Miracle-dz/UniFAR-FTUs huggingface dataset:
Reactions Catalyzed by Bacterial Cytochromes P450

The cytochromes P450 are a large family of oxidative haemoproteins that are responsible for a wide variety of oxidative transformations in a variety of organisms. This review focuses upon the reactions catalyzed specifically by bacterial enzymes, which includes aliphatic hydroxylation, alkene epoxidation, aromatic hydroxylation, oxidative phenolic coupling, heteroatom oxidation and dealkylation, and multiple oxidations including C-C bond cleavage. The potential for the practical application of the oxidizing power of these enzymes is briefly discussed.
Connected Key Node Set-Based Skyline Query Processing over Wireless Sensor Networks ∗

(2. Zhejiang Fashion Institute of Technology, Ningbo 315021, China) Abstract — Skyline query has been applied widely in sensor networks. We propose a connected key node set- based skyline Efficient skyline query processing (EffiSky) algorithm to minimize communication traffic for resources- limited sensor networks. In the EffiSky algorithm, we dis- cover a Connected key node set (CKNS) used to trans- mit and collect queries and results among the sensor nodes, which can reduce the average communication cost of the networks significantly. We set up a two-level fil- tering scheme that prunes many useless dominated tu- ples. Both the theoretical analysis and experiment results demonstrate that EffiSky excels the existing work in terms of network traffic, scalability in network expansion, node density, and dimension change.
LIESHOU : A Mandarin Conversational Task Agent for the Galaxy-II Architecture

Multilinguality is an important component of spoken dialogue systems, both because it makes the systems available to a wider audience and because it leads to a more flexible system dialogue strategy. This thesis concerns the development of a Chinese language capability for the ORION system, which is one of many spoken dialogue systems available within the GALAXY-II architecture. This new system, which we call LIESHOU, interacts with Mandarin-speaking users and performs off-line tasks, initiating later contact with a user at a pre-negotiated time. The development and design of LIESHOU closely followed the design of similar multilingual GALAXY-II domains, such as MUXING (Chinese JUPITER), and PHRASEBOOK (Translation Guide for Foreign Travelers). The successful deployment of LIESHOU required the design and implementation of four main components speech recognition, natural language understanding, language generation, and speech synthesis. These four components were implemented using the SUMMIT speech recognition system, TINA Natural Language understanding system, GENESIS-II language generation system, and ENVOICE speech synthesis system respectively. The development of the necessary resources for each of these components is described in detail, and a system evaluation is given for the final implementation. Thesis Supervisor: Stephanie Seneff Title: Principal Research Scientist
Anticipatory Versus Traditional Genetic Algorithm

This paper evaluates the performances of a new type of genetic algorithms - anticipatory genetic algorithms (AGA) versus traditional genetic algorithms (GA). The performances are evaluated based on two simple problems using different genetic operators. The evaluation included in the paper shows that AGA is superior to traditional genetic algorithm from both speed and accuracy points of view. Then we evaluate the two types of genetic algorithms for solving the problem of image annotation, which will be used in content based image retrieval systems. In this case the AGA performances are superior to GA, too.
GESTURE RECOGNITION USING THE LINEAR COMBINATION OF MEMBERSHIP DEGREES OF OBSERVATIONS

This paper introduces a novel gesture recognition method. In the method, hand trajectory is represented by the sequence of symbols and each symbol has a specific membership degree obtained from the genetic algorithm training. In order to determine the membership degree of input observations sequence in a class, the system uses the linear combination of membership degrees of observations in sequence. Because of using negative and positive samples for training gesture classes in the proposed method, the recognition system has a good performance in distinguishing very similar gestures. Experiments show that the method developed in this study outperforms HMM and SOMM methods in different gesture datasets.
Bayesian modeling of manner and path psychological data

How people and computers can learn the meaning of words has long been a key question for both AI and cognitive science. It is hypothesized that a person acquires a bias to favor the characteristics of their native language, in order to aid word learning. Other hypothesized aids are syntactic bootstrapping, in which the learner assumes that the meaning of a novel word is similar to that of other words used in a similar syntax, and its complement, semantic bootstrapping, in which the learner assumes that the syntax of a novel word is similar to that of other words used in similar situations. How these components work together is key to understanding word learning. Using cognitive psychology and computer science as a platform, this thesis attempts to tackle these questions using the classic example of manner and path verb bias. A series of cognitive psychology experiments was designed to gather information on this bias. Considerable flexibility of the subject’s bias was demonstrated during these experiments. Another separate series of experiments was conducted using different syntactic frames for the novel verbs to address the question of bootstrapping. The resulting information was used to design a Bayesian model which successfully predicts the human behavior in the psychological experiments that were conducted. Dynamic parameters were required to account for subjects revising their expected manner and path verb distributions during the course of an experiment. Bayesian model parameters that were optimized for rich syntactic frame data performed equally well in predicting poor syntactic frame data. Thesis Supervisor: Robert C. Berwick Title: Professor of Computer Science and Engineering, and Computational Linguistics
Relationship between back pain and personality Psychologic vulnerability as risk factor for the development of chronic back pain

One hundred and forty-five acute back-pain patients were tested for the presence of personality traits connected with psychologic vulnerability, traits often found among chronic back-pain patients. All patients in the experimental group and the healthy individuals in the control group were tested with the Patient Pain Drawing test (PPD) and with the Minnesota Multiphasic Personality Inventory (MMPI) on the scales hypochondriasis (Hs), depression (D), and hysteria (Hy). The patient group differed significantly from the control group on average Hs, D, and Hy scores and on the quantified PPD (measuring somatization pro-neness). The patients with the highest PPD scores had the highest values on MMPI (Hs, D, Hy), and the patients with low scores on the PPD-indicating low tendency to somatize -had MMPI values that did not differ significantly from those of the healthy controls. The study indicates that personality may influence the individual's tendency to somatize and express psychic and psychosocial problems .
Theoretical Analysis of the Torsion-Induced Optical Effect in a Plastic Optical Fiber

Abstract We have analyzed the optical effects induced by a torsion stress in a plastic optical fiber (POF). As a result of the torsion, the POF becomes biaxial and inhomogeneous. The new principal axes of the optical indicatrix and the new indices of refraction referred to them depend on the torsion strength, on the fiber transverse coordinates, and on the difference between the two components of the stress-optical tensor [ q ]. The changes in the indices of refraction are expected to be slightly smaller than those provoked by tensile or bending stresses.
Acquisition of very high resolution images using stereo cameras

Abstract 'The 1llethO(1 of iniage acquisil ion is one ol 1 lie 1)1inciPal P101)1e111S loi ii all(lliUg veiv high resolution iniages. 1his h)iI)e1 h)I(sents a iie sclieiiie for acquii'iiig high ieo1iitioii J)ctu1€1 by J)t'OCCSSi ug stereo i inages . Th ie ii el hod I ii t egia 1 es low resolu tioli I iliages i ii 0 a h ii gh resolution iniage. Analysis of the achievable passh)ali (1 is given froiu a 1)ouit of view of the ililager1)hotodetectol structure. Coiii1ited to an liltaging (levice vit ii e(jllivalent resolution . it may be less sensi tive to shot noise which becoiiies more donui naut as I he p xel size of an i inager is further Ie(1 LiCe(I . Prehimni itamy exl)eri iiieiit S lEaVe slio\v1I clear illlh)1OVelliellt iii the high frequencies an(h image (het ails. in addi I ion. a s(hielne for Iii I! h'i in cleasi mg t le tesol u tion ismention e(l. 1 Background & Motivation In recent yeais, mescaiclicis in tlie a(hvance(l televisioii svstcimi area have co1ic(1mt 1ate(l on high (lefilu-tion television (
Demo I Microsoft Surface and the Single View Platform

Microsoft Surface is a revolutionary surface-computing platform that provides a true multi-user collaboration experience. Information Strategies will demonstrate how Microsoft Surface can bring business applications and data together with Virtual Earth on the Microsoft Single View Platform. Microsoft Surface turns an ordinary tabletop into a vibrant, interactive surface. It's the first commercially-available surface computing platform from Microsoft. The product provides effortless access to digital content through natural gestures, touch and physical objects. Today, Microsoft Surface is a 30-inch diagonal display in a table-like form factor that's easy for individuals or multiple people to interact with in a way that feels familiar, just like in the real world. It features four key attributes: • Direct Interaction: Users can actually “grab” digital information with their hands - interacting with content by touch and gesture, without the use of a mouse or keyboard. • Multi-Touch: Surface computing recognizes many points of contact simultaneously, not just from one finger like with a typical touch-screen, but up to dozens of items at once. • Multi-User: The horizontal form factor makes it easy for several people to gather around Microsoft Surface together, providing a collaborative, face-to-face computing experience. • Object Recognition: Users can place physical objects on the display to trigger different types of digital responses; in the future, this will include the ability to transfer digital content.
Pronunciation modeling for conversational speech recognition

Conversational speech exhibits considerable pronunciation variability, which has been shown to have a detrimental effect on the accuracy of automatic speech recognition. For this reason, pronunciation modeling has received considerable attention in recent automatic speech recognition literature. Most of the attention however has focussed on describing an alternate pronunciation as a different sequence of phonetic units using the same inventory of phones which describe canonical pronunciations. Use of such pronunciation models during recognition is known to yield moderate improvements in recognition accuracy. In this dissertation we present new pronunciation modeling techniques developed to accommodate the high degree of pronunciation variability encountered in conversational speech with significant gain in recognition performance. Analysis of manual phonetic transcription of conversational speech reveals a large number (>20%) of instances where human labelers disagree on the identity of the surface form. We present acoustic evidence that offers an explanation: when a pronunciation deviates from its canonical form, it is often the case that neither the canonical nor the alternate phone represent the acoustics very well. The actual pronunciations lie on a continuum between these two extremes. Based on this analysis, two methods for accommodating pronunciation variation are developed. The first method attempts to solve the problem by separately modeling each baseform/surface-form pair. The second method accommodates the nonstandard pronunciations in a novel manner. Rather than allowing a phoneme in the canonical pronunciation to be realized as one of a few distinct alternate phones, the Hidden Markov Model (HMM) states of the phoneme's model are instead allowed to share Gaussian mixture components with the HMM states of the model(s) of the alternate realization(s). This dissertation provides a fundamental and quantitative insight into pronunciation variability in spontaneous speech and demonstrates techniques for accommodating this variability within the framework of traditional automatic speech recognition systems that assume temporally non-overlapping phonetic segments.
Give-to-Get: free-riding resilient video-on-demand in P2P systems

Centralised solutions for Video-on-Demand (VoD) services, which stream pre-recorded video content to multiple clients who start watching at the moments of their own choosing, are not scalable because of the high bandwidth requirements of the central video servers. Peer-to-peer (P2P) techniques which let the clients distribute the video content among themselves, can be used to alleviate this problem. However, such techniques may introduce the problem of free-riding, with some peers in the P2P network not forwarding the video content to others if there is no incentive to do so. When the P2P network contains too many free-riders, an increasing number of the well-behaving peers may not achieve high enough download speeds to maintain an acceptable service. In this paper we propose Give-to-Get, a P2P VoD algorithm which discourages free-riding by letting peers favour uploading to other peers who have proven to be good uploaders. As a consequence, free-riders are only tolerated as long as there is spare capacity in the system. Our simulations show that even if 20% of the peers are free-riders, Give-to-Get continues to provide good performance to the well-behaving peers. In particular, they show that Give-to-Get performs very well for short videos, which dominate the current VoD traffic on the Internet.
Enertex : un système basé sur l’énergie textuelle

Dans cet article, nous présentons des applications du système Enertex au Traitement Automatique de la Langue Naturelle. Enertex est basé sur l’énergie textuelle, une approche par réseaux de neurones inspirée de la physique statistique des systèmes magnétiques. Nous avons appliqué cette approche aux problèmes du résumé automatique multi-documents et de la détection de frontières thématiques. Les résultats, en trois langues : anglais, espagnol et français, sont très encourageants.
Multiscale Statistical Models for Hierarchical Spatial Aggregation

Scale dependency is an inherent property of geographic phenomena since most geographic patterns under observation vary with scale. Across numerous disciplines, including geography, various types of so-called “multiscale” models have been used for the task of modeling and understanding the effects of scale. However, most of these models are descriptive—as opposed to inferential—in nature, and few of them (particularly outside geography) are well adapted to the wide variety of data structures typically encountered in geography. In this paper, we introduce a new, general framework for multiscale statistical modeling and inference that is explicitly designed for a broad class of geographic data. The key structural assumption underlying these models is that of a set of hierarchically defined partitions, corresponding to successive aggregations of an initial data space. Within our framework the effects of scale associated with such aggregation are captured through a fundamental decomposition of the data likelihood, directly induced by the hierarchical nature of the partitions, into individual components of local information at all possible spatial resolutions. Upon combining these multiscale likelihoods with an appropriately defined Bayesian prior probability structure, a powerful inferential framework results. We describe in detail how this framework may be used for the tasks of statistical estimation and classification, and illustrate its usage with an analysis of data from census geography.
DYNAMICAL FUNCTIONAL ARTIFICIAL NEURAL NETWORKS (D-FANNS) FOR INTELLIGENT SIGNAL PROCESSING (INVITED PAPER)

For the sake of clarity and precision, intelligent signal processing will be defined as the process of mapping a signal x into a binary vector y, so that y enables the detection, classification, or interpretation of an event present in x. We denote by f the input-output map of such an intelligent signal processing filter. In a number of applications it is possible to implement the nonlinear filter map f by an artificial neural network(ANN). In the present paper we consider the case in which the signal x is an analog signal (waveform) belonging to L2(1), where I is an appropriate interval of the real line R1, and propose the realization of f by an artificial neural network in which the synaptic weight actions of the first layer are implemented by a filter bank. We call such a network a dynamical functional artificial neural network (D-FA") to distinguish it from a conventional functional artificial neural network (FANN), where a synaptic weight action is implemented by a scalar product in L2(1), between the incoming waveform x and a functional weight. Thus, compared with conventional FANNs, D-FANNs permit simple and meaningful causal realizations of intelligent analog signal processors. A novel element is the introduction of a D-FANN gain equation, in a way analogous to that in Kalman Filtering. Applications of DFANNs to real and simulated data are now in progress and these results will be presented at the symposium (ISCAS-98).
A micro-simulation model system of individuals' daily activity behavior that incorporates spatial, temporal and coupling constraints

軟 にすることで通勤 混 雑 の緩 和を図るフレックスタイム制,あ るいは,週 休 二 日制 等 の各 個 人 の交 通需 要 をマネ ージメン トす ることで交通 混 雑 の緩 和 を図る方 策 が必 要 となってきて いる. こういった交通 需 要のマネー ジメントを実現 化す るため には,各 個 人の交 通 需要 の発 生構 造 を的 確 に把握 し,交 通 需 要 と,交 通 需要 に影 響 を及 ぼす 種 々の 要 因との 関係 を的 確 に把 握 することが極 めて重 要な課 題 であるものと考 えられ る. 個 人 の交 通行 動 は,そ の個 人が 実行 す る生活 行 動 と独 立 に実行 され るもの とは 考えがたい. す な わち,交 通 需 要 は, 生活 行 動 の派 生 的な 需要 であるものと捉 えることがで きるも のと思 わ れる. こ の 点 に着 目した交 通 需 要 解 析 のアプ ロー チ が,ア クティビティ分 析 である1). アクティビティ分 析 の アプ ロー チ に基 づ いた生 活 行 動 ・交 通行 動 モデル として,多 くのものが提案 されている. 個 人の ト リップチ ェインをマルコフ過 程 とみなし,そ の 上で各 トリップ間 の活 動時 間 を考慮 したモデ ルがKitamura and Lam2)に よっ て提案 され てい る. また,Robinsonら3),瀬 戸 ら4),藤井 ら5)は, 一 日を通 じての活 動 時 間や トリップ 数 等 の交 通 行 動 ,生 活 行 動の指 標 と,個 人属 性 や 交通環 境 との因果 関係 を構 造方 程 式 の枠 組 みでモ デル化 している. 離 散 選択 モデ ルの枠 組 み で交 通 行 動パ ター ン,生 活 行動 パ ター ンをモデル 化 した 例 としては,藤 井 ら6)7),Adler and Ben-Akiva8),河 上 ら9)の研 究が 挙 げられ る. さ らに,活 動 の実 行 を時 間資 源 の配 分 問 題 として捉 えた行動 モデ ル は,Supernak10),Kitamuraら11)が 提案 している. これ らの モデル は,い ずれ も,個 人 の 生活 行 動パ ター ンを 予 測す ることで,そ の 個 人 の生活 行 動 の 一 部である交 通 行 動 を把 握 す ることを目指 しているものである. こういった生 活行 動 モデル の開発 を図る流 れの 中で,近 年, マイクロシミュレーションの 枠組 みで,時 間軸 上 で の個 人 の 生 活行 動 の 再現 を図 る研 究も行 われ てきている. 種 々の 交 通 需 要マネ ージメント政 策 の実 施 に伴 う個 人 の生 活 行 動 の 変化 を予 測 することを目的として開発 され たAMOS12)が その 例 として挙 げられ る. ま た,観 光 地での個 人 の周遊 交 通 行動 の再 現 を図 る森 川 らの モデ ル13)なども,時 間 軸 上 での観 光
Array Processing Techniques for Broadband Acoustic Beamforming

Audio acquisition and recording can benefit from directional reception of the acoustic signals. Current acoustic designs of highly-directional microphones are bandwidth limited and physically large. A microphone array used in conjunction with a beamforming algorithm can acquire and spatially filter the signal, but traditionally this has suffered from limitations similar to those of the purely acoustic designs. The work presented in this paper attempts to overcome these limitations by producing and analyzing three atypical techniques for broadband beamforming. The last and most successful technique employs an algorithm which calculates the difference in group delay of the acquired signals and uses that information to determine the direction of the incoming signals as a function of frequency.
Interrelationships of Physical and Chemical Properties of Kaolinites

Rank-correlation coefficients are utilized to show relationships between physical and chemical properties of Georgia and English kaolins. Montmorillonite impurity in the Cretaceous kaolins shows high level correlations with magnesium, iron, silica-alumina ratio, CEC, water sorption, surface area, sediment volume, and Brookfield viscosity. Cation exchange capacity of these kaolins is believed to be related primarily to montmorillonite impurity. Low shear viscosity measurements show a strong correlation to properties indicative of montmorillonite. Correlations with viscosity are believed to be related primarily to surface area and particle packing. Packing volume exerts a dominant effect on high shear rheology. Differences in particle shape are not of sufficient magnitude to show a significant effect on rheology. A strong inverse relationship of vanadium with high shear viscosity indicates that the wetting effect of vanadium organic complexes or adsorption of (VO4)−3 tetrahedra at gibbsite edge faces may be mechanisms for viscosity reduction. Brightness and whiteness are related to titanium and iron-bearing impurities as well as the amount of particles having optimum diameters for light scattering. Well-crystallized kaolinites are believed to have been derived primarily from feldspar. Muscovite alteration may be retarded where well-crystallized kaolinites occur. To account for the inverse relation of vanadium with crystallinity, it is suggested that complex vanadium ions may act as growth poisons.
Job Scheduling in Cloud Environment based on Shuffled Frog Leaping Algorithm

In this research, an optimized cloud task scheduling algorithm based on shuffled frog leaping algorithm (SFLA) is proposed. The classic methods of scheduling tasks in operating systems and cloud environment are FCFS, SJF, RR, etc. but researchers consider the scheduling algorithms as an optimization problem to achieve better and stable results. In this work, the proposed method is implemented by CloudSim and compared to FCFS and ACO algorithms to prove the high performance and efficiency. The results show that our algorithm is running in lower time and make span in comparison with FCFS as a classic algorithm and ACO as an optimization problem .
Learning Latent Semantic Models for Music from Social Tags

Abstract In this paper we describe how to build a variety of information retrieval models for music collections based on social tags. We discuss the particular nature of social tags for music and apply latent semantic dimension reduction methods to co-occurrence counts of words in tags given to individual tracks. We evaluate the performance of various latent semantic models in relation to both previous work and a simple full-rank vector space model based on tags. We investigate the extent to which our low-dimensional semantic spaces respect traditional catalogue organization by artist and genre, and how well they generalize to unseen tracks, and we illustrate some of the concepts expressed by the learned dimensions.