Miracle-dz/UniFAR-FTUs huggingface dataset:
An Energy-Efficient Buffer Cache Replacement

Power consumption is an increasingly impressing concern for data servers as it directly affects running costs and system reliability. Prior studies have shown most memory space on data servers are used for buffer caching and thus cache replacement becomes critical. This paper investigates the tradeoff between these two interacting factors and proposes three energy-aware buffer cache replacement algorithm. On a cache miss for a new block b in a file f , it evicts an victim block from the most recently accessed memory chip. Simulation results based real-world TPC-R I/O trace show that our algorithm can save up to 12.2% energy with marginal degradation in hit rates.
Enhanced TCP-friendly rate control for supporting video traffic over internet

Video traffic nowadays forms the majority of traffic over the Internet, and is predicted to be the most prevailing traffic type in the coming few years. TCP-Friendly Rate Control (TFRC) is one of the most promising end-to-end congestion control protocols that is intended for unicast playback of Internet streaming applications. This paper presents a new TCP-Friendly congestion control protocol, called Enhanced TCP-Friendly Rate Control (ETFRC), for supporting real time video traffic over the Internet. The proposed protocol is developed by adjusting the sending rate, at the sender side, dynamically based on the current state of the network, and the current state of the receiver. In other words, ETFRC embodies a new algorithm to tune (increase or decrease) the sending rate, at the sender side, according to the difference between the calculated rate by the sender and the reported rate from the receiver side. The performance of the proposed ETFRC protocol is evaluated using the network simulator ns-2 considering different scenarios. In these scenarios, simulated video traffic from the Evalvid framework is sent over the designed topology and different performance parameters are measured and compared with that obtained by applying the original TFRC protocol. The simulation results show that ETFRC performance surpassed TFRC in terms of throughput, jitter, and packet loss.
An Enhanced Positioning Algorithm for a Self-Referencing Hand-Held 3D Sensor

This study deals with the design of an enhanced selfreferencing algorithm for a typical hand-held 3D sensor. The enhancement we propose takes the form of a new algorithm which forms and matches triangles out of the scatter of observed reference points and the sensor’s list of reference points. Three different techniques to select which triangles to consider in each scatter of points are considered in this paper, and theoretical arguments and experimental results are used to determine the best of the three.
The top ten list: dynamic fault prediction

To remain competitive in the fast paced world of software development, managers must optimize the usage of their limited resources to deliver quality products on time and within budget. In this paper, we present an approach (the top ten list) which highlights to managers the ten most susceptible subsystems (directories) to have a fault. Managers can focus testing resources to the subsystems suggested by the list. The list is updated dynamically as the development of the system progresses. We present heuristics to create the top ten list and develop techniques to measure the performance of these heuristics. To validate our work, we apply our presented approach to six large open source projects (three operating systems: NetBSD, FreeBSD, OpenBSD; a window manager: KDE; an office productivity suite: KOffice; and a database management system: Postgres). Furthermore, we examine the benefits of increasing the size of the top ten list and study its performance.
Integrating Mission, Logistics, and Task Planning for Skills-Based Robot Control in Industrial Kitting Applications

This paper presents an integrated cognitive robotics systemfor industrial kitting operations in a modern factory setting.The robot system combines low-level robot control and execution monitoring with automated mission and task planning,and a logistics planner which communicates with the factory’smanufacturing execution system. The system has been implemented and tested on a series of automotive kitting problems,where collections of parts are picked from a warehouse anddelivered to the production line. The system has been empirically evaluated and the complete framework shown to besuccessful at assembling kits in a small factory environment.
Learning Consistent, Interactive, and Meaningful Task-Action Mappings: A Computational Model

Within the field of human-computer interaction, the study of the interaction between people and computers has revealed many phenomena. For example, highly interactive devices, such as the Apple Macintosh, are often easier to learn and use than keyboard-based devices such as Unix. Similarly, consistent interfaces are easier to learn and use than inconsistent ones. This article describes an integrated cognitive model designed to exhibit a range of these phenomena while learning task-action mappings: action sequences for achieving simple goals, such as opening a file in a word processor. The model, called TAL, is of a user who is familiar with the basic operations of a keyboard and mouse, but unfamiliar with the particular menu structures, words, and actions required to use the device. The model is constructed in Soar and employs a single set of architectural mechanisms. It exhibits behavior that captures human preference for consistent, interactive, and meaningful task-action mappings.
Consumer Response to Functional Foods Produced by Conventional, Organic, or Genetic Manipulation

The agro-food industry is developing a “second generation” of genetically modified (GM) foods that can offer functional health benefits to consumers. Many consumers, however, are turning to organic foods in order to avoid GM foods. This report attempts to differentiate consumer valuation of functional health properties in conventional, organic, and GM foods. A representative sample of 1,008 Canadian household food shoppers responded to twelve stated-choice experiments during a telephone survey. Because opinions about organic and GM foods varied greatly, random parameters logit models were used to analyze their choices. Results indicate that many Canadian consumers will avoid GM foods, regardless of the presence of functional health properties. For others, the introduction of GM functional plant foods should increase acceptance of GM production methods, but many consumers will likely avoid functional foods derived from GM animals. The organic food industry could also profit from the introduction of organic functional foods. [EconLit citations: I120; D120. ] © 2004 Wiley Periodicals, Inc. Agribusiness 20: 155–166, 2004.
The Timing and Probability Workbench: A Tool for Analysing Timed Processes

We describe the implementation of a tool for analysing systems described in the TPCCS process algebra (CCS extended with time and probability). The tool essentially provides three functions: (i) simulation of TPCCS speciications, (ii) checking whether two TPCCS speciications are equivalent with respect to TPCCS strong bisimulation equivalence, and (iii) checking whether a TPCCS speciication satisses a system property described in TPCTL, a branching time logic similar to CTL in which timing and probabilistic properties of systems can be expressed. The printed version of the thesis diiers from the original text in some minor details. The introduction contains a short discussion on the diierences between the versions.
FILA in gameland, a holistic approach to a problem of many dimensions

Multiplayer online games have now become popular with millions across the globe, capturing the attention of both researchers and practitioners. Unfortunately, online games still have to deal with the limitations imposed by some unresolved issues. Interactivity, consistency, fairness, and scalability are the major requirements that need to be addressed efficiently in order to provide an appealing product to a huge number of potential customers worldwide. To answer this demand, we describe a holistic approach that can exploit the semantics of the game to satisfy the aforementioned requirements. We provide extensive and comparative results that demonstrate how our scheme copes efficiently with an elevated level of game traffic.
Molecular Disassembly With Rrt-Like Algorithms

This paper addresses the problem of computing pathways for a ligand to exit from the active site of a protein. Such problem can be formulated as a mechanical disassembly problem for two articulated objects. Its solution requires searching paths in a constrained high-dimensional configuration-space. Indeed, the ligand passageway inside the protein is often extremely cluttered so that current path planning techniques are unable to solve the disassembly problem in reasonable computing time. The techniques presented in this paper are based on the RRT algorithm. First we discuss some simple and general modifications of the basic algorithm that significantly improve its performance. Then we describe a new variant of the planner that treats ligand and protein degrees of freedom separately. This new algorithm outperforms the basic RRT, particularly for very constrained problems, and is able to handle models with hundreds of degrees of freedom. We analyze the effects of each RRT variant via several examples of different complexity. Although discussions and results of this paper focus on molecular models, the ideas behind the algorithms are general and can be applied to path planners for disassembling articulated mechanical parts.
Haplotyping and Haplotype Frequency Estimates on Trio Genotype Data

The problems of haplotyping and haplotype frequency estimation on trio genotype data under the Mendelian law of inheritance and the assumption of Hardy-Weinberg equilibrium are studied in this paper.Since most past efforts only focused on haplotyping on genotype data of unrelated individuals and data with general pedigrees,but gave insufficient efforts to the special case of trio genotype data,there is coming an increasing demand in analyzing them in particular,especially when taking into account that part of HAPMAP database is exactly trio data.This paper presents a two-staged method to estimate haplotype frequencies in trios:i)haplotyping stage,find haplotype configurations without recombinant for each trio;ii)frequency estimation stage,use the expectation-maximization(EM)algorithm to estimate hapiotype frequencies based on these inferred haplotype configurations.Both the haplotyping algorithm and the EM algorithm are implemented in software package TRIOHAP using C language.Its effectiveness and efficiency and tested on simulated and real data sets as well.The experimental results show that,TRIOHAP runs much faster than a popular frequency estimation software which discards trio information.Moreover,because TRIOHAP utilizes such information,its estimation is more reliable.
Privacy-preserving social network analysis for criminal investigations

Social network analysis (SNA) is now a commonly used tool in criminal investigations, but evidence gathering and analysis is often restricted by data privacy laws. We consider the case where multiple investigators want to collaborate, but do not yet have sufficient evidence that justifies a plaintext data exchange. This paper proposes a solution for privacy-preserving social network analysis where several investigators can collaborate without actually exchanging sensitive private information. An investigator can request data from other sites to augment his view without revealing personally identifiable data. The investigator can compute important metrics by means of a SNA on the subject while keeping the entire social network unknown him.
Sexual Behavior, Condom Use, and Human Papillomavirus: Pooled Analysis of the IARC Human Papillomavirus Prevalence Surveys

Human papillomavirus (HPV) is a sexually transmitted infection but it is unclear whether differences in transmission efficacy exist between individual HPV types. Information on sexual behavior was collected from 11 areas in four continents among population-based, age-stratified random samples of women of ages ≥15 years. HPV testing was done using PCR-based enzyme immunoassay. Unconditional logistic regression was used to estimate odds ratios (OR) of being HPV positive and corresponding 95% confidence intervals (95% CI). Variables were analyzed categorically. When more than two groups were compared, floating confidence intervals were estimated by treating ORs as floating absolute risks. A total of 11,337 women (mean age, 41.9 years) were available. We confirmed that lifetime number of sexual partners is associated with HPV positivity (OR for ≥2 versus 1, 1.86; 95% CI, 1.63-2.11) but the association was not a linear one for HPV18, 31, and 33 (i.e., no clear increase for ≥3 versus 2 sexual partners). Women who had multiple-type infection and high-risk HPV type infection reported a statistically nonsignificant higher number of sexual partners than women who had single-type and low-risk type infections, respectively. Early age at sexual debut was not significantly related to HPV positivity. Husband's extramarital sexual relationships were associated with an OR of 1.45 (95% CI, 1.24-1.70) for HPV positivity in their wives after adjustment for age and lifetime number of women's sexual partners. We did not observe a significant association with condom use. Our study showed an effect of both women's and their husbands' sexual behavior on HPV positivity. Furthermore, it suggests some differences in the pattern of the association between sexual behavior and different HPV types. (Cancer Epidemiol Biomarkers Prev 2006;15(2):326–33)
Home network infrastructure for handheld/wearable appliances

A server infrastructure allows wireless wearable appliances or portable handsets to access consumer services offered via the server. Services are accessed via a universal home services interface (UHSI) which is shared by all access devices. The UHSI can include a voice-activated interface to simplify usage from non-graphical terminals. In a home network, the infrastructure resides on a home gateway or central home computer and allows users access to local subsystems or external WAN services. An implementation based on a universal plug and play (UPnP) home network is described.
Uncertain Data Mining using Decision Tree and Bagging Technique

Classification is one of the important data mining techniques and Decision Tree is a most common structure for classification which is used in many applications. Decision tree classifier works on precise and known data. Traditional classifier extended to handle uncertain data caused by faulty data collection processes. To handle uncertainty feature value is represented by probability distribution function instead of single value. This improves accuracy of decision tree as complete information is used. Probability density function (PDF) requires many calculations. Pruning techniques are used to remove unwanted intervals and to reduce execution time. In this paper bagging method is combined with decision tree technique to stabilize the performance of decision tree and to improve accuracy of decision tree. Keywords— Bagging; Classification; Decision Tree; Probability distribution; Uncertainty.
Mechanisms for increased myocardial fatty acid utilization following short-term high-fat feeding.

AIMS Diet-induced obesity is associated with increased myocardial fatty acid (FA) utilization, insulin resistance, and cardiac dysfunction. The study was designed to test the hypothesis that impaired glucose utilization accounts for initial changes in FA metabolism. METHODS AND RESULTS Ten-week-old C57BL6J mice were fed a high-fat diet (HFD, 45% calories from fat) or normal chow (4% calories from fat). Cardiac function and substrate metabolism in isolated working hearts, glucose uptake in isolated cardiomyocytes, mitochondrial function, insulin-stimulated protein kinase B (Akt/PKB) and Akt substrate (AS-160) phosphorylation, glucose transporter 4 (GLUT4) translocation, pyruvate dehydrogenase (PDH) activity, and mRNA levels for metabolic genes were determined after 2 or 5 weeks of HFD. Two weeks of HFD reduced basal rates of glycolysis and glucose oxidation and prevented insulin stimulation of glycolysis in hearts and reduced insulin-stimulated glucose uptake in cardiomyocytes. Insulin-stimulated Akt/PKB and AS-160 phosphorylation were preserved, and PDH activity was unchanged. GLUT4 content was reduced by 55% and GLUT4 translocation was significantly attenuated. HFD increased FA oxidation rates and myocardial oxygen consumption (MVO2), which could not be accounted for by mitochondrial uncoupling or by increased expression of peroxisome proliferator activated receptor-alpha (PPAR-alpha) target genes, which increased only after 5 weeks of HFD. CONCLUSION Rates of myocardial glucose utilization are altered early in the course of HFD because of reduced GLUT4 content and GLUT4 translocation despite normal insulin signalling to Akt/PKB and AS-160. The reciprocal increase in FA utilization is not due to PPAR-alpha-mediated signalling or mitochondrial uncoupling. Thus, the initial increase in myocardial FA utilization in response to HFD likely results from impaired glucose transport that precedes impaired insulin signalling.
Dynamic reverse engineering of GUI models for testing

A significant challenge in application of model-based testing (MBT) is that manually designing the test models requires considerable amount of effort and deep expertise in formal modeling. Reverse engineering can be used to automate parts of the modeling process but in applications with a graphical user interface (GUI), the dynamic behavior of the GUI is difficult to extract with static reverse engineering. Therefore we propose to use dynamic reverse engineering for automatically generating GUI models suitable for MBT. In this paper we compare various approaches for automated GUI modeling including an empirical tool study, propose a GUI component classification suitable for GUI automation, and present some examples of GUI automation strategies for efficient modeling of GUI applications.
Natural Communication withMobile

We describe an implemented system which mediates between an un-modiied reactive mobile robot architecture and domain-restricted natural language. We introduce reactive-odometric plans and demonstrate their use in plan recognition, fault-tolerant plan execution, and learning to associate human terms with locations in the environment which are perceptually unremarkable to the robot. The communication component of our architecture supports typewritten natural language discourse with people. It lets users name places either immediately or in relation to other known places, ask questions about the robot's plans and the spatial relationships of known places, and give the robot short and long term goals. We have implemented this architecture in a physical mobile robot system, and describe experiments performed in several environments and with several diierent users. This paper has not already been accepted by, and is not currently under review for, a journal or another conference. Nor will it be submitted for such during IJCAI's review period. Abstract We describe an implemented system which mediates between an un-modiied reactive mobile robot architecture and domain-restricted natural language. We introduce reactive-odometric plans and demonstrate their use in plan recognition, fault-tolerant plan execution, and learning to associate human terms with locations in the environment which are perceptually unremarkable to the robot. The communication component of our architecture supports typewritten natural language discourse with people. It lets users name places either immediately or in relation to other known places, ask questions about the robot's plans and the spatial relationships of known places, and give the robot short and long term goals. We have implemented this architecture in a physical mobile robot system, and describe experiments performed in several environments and with several diierent users.
Generating Good Degree Distributions for Sparse Parity Check Codes using Oracles

Fast forward error correction codes are becoming an important component in bulk content delivery. They t in naturally with multicast scenarios as a way to deal with losses and are now seeing use in peer to peer networks as a basis for distributing load. In particular, new irregular sparse parity check codes have been developed with provable average linear time performance, a signi cant improvement over previous codes. In this paper, we present a new heuristic for generating codes with similar performance based on observing a server with an oracle for client state. This heuristic is easy to implement and provides further intuition into the need for an irregular heavy tailed distribution.
A Measure of Control Flow Complexity in Program Text

This paper discusses the need for measures of complexity and unstructuredness of programs. A simple language independent concept is put forward as a measure of control flow complexity in program text and is then developed for use as a measure of unstructuredness. The proposed metric is compared with other metrics, the most notable of which is the cyclomatic complexity measure. Some experience with automatic tools for obtaining these metrics is reported.
Causal-Based Property Generalization

A central question in cognitive research concerns how new properties are generalized to categories. This article introduces a model of how generalizations involve a process of causal inference in which people estimate the likely presence of the new property in individual category exemplars and then the prevalence of the property among all category members. Evidence in favor of this causal-based generalization (CBG) view included effects of an existing feature's base rate (Experiment 1), the direction of the causal relations (Experiments 2 and 4), the number of those relations (Experiment 3), and the distribution of features among category members (Experiments 4 and 5). The results provided no support for an alternative view that generalizations are promoted by the centrality of the to-be-generalized feature. However, there was evidence that a minority of participants based their judgments on simpler associative reasoning processes.
A document-based data model for large scale computational maritime situational awareness

Computational Maritime Situational Awareness (MSA) supports the maritime industry, governments, and international organizations with machine learning and big data techniques for analyzing vessel traffic data available through the Automatic Identification System (AIS). A critical challenge of scaling computational MSA to big data regimes is integrating the core learning algorithms with big data storage modes and data models. To address this challenge, we report results from our experimentation with MongoDB, a NoSQL document-based database which we test as a supporting platform for computational MSA. We experiment with a document model that avoids database joins when linking position and voyage AIS vessel information and allows tuning the database index and document sizes in response to the AIS data rate. We report results for the AIS data ingested and analyzed daily at the NATO Centre for Maritime Research and Experimentation (CMRE).