Miracle-dz/UniFAR-FTUs huggingface dataset:
Fluorescent Labeling Reagents. Part 1. 3-(4-(Bromomethyl)phenyl) -7-(diethylamino)-2H-1-benzopyran-2-one (MPAC-Br): A Highly Sensitive Fluorescent Derivatization Reagent for Carboxylic Acids in High-Performance Liquid Chromatography.

7-Dimethylaminocoumarin derivatives were synthesized and the characteristics of their absorption and emission spectra were investigated. Among them, 3-aryl-7-dimethylaminocoumarins were shown to be promising candidates as the fluorogenic groups for highly sensitive derivatization reagents. Based on the spectroscopic studies, 3-[4-(bromomethyl)phenyl]-7-(diethylamino)-2H-1-benzopyran-2-one (MPAC-Br) was designed and synthesized as a fluorescent derivatization reagent for carboxylic acids in HPLC. Saturated carboxylic acids (C4-C18) were derivatized almost quantitatively into the corresponding fluorescent MPAC-esters by treatment with MPTAC-Br. The MPAC-esters of these acids were clearly separated on a reversed-phase HPLC column (Intertsil ODS-2, mobile phase : methanol-water, excitation wavelength 403 nm; emission wavelength 474 nm). The detection limit (S/N=17) of lauric acid, as a test compound, was 15 fmol/10 μl.
Hybrid Simulated Annealing and Case-Based Reasoning Approach for Computationally Intensive Transportation Problems: Rationale and Design Issues

A hybrid artificial intelligence approach based on combining simulated annealing (SA) and case-based reasoning (CBR) is presented. The approach is designed to allow for solving complex, time-critical optimization problems, examples of which lie at the heart of several intelligent transportation systems applications. According to this hybrid approach, the system, when faced with a new problem, first accesses the case base and attempts to locate a sufficiently similar case. If such a case can be located, the solution of the CBR-retrieved case is directly reused. If not, the SA algorithm is used to solve the problem, with the solution of the CBR-retrieved case serving as a starting point for the search algorithm. The rationale behind the approach is discussed, and its major design issues are analyzed. A case study is then presented to illustrate how the approach could be designed and to demonstrate its advantages. Results indicate that combining SA and CBR offers an efficient approach to solving complex, time-critical optimization problems. The results also indicate that SA, used in conjunction with CBR, should be started from a very low temperature to take advantage of the fact that the CBR-retrieved solution is close to the optimum.
A graphics API for learning data structures and algorithms

Generation Z are the next generation of college students. These students have demanded new teaching practices. The use of visual resources for learning and the anxiety for immediate results are one of their demands. This paper discusses a strategy for teaching and learning data structures supported by the DSGraph library. This strategy has been used in Federal University of Juiz de Fora in order to adapt the teaching of abstract concepts such data structures and its algorithms for the new generation of students. The library aims, through visual representation, the elucidation of the concepts covered during the course of data structures, combined with active student participation in the construction and development of its solutions. An experimental study was carried out for two years with two groups of students. The first group was submitted to the proposed methodology and other group was submitted to the traditional methodology. The results show that the methodology proposed reaches satisfactory improvement of the approval rate and the students’ satisfaction.
Cross Layer Design Energy Efficient Protocol Integrating with MAC and Routing

This paper proposes an enhanced AIMRP protocol——E-AIMRP.Designing for the event detecting and quick reporting applications,it integrates MAC and routing with cross layer mechanisms,solves the problems in AIMRP of low energy efficient resulting from the multi-node event detecting and reports,and enhances the topology of single node detecting model.Simulation results show that E-AIMRP outperforms AIMRP for energy efficiency and time delay in the event-detection applications.
Retrieving Non-Latin Information in a Latin Web: The Case of Greek

Over 60% of the online population are non-English speakers and it is probable the number of non-English speakers is growing faster than English speakers. Most search engines were originally engineered for English. They do not take full account of inflectional semantics nor, for example, diacritics or the use of capitals. The main conclusion from the literature is that searching using non-English and non-Latin based queries results in lower success and requires additional user effort so as to achieve acceptable recall and precision. In this chapter a Greek query log is morphologically and grammatically analyzed and a number of queries are submitted to search engines and their relevance is evaluated with the aid of real users. A Greek meta-searcher redirecting normalized queries to Google.gr is also presented and evaluated. An increase in relevance is reported when stopwords are eliminated and queries are normalized based on their morphology.
Zastosowanie metody chan-vese w segmentacji obrazów medycznych

The article presents the problem of determining the edges of objects enclosed in a medical CT images, which will be subject to further analysis, for the purpose of medical diagnosis. The use of a transformation which introduces two-point thresholding, eliminates presenting pixels of objects for tissues that are not a subject to further analysis. This approach allowed us to sharpen the edges of objects presenting soft tissue. A way to detect the edge of the soft tissue was compared for the original image and processed one using the transformation using the method of Chan-Vese. Sharpening of edges of the image have improved the accuracy of detection of objects presenting the soft tissue.
Image classification and retrieval based on correlation

An efficient method which based on the image classification is being used to the image retrieval . The cross correlation among the images is being used as the distance to cluster ,and the central image of per classification is found . The image retrieval method consists of two phases : (1) finding the central image which has the best matching in all the central images (2) finding the perfect matching image from the classification which has the central image . The image classification and the finding for the central image are the off-line works , so they accelerate the image retrieval . And the information entropy is also being used to prove the validity of the image classification . The experiment indicates that the method has advantage over other methods .
X 15 Extending The Frontiers Of Flight

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Efficient Online Scheduling for Deadline-Sensitive Batch Computing

We consider mechanisms for online deadline-aware scheduling in large computing clusters. Batch jobs that run on such clusters often require guarantees on their completion time (i.e., deadlines). However, most existing scheduling systems implement fair-share resource allocation between users, an approach that ignores heterogeneity in job requirements and may cause deadlines to be missed. In our framework, jobs arrive dynamically and are characterized by their value and total resource demand (or estimation thereof), along with their reported deadlines. The scheduler’s objective is to maximize the aggregate value of jobs completed by their deadlines. We circumvent known lower bounds for this problem by assuming that the input has slack, meaning that any job could be delayed and still finish by its deadline. Under the slackness assumption, we design a preemptive scheduler with a constant-factor worst-case performance guarantee. Along the way, we pay close attention to practical aspects, such as runtime efficiency, data locality and demand uncertainty. We evaluate the algorithm via simulations over real job traces taken from a large production cluster, and show that its actual performance is significantly better than other heuristics used in practice. We then extend our framework to handle provider commitments: the requirement that jobs admitted to service must be executed until completion. We prove that no algorithm can obtain worst-case guarantees when enforcing the commitment decision to the job arrival time. Nevertheless, we design efficient heuristics that commit on job admission, in the spirit of our basic algorithm. We show empirically that these heuristics perform just as well as (or better than) the original algorithm. Finally, we discuss how our scheduling framework can be used to design truthful scheduling mechanisms, motivated by applications to commercial public cloud offerings.
An Intuitionistic Fuzzy Bidirectional Projection–Based Approach for Patent Pool Partner Selection

The patent pool partner selection is an important multi-attribute decision-making (MADM) problem, and especially that based on intuitionistic fuzzy (IF) is becoming an extremely active research field. The aim of this article is to present a new method for patent pool partner selection with no weight information in IF based on bidirectional projection (BP). In the proposed model, we substitute BP for traditional one-way projection, and develop a new ranking alternatives rule on the basis of close degree; we construct a non-linear programming model combing the BP with intuitionistic fuzzy entropy (IFE) to determine the attribute weights, and obtain the optimum alternative; an example analysis is given to illustrate the rationality and scientificity of the proposed method; Finally, we conclude with recommendations for future work.
Semi-Supervised Learning Using Semi-Definite Programming

We discuss the problem of support vector machine (SVM) transduction, which is a combinatorial problem with exponential computational complexity in the number of unlabeled samples. Different approaches to such combinatorial problems exist, among which are exact integer programming approaches (only feasible for very small sample sizes, e.g. [1]) and local search heuristics starting from a suitably chosen start value such as the approach explained in Chapter 5, Transductive Support Vector Machines , and introduced in [2] (scalable to large problem sizes, but sensitive to local optima). In this chapter, we discuss an alternative approach introduced in [3], which is based on a convex relaxation of the optimization problem associated to support vector machine transduction. The result is a semi-definite programming (SDP) problem which can be optimized in polynomial time, the solution of which is an approximation of the optimal labeling as well as a bound on the true optimum of the original transduction objective function. To further decrease the computational complexity, we propose an approximation that allows to solve transduction problems of up to 1000 unlabeled samples. Lastly, we extend the formulation to more general settings of semi-supervised learning, where equivalence and inequivalence constraints are given on labels of some of the samples.
Dynamic motion analysis of gesture interaction

In human communication, nonverbal information such as gestures and facial expressions often plays a greater role than language, and an increasing number of devices are designed to be intuitively controlled by gestures. However, there are some disadvantages of this intuitive interaction. One of the chief problems is that these devices have difficulty in distinguishing between unconscious and intentional gestures; they tend to respond erroneously to unconscious movements. In this chapter, authors propose a new gesture analysis method based on the dynamic model. They focused on the “exaggerated gestures” that are effectively used in, such as Japanese Kabuki, effectively used in Disney’s animation, and tried to identify their common features and effects. They noted the “preparation” or “follow-through” motions just before and after the emphasized actions and each behavior can be quantified by the undershoot and overshoot value of changes in torque. These methods can provide important knowledge for analyzing features and distinguishing intentions when interacting with gestures.
Collecting Qualitative Data: A Practical Guide to Textual, Media and Virtual Techniques

Is there more to qualitative data collection than (face-to-face) interviews? This book answers with a resounding yes, and introduces the reader to a range of exciting, often novel, techniques for collecting qualitative data in the social and health sciences. Collecting qualitative data provides a practical and accessible introduction to everything from gathering blog data to asking participants to write stories in response to a researcher-designed story ‘cue’; the story completion method. The book is divided into three sections – textual, media and virtual – and provides stepwise guidance on methods that are under-utilised within qualitative research, or that offer new and interesting angles to qualitative researchers. Contributors from a wide range of disciplines share their experiences of implementing a particular technique and highlight both its potentials and pitfalls. What unites all the methods featured in this book is that they are ideally suited to student projects and other time- and resource-limited research. The book is written both for readers new to qualitative research and for established researchers seeking to broaden their methodological repertoire or seeking inspiration to get out of an interviewing treadmill!
Maths In Minutes 200 Key Concepts Explained In An Instant

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Characteristics, Formation Mechanisms and Potential Transport Pathways of PM2.5 at a Rural Background Site in Chongqing, Southwest China

Daily PM2.5 samples were collected at a rural background station (JinYun) located in Chongqing across four consecutive seasons from October 2014 to July 2015. The major water-soluble inorganic ions (WSIIs), organic carbon (OC) and elemental carbon (EC) were analyzed, and their chemical characteristics, transport pathways and potential source regions were investigated. The average annual PM2.5 concentration was 56.2 ± 31.0 µg m–3, of which secondary inorganic aerosol (SNA) and carbonaceous aerosols composed 41.0% and 29.4%, respectively. Higher concentrations of and contributions from SO42–, which were likely caused by the secondary transformation of SO2 into SO42–, were observed in summer than in autumn and spring. Additionally, transportation from the urban area of Chongqing (Yubei) played an important role in elevating the SO42– during this season. Although the accumulation of PM2.5 during pollution episodes in winter was also due to aqueous-phase reactions, based on the entire year, NO3– formation may have been primarily driven by homogeneous gas-phase reactions. Furthermore, the aerosol environment was ammonium-rich, and NH4+ formation promoted the production of NO3– at lower temperatures. The carbonaceous component, which consisted of 81.0–84.6% OC, exhibited higher concentrations in winter than in the other seasons; 50.0–77.2% of the total OC, in turn, was contributed by primary organic carbon (POC). Potential source contribution function (PSCF) analysis suggests that the site was mainly affected by regional pollution originating in the southwestern and northern areas of Chongqing.
Intermediate Cantonese A Grammar And Workbook

intermediate cantonese a grammar and workbook is available in our book collection an online access to it is set as public so you can download it instantly. Our books collection hosts in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the intermediate cantonese a grammar and workbook is universally compatible with any devices to read.
Model checking web services choreography in process analysis toolkit

万维网服务(WS ) 是一种新兴的软件技术，特别在云计算扮演一个重要角色。 WS 舞蹈表演描述语言(WS-CDL ) 是为从一个全球观点越过多重参加者为 WS 作文的看得见的行为建模的标准。 然而，它正式语义缺乏并且能容易导致误解和不同实现。 在这份报纸， WS-CDL 基于说明正式在一传达顺序的过程支持被提取检查 WS 的一条正式途径当模特儿。 另外，形式体系并且模型检查明确地在模型检查器过程分析工具箱的帮助下通过一个简单却重要的例子被说明(轻拍) 。
ON THE USE OF CMOS TERNARY GATES TO REALIZE A SELF-CHECKING BINARY LOGIC SYSTEM

A scheme is proposed by which ternary gates realized with CMOS technology implement a self-checking binary system. All single faults in these gates can be divided into three types, called mid-seeking, mid-rejecting and masked. It is proven that the binary logic system realized with these gates is totally self-checking for mid-seeking faults. For mid-rejecting faults, the system is shown to be easily testable. A procedure of deriving test codes for mid-rejecting faults is presented. Furthermore, the effects of masked faults in the system are analysed.
Review of pattern recognition based on support vector machine

The principle and applications of the support vector machine(SVM) are briefly reviewed.Firstly,the background and the development prospects of SVM are described and then the definition,classification and algorithms of SVM are briefly introduced.Finally,we discussed the SVM-based applications,such as in text identification,handwritten numeral recognition,face detection,recognition and verification,regression analysis and prediction,image retrieval,feature selection and so on.
Optimal asset allocation of wind energy units in conjunction with demand response for a large‐scale electric grid

Demand response is considered to be a realistic and comparatively inexpensive solution aimed at increasing the penetration of renewable generations into the bulk electricity systems. The work in this paper highlights the demand response in conjunction with the optimal capacity of installed wind energy resources allocation. Authors proposed a total annual system cost model to minimize the cost of allocating wind power generating assets. This model contains capacity expansion, production, uncertainty, wind variability, emissions, and elasticity in demand to find out cost per hour to deliver electricity. A large‐scale electric grid (25 GW) is used to apply this model. Authors discovered that demand response based on interhourly system is not as much helpful as demand response grounded on intrahourly system. According to results, 32% wind generation share will provide the least cost. It is also worth noting that optimal amount of wind generation is much sensitive to installation cost as well as carbon tax.
Piezoelectricity and pyroelectricity in polymers

Piezoelectric activities of polymers arise from poling-induced orientation of dipoles (class 1) and uniaxial orientation of chiral molecules (class 2). The former accompanies pyroelectricity while the latter produces pyroelectricity if the spontaneous shear strain is incorporated. Strong activities have been found in class 1, namely, ferroelectric polymers, polar polymers having large dielectric relaxations, and composites containing a large amount of PZT. Poling conditions, factors that determine piezoelectric and pyroelectric activities, and their basic mechanisms are discussed. <<ETX>>
A novel approach for optimizing neural networks with genetic algorithms

A novel approach for optimizing feed forward neural networks is proposed in this paper, the genetic algorithms is not based on the traditional criterion of minimized square error, however its fitness function is determined by the average risk. The method considered not only the errors between the network's outputs and the desired outputs, but also the risk caused by these errors, because the errors for different types of samples in training set may present different risks. The neural networks optimized by the proposed approach shows good performance on the samples both inside and outside training set.
Tile-based modeling and its applications in computer graphics

Our ancient ancestors invented tiles predominantly for the purpose of decorating architectural interior and exterior structures varying from ceilings, floors to walls. Due to the beauty of tiles, mathematical analysis of 2D tilings has been well studied and classified, for example Wang and Corner Tiles, Periodic Tilings, and Non-Periodic Tilings. Graphics researchers, on the other hand, focused on the discovery of technique on applying tilings to various Computer Graphics classic applications like texture mapping, texture synthesis, and sampling. Applications on surface modeling were freshly proposed at the time this work began. Given the various properties of different types of tiles, say aperiodic, it is well concluded that tile-based techniques often offer a minimization of computational power and memory consumption, while keeping a high degree of freedom to provide wide range of flexible solutions to those classic applications. On the contrary, tiling in 3D space is a relatively new research area, and its applications have great potential in Computer Graphics and Computational Fabrication, which many of them have not yet been discovered until this work or similar works are established. Furthermore, there are many traditional art works hand-created by making use of 2D tiling concept, for example M. C. Escher’s artistic tessellation. Some of those art works present an optical illusion that confuses our visual system in reconstructing 3D geometry from the 2D drawing. There are very limited analysis and research on 3D visualization of such perceptual tiling art works. This thesis aims to study three various novel forms of tile-based models and their applications: Tile-based 3D Reconstruction and Navigation of Impossible World. In this work, we present a tile-based approach towards 3D gaming with impossible figures, delivering for the first time free view navigation in 3D mazes constructed from impossible figures. Such result cannot
Moving Object Tracking Using MHI and M-bin Histogram

In this paper, we propose an efficient moving object tracking technique for multi-camera surveillance system. Color CCD cameras used in this system are network cameras with their own IP addresses. Input image is transmitted to the media server through wireless connection among server, bridge, and Access Point (AP). The tracking system sends the received images through the network to the tracking module, and it tracks moving objects in real-time using color matching method. We compose two sets of cameras, and when the object is out of field of view (FOV), we accomplish hand-over to be able to continue tracking the object. When hand-over is performed, we use MHI(Motion History Information) based on color information and M-bin histogram for an exact tracking. By utilizing MHI, we can calculate direction and velocity of the object, and those information helps to predict next location of the object. Therefore, we obtain a better result in speed and stability than using template matching based on only M-bin histogram, and we verified this result by an experiment.