Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of braids which give rise to interchange

It is well known that the existence of a braiding in a monoidal category V allows many higher structures to be built upon that foundation. These include a monoidal 2‐category V ‐Cat of enriched categories and functors over V , a monoidal bicategory V ‐Mod of enriched categories and modules, a category of operads in V and a 2‐fold monoidal category structure on V . These all rely on the braiding to provide the existence of an interchange morphism necessary for either their structure or its properties. We ask, given a braiding on V , what non-equal structures of a given kind from this list exist which are based upon the braiding. For example, what non-equal monoidal structures are available on V ‐Cat, or what non-equal operad structures are available which base their associative structure on the braiding in V . The basic question is the same as asking what non-equal 2‐fold monoidal structures exist on a given braided category. The main results are that the possible 2‐fold monoidal structures are classified by a particular set of four strand braids which we completely characterize, and that these 2‐fold monoidal categories are divided into two equivalence classes by the relation of 2‐fold monoidal equivalence. 57M99
Implications of CPU Caching on Byte-addressable Non-Volatile Memory Programming

Byte-addressable non-volatile memory may usher in a new era of computing where in-memory data structures are persistent and can be reused directly across machine restarts. However, sudden failures complicate matters because a program state may partially reside in volatile buffers and caches as opposed to primary non-volatile memory. We study the implications of different CPU caching modes and show that a particular choice affects both programmability and performance of a program.
A Multitemporal Method for Correction of Tropospheric Effects in Differential SAR Interferometry: Application to the Gulf of Corinth Earthquake

Tropospheric inhomogeneities can form a major error source in differential synthetic aperture radar interferometry measurements, which are used in slow-deformation monitoring. Indeed, variations of atmospheric conditions between two radar acquisitions produce variations in the signal path of two images and, thus, additional fringes on differential interferograms. These effects have a strong influence on interferograms and must be compensated to obtain reliable deformation measurements. This paper presents a methodological approach to reduce at both global and local scales tropospheric contributions directly from differential interferograms. It first requires refined knowledge of the stable scatterers that can only be obtained from the analysis of a large population of multitemporal interferograms. The correction of global-scale atmospheric contribution exploits the correlation between phase and topography. The correction of local artifacts is based on the correlation between interferograms containing one common acquisition. This technique is validated on a database of 81 differential interferograms covering the Gulf of Corinth (Greece) and used to improve the measurements of ground deformation compared to global positioning system measurements
A Fast-training Approach Using ELM for Satisfaction Analysis of Call Centers

Analysis of the customers' satisfaction guarantees the improvement of service quality in call centers. In this paper, an intelligent satisfaction recognition system is introduced to analyze the customers' satisfaction through the customers' emotion recognition. The nature dialogues are collected from the Chinese call center. Support Vector Machine (SVM) and Extreme Learning Machine (ELM) are used for the mapping model respectively. According to the experiment, the best F score of SVM is 0.71. Compared to SVM, the best F of ELM is up to 0.723. The training time of SVM ranges from 1268s to 5002s while ELM's only ranges from 7.28s to 15.82s, with a decrease of 99%. ELM shortens the training time largely without damaging the performance. Because of the faster training speed, ELM is more beneficial to the model updating in real time. Therefore, ELM has a great edge on online learning.
Financial Contracting , Reorganization and Mixed Finance : A Theory of Banking Systems

Banking systems vary widely in the degree of specialization they impose on financial intermediaries. In particular, banks are often limited to holding only one category of financial claims. By contrasting two polar extremes the ’American’ model of specialized banking and the ’German’ model of universal banking this paper explores the institutional consequences of such regulatory restrictions. In an incomplete contracts setting, intermediaries first decide on the acquisition of managerial resources that later determines their course of action in a financing, renegotiation and interference game. German style universal financial intermediation results in optimal mixed debt-equity finance, contractual corporate governance, absence of secondary markets and non-renegotiated reorganization by banks. American style specialized banking leads to suboptimal outcomes with renegotiation, markets for corporate control and financial specialization unless several sources of outside finance are selected in order to replicate efficient capital structures. The results also shed light on the emerging new American banking paradigm, the duality between managerial labor and capital markets and banking system design. ∗Stimulating discussions with and advice from Masa Aoki, Tony Bernardo, Thomas Gehrig, Ron Gilson, Andreas Hackethal, Christian Harm (the EFA discussant), Ron McKinnon, Paul Pfleiderer, Manju Puri (the WFA discussant), Yingyi Qian, Lemma Senbet, Eric Talley and Haluk Unal are gratefully acknowledged. Special thanks go to an anonymous referee whose very thorough comments greatly improved the paper. I also benefitted from comments and suggestions of seminar participants at Stanford, Toronto, Columbia, Rochester, Maryland, Mainz, Wisconsin, the 1996 WFA Meetings, the 1996 EEA Meetings, the 1996 EFA Meetings, the Deutsche Bundesbank, the Federal Reserve Board, the Federal Reserve Bank of Cleveland, Boston College, ESSEC, Oxford, McGill, Illinois-Chicago, Indiana, INSEAD and LSE. All errors, omissions or misinterpretations are solely my responsibility.
An Evolvable Network Controller Model for Reconfigurable Network Devices

The concept of Evolvable Hardware has attracted increased attention because it offers adaptive and highly optimized systems. Also there have been some researches toward implementing reconfigurable network devices that can change their architecture while running as a network node. In combination with evolvable hardware concept we can build adaptive and self-optimizing network systems which can autonomously adapt themselves with dynamically changing network conditions by means of evolutionary algorithms. In this paper a new model for a high-performance and flexible implementation of evolvable network controllers is proposed. Modularity of network controllers is used to decrease the complexity of such a system and as a case study we have focused on designing an Evolvable CRC generator module. Index Terms—Adaptive networks, Evolvable hardware, FPGA, Genetic algorithm, Reconfigurable network devices.
Usability Evaluation of Spoken Dialogue Systems

This paper concerns the methodologies currently applied to evaluation of spoken and multi modal dialogue systems. Usability is concerned with the effectiveness, efficiency and satisfaction by which users achieves their goals when using a system. The methods developed and applied by the speech community over the past decade to measure the usability of Spoken Dialogue Systems (SDS) are discussed and critically reviewed. The paper starts by giving a general review and discussion of the current issues and problems of establishing SDS usability. This is supported by the presentation and analysis of a case, where it is shown that e.g. learnability can be derived from simple performance measures, such as duration and turn-taking. Results of applying the PARADISE method are presented and discussed. 1. Formerly the Center for PersonKommunikation CPK. CPK is now fully integrated into the Department of Communication Technology URL: http://cpk.auc. dk/staff/staff.html? lbl
Beyond point and level systems: moving toward child-centered programming.

Many residential treatment facilities and child inpatient units in the United States have been structured by way of motivational programming such as the point and/or level systems. On the surface, they appear to be a straightforward contingency management tool that is based on social learning theory and operant principles. In this article, the authors argue that the assumptions upon which point and level systems are based do not hold up to close empirical scrutiny or theoretical validity, and that point and level system programming is actually counterproductive with some children, and at times can precipitate dangerous clinical situations, such as seclusion and restraint. In this article, the authors critique point and level system programming and assert that continuing such programming is antithetical to individualized, culturally, and developmentally appropriate treatment, and the authors explore the resistance and barriers to changing traditional ways of "doing things. " Finally, the authors describe a different approach to providing treatment that is based on a collaborative problem-solving approach and upon which other successful models of treatment have been based.
Delay and peak power minimization for on-chip buses using temporal redundancy

In this paper, we propose a novel temporal redundancy based encoding technique for delay and peak power minimization. The proposed encoding scheme is tested with the SPEC2000 CINT benchmarks for 90nm and 65nm technologies. The experimental results show that our approach is very effective in reducing the peak power. From the delay perspective, our approach reduces the delay by at least 11% (4%) in the address (data) buses compared to the data transmission without encoding.
Algorithms for Hub Label Optimization

We consider the hub label optimization problem, which arises in designing fast preprocessing-based shortest-path algorithms. We give O(log n)-approximation algorithms for the objectives of minimizing the maximum label size (ℓ∞-norm) and simultaneously minimizing a constant number of ℓp-norms. Prior to this, an O(log n)-approximation algorithm was known [Cohen et al. 2003] only for minimizing the total label size (ℓ1-norm).
Administrative Reforms in Malaysia Strategies for Promoting Efficiency and Productivity in the Public Service, 1981-91

This article is a macro-analysis of reform in the Malaysian civil service, covering the ten-year period between 1981 and 1991. These reforms were dictated by the need to increase efficiency, effeclivcness and productivity in order to speed up the implementation of development policies and deliver the economic goods to lhe people. This article brings into focus the opinions of high-ranking civil servants about reforms initialed during this period. The article concludes that though more effort is still needed, especially in determining how close programmes and policies have come to achieving their target, bureaucratic reforms carried out in Malaysia between 198] and] 99] have generally been successful in changing attitudes of civil servanl.S towards lhe goals of efficiency, effectiveness and productivity.
Granularity on Persistent Data Flow Testing of Active Database Applications

Active databases have been traditionally used as an alternative to implement persistent data requirements of applications on several knowledge domains. Their principle is the activation of tasks with specific functionalities as a response to events. These reactive abilities are generally expressed with active rules defined within the database itself. We investigate the use of data flowbased testing to identify the presence of faults in active rules written in SQL. Our research is based on the precision of data flow analysis, also named as data flow granularity, aiming at comparing different granularities and preliminarily evaluating their fault-revealing effectiveness. This analysis has an important impact on the cost of database application testing. The results point to higher granularities do not improve the fault detecting ability.
Motif discovery in physiological datasets: A methodology for inferring predictive elements

In this article, we propose a methodology for identifying predictive physiological patterns in the absence of prior knowledge. We use the principle of conservation to identify activity that consistently precedes an outcome in patients, and describe a two-stage process that allows us to efficiently search for such patterns in large datasets. This involves first transforming continuous physiological signals from patients into symbolic sequences, and then searching for patterns in these reduced representations that are strongly associated with an outcome. Our strategy of identifying conserved activity that is unlikely to have occurred purely by chance in symbolic data is analogous to the discovery of regulatory motifs in genomic datasets. We build upon existing work in this area, generalizing the notion of a regulatory motif and enhancing current techniques to operate robustly on non-genomic data. We also address two significant considerations associated with motif discovery in general: computational efficiency and robustness in the presence of degeneracy and noise. To deal with these issues, we introduce the concept of active regions and new subset-based techniques such as a two-layer Gibbs sampling algorithm. These extensions allow for a framework for information inference, where precursors are identified as approximately conserved activity of arbitrary complexity preceding multiple occurrences of an event. We evaluated our solution on a population of patients who experienced sudden cardiac death and attempted to discover electrocardiographic activity that may be associated with the endpoint of death. To assess the predictive patterns discovered, we compared likelihood scores for motifs in the sudden death population against control populations of normal individuals and those with non-fatal supraventricular arrhythmias. Our results suggest that predictive motif discovery may be able to identify clinically relevant information even in the absence of significant prior knowledge.
Environment-Independent Task Specifications via GLTL

We propose a new task-specification language for Markov decision processes that is designed to be an improvement over reward functions by being environment independent. The language is a variant of Linear Temporal Logic (LTL) that is extended to probabilistic specifications in a way that permits approximations to be learned in finite time. We provide several small environments that demonstrate the advantages of our geometric LTL (GLTL) language and illustrate how it can be used to specify standard reinforcement-learning tasks straightforwardly.
School principal self-efficacy: a study on self-efficacy levels of the Turkish primary school principals

The aim of this study was to determine self-efficacy levels of Turkish primary school principals. The study, designed with survey method, was conducted with 198 (33 principals & 165 vice principals) participants selected through stratified sampling. School Administrator Efficacy Scale (SAES, McCollum, Kajs & Minter, 2006a) was employed as an instrument in this study. Independent samples t-test, Kruskal Wallis-H test and correlation analysis were carried out during data analysis process. The findings of the study indicated that the highest level of school principal self-efficacy was in ‘Resource and Facility Management’ dimesion and the lowest level was in ‘Use of Community Resources’ dimension
Genetic State-Space Search for Constrained Optimization Problems

This paper introduces GSSS (Genetic State-Space Search). The integration of two general search paradigms--genetic search and state-space-search - provides a general framework which can be applied to a large variety of search problems. Here, we show how GSSS solves constrained optimization problems (COPs). Basically, it searches for "promising search states" from which good solutions can be easily found. Domain knowledge in the form of constraints is used to limit the space to be searched. Interestingly, our approach allows the handling of constraints within genetic search at a general domain independent level. First, we introduce a genetic representation of search states. Next, we provide empirical results which compare the relative merit of the introduction of constraints during the generation of the initial population, during the fitness calculation, and during the application of genetic operators. Finally, we describe some extensions to our method which came about when applying it to factory floor scheduling problems.
Journal of Theoretical and Applied Information Technology a Method for Requirements Management in Distributed Extreme Programming Environment

Both Distributed Software Development (DSD) and eXtreme Programming (XP) approaches have gained significant Popularity. Both DSD and XP method are growing trends as software business requires quicker quality production at a cheaper price. Requirement Management (RM) is not easy to perform even under the best of circumstances and it becomes more difficult when performed globally because of the nature of distributed development projects and the diversity of stakeholders. This article presents an investigation of the possibility to integrate Requirement Management in Distributed eXtreme Programming. One reason for integrating RM with DXP was that XP emphasizes lightweight documentation in XP based development. We propose the development of model and tool for executing RM in DXP that are required for proper software engineering and that activity should not restrict the efficient execution of XP method in DSD.
An efficient BER-based reliability method for SRAM-based FPGA

Single Event Upset (SEU) is a major concern for SRAM-based FPGAs where a simple bit-flip can lead to an abnormal execution. We present in this paper, a new fault tolerance method based on hardware BER (Backward Error Recovery) to protect/correct system against the occurrence of transient faults. We use the partial dynamic reconfiguration offered by Xilinx Virtex-5 FPGAs to ensure hardware checkpoint and upon detection of fault we use recovery. Our method has several advantages: first it is non-intrusive (no internal modification of hardware modules of the system), second it is not based on redundant hardware resources (like most methods in the literature), and finally it has a static area overhead ratio when applied to a system. To validate our approach, we implemented it on a Xilinx platform based on a Partial Reconfigurable Region (PRR).
Inhibition of HCV translation by disrupting the structure and interactions of the viral CRE and 3′ X-tail

A phylogenetically conserved RNA structure within the NS5B coding region of hepatitis C virus functions as a cis-replicating element (CRE). Integrity of this CRE, designated SL9266 (alternatively 5BSL3.2), is critical for genome replication. SL9266 forms the core of an extended pseudoknot, designated SL9266/PK, involving long distance RNA–RNA interactions between unpaired loops of SL9266 and distal regions of the genome. Previous studies demonstrated that SL9266/PK is dynamic, with ‘open’ and ‘closed’ conformations predicted to have distinct functions during virus replication. Using a combination of site-directed mutagenesis and locked nucleic acids (LNA) complementary to defined domains of SL9266 and its interacting regions, we have explored the influence of this structure on genome translation and replication. We demonstrate that LNAs which block formation of the closed conformation inhibit genome translation. Inhibition was at least partly independent of the initiation mechanism, whether driven by homologous or heterologous internal ribosome entry sites or from a capped message. Provision of SL9266/PK in trans relieved translational inhibition, and mutational analysis implied a mechanism in which the closed conformation recruits a cellular factor that would otherwise suppresses translation. We propose that SL9266/PK functions as a temporal switch, modulating the mutually incompatible processes of translation and replication.
A 1.8mW Wideband 57dBΩ transimpedance amplifier in 0.13µm CMOS

In multi-hundred Gb/s parallel optical links for on-chip or chip-to-chip data transfer, system components should be very low power while occupying small chip areas. This paper presents a low power transimpedance amplifier (TIA) that is based on regulated cascode with vertically stacked inductors, and can operate up to 10Gb/s in presence of 370fF input capacitance. The 0. 13µm CMOS TIA consumes 1.8mW to provide 57 dBΩ transimpedance gain, while occupying 150µm×100µm active area. The measured input referred current noise of the differential TIA is less than 30pA/√Hz across 8 GHz.
Impulse Response Matching Estimators for DSGE Models

One of the leading methods of estimating the structural parameters of DSGE models is the VAR-based impulse response matching estimator. The existing asymptotic theory for this estimator does not cover situations in which the number of impulse response parameters exceeds the number of VAR model parameters. Situations in which this order condition is violated arise routinely in applied work. We establish the consistency of the impulse response matching estimator in this situation, we derive its asymptotic distribution, and we show how this distribution can be approximated by bootstrap methods. Our methods of inference remain asymptotically valid when the order condition is satisfied, regardless of whether the usual rank condition for the application of the delta method holds. Our analysis sheds new light on the choice of the weighting matrix and covers both weakly and strongly identified DSGE model parameters. We also show that under our assumptions special care is needed to ensure the asymptotic validity of Bayesian methods of inference. A simulation study suggests that the frequentist and Bayesian point and interval estimators we propose are reasonably accurate infinite samples. We also show that using these methods may affect the substantive conclusions in empirical work.
Computational Grid as an Appropriate Infrastructure for Ultra Large Scale Software Intensive Systems

Ultra large scale (ULS) systems are future software intensive systems that have billions of lines of code, composed of heterogeneous, changing, inconsistent and independent elements that are dispersed through worldwide global networks. Huge scale of this heterology in addition to distinctive characteristics like decentralization of operation, management, deployment and evolution, continuous evolving, people participation in system operation and normal failures that dominate in ULS systems face them to new challenges that today software architectures and developers have less or no concerns about them. To face these challenges there must be an appropriate infrastructure with enough or at least extendable features and capabilities to support ULS distinctive characteristics. In this paper we propose computational grid as an appropriate infrastructure for ULS systems that not only supports some of ULS characteristics itself, but also can exploit service oriented architecture, fault tolerant approaches, distributed management algorithms and many other mechanisms in order to extend its fundamental capabilities to adapt itself with ULS systems. We explain what kind of grid is appropriate for ULS and expound how it provides solutions for each of the ULS particular characteristics.