Miracle-dz/UniFAR-FTUs huggingface dataset:
Bis Working Papers Monetary and Economic Department the Impact of Pre-announced Day-to-day Interventions on the Colombian Exchange Rate

No 428 The impact of pre-announced day-today interventions on the Colombian exchange rate BIS Working Papers are written by members of the Monetary and Economic Department of the Bank for International Settlements, and from time to time by other economists, and are published by the Bank. The papers are on subjects of topical interest and are technical in character. The views expressed in them are those of their authors and not necessarily the views of the BIS. This publication is available on the BIS website (www.bis.org). Brief excerpts may be reproduced or translated provided the source is stated. Abstract The adoption of a managed regime assumes that interventions are relatively successful. However, while some authors consider that foreign exchange interventions are not effective, arguing that domestic and foreign assets are close substitutes, others advocate their use and maintain that their effects can even last for months. There is also a lack of consensus on the related question of how to intervene. Are dirty interventions more powerful than pre-announced constant ones? This paper compares the effects of day-today interventions with discretionary interventions by combining a Tobit-GARCH reaction function with an asymmetric power PGARCH(1,1) impact function. Our results show that the impact of pre-announced and transparent US$ 20 million daily interventions, adopted by Colombia in 2008-2012, has been much larger than the impact of dirty interventions adopted in 2004-2007.We find that the impact of a change in daily interventions (from US$20 million to US$ 40 million) raises the exchange rate by approximately Col $2, implying that actual interventions of US$ 1000 million increase the exchange rate in one day by 5.50%. We also find a positive impact of capital controls. 1 The views expressed in this Working Paper are those of the authors, and do not necessarily represent those of the Colombian Central Bank. We want to thank the comments of
Ira'S And Households Saving

This paper examines the effects of Individual Retirement Accounts (IRAs) on private and national saving. The authors construct a formal model of dynamic utility maximization that generates closed-form equations for IRA and other saving. Their empirical estimates indicate that raising the annual IRA contribution limit between 1983 and 1986 would have resulted in little, if any, increase in national saving. Results from sensitivity analysis imply substantially smaller effects on national saving than most previous researchers have estimated. The authors' results are consistent with new evidence they present indicating considerable potential among IRA holders to shift taxable forms of saving into IRAs. Copyright 1994 by American Economic Association. (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (This abstract was borrowed from another version of this item.) (T (This abstract was borrowed from another version of this item.)
Design of a high gain power amplifier for 77 GHz radar automotive applications in 65-nm CMOS

A 77 GHz power amplifier (PA) fabricated in a standard CMOS 65-nm process for radar automotive applications is presented. Based on passive transformer-coupled architectures, a high gain PA has been developed for a 76-77 GHz frequency range. The proposed PA achieves a 18.5 dB gain with output compression point (OP1dB) of +9.5 dBm and a saturated output power of +10.5 dBm for a 1.2 V supply. The isolation between input and output ports is better than 42 dB, and peak power added efficiency (PAE) is 7.1 %. Return losses at the input and output ports are less than -10 dB across the 67-100 GHz band. The PA has a compact size of 0.4 × 0.85 mm2.
ON THE EQUIVALENCE OF A MINIMAL ORDER MPC AND A GTDOF CONTROL OF TIME-DELAY PLANTS

Abstract It is shown that for open-loop stable plants the task of an MPC can be solved by identifying the plant model only instead of the redundant prediction model. Interesting structural considerations can be derived from comparison of the topologies and structural forms of regulators obtained by pole-placement design, the GTDOF scheme and the MPC . A new simple method is also introduced for adaptive and combined iterative identification and control for time-delay plants.
Novel Approach for Fault Detection in Wireless Sensor Network

The Wireless Sensor Network is the wireless autonomous network with a large number of distributed sensor nodes. The nodes in WSN are small in size hence very much portable. These sensor nodes are mainly used to monitor environmental conditions. They collect information from its surroundings and also from each neighbour. Then whole data are sent to main location for its analysis. This cooperative approach of message transmission has made sensor network much reliable. But if they receive any wrong information from their neighbours, it makes them faulty. For the whole system’s performance, it is very important to maintain the accuracy of data. Hence detecting faulty nodes in sensor network is a measure issue in network management. If no central system is there to monitor the fault issues, sensor nodes have to implement their own ways to detect fault. This paper focuses on the implementation of fault detection feature. We have proposed fault detection algorithm for diagnosing the hardware fault and implemented the algorithm which is having better performance over the existing algorithm. Keywords-Wireless Sensor Network, Fault Detection, Fault Diagnosis.
A Dynamic Model of an Imperfectly Competitive Bid-Ask Market

This paper studies a dynamic model of an imperfectly competitive bid- ask market with a few large and many small traders. Large traders are risk- averse and exchange a risky asset for hedging purposes. The only private information in the model concerns their hedging demands. We find that large traders trade quickly when there are many small traders in the market, and do so at a decreasing rate over time. With fewer small traders they trade more slowly at an increasing and then at a decreasing rate, and the outcome is much more inefficient than what static double auction models predict. We also find that if the market clears more frequently, large traders trade faster if there are many small traders and vice- versa. Finally large traders are better off if information regarding their hedging demands is publicly known, when they account for a substantial part of the trading volume.
Schools as Collaborative Cultures Creating the Future Now, Ann Lieberman. 1990. Falmer Press, New York, NY. 261 pages. ISBN: 1-85000-673-3. $29.95

Part 1 Understanding what we value: recanting bureaucracy - a democratic structure for leadership in schools, David L Clark,Judith M Meloy teacher professionalism, Linda Darling-Hammond what are schools of education for? Seymour Sarason. Part 2 Examining critical issues of fundamental change: a fundamental puzzle of school reform, Larry Cuban education reform strategies - will they increase teacher commitment? Susan J Rosenholtz teaching incentives - contraint and variety, Gary Sykes healing our schools - restoring the heart, Terry Deal. Part 3 Changing the roles, relationships and the culture of schools: the social realities of teaching, Ann Lieberman and Lynne Miller teachers as colleagues, Judith Warren Little leadership for curriculum improvement - the school administrator's role, Gary A Griffin staff development and school change, Milbrey W McLaughlin and David D Marsh schools for the 21st century - the conditions for invention, Phillip C Schlechty.
Load Balancing for Data-Parallel Applications on Network-on-Chip Enabled Multi-processor Platform

As the computation cost increases to meet the design requirements for computation-intensive applications on today's systems, the pressure to develop high performance parallel processors on a chip will increase. Network-on-Chip (NoC) techniques that interconnect multiple processing elements with routers are the solution for reducing computation time and power consumption by parallel processing on a chip. The shared communication platform is also essential to meet the scalability and complexity challenges for System-on-Chip (SoC). However not many parallel applications have been studied for such an architecture and workload characterizations have not been researched to benefit the architecture design optimization. In this paper, we study multiple data-parallel applications on a multicore NoC architecture with distributed memory space. We introduce an efficient runtime workload distribution algorithm that balances workloads of parallel processors and apply for selected embedded applications. Using our cycle accurate multicore simulator, we simulated our NoC-enabled multicore architecture model and executed data-parallel applications on various number of processing elements using the proposed runtime load balancing algorithm and analyzed performance and communication overheads.
NEmESys: neural emotion eliciting system

This paper describes the development of a new model of agent emotion elicitation called Nemesys. It enhances interfaces with emotional and social information. Nemesys is based on an artificial neural network and is able to learn six basic emotional states. The elicitation of emotions is based on models drawn from the state of the art in modeling emotions in the field of psychology. Further the described framework includes the Five-Factor Model of Personality to represent different agent personalities.Nemesys (called after Nemesis, the Greek goddess of righteous anger) is designed to perform in various types of interfaces. The usage of Nemesys is presented with an application scenario employing a commercial 3D game-engine. Additionally a critical review of the current elicitation behavior of Nemesys is presented and discussed.
Optimized Firewall with Traffic Awareness

Firewall is one of the well known network-based security devices that have been widely used since the initial days of computer network security. Firewall is designed to allow or reject network traffic depending on firewall rules that displays the types of packets should be accepted or rejected in protected network. Currently growth complexity in network is high and it’s very common to find firewall policies consisting of many rules. Packet filtering is the one of the major contemporary firewall design techniques. An important design goal is to arrive at the decision at the packet only [1]. Firewall access rule list consists of rules which are sequentially checked. This implies that firewall filtering overhead and costing will be higher when the order of the matching rules is higher. Hence it is vital, to minimize the filtering overhead. It’s critical to have necessary ordering of rules in the firewall rule set. Firewall validates all inbound and outbound packets by analyzing data packet and then by comparing packets with many firewall rules, that defines whether to accept or discard the traffic. It is very important to improve the firewall policies to improve performance of network. Index Terms – Firewall, Security, Filtering, Traffic.
A Semantic Context-Based Model for Mobile Web Services Access Control

As mobile web services becomes more pervasive, applications based on mobile web services will need flexible access control mechanisms. Unlike traditional approaches based on the identity or role for access control, access decisions for these applications will depend on the combination of the required attributes of users and the contextual information. This paper proposes a semantic context-based access control model (called SCBAC) to be applied in mobile web services environment by combining semantic web technologies with context-based access control mechanism. The proposed model is a context-centric access control solutions, context is the first-class principle that explicitly guides both policy specification and enforcement process. In order to handle context information in the model, this paper proposes a context ontology to represent contextual information and employ it in the inference engine. As well as, this paper specifies access control policies as rules over ontologies representing the concepts introduced in the SCBAC model, and uses semantic web rule language (SWRL) to form policy rule and infer those rules by JESS inference engine. The proposed model can also be applied to context-aware applications. Index Terms—mobile web services, context-based access control, ontology technology, OWL, SWRL
Towards energy efficient relay placement and load balancing in future wireless networks

This paper presents an energy efficient relay deployment algorithm that determines the optimal location and number of relays for future wireless networks, including Long Term Evolution (LTE)-Advanced heterogeneous networks. We formulate an energy minimization problem for macro-relay heterogeneous networks as a Mixed Integer Linear Programming (MILP) problem. The proposed algorithm not only optimally connects users to either relays or eNodeBs (eNBs), but also allows eNBs to switch into inactive mode. This is possible by enabling relay-to-relay communication which forms the basis for relays to act as donors for neighboring relays instead of eNBs. Moreover, it relaxes traffic load of some eNBs in order to allow them to enter the inactive mode. We characterize the optimal as well as provide an approximate solution, which, however, performs very closely to the optimum. Our performance evaluation shows that an optimal relay deployment with relays acting as donors can significantly improve system energy efficiency.
Dynamical mass matrices from moduli fields

We review recent work on the structure of the fermion mass matrices in supergravity effective superstrings. They are generally given at low energy by non-trivial functions of the gauge singlet moduli fields. Interesting structures appear in particular if they are homogeneous functions of zero degree in the moduli. In this case we find Yukawa matrices very similar to the ones obtained by imposing a $U(1)$ family symmetry to reproduce the observed hierarchy of masses and mixing angles. The role of the $U(1)$ symmetry is played here by the modular symmetry. The Flavor Changing Neutral Currents effects at the Planck scale coming from the soft terms are identically zero. A dynamical scenario is discussed which allow to generate the observed hierarchies.
Control plane design for reliable optical networks

The application of an IP-based control plane to optical networks has opened up new opportunities and challenges for network designers. Although much work has been done on standardization of protocols for IP networks, the applicability of these protocols to controlling optical networks and the overall reliability of optical networks needs further investigation. This article provides a detailed discussion of a number of subtle protocol design and implementation issues that were not addressed in early standardization efforts or published papers.
Integrating gene ontology into discriminative powers of genes for feature selection in microarray data

One of the main challenges in the classification of microarray gene expression data is the small sample size compared with the large number of genes, so feature selection is an essential step to remove genes not relevant to class labels. Most feature selection methods are solely based on expression values to determine discriminative values of genes and remove redundancy. However, due to the characteristics of microarray technology, some values may not be accurately measured. This may reduce the effectiveness of these models. To cope with this problem, in this paper, we integrate Gene Ontology (GO) annotations into gene selection. The novelty of our work is to evaluate genes based on not only their individual discriminative powers but also the powers of GO terms that annotate them. This strategy implicitly verifies the accuracies of the measurements and reduces redundancy. Experimental results in four public datasets demonstrate the effectiveness of the proposed method.
Deflator selection and generalized linear modelling in market-based regression analyses

The scale factor refers to an unknown size variable which affects some or all observed variables in a multiplicative fashion. The scale effect studied by several researchers in market-based regression analyses is defined here as the intriguing combination of coefficient bias and heteroscedasticity caused by the scale. Deflation is the most popular technique used in previous market-based studies to mitigate the scale effect. Selection of a suitable deflator, however, remains as a difficult and challenging task due to the lack of a general statistical framework for this type of research. In this article, we establish a general statistical framework for deflator and model selection. We argue and show that the existence and severity of the scale effect can be identified and measured using the Average Absolute Values of Studentized Residuals and the Relative Total Prediction Error for stratified firm groups. The proposed framework consists of five major components. Results from our simulation studies and sensitivity analyses show that if the true scale variable is used as a deflator to produce one of the deflated candidate models, this model can be correctly identified using the proposed strategy, even if the working model is mildly misspecified. In addition, our studies show that the generalized linear modelling method can be very useful for mitigating the scale effect when the unknown true scale variable is related to the whole set of independent variables through the so-called mean function.
Emerging patterns: mining and applications

Emerging patterns are collections of items whose frequency changes significantly from one dataset to another. They are a means of discovering distinctions and contrasts between a collection datasets and have been shown to be a powerful method for constructing accurate classifiers. In this paper, we examine some different types of emerging patterns, look at techniques for mining them from large datasets and show they can be used for classification.
Elicitation of Requirements for the Design of Mobile Financial Advisory Services -- Instantiation and Validation of the Requirement Data Model with a Multi-method Approach

The mobile channel is becoming more vital for the private banking customer segment. Recent studies suggest that mobile will even become a key differentiator for private banks in the ever-increasing competitive environment. This study elicits requirements for the design of a mobile financial advisory service (mFAS) by instantiating and validating the Requirement Data Model (RDMod). In order to achieve this goal, we chose a multi-method approach conducting ten expert interviews, four focus groups and a literature review. The findings suggest a list with ten customer and stakeholder, two process, two environment as well as two bank requirements. Furthermore, we contribute to existing theory by instantiating the RDMod with a feature-based evaluation.
Synthesis, accumulation and encapsidation of individual brome mosaic virus RNA components in barley protoplasts.

Summary The rates of virus RNA synthesis and virion accumulation were investigated in brome mosaic virus-infected barley protoplasts. Single-stranded virus RNAs could be detected as early as 6 h after inoculation. Only RNA components 1 and 2 were detected at this time, suggesting that their synthesis is initiated relatively early in infection. The RNAs were synthesized at similar rates from 16 to 35 h post inoculation with maximal synthesis until approx. 25 h after inoculation. Double-stranded replicative forms of the four virus RNAs were observed. Their synthesis was first detectable at 6 h post inoculation and followed a time course similar to that of the single-stranded RNA species. Analysis of RNA encapsidation and infectivity assays of protoplast homogenates revealed that virion formation was greatest between 10 and 25 h after inoculation. All four RNAs were present in virions at 10 h post inoculation. Particles containing RNA 3 and RNA 4 accumulated at a faster rate than particles containing RNA 1 or RNA 2.
A high-linearity CMOS Programmable Gain Amplifier for wireless communications

A low-power high-linearity PGA (Programmable Gain Amplifier) is proposed in this paper. The PGA adopts a differential degeneration structure to vary voltage gain and uses the closed-loop structure including the input op-amps to enhance the linearity. This PGA is fabricated in TSMC 0.13um CMOS technology. The measurements show that the PGA provides 64dB (3dB∼66dB) gain range with a step of 1dB, the bandwidth of the multi-stage PGA is higher than 20MHz. The IIP3 (third order input referred intercept point) of the PGA is measured to be as high as 20dBm at the minimum gain, meanwhile the NF is 28dB when the PGA gain at 34dB settings. The PGA chain consumes 7mA (I path) from 3.3V single supply voltage.
The Warmer the Weather, the More Gram-Negative Bacteria - Impact of Temperature on Clinical Isolates in Intensive Care Units

Background We investigated the relationship between average monthly temperature and the most common clinical pathogens causing infections in intensive care patients. Methods A prospective unit-based study in 73 German intensive care units located in 41 different hospitals and 31 different cities with total 188,949 pathogen isolates (102,377 Gram-positives and 86,572 Gram-negatives) from 2001 to 2012. We estimated the relationship between the number of clinical pathogens per month and the average temperature in the month of isolation and in the month prior to isolation while adjusting for confounders and long-term trends using time series analysis. Adjusted incidence rate ratios for temperature parameters were estimated based on generalized estimating equation models which account for clustering effects. Results The incidence density of Gram-negative pathogens was 15% (IRR 1.15, 95%CI 1.10–1.21) higher at temperatures ≥20°C than at temperatures below 5°C. E. cloacae occurred 43% (IRR = 1.43; 95%CI 1.31–1.56) more frequently at high temperatures, A. baumannii 37% (IRR = 1.37; 95%CI 1.11–1.69), S. maltophilia 32% (IRR = 1.32; 95%CI 1.12–1.57), K. pneumoniae 26% (IRR = 1.26; 95%CI 1.13–1.39), Citrobacter spp. 19% (IRR = 1.19; 95%CI 0.99–1.44) and coagulase-negative staphylococci 13% (IRR = 1.13; 95%CI 1.04–1.22). By contrast, S. pneumoniae 35% (IRR = 0.65; 95%CI 0.50–0.84) less frequently isolated at high temperatures. For each 5°C increase, we observed a 3% (IRR = 1.03; 95%CI 1.02–1.04) increase of Gram-negative pathogens. This increase was highest for A. baumannii with 8% (IRR = 1.08; 95%CI 1.05–1.12) followed by K. pneumoniae, Citrobacter spp. and E. cloacae with 7%. Conclusion Clinical pathogens vary by incidence density with temperature. Significant higher incidence densities of Gram-negative pathogens were observed during summer whereas S. pneumoniae peaked in winter. There is increasing evidence that different seasonality due to physiologic changes underlies host susceptibility to different bacterial pathogens. Even if the underlying mechanisms are not yet clear, the temperature-dependent seasonality of pathogens has implications for infection control and study design.