Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Kernel I-Cache Optimization

We have developed a facility for run-time optimization of a commodity operating system kernel. This facili first step towards an evolving operating system, one that adapts and changes over time without need for reb Our infrastructure, currently implemented on UltraSPARC Solaris 7, includes the ability to do a detailed analy the running kernel's binary code, dynamically insert and remove code patches, and dynamically install new ve of kernel functions. As a first use of this technology, we have implemented a run-time kernel version of the cod tioning I-cache optimizations, and obtained noticeable speedups in kernel performance. As a first case study, formed run-time code positioning on the kernel’s TCP read-side processing routine while running a Web benchmark. We found that the code positioning optimizations reduced this function’s execution time by 17.6% ing in an end-to-end benchmark speedup of 7%. The primary contributions of this paper are the first run-time kernel implementation of code positioning, an infrastructure for turning an unmodified commodity kernel into an evolving one. Two further contributions are m in kernel performance measurement. First, we provide a simple and effective algorithm for deriving control flow execution counts from basic block execution counts, which contradicts the widely held belief that edge counts be derived from block counts. Second, we describe a means for converting wall time instrumentation-based measurements into virtual (i.e., CPU) time measurements via instrumentation of the kernel’s context switch ha
Analytical inference model for prediction and customization of inter-agent dependency requirements

Inter-agent communication is one of the main concerns of Agent Oriented Requirements Engineering (AORE). The concern is delineated as managing inter-dependencies and interaction among various agents performing collaborative activities. To carry out cooperative activities, the application areas viz. electronic commerce and enterprise resource planning in the distributed environment require an agent to predict and customize dependency needs termed as Degree of Dependency (DoD) so that the goal may be obtained within resource constraints and with optimal number of agents. To quantify and predict exertion load of an agent within resource constraints, this paper proposes an Analytical Inference Model (AIM) that would facilitate the developer to evaluate and envisage DoD and hence analyze the optimum number of agents to obtain predicted DoD. In this work, Adaptive Neuro Fuzzy Inference System (ANFIS) combining the potential benefits of Artificial Neural Network (ANN) and Fuzzy Logic (FL) is employed to discover the linear relationship in input domain attributes and DoD. The resultant optimization of exertion loads would immensely improve the quality of the Multi-Agent System. The hybrid, as well as back propagation learning algorithm, is employed to adapt from training data. The bestfitness of proposed model against test data is examined by the performance indicators-Coefficient of Correlation (CORR) and the Normalized Root Mean Square Error (NRMSE). It is observed that hybrid learning algorithm outperforms the back propagation algorithm.
Information credibility assessment of Islamic and Quranic information on the web

This research studies the user's assessment on the information credibility of Islamic and Quranic information retrieved from the Web. Thirty one interviews were given to various groups of online users regarding their assessment process when retrieving Islamic, particularly those of Quranic-related, information on the Web. Interview data were transcribed and then analysed inductively to identify emergent themes using inductive content analysis. The data analysis focused on extracting common themes, patterns and concepts from the transcripts which were coded by categories that emerged as the process continued. The participants interviewed discussed the assessment process which includes verification and cross-checking with other resources, online and offline. The findings provide important insights on user's assessment process when retrieving for Islamic and Quranic information on the Web. It can serve to give Web designers and content providers on what the users are actually concerned with to better adjust their services according to the needs of end users.
Annotating information status in spontaneous speech

We propose a fine-grained annotation scheme for the analysis of information status in spoken language, subdivided into a referential and a lexical level. The taxonomy is easy to handle and allows for a precise and comprehensive way of capturing the informational differences between nominal expressions in texts. First results on the prosodic marking of an item’s information status in a small corpus of spontaneous monologues in German confirm the relevance of the two levels of description. There are significant effects of both levels of information status on (de)accentuation in isolation and in combination. However, results show more accents than postulated by our hypotheses.
Pc-based Tms320c30 Implementation of the Gaussian Mixture Model Text-independent Speaker Recognition System

The utility of identifying a person from the characteristics of his/her voice is increasing with the growing use of speech interaction with computers. Many speaker identification systems have been successfully applied in simulations on speech databases, but there are several challenges that must be addressed in moving a system from the laboratory to a field application. In this paper, a real-time, PC-based TMS320C30 implementation of a text-independent speaker identification system which serves as a platform for field testing is described. The system is based on Gaussian mixture speaker models which have demonstrated high text-independent identification performance. The implementation uses "off-the-shelf" hardware and takes advantage of the current level of high-level DSP software development tools. The paper describes the development platform, major component implementation, and system timings. An application of the real-time system to an interactive telephone speech experiment is also described.
The Current State of Lean Implementation in Health Care: Literature Review

Purpose: The purpose of this article is to discuss the current state of implementation of Lean production in health care. The study focuses on the definition of Lean in health care and implementation process, barriers, challenges, enablers, and outcomes of implementing Lean production methods in health care. Design/Methodology/Approach: A comprehensive search of the literature concerning the implementation of Lean production in health care was used to generate a synthesis of the literature around the chosen research questions. Findings: Lean production in health care is mostly used as a process improvement approach and focuses on 3 main areas: (1) defining value from the patient point of view, (2) mapping value streams, and (3) eliminating waste in an attempt to create continuous flow. Value stream mapping is the most frequently applied Lean tool in health care. The usual implementation steps include conducting Lean training, initiating pilot projects, and implementing improvements using interdisciplinary teams. One of the barriers is lack of educators and consultants who have their roots in the health care sector and can provide support by sharing experience and giving examples from real-life applications of Lean in health care. The enablers of Lean in health care seem not to be different from the enablers of any other change initiative. The outcomes can be divided into 2 broad areas: the performance of the health care system and the development of employees and work environment.
The Neurobiological Basis of Adolescent-onset Borderline Personality Disorder.

OBJECTIVE Over the past two decades, neurobiological studies in adult onset borderline personality disorder have made important strides, but inquiry into adolescent-onset BPD is still in its infancy and our understanding of the neurobiology of adolescent BPD remains highly tentative. METHODS This paper highlights recent findings in genetics, neuroendocrinology and neuroimaging for adult and adolescent-onset BPD. RESULTS Neurobiological studies of adolescent-onset BPD to date have focused mainly on volumetric studies of various brain regions and measurements of HPA axis components, with comparatively few publications on brain functioning. CONCLUSION Such information is essential to developing more effective screening, treatment and preventive strategies.
Demand-based flash translation layer considering spatial locality

A flash translation layer (FTL) is a firmware inside a SSD to support traditional file systems with NAND flash memory. One such FTL, the page mapping scheme shows high performance but requires a large mapping table to be stored in random access memory (RAM). Demand-based FTL (DFTL), which only stores frequently used mapping entries in RAM, overcomes this drawback. However, it has a weakness that the cached mapping table (CMT) that contains frequently used mapping entries must be sequentially searched; moreover, if the CMT is kept too small, frequent replacement of mapping entries may impair performance. Here, we propose a scheme in which the spatial locality of typical disk patterns is employed and clustered mapping entries are loaded into RAM. The scanning overhead of the CMT is also eliminated by using two-level mapping tables. We experimentally show that the presented scheme significantly reduces RAM usage while retaining comparable performance.
Comparative analysis of electronic banking websites in selected banks in Poland in 2014

The main objective of this article is to identify the best e-banking websites in Poland from the point of view of an individual customer. Using modern IT tools for communications with customers of banking services, banks create competitive advantages, as well as, opportunities for providing banking services in a convenient way for consumers. After a short introduction the authors defines the assumptions for the study. The methodological approach-based on theoretical and empirical study in the field of e-banking, allows them to build the evaluation model for the construction of high quality e-banking website. Subsequently, the authors carried out multilateral analyses and presented the conclusions of the study. The identified categories are classified into three groups: economic, technological and anti-crisis. The originality of the work comes down to knowledge of the determinants of customer's quality perception of websites and a starting point for an effective quality management of their e-services system.
DIFFUSION OF SUPPLY CHAIN TECHNOLOGIES

With the growth of new technologies to aid in supply chain management, including computer-aided design, computer-aided manufacturing and electronic data interchange, it has been estimated that 40 percent of new capital equipment investment in the U.S. goes to this kind of device. This study attempts to determine, through more than 100 pilot interviews, the diffusion of new technologies and begin to assess their effect on supply chain management, primarily in the U.S. The technologies to be studied were selected based on their being concerned with information exchange within and between organizations and managing supply-chain-related data and activities. The study expands the scope of technology adopted to include a variety of inter- and intra-organizational technologies and software applications. This research uses survey data to identify the types of technologies that firms have adopted. The study also attempts to determine managers' perceptions of the impact of new technologies on integration between organizations. Describes survey methods and shows tables with data describing types and extent of technologies adopted. Also provides measures of supply chain improvements using a number of metrics. One of the most obvious advantages reported is the speeding of information exchange with partners to better control inventory throughout the supply chain, but firms have not yet widely adopted technologies that extend these capabilities through the entire supply chain. Results also suggest that high adoption rates do not translate directly into equivalent gains in efficiencies, which respondents blame on system marketers selling them technologies that are more complex than they need or that are too difficult to implement. Many others, however, reported high levels of satisfaction with their investments. More research is needed about specific technologies and instances where new technologies have created barriers to adoption.
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The paper describes a technique for comparison of computational effectiveness of two approaches to generation of approximately Pareto-optimal solutions with the use of metaheuristics. In the on-line generation approach the approximately Pareto-optimal solutions are generated during the interactive process, e.g. by optimization of some scalarizing functions. In the off-line generation approach, the solutions are generated prior to the interactive process with the use of multiple objective metaheuristics. The results of experiment on travelling salesperson instances indicate that in the case of some multiple objective metheuristics the off-line generation approach may be computationally effective alternative to the on-line generation of approximately Pareto-optimal solutions.
Flipping one-shot library instruction: using Canvas and Pecha Kucha for peer teaching.

OBJECTIVE This study sought to determine whether a flipped classroom that facilitated peer learning would improve undergraduate health sciences students' abilities to find, evaluate, and use appropriate evidence for research assignments. METHODS Students completed online modules in a learning management system, with librarians facilitating subsequent student-directed, in-person sessions. Mixed methods assessment was used to evaluate program outcomes. RESULTS Students learned information literacy concepts but did not consistently apply them in research assignments. Faculty interviews revealed strengthened partnerships between librarians and teaching faculty. CONCLUSION This pedagogy shows promise for implementing and evaluating a successful flipped information literacy program.
Exponentiable morphisms of domains

Given a map f in the category ω-Cpo of ω-complete posets, exponentiability of f in ω-Cpo easily implies exponentiability of f in the category Pos of posets, while the converse is not true. We investigate the extra conditions needed on f exponentiable in Pos to be exponentiable in ω-Cpo by showing the existence of partial products of the two-point ordered set S={0<1} (Theorem 2.8). Using this characterisation and the embedding through the Scott topology of ω-Cpo in the category Top of topological spaces, we compare exponentiability in each setting and find that a morphism in ω-Cpo that is exponentiable in both Top and Pos is exponentiable in ω-Cpo also. Furthermore, we show that the exponentiability in Top and Pos are independent of each other.
Cross-View Feature Learning for Scalable Social Image Analysis

Nowadays images on social networking websites (e.g., Flickr) are mostly accompanied with user-contributed tags, which help cast a new light on the conventional content-based image analysis tasks such as image classification and retrieval. In order to establish a scalable social image analysis system, two issues need to be considered: 1) Supervised learning is a futile task in modeling the enormous number of concepts in the world, whereas unsupervised approaches overcome this hurdle; 2) Algorithms are required to be both spatially and temporally efficient to handle large-scale datasets. In this paper, we propose a cross-view feature learning (CVFL) framework to handle the problem of social image analysis effectively and efficiently. Through explicitly modeling the relevance between image content and tags (which is empirically shown to be visually and semantically meaningful), CVFL yields more promising results than existing methods in the experiments. More importantly, being general and descriptive, CVFL and its variants can be readily applied to other large-scale multi-view tasks in unsupervised setting.
Cognitive Dysfunction in Parkinson’s Disease: The Role of Frontostriatal Circuitry

It has been known for many years that the classic motor symptoms of Parkinson’s disease are accompanied by deficits of executive function that resemble those seen after frontal lobe damage in humans. What is less clear is how different components of frontostriatal circuitry contribute to these impairments. Recently, improved methods of clinical assessment and classification, combined with novel technical approaches, such as functional neuroimaging, have led to great advances in our understanding of the fundamental mechanisms that drive frontostriatal circuitry. As a direct result, it has been possible to redefine impairments of executive function in Parkinson’s disease more precisely in terms of the specific neuropsychological, neuroanatomical, and psychopharmacological mechanisms involved.
Development of a Tracking Algorithm for an In-Vivo RF Capsule Prototype

This paper presents the design of a tracking algorithm for an in-vivo capsule swallowed by patients. Such devices play a very important role in the diagnosis and treatment of internal disorders, for example, in the digestive tract. Tracking the location of the capsule as it travels down the digestive tract is critical to ensure its position near the affected area. Various sensing mechanisms that can be applied for tracking the capsule include the use of radio frequency and magnetic signals. The work reported in this paper mainly focuses on the development of an intelligent tracking algorithm that could potentially be coupled with a variety of sensing technologies. In this paper we use RF-based capsule and sensor prototypes for developing and testing the tracking algorithm. Encouraging practical results have been obtained which demonstrate the validity of the tracking algorithm and the underlying look-up table based methodology
Concept learning and the use of three common psychophysical paradigms in the archerfish (Toxotes chatareus)

Archerfish are well known for their specialized hunting technique of spitting water at prey located above the water line. This unique ability has made them a popular focus of study as researchers try to understand the mechanisms involved in targeting and spitting. In more recent years, archerfish have also become an increasingly popular model for studying visual discrimination and learning in general. Until now, only the alternative forced-choice (AFC) task has been used with archerfish, however, they may be capable of learning other classical discrimination tasks. As well as providing alternative, and potentially more efficient, means for testing their visual capabilities, these other tasks may also provide deeper insight into the extent to which an organism with no cortex can grasp the concepts underlying these tasks. In this paper, we consider both the matched-to-sample (MTS) and the odd-one-out (OOO) tasks as they require the subject to learn relatively sophisticated concepts rather than a straight, stimulus-reward relationship, of the kind underlying AFC tasks. A variety of line drawings displayed on a monitor were used as stimuli. We first determined if archerfish could complete the MTS and OOO test and then evaluated their ability to be retrained to new stimuli using a 4-AFC test. We found that archerfish were unable to learn the MTS and had only a limited capacity for learning the OOO task. We conclude that the MTS and OOO are impractical as paradigms for behavioral experiments with archerfish. However, the archerfish could rapidly learn to complete an AFC test and select the conditioned stimulus with a high degree of accuracy when faced with four stimuli, making this a powerful test for behavioral studies testing visual discrimination. In addition, the fish were able to learn the concept of oddity under particular training circumstances. This paper adds to the growing evidence that animals without a cortex are capable of learning some higher order concepts.
Change of search time and non-search time in X-ray baggage screening due to training

As found in studies of aircraft structural inspection, the time used for judging if a part of an aircraft shows tiny cracks is composed of search time, used for actively scanning, and non-search time, used for matching and decision while fixating a region of interest (Drury et al. 1997). These findings can be applied to detection of threats by X-ray screening of passenger bags at airports. To investigate whether search time and non-search time change when an experienced screener is given additional training in recognising threat objects in passenger bags, data from a European airport were analysed. A comparison of detection performance and reaction time between two large groups of screeners, one trained for 6 months, shows a large impact of training on overall performance and on both search and non-search components of the task. There was also a small but consistent decline in performance measures with screener age. This study shows a way to localise the effect of training on threat detection performance for aviation security screening. Analysis of the time needed for screening each passenger bag showed that training had a significant effect, particularly on the non-search part of the searching process (i.e. identification, recognition, decision, response execution, etc.).
Recoverable Cuts to Make Agreement among Peers

In peer-to-peer (P2P) applications, peers make an agreement on one opinion. Agreement procedures have to be so flexible that persons can change their opinions. We discuss a flexible agreement protocol of multiple peers by taking advantage of human behaviors in a fully unstructured P2P network. There are forward, backward, mining, and observation strategies for each peer to find a value to make an agreement. In the forward strategy, a peer shows a new value to the other peers. In the backward one, a peer backs to a previous round. In order to back to the previous round, values taken after the round have to be withdrawn. In the mining one, a peer tries to find a tuple of previous values named a cut which satisfies the agreement condition. In the observation one, a peer does not take a new value. Since each peer autonomously takes one of the strategies at each round, the peers might take inconsistent strategies. For example, only if every peer takes the mining strategy, the mining strategy can be adopted. The mining strategy is inconsistent with the others. The peers have to do negotiation with each other to take consistent strategies. We discuss how peers cooperate to take consistent strategies at each round.
Visual Deprivation Reactivates Rapid Ocular Dominance Plasticity in Adult Visual Cortex

Brief monocular deprivation (≤3 d) induces a rapid shift in the ocular dominance of binocular neurons in the juvenile rodent visual cortex but is ineffective in adults. Here, we report that persistent, rapid, juvenile-like ocular dominance plasticity can be reactivated in adult rodent visual cortex when monocular deprivation is preceded by visual deprivation. Ocular dominance shifts in visually deprived adults are caused by a rapid depression of the response to stimulation of the deprived eye, previously only reported in juveniles, and a simultaneous potentiation of the response to stimulation of the nondeprived eye. The enhanced ocular dominance plasticity induced by visual deprivation persists for days, even if binocular vision precedes monocular deprivation. Visual deprivation also induces a significant decrease in the level of GABAA receptors relative to AMPA receptors and a return to the juvenile form of NMDA receptors in the visual cortex, two molecular changes that we propose enable the persistent reactivation of rapid ocular dominance plasticity.