Miracle-dz/UniFAR-FTUs huggingface dataset:
Reconfigurable equalization for 10-Gb/sec serial data links in a 0.18-μm CMOS technology

for their technical discussion and guidance for the research directions. I am indebted my colleague members in Microwave Application Group for making good environment as a team supporting each other. I owe special thanks to the mixed signal team members for their numerous technical discussions in circuit and system design. Chyung for their constant love and support throughout my life. I have to acknowledge my beloved wife, Jennifer Jiyun Bien for her endless support during the research work. She has been the source of encouragement in my life. Without her help and love, this work would not be completed.
CS 511 - Spring 2006, Object-Oriented Software Principles Term Project Technical Report

The purpose of this project is the creation of a graphical \programming" interface for a sensor network tasking language called STEP. The graphical interface allows the user to specify a program execution graphically from an extensible pallet of functionalities and save the results as a properly formatted STEP flle. Moreover, the software is able to load a flle in STEP format and convert it into the corresponding graphical representation. During both phases a type-checker is running on the background to ensure that both the graphical representation and the STEP flle are syntactically correct. This project has been motivated by the Sensorium project at Boston University. In this technical report we present the basic features of the software, the process that has been followed during the design and implementation. Finally, we describe the approach used to test and validate our software.
Data encryption method based on privacy preserving

In order to improve the security of data privacy and prevent data leakage, a novel data encryption algorithm is proposed in this paper based on privacy preserving. Digital and operator are encrypted into key special word, and the key word is input to the bloom filter to hit and decided to achieve the data comparison and protect the data, the validity and superiority of algorithm are tested by simulation experiments. The simulation results show that the proposed algorithm can enhance the security of data, and has the advantages of easy implementation, high practicability, so it can meet all kinds of data protection conditions.
Dipole model analysis of high precision HERA data

We analyse, within a dipole model, the inclusive DIS cross section data, obtained from the combination of the H1 and ZEUS HERA measurements. We show that these high precision data are very well described within the dipole model framework, which is complemented with a valence quark structure functions. We discuss the properties of the gluon density obtained in this way.
Countercurrent Chromatography Apparatus Theory And Applications

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Image Processing And Analysis A Practical Approach

image processing and analysis a practical approach is available in our book collection an online access to it is set as public so you can download it instantly. Our book servers hosts in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the image processing and analysis a practical approach is universally compatible with any devices to read.
Face Recognition Based on Embedded Systems

Machine learning in general, and artificial neural networks in particular, have gained a lot of attention in recent years. Using deep neural networks for classification tasks, such as face recognition, has proven more and more successful over time. The performance increase is partly due to more complex network architectures, and partly due to the use of larger datasets. The increased complexity of networks has lead to an increase in parameters, which in turn results in slower training and inference, making it hard to deploy such models on limited hardware. The main objective of this master's thesis is to train a convolutional neural network for face recognition, and deploy it on an embedded system, with the aim of real-time performance. By using transfer-learning as a means to adjust a pre-trained model to fit new data, the time needed for the training phase is reduced. The resulting model achieves an accuracy of 91.66%, while distinguishing between 2,904 identities. The model is then compressed by a method referred to as pruning, reducing the amount of parameters in the fully connected layers by a factor of 20, greatly reducing the memory footprint while remaining within 1% of the original accuracy. Finally, by combining the resulting neural network model with a custom built framework and a live video stream, real-time face recognition is achieved on an embedded device. (Less)
Design of Intelligent Valve Positioner Based on PROFIBUS-DP

Valve positioner as the main accessory of pneumatic control valve can realize the pinpoint of valve position.This paper took MCU S3C44BO as the core,constructed the intelligent valve positioner based on PROFIBUS-DP,applied the power supply for two-wire system and modularize programmer for the hardware circuit design.This valve positioner has higher application value because of higher integration,less mechanical components and more convenient maintenance compared with the traditional one.
Construction, Expression, and Purification of p28 as a Cell-Penetrating Peptide ‎with Anticancer Effects on Burkitt’s Lymphoma Cell Line

Background: The p28 is a small-sized cell-penetrating peptide derived from bacterial protein azurin and can function as a cancer-speciﬁcanti-proliferativeagent. Itcanpenetratecancertissueseasilywithoutinvolvingtheimmunesystem,andincreasetheintra-cellular concentration of p53. Objectives: In this study, we have expressed and puriﬁed recombinant p28, then evaluated its anti-proliferative and pro-apoptotic eﬀects on Raji cancer cell line. Methods: The p28 gene was ampliﬁed and cloned into pTZ57R cloning vector and was sequenced subsequently. Afterward, it was transformed into E. coli BL21 bacterial host by using pET-28a expression vector. Peptide puriﬁcation was carried out using Ni-NTA chromatography system. Bradford, SDS-PAGE, and western blotting assays were applied to assess the concentration and expression level of the recombinant peptide. The proﬁciency of p28 in inhibition of tumor growth and induction of apoptosis in cancerous cells was investigated by evaluating the Raji and HEK-293 cells treated with diﬀerent concentrations of p28. Results: The overexpression of the p28 peptide in the bacterial host was conﬁrmed by SDS-PAGE and western blotting. Moreover, Bradfordassayrevealeddesirableconcentrationsof therecombinantp28beforeandafterdialysis. TheMTTandPE-AnnexinVapop-tosis assays indicated the speciﬁc function of p28 in impeding the proliferation of cancerous cells and triggering the apoptosis. Conclusions: Thep28inducesapoptosisincancerouscellsbutnotinnormalcontrolcells. Insummary,p28isanon-immunogenic small peptide that can penetrate cancerous cells preferentially, impede the cell proliferation, and induce the apoptosis. Overall, these ﬁndings suggest p28 as a promising anticancer drug.
A trust-based sentiment delivering calculation method in microblog

Public sentiment analysis in microblog has become a flourishing frontier in social network big data mining. A trust-based sentiment delivering calculation method is proposed from the view of sentiment delivering and interaction to solve the problem of discovering sentiment propagation mechanism in microblog. Firstly, a trust model of microblog user, which evaluates users' trusts-based on aspects of user past interaction data and composition of integration path, is presented. Secondly, models of microblog sentiment delivering and sentiment delivering interaction were proposed for describing the process of sentiment delivering formally. Further, calculation methods of sentiment delivering effect and sentiment delivering interaction in above two models are given respectively. Finally, experimental results verified the effectiveness and feasibility of our proposed method.
Gene expression mining using clustering and association mining techniques

Mining DNA microarray gene expression data for discovering in silico biological knowledge is an emerging area of research in computational biology. Data mining is an important tool that has been applied successfully during the last two decades to analyze gene expression data. Clustering and classification have been widely used to analyze gene expression data. Association mining is relatively a promising and established technique in the area of data mining and knowledge discovery. However, a very little work has been done using association mining techniques to analyze expression data to obtain insights from data with regards to biological relevance. The purpose of this thesis is to study various association mining as well as clustering techniques and apply the techniques for gene expression data analysis. Our first contribution is a correlogram matrix based one-pass association mining technique (OPAM) for finding frequent itemsets from transaction database without candidate generation. We apply the correlogram matrix in finding strongly correlated item pairs (SCOPE) from transaction data using support based Pearson correlation coe cient. We also contribute an alternative non-parametric correlation coe cient measure for calculating strongly correlated item pairs. Comparison of SCOPE with other competitive algorithms using several synthetic and real world datasets shows the superiority of our methods. We have extended the concept for reconstruction of co-regulated gene co-expression network (GeCON). We use both synthetic and real dataset to establish that GeCON is superior in predicting gene network compare to other similar techniques and networks generated are having high biological significance. Finally, we contribute a BiClust tree based technique (CoBi) for extracting coregulated biclusters from gene expression data. The advantage of CoBi is twofold. First, it is one-pass in nature, and second, it can extract biclusters of high biological significance in polynomial time. We evaluated the performance of the proposed method using several benchmark gene expression datasets and the results are satisfactory.
Dutch hypernym detection: does decompounding help?

This research presents experiments carried out to improve the precision and recall of Dutch hypernym detection. To do so, we applied a data-driven semantic relation finder that starts from a list of automatically extracted domain-specific terms from technical corpora, and generates a list of hypernym relations between these terms. As Dutch technical terms often consist of compounds written in one orthographic unit, we investigated the impact of a decompounding module on the performance of the hypernym detection system. In addition, we also improved the precision of the system by designing filters taking into account statistical and linguistic information. The experimental results show that both the precision and recall of the hypernym detection system improved, and that the decompounding module is especially effective for hypernym detection in Dutch.
EFFICIENT AND EFFECTIVE USE OF LOW-COST 3D AUDIO SYSTEMS

Commercial, off-the-shelf (COTS) 3D sound cards offer a readily available low-cost option to consumers, researchers, and developers of 3D auditory displays. However, drawbacks of current 3D sound cards include computing platform support limitations, Application Programming Interface (API) complexity, vendor instabilities, and the lack of individualized Head-Related Transfer Functions (HRTFs). To address these issues, we have developed a client/server system utilizing COTS 3D sound cards and have investigated a method of visualfeedback training for 3D sound localization.
Service Function Chaining Use Cases In Data Centers

Data center operators deploy a variety of layer 4 through layer 7 service functions in both physical and virtual form factors. Most traffic originating, transiting, or terminating in the data center is subject to treatment by multiple service functions. This document describes use cases that demonstrate the applicability of Service Function Chaining (SFC) within a data center environment and provides SFC requirements for data center centric use cases, with primary focus on Enterprise data centers.
Practical Methods for Computing Large Covering Tours and Cycle Covers with Turn Cost

We study the problem of computing provably optimal and near-optimal solutions for the NP-hard problem of ﬁnding covering tours and cycle covers with turn cost, which are of practical importance for a variety of applications, such as pest control and precision farming. Previous work has largely focused on theoretical aspects, such as complexity and approximation. We develop a number of algorithm engineering techniques and reﬁnements to make such theoretical insights practically useful, resulting in a comprehensive study for solving a wide spectrum of large instances. We compute provably optimal solutions for instances with more than 1000 pixels, from the largest previous solved instance size of 76 (de Assis and de Souza 2011). Making use of additional algorithm engineering techniques for handling very large instances, we also compute near-optimal solutions for instances with up to 300 000 pixels, for which we give solutions that are typically within a few percent of our computed lower bounds. We also provide an experimental comparison of a practically reﬁned version of our new theoretical approach with the approximation technique of Arkin et al. that dates back to 2001; we show that our new LP/IP-based approximation method closes 70% of the remaining optimality gap to the lower bound.
Controversies In Applied Linguistics

Thank you very much for reading controversies in applied linguistics. Maybe you have knowledge that, people have search numerous times for their chosen novels like this controversies in applied linguistics, but end up in harmful downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they are facing with some malicious bugs inside their desktop computer. controversies in applied linguistics is available in our book collection an online access to it is set as public so you can get it instantly. Our book servers hosts in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the controversies in applied linguistics is universally compatible with any devices to read.
Personalized Teaching of Multiple Languages through the Web

This paper describes the development of a personalized teaching system, which aims to be useful in multiple language learning. Web services provide remote access to the system, which performs affective user modeling. The system holds student models, namely it creates a profile for every student and provides individualized help, via the advice generator component. The error diagnosis component is also useful for evaluating students’ errors, which is performed for all the system’s supported languages. Given that software applications that operate over the web are targeted to a wide range of users, we promote the adaptivity and individualization to each user that interacts with the application and we give students the important facility of learning multiple languages over the Web. The student modeler may be authored by the instructor, along with all the functional components of our tutoring system.
Transfer Learning for Collaborative Filtering Using a Psychometrics Model

In a real e-commerce website, usually only a small number of users will give ratings to the items they purchased, and this can lead to the very sparse user-item rating data. The data sparsity issue will greatly limit the recommendation performance of most recommendation algorithms. However, a user may register accounts in many e-commerce websites. If such users’ historical purchasing data on these websites can be integrated, the recommendation performance could be improved. But it is difficult to align the users and items between these websites, and thus how to effectively borrow the users’ rating data of one website (source domain) to help improve the recommendation performance of another website (target domain) is very challenging. To this end, this paper extended the traditional one-dimensional psychometrics model to multidimension. The extended model can effectively capture users’ multiple interests. Based on this multidimensional psychometrics model, we further propose a novel transfer learning algorithm. It can effectively transfer users’ rating preferences from the source domain to the target domain. Experimental results show that the proposed method can significantly improve the recommendation performance.
Multi-scale Attention Network for Single Image Super-Resolution

By exploiting large kernel decomposition and attention mechanisms, convolutional neural networks (CNN) can compete with transformer-based methods in many high-level computer vision tasks. However, due to the advantage of long-range modeling, the transformers with self-attention still dominate the low-level vision, including the super-resolution task. In this paper, we propose a CNN-based multi-scale attention network (MAN), which consists of multi-scale large kernel attention (MLKA) and a gated spatial attention unit (GSAU), to improve the performance of convolutional SR networks. Within our MLKA, we rectify LKA with multi-scale and gate schemes to obtain the abundant attention map at various granularity levels, therefore jointly aggregating global and local information and avoiding the potential blocking artifacts. In GSAU, we integrate gate mechanism and spatial attention to remove the unnecessary linear layer and aggregate informative spatial context. To confirm the effectiveness of our designs, we evaluate MAN with multiple complexities by simply stacking different numbers of MLKA and GSAU. Experimental results illustrate that our MAN can achieve varied trade-offs between state-of-the-art performance and computations. Code is available at https://github.com/icandle/MAN.
Orientational disorder of the nitrite anion in the sodalite Na8[AlSiO4]6(NO2)2

Cristallisation dans P43m avec a=8,923 A, Z=1; affinement jusqu'a R=0,021. Le reseau sodalite est un arrangement ordonne et alterne de tetraedres AlO 4 et SiO 4 de sommets communs. Chaque cage [4 6 6 8 ] contient quatre cations Na qui entourent un anion NO 2 de facon tetraedrique. L'atome N est situe a 0,37 A du centre de la cage. Le desordre de l'anion est au moins d'ordre 12, et les interactions de ses atomes N et O avec Na sont fortes
Tungstophosphoric acid supported on titania as an eco-friendly, green and reusable catalyst for the solvent-free Hantzsch multi-component condensation

Tungstophosphoric acid supported on titania (PW/TiO 2 ), catalyzed three and four component coupling of various β-dicarbonyl compounds, aldehydes and amines under solvent free conditions. Different 4-aryl, N-hydroxy ethyl and N-aryl substituted 1, 4-dihydropyridines and polyhydroquinoline derivatives, have been synthesized with high to excellent yields. Short reaction times, simple work-up, and mild reaction conditions are advantages of this procedure. The catalyst is reusable without loss of activity for five runs.
Research on underwater single-pixel imaging system

Owing to the complicated underwater imaging conditions which seriously restrict the development of underwater imaging,especially the remote underwater imaging,a novel underwater imaging framework based on the compressive sensing(CS) is proposed in this paper.The single-pixel camera based on CS is firstly applied to the underwater imaging field.Incorporating the range gate and laser pulse illumination technology,we design the architecture of the underwater CS single-pixel camera system,and construct the measurement matrix and the reconstruction algorithm for this system.By the theory analysis and simulated experiment,the image resolution and the imaging distance of our method are compared with those of range-gate imaging and other underwater imaging methods respectively.The results show that the proposed method not only increases the imaging distance but also improves the image quality.
Chiral 1,1′‐Binaphthyl‐2,2′‐Disulfonic Acid (BINSA) and Its Derivatives for Asymmetric Catalysis

Chiral Bronsted acid catalysts, which are derived from commercially available (R)- or (S)- 1,1′-bi-2-naphthol (BINOL), have found widespread application as chiral organocatalysts and chiral ligands for metal species. The Bronsted acidity of these catalysts is considered to be associated with their catalytic activity. Therefore, due to the rapid development of asymmetric organocatalysis, chiral 1,1′-binaphthyl-2,2′-disulfonic acid (BINSA) and the corresponding chiral binaphthyl disulfonimides are highly attractive as stronger chiral Bronsted acid catalysts than carboxylic acids, phosphoric acids, and phosphoramides. This Focus Review summarizes the latest achievements in chiral BINSA chemistry, particularly in the field of asymmetric organocatalysis.
Cfa2: pushdown flow analysis for higher-order languages

In a higher-order language, the dominant control-flow mechanism is function call and return. Most higher-order flow analyses do not handle call and return well: they remember only a bounded number of pending calls because they approximate programs as finite-state machines. Call/return mismatch introduces precision-degrading spurious execution paths and increases the analysis time. We present flow analyses that provide unbounded call/return matching in a general setting: our analyses apply to typed and untyped languages, with first-class functions, side effects, tail calls and first-class control. This is made possible by several individual techniques. We generalize Sharir and Pnueli's summarization technique to handle expressive control constructs, such as tail calls and first-class continuations. We propose a syntactic classification of variable references that allows precise lookups for non-escaping references and falls back to a conservative approximation for references captured in closures. We show how to structure a flow analysis like a traditional interpreter based on big-step semantics. With this formulation, expressions use the analysis results of their subexpressions directly, which minimizes caching and makes the analysis faster. We present experimental results from two implementations for Scheme and JavaScript, which show that our analyses are precise and fast in practice.
Parallel Collaborative Filtering Recommendation Algorithm based on Cloud Computing

The paper Proposed Item parallel collaborative filtering recommendation algorithm (IP-CF). Through designing efficient parallel algorithm, compute-extensive procedures are distributed to different processing nodes in Hadoop platform. Taking advantage of parallel computing, we accelerate the response of recommendation. The experimental results show that our proposed algorithm IP-CF is more efficient and scalable than current parallel algorithms.