Miracle-dz/UniFAR-FTUs huggingface dataset:
The Expressiveness of Simple and Second-Order Type Structures

Typed lambda (? `-) calculi provtde convement mathematical settings in which to investigate the effects of type structure on the function definmon mechamsm m programming languages. Lambda expressaons mtm~c programs that do not use while loops or carcular function definitions. Two typed ? `-calculi are investigated, the sunply typed ? `-calculus, whose types are similar to Pascal types, and the second-order typed ? ,-calculus, which has a type abstractaon mechamsm simdar to that of modern data abstraction languages such as ALPHARD. Two related questions are considered for each calculus: (1) What functaons are definable m the calculus? and (2) How difficult is the proof that all expressions in the calculus are normahzable 0.e. , that all computaUons termmate)* The simply typed calculus only defines elementary functtons. Normahzation for this calculus ~s provable using commonplace forms of reasoning formalazable m Peano arithmetic The second-order calculus defines a huge hierarchy of funcuons going far beyond Ackermann's function These funcuons are so rapidly increasing that Peano arithmetic cannot prove that they are total In fact, normalizataon for the second-order calculus cannot be proved even m second-order Peano artthmetic, nor m Peano anthmettc augmented by all true statements Also d~scussed are the lmphcataons of the present ? `-calculus results for the programming languages PASCAL, ALPHARD, RUSSELL, and MODEL. Categories and SubJect Descriptors: D 3.3 [Programming Languages]: Language Constructs--control structures, data types and structures; F. 1 1 [Computation by Abstract Devices]" Models of Computation computablhty theory, F.4 1 [Mathematical Logic and Formal Languages]" Mathematical Logic--computabzlity theory, lambda calculus and related systems General Terms Algorithms, Languages, Theory Addltaonal
E L 04 1 New Floating Capacitance Multipliers

In this paper, a technique for realizing a floating capacitance multiplier based on the use of dual output current conveyors and grounded capacitance is proposed. Its multiplication factor can be tuned by changing the ratio of resistors. Moreover, the circuit is easily modified to electronically tunable floating capacitance multiplier by using current controlled conveyor. Simulation results are obtained to show adequate agreement with theory. Keyword: current conveyor, capacitance multiplier
Prehistory of the SDR Studies in Japan - A Role of ARIB Study Group -

This paper reports the prehistory of software defined radio (SDR) studies in Japan. In 1999, a boom in the field of SDR started in Japan, and this year an ARIB study group completed its final report on SDR. SDR is a recently proposed technology concept and has attracted the attention of many communication engineering researchers. SDR will become one of the most important technologies in advanced communication, broadcasting and intelligent transportation systems on the 21st century. Although SDR has several attractive features, there are also many design issues to be solved. In this work we have examined these issues and discussed a new design methodology for wireless receivers in the SDR era. key words: software de ned radio, mobile communications, pro-
An enhanced QoS decomposition approach for efficient service composition

For each service class, there exist many alternative web services that provide the same functionality and different quality parameters, to find an optimal composition, most service selection approach in decentralized environment enumerate all possible combinations of service candidates. However, with the growing number of alternative services, those approaches will achieve a poor performance. To improve the performance, in this paper we proposed a QoS decomposition approach, that divide the global constraints into separate ones for each involved service class. With the separate constraints, each service class engages in service selection independently and simultaneously. Moreover, besides sequential pattern our approach also supports parallel pattern. Experimental results indicate that our approach performs efficiently and can achieve near-optimal solutions.
Buffer Design and Assignment for Structured ASIC

In modern VLSI design, interconnection delay dominates the circuit delay due to its heavy downstream capacitance. Buffer insertion is a widely used technique for splitting a long wire into several buffered wire segments for circuit performance improvement. In this paper, we investigate buffer insertion issues in structured ASIC design style. We design the layout for two dedicated buffers and extract the technology-dependent parameters for evaluation. Furthermore, we propose post-routing channel migration techniques, which employ intra-channel migration and inter-channel migration, to deal with the sub-channel saturation problem during buffer assignment. Compared to the baseline designs with 4X-buffer at the CLB output, our proposed structured ASIC design and optimization techniques improve the circuit performance by 65.7% and the ratio of wire delay to gate delay from 8.2 to 0.8.
The Etiology of Observed Negative Emotionality from 14 to 24 Months

We examined the magnitude of genetic and environmental influences on observed negative emotionality at age 14, 20, and 24 months. Participants were 403 same-sex twin pairs recruited from the Longitudinal Twin Study whose emotional responses to four different situations were coded by independent raters. Negative emotionality showed significant consistency across settings, and there was evidence of a latent underlying negative emotionality construct. Heritability decreased, and the magnitude of shared environmental influences increased, for the latent negative emotionality construct from age 14 to 24 months. There were significant correlations between negative emotionality assessed at age 14, 20, and 24 months, and results suggested common genetic and shared environmental influences affecting negative emotionality across age, and that age-specific influences are limited to non-shared environmental influences, which include measurement error.
Three New Supernova Remnant OH Masers Near the Galactic Center: Evidence for Large-Scale Maser Emission from Supernova Remnants

A survey of the inner 8°×1° of the Galactic plane toward the Galactic center has been carried out at the 1720 MHz transition of the OH molecule using the VLA in its D configuration with a resolution of ≈70′′×45′′. The detection of compact 1720 MHz OH masers associated with three supernova remnants G357.7+0.3, G1.13-0.1 (Sgr D), and G1.4-0.1 as well as new extended maser line emission from G357.7+0.3 and G357.7-0.1 (the Tornado Nebula) were then followed up by A-array observations with spectral and spatial resolutions of 0.3 km s-1 and ≈3′′×2′′, respectively. The 1720 MHz OH maser line emission is considered to be a powerful shock diagnostic and is collisionally pumped by H2 molecules at the site where C-type supernova shocks drive into adjacent molecular clouds. The new observations show clear evidence of extended features coincident with compact and bright masers, the best example of which is a coherent feature over a scale of about 20 pc surrounding the shell of the SNR G357.7+0.3. We argue that this remarkable feature is an OH maser and is physically associated with the remnant. This implies that the ambient molecular cloud is uniform in its density and temperature with a restricted range of pumping conditions and survives the passage of a large-scale shock front.
Evolutionary Functional Testing of a Vehicle Brake Assistant System

The safety of today’s vehicles is one of the major concerns of the automotive industry. Modern cars are equipped more and more with vehicle assistance functions in order to increase vehicle safety. Vehicle assistance functions are realised using electronic control units (ECUs), designed for the use in a vehicle. It is of critical importance that the ECUs used in vehicles operate properly. Thus, the high quality of the ECU’s software is an important requirement for a correct vehicle assistance function. Up to now, one of the most important measures to ensure software quality is extensive testing, but testing is time-consuming and costly. This is, because testing requires the deflnition and execution of test cases and the evaluation of the test results. Manual deflnition of test cases is di‐cult and time-consuming. Evolutionary testing has the potential to automate test case design. A test environment for an evolutionary functional test of a brake assistance function will be described in this work. First, the brake assistance function is described, which is subject to testing as application in a vehicle. Second, an introduction to evolutionary testing is given. Then, the theory and architecture for an evolutionary functional test of a brake assistance function is presented. The practical experiments which were carried out and the obtained results are shown. Finally, a conclusion is drawn and some prospects for possible future work are given.
Data-Driven Based Interactive Motion Blending

Motion blending is an important techonology of character animation, which produces new motion by combining two or more motion clips according to blending parameters. But previous methods can hardly generate the convincing motion in real time , and require too much manual intervention and preprocessing. In this paper, we introduce a new time synchronization algorithm, which represents data based on bone levels instead of joint levels, applying curve simplified algorithm to time synchronization of motion blending. Extracted time synchronization points are used for grading time synchronization of motion blending. After that, we do the motion blending by aligning coordinate, interpolation and recreating root joint. Finally we develop different kinds of motion blending generators, and design and perform visual editor for motion blending. It is convenient for users to adjust blending parameters on line and observe blending effects. Our method is efficient enough and simple for achieving good blending effects without complicated preprocessing.
Naïve Bayesian Based on Chi Square to Categorize Arabic Data

Text classification is a supervised technique that uses labelled training data to learn the classification system and then automatically classifies the remaining text using the learned system. This paper investigates Naive Bayesian algorithm based on Chi Square features selection method. The base of our comparisons are macro F1, macro recall and macro precision evaluation measures. The experimental results compared against different Arabic text categorization data sets provided evidence that feature selection often increases classification accuracy by removing rare terms.
Towards a closed-form solution of constraint networks for maximum likelihood mapping

Several recent algorithms address simultaneous localization and mapping as a maximum likelihood problem. According to such formulation map estimation is achieved by finding the configuration that minimizes the error function associated to the constraint network representing the map. Almost all the proposed algorithms exploit iterative fixed-point techniques. Less attention has been paid to the evaluation of the structure of the problem. In this paper, we derive the closed form solution for a constraint network of planar poses when the error function is given in a particular form. The derivation of the exact solution allows a better knowledge of the problem and a more detailed investigation of the performance of existing numerical techniques. The system of equations, that are satisfied by the solution, are computed and a general algorithm to solve such equations is provided.
Availability Evaluation of Quorum-Based Mutual Exclusion Schemes in General Topology Networks

The use of quorums is a well-known approach to achieving mutual exclusion in distributed environments. In this paper, we propose a new availability evaluation method for quorum-based mutual exclusion schemes in the presence of failures. Most of the previously proposed methods take neither the topology of systems nor link failures into consideration, and exhaustive state enumeration has been the only approach that can deal with them so far. By incorporating a notion called Minimal Quorum Spanning Trees, this method can efficiently evaluate the availability of quorum-based mutual exclusion schemes in general topology networks with unreliable nodes and links. Through experimental results, we show the superiority of the proposed method over exhaustive state enumeration.
XFOR: Filling the Gap between Automatic Loop Optimization and Peak Performance

We propose a new loop structure named "xfor", offering programmers explicit control of the interactions between statements inside a loop nest. An xfor simultaneously represents several for-loops and several statements, and maps their respective iteration domains onto each other according to two parameters, called "grain" and "offset". Grains and offsets basically "stretch" and "shift" iteration domains relative to an implicit, global referential domain. We show that such a programming structure allows to fill important optimization gaps remained by automatic loop optimizers. We highlight five important gaps filled by xfor which are: insufficient data locality optimization, excess of conditional branches in the generated code, too verbose code with too many machine instructions, data locality optimization resulting in processor stalls, and finally missed factorization opportunities. We describe programming strategies where xfor-loops help produce efficient code and exhibit a set of benchmark programs rewritten with xfor, with significant, and sometimes dramatic, execution time speed-ups.
Phase Response Curves Determine the Responses of Neurons to Transient Inputs

Neuronal firing is determined largely by incoming barrages of ex-citatory postsynaptic potentials (EPSPs), each of which produce a transient increase in firing probability. To measure the effects of weak transient inputs on firing probability of cortical neurons, we compute Phase-Response Curves (PRC). PRCs, whose shape can be related to the dynamics of spike generation, document the changes in timing of spikes caused by an EPSP in a repetitively firing neuron as a function of when it arrives in the interspike interval (ISI). The PRC can be exactly related to the post-stimulus time histogram (PSTH) so that knowledge of one uniquely determines the other. Typically, PRCs have zero values at the start and end of the ISI, where EPSPs have minimal effects and a peak in the middle. Where the peak occurs depends in part on the firing properties of neurons. The PRC can have regions of positivity and negativity corresponding respectively to speeding up and slowing down the time of the next spike. A simple canonical model for spike generation is introduced which shows how both the background firing rate and the degree of post-spike afterhyperpolar
An efficient scheme for multi-rate network coding in wireless mesh networks

Designing high throughput wireless mesh networks is a challenge . Network coding has been shown to substantially improve throughput.According to the WMNs characteristic we study a multi-rate linear network coding for minimum-cost in wireless mesh networks and propose an scheme for efficient implementation . The scheme is in multi-rate codes which the source and intermediate nodes perform linear coding operations that do not have to be changed if a different subgraph is used. It operate at the minimum possible cost subgraph for each of the values of the throughput that are achievable.
Existence of financial equilibria in a multi-period economy with restricted participation

We consider the model of a financial exchange economy with finitely many periods having financial restricted participation i.e., each agents portfolio choice is restricted to a closed convex set containing zero, as in siconolfi([3]). Time and uncertainty are represented by a finite event-tree D. There is a market for physical commodities at any state today or in any date of future and financial transfers across time and across states are allowed by means of finitely many financial assets(including nominal assets). We prove a general existence result of equilibria for such a financial exchange economy in which agents may have non-ordered preferences.
A LOW COMPLEXITY FEC SCHEME BASED ON THEINTERSECTION OF INTERLEAVED BLOCK

We describe a class of asymptotically good codes built from the intersection of randomly permuted binary BCH codes. This family of pseudo-random error correcting codes, called Generalized Low Density (GLD) codes, is a direct generalization of Gallager's Low Density Parity Check (LDPC) codes. GLD codes belong to the larger family of Tanner codes based on a random bipartite graph. We study the GLD ensemble performance and prove the asymptotically good property. We also compare GLD codes minimum distance and performance to the Varshamov-Gilbert bound and BSC capacity respectively. The results show that Maximum-Likelihood decoding of GLD codes achieves near capacity eeciency. The sub-optimal iterative decoding of GLD codes is brieey presented. Experimental results of small and large blocklength codes are nally illustrated on both AWGN and Rayleigh fading channels.
A study of designing recursive 2-D digital filter from an analog bridged-T network

This paper proposes a new technique of designing 2-D recursive digital filters starting from a doubly-terminated analog bridged- T network. This network contains inductive and capacitive reactance elements in s1 and s2 domains. The different possibilities are examined . When compared with the fourth order Butterworth polynomial, only three possibilities exist and the corresponding impedances are obtained. Starting with such an analog bridged-T network, 2-D filters are obtained through the application of double generalized bilinear transformations with the coefficients in the specified ranges to ensure stability. Different filter outputs can be obtained, depending on the starting network and the coefficients of the generalized bilinear transformations
Stereotactic Aspiration versus Craniotomy for Primary Intracerebral Hemorrhage: A Meta-Analysis of Randomized Controlled Trials

Background A wealth of evidence based on the randomized controlled trials (RCTs) has indicated that surgery may be a better choice in the management of primary intracerebral hemorrhage (ICH) compared to conservative treatment. However, there is considerable controversy over selecting appropriate surgical procedures for ICH. Thus, this meta-analysis was performed to assess the effects of stereotactic aspiration compared to craniotomy in patients with ICH. Methods According to the study strategy, we searched PUBMED, EMBASE and Cochrane Central Register of Controlled Trials. Other sources such as the internet-based clinical trial registries, relevant journals and the lists of references were also searched. After literature searching, two investigators independently performed literature screening, assessment of quality of the included trials and data extraction. The outcome measures included death or dependence, total risk of complication, and the risk of rebleeding, gastrointestinal hemorrhage and systematic infection. Results Four RCTs with 2996 participants were included. The quality of the included trials was acceptable. Stereotactic aspiration significantly decreased the odds of death or dependence at the final follow-up (odds ratio (OR): 0.80, 95% confidence interval (CI): 0.69–0.93; P = 0.004) and the risk of intracerebral rebleeding (OR: 0.44, 95% CI: 0.26–0.74; P = 0.002) compared to craniotomy with no significant heterogeneity among the study results. Conclusions The present meta-analysis provides evidence that the stereotactic aspiration may be associated with a reduction in the odds of being dead or dependent in primary ICH, which should be interpreted with caution. Further trials are needed to identify those patients most likely to benefit from the stereotactic aspiration.
Towards Road Traffic Management with Forecasting on Wall Displays

Road traffic control centers are of vital importance to modern cities. Interviews with controllers in two such centers identified the need to incorporate the visualization of results from predictive traffic models with real traffic, to help operators choose among different interventions on the network. We explore this idea in a prototype that runs on a wall display, and supports direct touch and input from workstations and mobile devices. Apart from basic functionality to manage the current traffic such as changing traffic light duration or speed limits, the prototype incorporates traffic simulations for forecasting results of possible actions, highlighting their differences to current traffic. Based on needs identified in our interviews, we offer two techniques that visually combine simulated and real situations, taking advantage of the large display space: multiple independent views and DragMagic, a variation of magic lenses. A preliminary laboratory experiment suggests that both techniques are viable design options, even for monitoring several simulations and areas of interest, contrary to expectations from previous work. However DragMagics are easier to master.
Neural Networks and Fuzzy Logic for improving Facies recognition from well log data

Offshore oil exploitation is a high-risk expensive activity, potentially leading to high payoffs. Generally, many different analyses are employed to diminish the risks of perforating a dry well or letting escape a productive one. One of the analyses involves determining rock lithofacies in specific points. Well testimonial material are extracted and sent to lab interpretation. Well log data represents indicators of oil existence. The geologists' task is to analyze well log data and define facies from these indirect measurements. Statistical methods, such as discriminant analysis, have been used with unsatisfactory results. We developed a system, nFac, which addresses this interpretation problem combining a variety of AI techniques. The tool has been successfully deployed in 2001 and used to analyze either national or international reservoirs. This paper discusses the application that uses a combination of AI tools to improve human intuition when analyzing the potential of oil fields.
Detecting Abnormality in Activities Performed by People with Dementia in a Smart Environment

Recognition of abnormalities in the activities performed by users in smart environments has applications in many such fields as surveillance and medical care for differently abled and elderly persons. There are many causes for abnormality in user activities. Missing out some events of an activity, not maintaining the proper order of events and occurrence of irrelevant events are the major causes for abnormality in activities performed by persons with early stages of dementia. In this paper a simple and novel method for identifying missed out events, out of order events and irrelevant events is proposed. The method can be used for measuring how well an activity is performed by the user and for offering corrective suggestions. One of the possible applications of this method is enabling elderly people to lead an independent life. The proposed method was tested using a publicly available test data after introducing abnormalities manually, and is found to produce promising results.