Information Interfaces and Presentation (e.g., HCI)]: User Interfaces Interaction styles, Natural Language; I.2. 7 [Artificial Intelligence]: Natural Language Processing Language parsing and understanding; I.3. 6 [Computer Graphics]: Methodology and Techniques Interaction techniques, Languages, Standards; I.3. 7 [Computer Graphics]: Three-Dimensional Graphics and Realism Virtual reality
Distributed Enforcement of Unlinkability Policies : Looking Beyond the Chinese Wall Apu Kapadia ∗ Institute for Security Technology Studies ( ISTS ) Dartmouth College

This paper presents an access control model that preserves the unlinkability of audit-logs in a distributed environment. The model restricts entities from accessing and correlating two or more audit-records belonging to different service invocations created by the same user. While the traditional Chinese Wall (CW) model is sufficient to enforce this type of unlinkability, in distributed environments CW is inefficient because the simple security condition semantics requires knowledge of a user’s access history. Our model allows specifications that are simple and efficient to enforce in a decentralized manner without the need for an access history. The proposed enforcement architecture allows users to negotiate unlinkability policies with the system. The system attaches automatically generated policy constraints to the audit-records. When these constraints are enforced appropriately, they implement unlinkability policies that are provably secure and precise for a fixed protection state. The model extends to a versioning scheme that adapts to evolving protection state, trading off precision to maintain the security of deployed policies.
Sustainable production zoning for agroclimatic classification using GIS and remote sensing

Agriculture is a primary productivity sector which is highly dependent on environmental conditions. The agroclimatic potential of agricultural areas has to be assessed in order to achieve sustainable and efficient use of natural resources in combination with production maximization. Temperature and rainfall, in terms of quantity and spatiotemporal variability, are variables which determine the type of crops suitable to a given location. Rainfall variable can also be interpreted as availability of sufficient water required for production of given crops. These variables, in combination with soil type and geomorphology, also determine areas where high levels of production are appropriate, avoiding the threat of degrading the natural resources. In the current work, zones indicating water availability are combined with topographic features and soil types in order to identify areas for sustainable production. Firstly, aridity index (AI) and vegetation health index (VHI) are used in order to define zones adequate for sustainable farming according to water limitations. As crop growth is affected by water supply, these zones are named water limited growth environment (WLGE) zones. Al and VHI are computed on monthly time step for twenty hydrological years, from October 1981 to September 2001. VHI is derived from NOAA/AVHRR data, while in AI computations both satellite and conventional field data are used. Then, WLGE zones are combined with soil maps and a digital elevation model (DEM) of the area under investigation in order to define zones appropriate for sustainable production. The study area is the aquatic district of Thessaly, located in Central Greece. The current application has resulted in the definition of sustainable production zones by means of parallelepiped supervised classification using the two indices, soil maps and DEM. These zones can be further used for agroclimatic classification.
Information-theoretic Classification Accuracy: A Data-driven Criterion to Combining Ambiguous Outcome Labels in Multi-class Classification

Chihao Zhang1,2, Yiling Elaine Chen3, Shihua Zhang*1,2,4,5, and Jingyi Jessica Li ∗3, 6 1NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China 2School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China. 3Department of Statistics, University of California, Los Angeles, CA 90095 4Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China 5Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China 6Interdepartmental Program in Bioinformatics, Department of Computational Medicine and Department of Biostatistics, University of California, Los Angeles, CA 90095 Abstract