Miracle-dz/UniFAR-FTUs huggingface dataset:
privGAN: Protecting GANs from membership inference attacks at low cost

Generative Adversarial Networks (GANs) have made releasing of synthetic images a viable approach to share data without releasing the original dataset. It has been shown that such synthetic data can be used for a variety of downstream tasks such as training classifiers that would otherwise require the original dataset to be shared. However, recent work has shown that the GAN models and their synthetically generated data can be used to infer the training set membership by an adversary who has access to the entire dataset and some auxiliary information. Current approaches to mitigate this problem (such as DPGAN) lead to dramatically poorer generated sample quality than the original non--private GANs. Here we develop a new GAN architecture (privGAN), where the generator is trained not only to cheat the discriminator but also to defend membership inference attacks. The new mechanism provides protection against this mode of attack while leading to negligible loss in downstream performances. In addition, our algorithm has been shown to explicitly prevent overfitting to the training set, which explains why our protection is so effective. The main contributions of this paper are: i) we propose a novel GAN architecture that can generate synthetic data in a privacy preserving manner without additional hyperparameter tuning and architecture selection, ii) we provide a theoretical understanding of the optimal solution of the privGAN loss function, iii) we demonstrate the effectiveness of our model against several white and black--box attacks on several benchmark datasets, iv) we demonstrate on three common benchmark datasets that synthetic images generated by privGAN lead to negligible loss in downstream performance when compared against non--private GANs.
Classifying network protocols: A 'two-way' flow approach

The identification and classification of network traffic and protocols is a vital step in many quality of service and security systems. Traffic classification strategies must evolve, alongside the protocols utilising the Internet, to overcome the use of ephemeral or masquerading port numbers and transport layer encryption. This research expands the concept of using machine learning on the initial statistics of flow of packets to determine its underlying protocol. Recognising the need for efficient training/retraining of a classifier and the requirement for fast classification, the authors investigate a new application of k-means clustering referred to as 'two-way' classification. The 'two-way' classification uniquely analyses a bidirectional flow as two unidirectional flows and is shown, through experiments on real network traffic, to improve classification accuracy by as much as 18% when measured against similar proposals. It achieves this accuracy while generating fewer clusters, that is, fewer comparisons are needed to classify a flow. A 'two-way' classification offers a new way to improve accuracy and efficiency of machine learning statistical classifiers while still maintaining the fast training times associated with the k-means.
Fast time-to-depth conversion and interval velocity estimation in the case of weak lateral variations

Time-domain processing has a long history in seismic imaging and has always been a powerful workhorse that is routinely used. It generally leads to an expeditious construction of the subsurface velocity model in time, which can later be expressed in the Cartesian depth coordinates via a subsequent time-to-depth conversion. The conventional practice of such a conversion is done using Dix inversion, which is exact in the case of laterally homogeneous media. For other media with lateral heterogeneity, the time-to-depth conversion involves solving a more complex system of partial differential equations (PDEs). We have developed an efficient alternative for time-to-depth conversion and interval velocity estimation based on the assumption of weak lateral velocity variations. By considering only first-order perturbative effects from lateral variations, the exact system of PDEs required to accomplish the exact conversion reduces to a simpler system that can be solved efficiently in a layer-stripping (downward-stepping) fashion. Numerical synthetic and field data examples show that our method can achieve reasonable accuracy and is significantly more efficient than previously proposed methods with a speedup by an order of magnitude.
SRPH Journal of Interdisciplinary Studies

This open-access journal is published under the terms of the Creative Commons Attribution-Noncommercial 4.0 International License. Analyzing Advantages and Benefits of Information Technologies in Organizations Rayhon Davoudizadehand Seyed Amin Hosseini Seno Department of Management, Ferdowsi University of Mashhad, Mashhad, Iran. Department of Computer, Ferdowsi University of Mashhad, Mashhad, Iran.
Columbia University TRECVID-2005 Video Search and High-Level Feature Extraction

Oct. 28 2005 Descriptions of Submitted Runs High-Level feature extraction A_DCON1_1: Choose the best-performing classifier from the following runs for each concept. A_DCON2_2: linear weighted fusion of 4 SVM classifiers using color/texture, parts-base classifier, and tf-idf text classifier. A_DCON3_3: same as above, except a new input-adaptive fusion method was used. A_DCON4_4: average fusion of 4 SVM classifiers using color/texture, parts-based classifier, and naïve Bayesian text classifier. A_DCON5_5: same as above, except the naïve Bayesian text classifier was not fused. A_DCON6_6: Choose the best performing uni-model visual classifier among the 4 SVM’s and parts-based classifier for each concept. No classifier fusion was done. A_DCON7_7: a single SVM classifier using color and texture trained on the whole training set (90 videos) with 20% negative samples.
COMPARISON OF NONCOHERENT DETECTORS FOR SOQPSK AND GMSK IN PHASE NOISE CHANNELS

Shaped offset quadrature phase-shift keying (SOQPSK) and Gaussian minimum shift-keying (GMSK) are highly bandwidth efficient continuous phase modulation (CPM) schemes that are closely related when viewed as OQPSK-type modulations at the receiver. For both of these modulation schemes, coherent detectors are available with good performance in additive white Gaussian noise (AWGN). However in many applications noncoherent receivers are preferred as they are more robust, easy to synchronize and can recover input bits in the presence of phase noise. In this work we provide a comprehensive set of numerical performance results for SOQPSK and GMSK noncoherent detectors in phase noise channels. Since highly bandwidth efficient CPMs such as SOQPSK and GMSK require extremely complex receivers, we also address this problem with several complexity reduction procedures that have been proposed in literature. In particular, these are done for noncoherent detection of GMSK for the first time. We also provide results for serially concatenated (SC)-SOQPSK and SC-GMSK as SC systems with CPM as recursive inner codes have high coding gains at low power and are widely used.
Stream temperature‐equilibrium temperature relationship

Equilibrium temperature is the water temperature at which the sum of all heat fluxes through the water surface is zero. It can be calculated from weather data. Mean weekly stream temperature was found to be linearly related to mean weekly equilibrium temperature above 0°C. The slopes and intercepts of the linear relationship were used to identify effects of shading, sheltering, cold water inputs (groundwater, meltwater, and deep reservoir releases) and warm water inputs (wastewater, cooling water, and lake surface water). The linearity hypothesis was confirmed for data from 596 U.S. Geological Survey stream gaging stations in the eastern and central United States. For approximately 15% (89 of 596, NSC ≥ 0.90) of stream gaging stations, weekly equilibrium temperature was a good estimator of weekly stream temperature with zero wind sheltering and sun shading. With sheltering and shading the number rose to 26% (156 of 596). For these streams the heat exchange through the water surface has the most controlling effect on stream temperatures. For the remaining 74% of streams the relationship between weekly stream temperature and weekly equilibrium temperature was also linear, but its slope was significantly less than 1.0 (even after calibration for shading and sheltering), indicating that processes other than surface heat exchange have an influence. Cold water inflows were dominant for 8% (46 of 596) of stream gaging sites. Less than 5% of all stream gaging stations showed evidence of unnatural heat inputs. Fitting an equilibrium temperature linearly to recorded stream temperatures, e.g., at a weekly timescale, can be of use to project stream temperatures under different weather‐climate scenarios or to identify both natural and anthropogenic heat and hydrologic inputs to streams.
Convolution in the Cloud: Learning Deformable Kernels in 3D Graph Convolution Networks for Point Cloud Analysis

Point clouds are among the popular geometry representations for 3D vision applications. However, without regular structures like 2D images, processing and summarizing information over these unordered data points are very challenging. Although a number of previous works attempt to analyze point clouds and achieve promising performances, their performances would degrade significantly when data variations like shift and scale changes are presented. In this paper, we propose 3D Graph Convolution Networks (3D-GCN), which is designed to extract local 3D features from point clouds across scales, while shift and scale-invariance properties are introduced. The novelty of our 3D-GCN lies in the definition of learnable kernels with a graph max-pooling mechanism. We show that 3D-GCN can be applied to 3D classification and segmentation tasks, with ablation studies and visualizations verifying the design of 3D-GCN.
Implications of climate change for shipping: Opening the Arctic seas

This paper assesses the value and environmental feasibility of Arctic shipping by reviewing the relevant scientific and economic peer‐reviewed literature. From the physical perspective, this paper examines the impact of climate change on sea ice and marine weather and considers the resultant consequences for Arctic shipping accessibility. From an economic perspective, it reviews the major research investigating the economic feasibility of diverting ships from conventional shipping routes to Arctic routes, the attitudes of shipping stakeholders, and other major factors affecting the prospect of Arctic shipping. This review also identifies important research gaps. Ultimately, we find that the complex environmental and economic dynamics of the Arctic suggest that an appropriate understanding of Arctic shipping will require close collaboration between natural and social scientists.
Results of ASTM round robin testing for mode 1 interlaminar fracture toughness of composite materials

The results are summarized of several interlaboratory 'round robin' test programs for measuring the mode 1 interlaminar fracture toughness of advanced fiber reinforced composite materials. Double Cantilever Beam (DCB) tests were conducted by participants in ASTM committee D30 on High Modulus Fibers and their Composites and by representatives of the European Group on Fracture (EGF) and the Japanese Industrial Standards Group (JIS). DCB tests were performed on three AS4 carbon fiber reinforced composite materials: AS4/3501-6 with a brittle epoxy matrix; AS4/BP907 with a tough epoxy matrix; and AS4/PEEK with a tough thermoplastic matrix. Difficulties encountered in manufacturing panels, as well as conducting the tests are discussed. Critical issues that developed during the course of the testing are highlighted. Results of the round robin testing used to determine the precision of the ASTM DCB test standard are summarized.
Your Installed Apps Reveal Your Gender and More!

In this paper, we highlight a potential privacy threat in the current smartphone platforms, which allows any third party to collect a snapshot of installed applications without the user's consent. This can be exploited by third parties to infer various user attributes similar to what is done through tracking. We show that using only installed apps, user's gender, a demographic attribute that is frequently used in targeted advertising, can be instantly predicted with an accuracy around 70%, by training a classifier using established supervised learning techniques.
Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks

MOTIVATION An important problem in systems biology is the inference of biochemical pathways and regulatory networks from postgenomic data. Various reverse engineering methods have been proposed in the literature, and it is important to understand their relative merits and shortcomings. In the present paper, we compare the accuracy of reconstructing gene regulatory networks with three different modelling and inference paradigms: (1) Relevance networks (RNs): pairwise association scores independent of the remaining network; (2) graphical Gaussian models (GGMs): undirected graphical models with constraint-based inference, and (3) Bayesian networks (BNs): directed graphical models with score-based inference. The evaluation is carried out on the Raf pathway, a cellular signalling network describing the interaction of 11 phosphorylated proteins and phospholipids in human immune system cells. We use both laboratory data from cytometry experiments as well as data simulated from the gold-standard network. We also compare passive observations with active interventions. RESULTS On Gaussian observational data, BNs and GGMs were found to outperform RNs. The difference in performance was not significant for the non-linear simulated data and the cytoflow data, though. Also, we did not observe a significant difference between BNs and GGMs on observational data in general. However, for interventional data, BNs outperform GGMs and RNs, especially when taking the edge directions rather than just the skeletons of the graphs into account. This suggests that the higher computational costs of inference with BNs over GGMs and RNs are not justified when using only passive observations, but that active interventions in the form of gene knockouts and over-expressions are required to exploit the full potential of BNs. AVAILABILITY Data, software and supplementary material are available from http://www.bioss. sari.ac. uk/staff/adriano/research.html
Consumers' perception of mobile internet in Australia

Mobile Internet, which refers to the use of the Internet via a handheld device (such as mobile phone or PDA), has received much attention in various countries. At this stage, little is known why this technology has been used widely in some countries such as Japan and Korea, and has not been so in other countries. To enrich the existing studies in this context, which are currently limited, this paper explores the Australian consumer’s perception of mobile Internet in order to identify some factors that may foster or hinder its use. The Technology Acceptance Model (TAM) is employed to provide the theoretical foundation for this study. Based on the empirical data collected from a survey, the findings demonstrate the importance of functionality (usefulness), an easy-to-use interface, and social networks as critical influences on both intention to use and the extent of usage of mobile Internet in Australia.
L shell distribution of energetic electrons at Saturn

[1] Energetic electron fluxes (110-485 keV) observed by the MIMI/LEMMS instrument on the Cassini mission to Saturn were averaged into azimuthal bins and L shell bins for the period from day 150 2004 to day 366 2008. In local time, the electrons fluxes maximize on the night side between the Mimas and Rhea L shells and have a minimum near noon. This local time behavior may be a result of nightside injection combined with subcorotational drift in a nondipolar field. In SLS longitude, the electrons are smoothly distributed, showing no signs of spiral patterns on this multiyear timescale. The lower energy electrons (110-365 keV) form an inner belt near the Mimas L shell and an outer belt between the Dione and Rhea L shells.
Explaining Variations in Client Extra Costs between Software Projects Offshored to India Acknowledgements

Gaining economic benefits from substantially lower labor costs has been reported as a major reason for offshoring labor-intensive information systems (IS) services to low-wage countries; however, if wage differences are so high, why is there such a high level of variation in the economic success between offshored IS projects? This study argues that offshore outsourcing involves a number of extra costs for the client organization that account for the economic failure of offshore projects. The objective is to disaggregate these extra costs into its constituent parts and to explain why they differ between offshored software projects. The focus is set on software development and maintenance projects that are offshored to Indian vendors. A theoretical framework is developed a priori based on transaction cost economics (TCE) and the knowledge-based view of the firm, complemented by factors that acknowledge the specific offshore context. The framework is empirically explored using a multiple case study design including six offshored software projects in a large German Financial Service institution. The results of our analysis indicate that the client incurs post contractual extra costs for four types of activities: (1) requirements specification and design, (2) knowledge transfer, (3) control, and (4) coordination. In projects that require a high level of client-specific knowledge about idiosyncratic business processes and software systems, these extra costs were found to be substantially higher than in projects were more general knowledge was needed. Notably, these costs most often arose independently from the threat of opportunistic behavior, challenging the predominant TCE logic of market failure. Rather, the client extra costs were particularly high in client-specific projects because the effort for managing the consequences of the knowledge asymmetries between client and vendor were particularly high in these projects. Prior experiences of the vendor with related client projects were found to reduce the level of extra costs but could not fully offset the increase in extra costs in highly client-specific projects. Moreover, cultural and geographic distance between client and vendor as well as personnel turnover were found to increase client extra costs. Slight evidence was found, however, that the cost increasing impact of these factors was also leveraged in projects with a high level of required client-specific knowledge (moderator effect).
Behavioral/systems/cognitive Functional Interaction between the Hippocampus and Nucleus Accumbens Shell Is Necessary for the Acquisition of Appetitive Spatial Context Conditioning

The nucleus accumbens (NAc) has been implicated in a variety of associative processes that are dependent on the integrity of the amygdala and hippocampus (HPC). However, the extent to which the two subregions of the NAc, the core and shell, form differentiated circuits within the amygdala-and hippocampal-ventral striatal circuitry remains unclear. The present study investigated the effects of selective excitotoxic lesions of the nucleus accumbens shell or core subregion on appetitive elemental cue and context conditioning, shown previously to be dependent on the basolateral amygdala and hippocampus, respectively. Rats were trained sequentially to acquire discrete conditioned stimulus–sucrose conditioning, followed by spatial context–sucrose conditioning in a place preference apparatus characterized by three topographically identical chambers, the chambers being discriminable only on the basis of path integration. NAc shell lesions selectively impaired the acquisition of conditioned place preference and the use of spatial information to retrieve information about a discrete cue, whereas, as expected, NAc core lesions attenuated the acquisition of cue conditioning compared with sham rats. In a subsequent experiment, disconnection of the HPC from the NAc shell using unilateral asymmetric lesions of each structure resulted in a pattern of impairment in place conditioning and context-dependent cue retrieval similar to that produced by NAc shell lesions. These data not only suggest that the NAc core and shell subregions subserve distinct associative processes but also that the NAc shell and HPC are important functional components of a limbic corticostriatal network involved in spatial context conditioning.
Soil Gross Nitrogen Transformations in Typical Karst and Nonkarst Forests, Southwest China

Soil gross nitrogen (N) transformations are crucial for assessing forest N status. Although there is evidence suggesting that the N cycle is open in the karst forest, southwest China, process‐based investigation of gross soil N transformations is limited. In the current study, gross soil N transformations were investigated using 15N isotope dilution and 15N tracer techniques in a typical karst forest with calcareous soil (Calcareous lithosols) in comparison with an adjacent nonkarst forest with red soil (Haplic acrisol). The gross rates of N mineralization, nitrification, dissimilatory nitrate reduction to ammonium (DNRA), and nitrate immobilization were significantly greater in the karst forest. Ammonium immobilization was comparable to gross N mineralization, so that ammonium could be efficiently conserved in the nonkarst forest. Meanwhile, the produced nitrate was mostly retained via DNRA and nitrate immobilization. This resulted in a negligible net nitrate production in the nonkarst forest. In contrast, ammonium immobilization rate only accounted for half of gross N mineralization rate in the karst forest. The nitrate retention capacity is relatively low, with 41.6 ± 4.2% of the produced nitrate being retained via DNRA and nitrate immobilization. Due to relatively low nitrate retention capacity, nitrate was accumulated in the karst forest soil. Our results indicate that the nonkarst forest with red soil holds a very conservative N cycle, but the N cycle in the karst forest is leaky.
NaCl Crust Architecture and Its Impact on Evaporation: Three‐Dimensional Insights

Salt precipitation over porous media due to evaporation is known to affect various important processes, including evaporation itself. Many studies have shown that salt crust precipitation reduces evaporation rate, and it has been suggested that the crust constitutes a barrier to vapor flow. Nevertheless, it remains unclear how a porous medium such as the salt crust does not enable upward liquid water transfer by capillary flow. Herein, we show by various imaging methods that the salt crust grows out of specific nucleation centers, to create an elevated crust approximately 1 mm above the matrix surface, most of which is disconnected from the matrix. This indicates that evaporation from a porous medium that is covered by NaCl efflorescence salt crust may occur below the crust, at the soil surface.