Miracle-dz/UniFAR-FTUs huggingface dataset:
The Improvement of Naive Bayesian Classifier Based on the Strategy of Fuzzy Feature Selection with the Dual Space

Naive Bayesian classifier (NBC) is a simple and effective classification model. However, the fact that the assumption of independence is often violated in reality makes it perform poorly on some datasets. In our pre-research, we attempt to improve the NBC model based on the strategy of the fuzzy feature selection. The main idea of the improvement strategy is to adjust the features' contribution to classification through the feature important factor (FIF) which describes the importance of the features. This strategy overcomes deficiencies caused by the assumption of independence. Based on the pre-research, we optimize the strategy of fuzzy feature selection with the establishment of the dual NBC model in order to improve the NBC model more. Through the experimental analysis on the UCI datasets, the strategy of the fuzzy feature selection on the dual NBC model is proved effective.
1 Testing Graph Properties in the Dense Graph Model 2 2 Testing Graph Properties in the Bounded-Degree Graph Model 4 3 Testing Graph Properties in the General Graph Model 5

The standard models of testing graph properties postulate that the vertex-set consists of {1, 2, . , n}, where n is a natural number that is given explicitly to the tester. Here we suggest more flexible models by postulating that the tester is given access to samples the arbitrary vertex-set; that is, the vertex-set is arbitrary, and the tester is given access to a device that provides uniformly and independently distributed vertices. In addition, the tester may be (explicitly) given partial information regarding the vertex-set (e.g., an approximation of its size). The flexible models are more adequate for actual applications, and also facilitates the presentation of some theoretical results (e.g., reductions among property testing problems). This programmatic note contains no real results. It merely presents the suggested definitions and discusses them.
Action Theories over Generalized Databases with Equality Constraints (Extended Abstract)

In this work we study action theories of the situation calculus such that the initial KB is a generalized database with equality constraints (GFDBs). We show that GFDBs characterize the class of definitional KBs and that they are closed under progression. We also show that, under conditions, generalized projection queries can be decided based on an induced transition system and evaluation of local conditions over states.
Between the Lines : Decipher the Firms ’ Fundamentals with Artificial

Abstract Our paper studies whether language patterns elicited by a different level of stimulus during earnings conference calls are informative about firms' earnings. Executives endure various levels of pressure when presenting a scripted managerial discussion and spontaneous answering to analysts' scrutinized questions. Such stimulus induces evasive answers, incoherent responses, and disturbances in emotion and cognition. Our artificial intelligence based measures of language patterns, built upon deep learning and topic modeling, transform analysts' perceptions to FinTech solutions. We find that evasive and incoherent answers forecast firms' earnings and stock return. A trading strategy based on evasiveness yields a positive risk-adjusted return.
Modeling of Dissolution‐Induced Permeability Evolution of a Granite Fracture Under Crustal Conditions

This work focuses on the interaction between pressure solution creep and contact area expansion under hydrothermal conditions and proposes an innovative process‐based approach for describing contact area expansion by fracture closure. The formulation is established in the physical context of pressure solution creep and represents the dynamic process of enhanced mineral dissolution over grain contacts, which moves toward equilibrium as a result of decrease of mineral solubility by pressure drop. Then, a theoretical maximum of the contact area ratio Rc,max is obtained from the formulation whose existence demonstrates that pressure solution is with an energy threshold for activation rather than spontaneously taking place under any circumstances. Based upon the formulation, a 1‐D reactive transport model is developed and applied to investigate dissolution‐induced permeability evolution of a granite fracture under crustal conditions. The applicability of the developed model to a polymineralic system is examined against the experimental measurements reported in Yasuhara et al. (2011, https://doi.org/10.1016/j.apgeochem.2011.07.005). This investigation reconfirms the significance of pressure solution creep in fracture permeability evolution under low and moderate temperatures and provides a justified interpretation for the unusual experimental observation that fracture permeability reduction does not necessarily lead to apparent increases of effluent element concentrations. The surface topography of fracture channels markedly affects hydraulic feedback on chemical compaction in terms of both magnitude and rate of change. Temperature elevation contributes to accelerating the progression of pressure solution creep.
Two fast parallel GCD algorithms of many integers SEDJELMACI

We present two new parallel algorithms which compute the GCD of n integers of O(n) bits in O(n/ logn) time with O(n ) processors in the worst case, for any > 0 in CRCW PRAM model. More generally, we prove that computing the GCD of m integers of O(n) bits can be achieved in O(n / logn) parallel time with O(mn ) processors, for any 2 ≤ m ≤ n/ logn, i.e. the parallel time does not depend on the number m of integers considered in this range. We suggest an extended GCD version for many integers as well as an algorithm to solve linear Diophantine equations.
Indian Journal of

The present study is aimed at assessing the burden among the caregivers of the elderly in rural families and to standardize and compare Burden Assessment Scale (BAS) and Caregivers’ Reaction Assessment scale (CRA) in Indian context. A Sample of 300 (176 women and 124 men) caregivers of the elderly was selected using a systematic sampling method from three village panchayats of a predominantly rural mandal (Padmanabham) of Visakhapatnam district, Andhra Pradesh. An interview schedule covering basic socio-demographic data and the two measures i.e. BAS and CRA was used to collect data from the caregivers. Findings reveal that burden and satisfaction of care giving is associated with sex and age of caregiver, and family income. A large percentage of caregivers expressed satisfaction about the care-giving role played by them. However, only a small percentage of women, as compared to men, expressed satisfaction about their care-giving role probably because the major burden of caring the elderly was actually shouldered by women rather than by men. Similarly, more women caregivers reported tiredness and worsening health due to stress arising out of their care giving roles. Lastly, evidence showed that higher age and lower income was found to bring down the caregiver satisfaction significantly.
non-fragile filtering for networked systems with

This paper is concerned with the robust non-fragile ﬁltering for a class of networked systems with distributed variable delays. We model such a complex delay system with an augmented switched system. For the ﬁltering implementation uncertainty, a stochastic variable is employed to indicate random occurrence of the ﬁlter gain change
Multivariate two-part statistics for analysis of correlated mass spectrometry data from multiple biological specimens

Motivation: High through-put mass spectrometry (MS) is now being used to profile small molecular compounds across multiple biological sample types from the same subjects with the goal of leveraging information across biospecimens. Multivariate statistical methods that combine information from all biospecimens could be more powerful than the usual univariate analyses. However, missing values are common in MS data and imputation can impact between-biospecimen correlation and multivariate analysis results. Results: We propose two multivariate two-part statistics that accommodate missing values and combine data from all biospecimens to identify differentially regulated compounds. Statistical significance is determined using a multivariate permutation null distribution. Relative to univariate tests, the multivariate procedures detected more significant compounds in three biological datasets. In a simulation study, we showed that multi-biospecimen testing procedures were more powerful than single-biospecimen methods when compounds are differentially regulated in multiple biospecimens but univariate methods can be more powerful if compounds are differentially regulated in only one biospecimen. Availability and Implementation: We provide R functions to implement and illustrate our method as supplementary information. Contact: sltaylor@ucdavis.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Where is the money ? Modeling Bitcoin users

Bitcoin is a decentralized digital currency introduced in 2008 that enables instant payments to anyone, anywhere in the world. Its increasing popularity has raised many questions on who are the agents in the “bitcoin economy” and what is the nature of the transactions between them. In this paper we use the public bitcoin records to shed some light on these questions. We categorize users by looking at network features and applying heuristics and clustering algorithms. Then we analyze the flow in terms of transaction quantity and volume over time, identifying what are the most common economic patterns and how they are evolving while bitcoin gets more popular.
Efficient BDD Algorithms for FSM Synthesis and Verification

We describe a set of BDD based algorithms for efficient FSM synthesis and verification. We establish that the core computation in both synthesis and verification is forming the image and pre-image of sets of states under the transition relation characterizing the design. To make these steps as efficient as possible, we address BDD variable ordering, use of partitioned transition relations, and use of clustering. We provide an integrated set of algorithms and give references and comparisons with previous work. We report experimental results on a series of seven industrial examples containing from 28 to 172 binary valued latches.
Interactive Control of Avatars Animated with Human Motion Data

Figure 1: Real-time avatar control in our system. (Top) The user controls the avatar’s motion using sketched paths in maze and rough terrain environments. (Bottom left) The user selects from a number of choices in a playground environment. (Bottom right) The user is controlling the avatar by performing a motion in front of a camera. In this case only, the avatar’s motion lags the user’s input by several seconds.
' Capture ' IP ' Assembler ' TCP ' Assembler ' ( FlowID ) ' Protocol ' Detector ' ( FlowID ) ' SMTP ' Processor ' ( FlowID ) ' Naïve ' Bayes ' Classifier

This paper presents SCALANYTICS, a declarative platform that supports high-performance application layer analysis of network traffic. SCALANYTICS uses (1) stateful network packet processing techniques for extracting application-layer data from network packets, (2) a declarative rule-based language called ANALOG for compactly specifying analysis pipelines from reusable modules, and (3) a task-stealing architecture for processing network packets at high throughput within these pipelines, by leveraging multi-core processing capabilities in a load-balanced manner without the need for explicit performance profiling. We have developed a prototype of SCALANYTICS that enhances a declarative networking engine with support for ANALOG and various stateful components, integrated with a parallel task-stealing execution model. We evaluate our SCALANYTICS prototype on a wide range of pipelines for analyzing SMTP and SIP traffic, and for detecting malicious traffic flows. Our evaluation on a 16-core machine demonstrate that SCALANYTICS achieves up to 11.4× improvement in throughput compared with the best uniprocessor implementation. Moreover, SCALANYTICS outperforms the Bro intrusion detection system by an order of magnitude when used for analyzing SMTP traffic.
Measurement of Social Capital in Enterprise Social Networks: Identification and Visualisation of Group Metrics (master thesis)

Social Capital describes the value of social structures in a social network. Effects of Social Capital, which include the improvement of knowledge sharing, collaboration and cooperation, can be observed in Enterprise Social Networks. Thus organisations are increasingly looking to employ Enterprise Social Networks platforms to facilitate these effects. The generated data on such platforms can be analysed to measure Social Capital. The measurement of Social Capital is achieved by operationalising Social Capital with the help of Social Network Analysis. It can be explained as the analysis of relationships between individuals and groups within a network. It is based on graph theory and represents individuals or groups as nodes and their interactions as edges. Typical goals of such an analysis include the identification of influencers, leaders and high-performers in an organisation. This thesis proposes to represent social groups as collective actors to utilise already existing Social Network Analysis metrics. The metrics are collected in a metric repository which contains the calculation schemas and interpretations. The schemas formally describe how a metric can be calculated and the interpretations discuss the values of the metrics against the backdrop of the Social Capital theory. The metric repository is used as basis for the development of a prototypical analysis platform. The platform calculates all the metrics for a social network based on a realworld dataset and visualises them in a website. The identified metrics, their visualisation and the applicability of the group model approach are discussed.
InfoHarness : The System for Search and Retrieval of Heterogeneous Information

The “InfoHarness” prototype is aimed at providing integrated and rapid access to huge amounts of heterogeneous information independent of its type, representation, and location. InfoHarness provides advanced search and browsing capabilities without imposing the burden of restructuring, reformatting or relocating information on information suppliers. This is achieved through creating metadata entries (e.g., type, location, access rights, owner, creation date, etc.) and associating them with the original information. The metadata extraction methods ensure rapid and largely automatic creation of information repositories. A stable hierarchy of abstract classes is proposed to organize the processing and representation needs of different types of information. An extensible hierarchy of terminal classes simplifies support for new information types and utilization of new indexing technologies. InfoHarness repositories may be accessed through Mosaic or any other HyperText Transfer Protocol (HTTP) compliant browser.
Algebrization: A New Barrier in Complexity Theory

Any proof of P ≠ NP will have to overcome two barriers: relativization and natural proofs. Yet over the last decade, we have seen circuit lower bounds (e.g., that PP does not have linear-size circuits) that overcome both barriers simultaneously. So the question arises of whether there is a third barrier to progress on the central questions in complexity theory. In this article, we present such a barrier, which we call algebraic relativization or algebrization. The idea is that, when we relativize some complexity class inclusion, we should give the simulating machine access not only to an oracle A, but also to a low-degree extension of A over a finite field or ring. We systematically go through basic results and open problems in complexity theory to delineate the power of the new algebrization barrier. First, we show that all known nonrelativizing results based on arithmetization---both inclusions such as IP = PSPACE and MIP = NEXP, and separations such as MAEXP ⊄ P/poly---do indeed algebrize. Second, we show that almost all of the major open problems---including P versus NP, P versus RP, and NEXP versus P/poly---will require non-algebrizing techniques. In some cases, algebrization seems to explain exactly why progress stopped where it did: for example, why we have superlinear circuit lower bounds for PromiseMA but not for NP. Our second set of results follows from lower bounds in a new model of algebraic query complexity, which we introduce in this article and which is interesting in its own right. Some of our lower bounds use direct combinatorial and algebraic arguments, while others stem from a surprising connection between our model and communication complexity. Using this connection, we are also able to give an MA-protocol for the Inner Product function with O (√nlogn) communication (essentially matching a lower bound of Klauck), as well as a communication complexity conjecture whose truth would imply NL ≠ NP.
Forecast Combinations

Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the degree of correlation between forecast errors and the relative size of the individual models' forecast error variances). Although the reasons for the success of simple combination schemes are poorly understood, we discuss several possibilities related to model misspecification, instability (non-stationarities) and estimation error in situations where the numbers of models is large relative to the available sample size. We discuss the role of combinations under asymmetric loss and consider combinations of point, interval and probability forecasts.
Large Uncertainties in Urban‐Scale Carbon Emissions

Accurate estimates of fossil fuel carbon dioxide (FFCO2) emissions are a critical component of local, regional, and global climate agreements. Current global inventories of FFCO2 emissions do not directly quantify emissions at local scales; instead, spatial proxies like population density, nighttime lights, and power plant databases are used to downscale emissions from national totals. We have developed a high‐resolution (hourly, 1 km2) bottom‐up Anthropogenic Carbon Emissions System (ACES) for FFCO2, based on local activity data for the year 2011 across the northeastern U.S. We compare ACES with three widely used global inventories, finding significant differences at regional (20%) and city scales (50–250%). At a spatial resolution of 0.1°, inventories differ by over 100% for half of the grid cells in the domain, with the largest differences in urban areas and oil and gas production regions. Given recent U.S. federal policy pull backs regarding greenhouse gas emissions reductions, inventories like ACES are crucial for U.S. actions, as the impetus for climate leadership has shifted to city and state governments. The development of a robust carbon monitoring system to track carbon fluxes is critical for emissions benchmarking and verification. We show that existing downscaled inventories are not suitable for urban emissions monitoring, as they do not consider important local activity patterns. The ACES methodology is designed for easy updating, making it suitable for emissions monitoring under most city, regional, and state greenhouse gas mitigation initiatives, in particular, for the small‐ and medium‐sized cities that lack the resources to regularly perform their own bottom‐up emissions inventories.
Hierarchical Role-Based Viewing for Multilevel Information Security in Collaborative CAD

Abstract : Information security and assurance are new frontiers for collaborative design. In this context, information assurance (IA) refers to methodologies to protect engineering information by ensuring its availability, confidentiality, integrity, non-repudiation, authentication, and access control. In collaborative design, IA techniques are needed to protect intellectual property, establish security privileges, and create "need to know" protections on critical features. This paper provides a framework for information assurance within collaborative design based on a technique the authors call "Role-based Viewing. " They extend upon prior work to present "Hierarchical Role-based Viewing" as a more flexible and practical approach since role hierarchies naturally reflect an organization's line of authority and responsibility. They establish a direct correspondence between multi-level security and multiresolution surfaces where a hierarchy is represented as a weighted directed acyclic graph. The permission discovery process is formalized as a graph reachability problem and the path cost is used as input to a multiresolution function. By incorporating security with collaborative design, the costs and risks incurred by multi-organizational collaboration can be reduced. The authors believe that this work is the first of its kind to unite multi-level security and information clouding with geometric data, including multiresolution surfaces, in the fields of computer-aided design and collaborative engineering.
Extensive Chromatin Structure-Function Association Revealed by Accurate Compartmentalization Characterization

Chromosome conformation capture-based experiments have shown that eukaryotic chromosomes are partitioned into A and B compartments conventionally identified by the first eigenvector (EV1) of dimension reduction methods. However, many genomic regions show marginal EV1 values, indicating the ambiguity of A/B compartment scheme on these regions. We develop MOSAIC (MOdularity and Singular vAlue decomposition-based Identification of Compartments), an accurate compartmental state detection scheme. MOSAIC reveals that those ambiguous regions segregate into two additional compartmental states, which typically correspond to small genomic regions flanked by large canonical A/B compartments with opposite activities. They are denoted as micro-compartments accordingly. In contrast to the canonical A/B compartments, micro-compartments cover ~30% of the genome and are highly dynamic between cell types. More importantly, distinguishing the micro-compartments underpins accurate characterization of chromatin structure-function relationship. By applying MOSAIC to GM12878 and K562 cells, we identify CD86, ILDR1 and GATA2 which show concordance between gene expression and compartmental states beyond the scheme of A/B compartments. Taken together, MOSAIC uncovers fine-scale and dynamic structures underlying canonical A/B compartments. Our results suggest dynamic chromatin compartmentalization is underlying transcriptional regulation and disease.
Preservation of Midlatitude Ice Sheets on Mars

Excess ice with a minimum age of tens of millions of years is widespread in Arcadia Planitia on Mars, and a similar deposit has been found in Utopia Planitia. The conditions that led to the formation and preservation of these midlatitude ice sheets hold clues to past climate and subsurface structure on Mars. We simulate the thermal stability and retreat of buried excess ice sheets over 21 Myr of Martian orbital solutions and find that the ice sheets can be orders of magnitude older than the obliquity cycles that are typically thought to drive midlatitude ice deposition and sublimation. Retreat of this ice in the last 4 Myr could have contributed ~6% of the volume of the north polar layered deposits (NPLD) and more than 10% if the NPLD are older than 4 Myr. Matching the measured dielectric constants of the Arcadia and Utopia Planitia deposits requires ice porosities of ~25–35%. We model geothermally driven vapor migration through porous ice under Martian temperatures and find that Martian firn may be able to maintain porosity for timescales longer than we predict for retreat of the ice.