Miracle-dz/UniFAR-FTUs huggingface dataset:
A framework for layout-level logic restructuring

It is well known that optimizations made by traditional logic synthesis tools often correlate poorly with post-layout performance; this is largely a result of interconnect effects only visible after layout. As a result, several attempts at physically aware logic synthesis have been made (e.g.,[2], [9], [14], [4], [7], [12], [16], [15]). In this paper a corrective methodology is proposed for timing-driven logic restructuring at the placement level; the approach currently focuses on LUT-based FPGAs. Driven by placement level static timing analysis, the method induces relatively large, timing-critical fan-in trees via (temporary) replication as in [9]. Such trees are then reimplemented where the degrees of freedom include functional decomposition of LUTs, subject graph covering/mapping, and physical embedding. A dynamic programming algorithm optimizes over all of these freedoms simultaneously. All simple disjoint decompositions (i.e., Ashenhurst style) are encoded in the subject tree/graph using choice nodes similar to those in [11]. At the same time, because embedding is done simultaneously, interconnect delay is directly taken into account We have implemented the framework and in many cases we were able to approach a fixed flip-flop lower-bound on achievable clock period. Promising experimental results are reported with average 14.8% (up to 37.4%) clock period reduction compared with the timing-driven placement from VPR [13] and average 6.6% (upto 17%) reduction compared with the basic fan-in tree embedder from [9].
On the relationship between socio-economic factors and cell phone usage

The ubiquitous presence of cell phones in emerging economies has brought about a wide range of cell phone-based services for low-income groups. Often times, the success of such technologies highly depends on its adaptation to the needs and habits of each social group. In an attempt to understand how cell phones are being used by citizens in an emerging economy, we present a large-scale study to analyze the relationship between specific socio-economic factors and the way people use cell phones in an emerging economy in Latin America. We propose a novel analytical approach that combines large-scale datasets of cell phone records with countrywide census data to reveal findings at a national level. Our main results show correlations between socio-economic levels and social network or mobility patterns among others. We also provide analytical models to accurately approximate census variables from cell phone records with R2 ≈ 0.82.
Transmigration of Object Identity : The Programming Language Gilgul

Software requirements are in a constant flux. Some changes in requirements can be anticipated by software developers, but unanticipated changes of requirements occur repeatedly in practice, and they cannot be prepared for by definition. Furthermore, changes to software can usually be made effective only by stopping an old version of a program and starting the new one. Alternatively, programming languages and runtime systems should be equipped with features that allow for unanticipated adaptations of an already active program. In principle, unanticipated adaptation can always be dealt with by manual redirection of references. However, there are two consistency problems involved in this approach. Firstly, if there is more than one reference to an object, they all must be known to the programmer. Secondly, even if all references are known, they have to be redirected one by one. This approach is likely to lead to an inconsistent state if message sends to the involved objects occur in between. It would be straightforward if we could simply “replace” an object without changing the involved references, and thereby avoid these consistency problems. Gilgul is an extension to the Java programming language that introduces new operations in order to allow for this kind of dymanic replacement of objects. It also shows that a dissection of the concept of object identity and a strict separation of the included notions of reference and comparison is needed in order to define them in a semantically clean way.
GLOBAL INLAND WATER MONITORING FROM SATELLITE RADAR ALTIMETRY - A GLIMPSE INTO THE FUTURE

Satellite altimetry has been used to monitor the heights of the Earth's largest lakes for many years; however, river systems present far more challenging targets. Using an expert system approach, echoes from smaller lakes and river systems can be successfully retracked to yield height measurements. As the network of in situ gauges declines, this remote measurement technique gives a unique insight into the Earth's changing inland water resources. This paper presents a global analysis of the capability of the current generation of satellite radar altimeters to monitor inland water, including ERS2, EnviSat, TOPEX, Jason1 and Jason2. The results are analysed using an automated grading technique. A glimpse into the potential of future altimeters is gained from the EnviSat altimeter (RA-2) Individual Echoes, with 1800 Hz along-track sampling rate, demonstrating the substantial enhancement in monitoring capability afforded by the next generation of satellite altimeter missions.
VMdeploy: Improving Best-Effort Job Management in Grid'5000

Virtualization technologies have recently gained a lot of interest in Grid computing as they allow flexible resource management. Grid'5000 (G5K) is a French national Grid platform used for computer science research to experiment all layers of Grid software. Computer scientists reserve G5K nodes prior to their experiments. In G5K some low priority jobs are executed in best effort mode on the node idle time slots when the latter are not part of any reservation. However, best-effort jobs may be killed at any time by the Grid job scheduler when the nodes they use are subject to higher priority reservation. This behaviour leads potentially to a huge waste of compute time or at least requires users to deal with checkpoints of their best efforts jobs. In this paper, we describe the design and implementation of the VMdeploy framework which exploits virtual machines for executing best effort jobs in order to solve the best-effort issue in G5K platform. VMdeploy manages snapshots of the best effort jobs transparently to their users and thus ensures the progress of these jobs avoiding most of the waste of resources. Results of a preliminary experimental evaluation are presented. While designed in the context of G5K, VMdeploy can be used in combination of any job scheduler in clusters and grids.
The value of Community Informatics to participatory urban planning and design: a case-study in Helsinki

Normal 0 MicrosoftInternetExplorer4 st1\:*{behavior:url(#ieooui) } /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:. 0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman";} The aim of the article is to present and discuss the potentials of community informatics for participatory planning and design, as well as for ICT-mediated participation in general. The article is based on a case study of the co-design of a shared yard in Helsinki . The application of ICTs meant that tools such as the local website and the Urban Mediator were used as platforms and media to co-create, share and distribute information concerning the progress of the design of the yard. We argue that CI-assisted participatory planning and design provide a viable perspective and significant contribution to ICT-mediated participation in urban issues.
Neural Network Control of CSTR for Reversible Reaction Using Reverence Model Approach

In this work, non-linear control of CSTR for reversible reaction is carried out using Neural Network as design tool. The Model Reverence approach in used to design ANN controller. The idea is to have a control system that will be able to achieve improvement in the level of conversion and to be able to track set point change and reject load disturbance. We use PID control scheme as benchmark to study the performance of the controller. The comparison shows that ANN controller out perform PID in the extreme range of non-linearity. This paper represents a preliminary effort to design a simplified neutral network control scheme for a class of non-linear process. Future works will involve further investigation of the effectiveness of thin approach for the real industrial chemical process
A Bidding Approach to Turn-Taking

We propose a new turn-taking framework for spoken dialogue s ystems in which conversants bid for the turn. This differs from most current turn-taking approaches, where the turn only changes after the holder has eleased it. Our new framework uses Reinforcement Learning to choose approp riate turn bids, which indirectly estimates the utterance importance. We ev aluate this approach in an artificial task-oriented domain and we find that it outpe rforms conventional release-turn methods in a relatively realistic environmen t. Current performance is explained and future implications are discussed.
Learning Instance-Specific Predictive Models

This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algorithm learns Markov blanket models, carries out Bayesian model averaging over a set of models to predict a target variable of the instance at hand, and employs an instance-specific heuristic to locate a set of suitable models to average over. We call this method the instance-specific Markov blanket (ISMB) algorithm. The ISMB algorithm was evaluated on 21 UCI data sets using five different performance measures and its performance was compared to that of several commonly used predictive algorithms, including nave Bayes, C4.5 decision tree, logistic regression, neural networks, k-Nearest Neighbor, Lazy Bayesian Rules, and AdaBoost. Over all the data sets, the ISMB algorithm performed better on average on all performance measures against all the comparison algorithms.
Rationale, design, and implementation of the network neutrality bot

The “Network Neutrality Bot” (Neubot) is a software application that measures, in a distributed way, Internet access quality of service with a specific emphasis on detection of potential network neutrality violations (such as peer-to-peer traffic discrimination). It is based on a lightweight, open-source computer program that can be downloaded and installed by ordinary Internet users. The program performs background tests: the results are sent to a centralized server (or collection of servers), which publishes them, thus rebalancing, at least in part, the current deep information asymmetry between Internet Service Providers and users. The collected data will allow constant monitoring of the state of the Internet, enabling a deeper understanding of such crucial infrastructure, as well as a more reliable basis for discussing network neutrality policies.
Making Blood: The Haematopoietic Niche throughout Ontogeny

Approximately one-quarter of all cells in the adult human body are blood cells. The haematopoietic system is therefore massive in scale and requires exquisite regulation to be maintained under homeostatic conditions. It must also be able to respond when needed, such as during infection or following blood loss, to produce more blood cells. Supporting cells serve to maintain haematopoietic stem and progenitor cells during homeostatic and pathological conditions. This coalition of supportive cell types, organised in specific tissues, is termed the haematopoietic niche. Haematopoietic stem and progenitor cells are generated in a number of distinct locations during mammalian embryogenesis. These stem and progenitor cells migrate to a variety of anatomical locations through the conceptus until finally homing to the bone marrow shortly before birth. Under stress, extramedullary haematopoiesis can take place in regions that are typically lacking in blood-producing activity. Our aim in this review is to examine blood production throughout the embryo and adult, under normal and pathological conditions, to identify commonalities and distinctions between each niche. A clearer understanding of the mechanism underlying each haematopoietic niche can be applied to improving ex vivo cultures of haematopoietic stem cells and potentially lead to new directions for transplantation medicine.
Teaching abstraction in introductory courses

Abstraction is viewed as a key concept in computer science. It is not only an important concept but also one that is difficult to master. This paper focuses on the problems that novices experience when they first encounter this concept. Three assignments from introductory courses are analyzed, to understand why abstraction is difficult for novices. This analysis leads to a number of guidelines that can be used by instructors to support novices learning abstraction.
Ten Things to do About Patent Holdup of Standards (and One Not To)

Congress, the courts, scholars, and the press have focused more and more attention on what is shaping up to be the central public policy problem in intellectual property law today: the problem of holdup by patent owners, particularly but not exclusively in the context of standard setting. I will suggest ten things we might do to deal with this problem, and at least one thing we probably ought not to do.
What a Difference a Decade Makes: Growing Wealth Inequality among Ivy League Institutions.

Excerpt] The eight Ivy League institutions – Brown, Columbia, Cornell, Dartmouth, Harvard, Pennsylvania, Princeton and Yale are among our nations most selective undergraduate institutions. They also are among its wealthiest. They compete against each other for top faculty, graduate and undergraduate students, as well as on intercollegiate athletic fields. However, this competition has never taken place on a level “playing field” because of the vast differences in endowment resources that have always existed across the institutions. The prolonged stock market expansion during the 1990s magnified these differences in ways that many still do not fully comprehend.
A data-driven approach for fault diagnosis in HVAC chiller systems

Faulty operations of Heating, Ventilation and Air Conditioning (HVAC) chiller systems can lead to discomfort for the user, energy wastage, system unreliability and shorter equipment life. Faults need to be diagnosed early to prevent further deterioration of the system behaviour and energy losses. Since it is not a common practice to collect historical data regarding unforeseen phenomena and abnormal behaviours for HVAC installations, in this paper a semi-supervised, data-driven approach is employed for fault detection and isolation that makes no use of a priori knowledge. The proposed method exploits Principal Component Analysis to distinguish between anomalies and normal operation variability and a reconstruction-based contribution approach to isolate variables related to faults. The diagnosis task is then tackled by means of a decision table. The fault diagnosis algorithm performance is assessed by exploiting an experimental dataset from a frictionless centrifugal chiller system.
Pre-editing and Recursive-Phrase Composites for a Better English-to-Arabic Machine Translation

This research presents an approach for an English-to-Arabic Machine Translation System based on Building correct grammar and phrase structures first and then automatically deriving Translation Rules for phrase translation. For every English phrase, the grammar is first analysed and then a corresponding Arabic translation is given which would be used by the machine learning system to produce a translation rule with the help of a dictionary and the user. These same derived rules can partially be used for other phrase sequences especially in the case of a phrase consisting of a number of smaller phrases and thus implemeting the idea of recusive phrase strucutres. The approach was implemented and tested on simple cases and the results are given which indicate that this approach is successful for small to medium phrases. Our approach is an enhancement on existing phrase translation techniques because it analyses the source language grammar first, then builds a syntactic structure before proceeding with the machine learning process of learning the translation rules. Our approach is enhancement on existing phrase based translations in two directions: the grammar editing before the translation rules and the derived translation rules can be complete for complete phrases or are rules for translatioing smaller phrases which are subsets or larger phrases. The approach has improved the spped and correctness of phrase translations.
Quantum Circuits for Isometries

We consider the decomposition of arbitrary isometries into a sequence of single-qubit and controlled-not (cnot) gates. In many experimental architectures, the cnot gate is relatively costly and hence we aim to keep the number of these as low as possible. We derive a theoretical lower bound on the number of cnot gates required to decompose an arbitrary isometry from $m$ to $n$ qubits and give three explicit gate decompositions that achieve this bound up to a factor of about 2 in the leading order. We also perform some further optimizations for certain cases where $m$ and $n$ are small. In addition, we show how to apply our result for isometries to give a decomposition scheme for an arbitrary quantum operation via Stinespring's theorem and derive a lower bound on the number of cnot gates in this case too. These results will have an impact on experimental efforts to build a quantum computer, enabling them to go further with the same resources.
Preconditioning the Lanczos Algorithm for Sparse Symmetric Eigenvalue Problems

A method for computing a few eigenpairs of sparse symmetric matrices is presented and analyzed that combines the power of preconditioning techniques with the efficiency of the Lanczos algorithm. The method is related to Davidson’s method and its generalizations, but can be less expensive for matrices that are fairly sparse. A double iteration is used. An effective termination criterion is given for the inner iteration. Quadratic convergence with respect to the outer loop is shown.
Surplus Cost Potential as a Life Cycle Impact Indicator for Metal Extraction

In the evaluation of product life cycles, methods to assess the increase in scarcity of resources are still under development. Indicators that can express the importance of an increase in scarcity of metals extracted include surplus ore produced, surplus energy required, and surplus costs in the mining and the milling stage. Particularly the quantification of surplus costs per unit of metal extracted as an indicator is still in an early stage of development. Here, we developed a method that quantifies the surplus cost potential of mining and milling activities per unit of metal extracted, fully accounting for mine-specific differences in costs. The surplus cost potential indicator is calculated as the average cost increase resulting from all future metal extractions, as quantified via cumulative cost-tonnage relationships. We tested the calculation procedure with 12 metals and platinum-group metals as a separate group. We found that the surplus costs range six orders of magnitude between the metals included, i.e., between $0.01–$0.02 (iron) and $13,533–$17,098 (rhodium) USD (year 2013) per kilogram of metal extracted. The choice of the reserve estimate (reserves vs. ultimate recoverable resource) influenced the surplus costs only to a limited extent, i.e., between a factor of 0.7 and 3.2 for the metals included. Our results provide a good basis to regularly include surplus cost estimates as resource scarcity indicator in life cycle assessment.
Weak lensing measurements of dark matter halos of galaxies from COMBO-17

Received / Accepted Abstract. We present a measurement of mass estimates for dark matter halos around galaxies from the COMBO- 17 survey using weak gravitational lensing. COMBO-17 is particularly useful for this kind of investigation because it covers observations in 17 optical filters from which accurate photometric redshifts and spectral classification for objects with R < 24 are derived. This allows us to select lens and source galaxies from their redshifts and to thus avoid any uncertainties from estimates of the source redshift distribution. We study galaxy lenses at redshifts zd = 0.2 − 0.7 by fitting the normalization of either singular isothermal spheres (SIS) or Navarro- Frenk-White (NFW) profiles to the whole lens sample; we then consider halos around blue and red subsamples separately. We also constrain the scaling of halo mass with light. For the NFW model, we find virial masses M � vir = 3.9
Intellectual Capital Efficiency Analysis of Indian Private Sector Banks

Banks happen to be one of the largest Intellectual Capital (IC)-intensive sectors. Measurement and management of intellectual capital, therefore, become essential, as it reflects the true value of the firm. The main aim of this paper is to estimate and analyze the Value Added Intellectual Coefficient (VAIC) for measuring the value-based performance of the Indian private sector banks for a period of five years from 2002-2007. The source of the data is the annual report, especially the profit/loss account and balance sheet, of the concerned banks for the relevant years. The data was collected through the RBI online database on Indian economy. The methodology was finalized based on an extensive review of international literature on intellectual capital with specific reference to literature that reviews measurement techniques and tools of intellectual capital. This study applies the VAIC method (propounded by Pulic Ante in 2000) in order to analyze the data of Indian private sector banks for the five-year period. It analyzes the intellectual or Human Capital (HC) and Physical Capital (CA) of the Indian banking sector and discusses their impact on the banks’ value-based performance. The significance of this study is that it approaches the performance measurement and efficiency of banks in India with a new perspective and dimension. The performance of the banks is closely linked to their valuation and also their future strategies related to mergers and acquisitions.
Causation Among Socioeconomic Time-Series

Using annual U. S. time series data from 1950-1974, formal tests of causation are performed among three socioeconomic phenomena: women's labor force participation rates, fertility rates, and divorce rates. Box-Jenkins and other techniques are employed with Granger-Sims type definition of causation based on leads and lags. Women's labor force participation appears to be causally prior to both fertility and divorce; the direction of effect on fertility is negative and on divorce, positive. Additional tests with alternative definitions of variables and a longer (1924-1974) time span also exhibit causal influence from fertility to divorce (with no feedback). When per capita income is also tested for causal influence, it, too, appears causally prior to fertility and divorce.