Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-perspective modeling: managing heterogeneous manufacturing knowledge based on ontologies and topic maps

Knowledge organisation is an important topic for knowledge management and application. However, in the current knowledge-intensive manufacturing environment, documents are heterogeneous and come from multi-disciplinary domains and product process phases, which make the knowledge behind documents difficult to represent and manage. This hinders knowledge sharing and reuse in manufacturing activities. In order to solve the problem, this paper presents a novel multi-perspective modelling approach for manufacturing knowledge representation and organisation. It combines the ideas of ontologies and topic maps together to give a unified representation of knowledge association semantically. This new modelling method takes advantage of both ontologies and topic maps: general knowledge in domains is described with ontology-based descriptions, and specific knowledge, such as extended or new knowledge entities and relations, is described with topic map-based descriptions. It supports various relation types in manufacturing knowledge and organises association in different facets at several levels. In addition, it can be used in association management, information retrieval, semantic inference and expansion, recommendation and navigation for knowledge sharing and reuse. A case study for representing electronic manufacturing knowledge is introduced to demonstrate the implementation of the proposed method, which shows that it is valid and practical.
Meta analysis on the effect of reading development program on reading comprehension

The purpose of this study is to examine the effect of reading development program on reading comprehension using meta-analysis method. The authors synthesized 70 studies regarding reading comprehension conducted during 2001 through 2011. The analyses revealed that 1) the average effect size of the reading development program yielded.763, which is regarded considerably large, 2) the effect size of elementary school group was the biggest, 1.030. There were statistically significant differences amongst school levels, 3) the average effect size of published journal articles was 1.250, which is statistically significantly larger than that of dissertation`s.700, 4) regarding the methods to measure the effect of reading comprehension, the effect size of reading method was larger, and 5) the effect size of Korean reading development program was statistically larger than that of English reading development program. This study has limitation as it didn`t include unpublished manuscripts, conference presentations, and the like, however this study is meaningful in terms that it tried to draw integrated conclusion about the effect of reading development programs using meta-analysis.
Extrapolation of optimal lifted system ILC solution, with application to a waferstage

The optimal solution from the lifted system design methods presented by Tousain (2001) has many advantages over classic iterative learning control (ILC) design methods, with one drawback: the ILC solution has to be recalculated for every trajectory of a different length. This paper shows that it is very well possible to avoid this by expressing the solution for the lifted system ILC as a finite time function of the plant parameters. This solution will be referred to as an extrapolated solution since the solution can be used for a trajectory of any length without recalculating the solution. This low order extrapolated solution has been compared to a high order lifted system optimal control (Q-)ILC solution in the application to an industrial grade wafer stage, showing the value of this extrapolated solution.
Examination on ICT Integration into Special Education Schools for Developing Countries.

Information, communication and technology (ICT) is a bridge in fostering learning who have special needs in education. It becomes a medium of connecting their way of lives and their socialization within education life. Integration of ICT plays a great role in special education. Most of the developing countries pay attention to ICT practices in their education reports in order to provide equality in education and make all citizens active and digital cabaple. In reports, education context, ICT policy, ICT in curriculum and teacher education, ICT and digital resources were higlighted. Some of the reports of developing countries did not set special education needs, learners and ICT support for their learning. Although they pay attention to learners who have special needs, there is an intensified need to make comprehensive analysis of ICT integration into special education schools. This research study aims to analyze ICT integration and facilities in special education schools in North Cyprus in order to set ICT policy in education. Documentary analysis and interviews were conducted to gain reflections and tendencies about ICT integration in special education. This research study shows adaptabilty of developing country to European ICT policy and furthermore the research provides comparison between context capacity with other counties in terms of a situational analysis.
The Impact of Erythrocytes Injury on Blood Flow in Bionic Arteriole with Stenosis Segment

Ventricular assist device (VAD) implantation is an effective treatment for patients with end-stage heart failure. However, patients who undergo long-term application of VADs experience a series of VAD-related adverse effects including pump thrombosis, which is induced by rotate impeller-caused blood cell injury and hemolysis. Blood cell trauma-related flow patterns are the key mechanism for understanding thrombus formation. In this study, we established a new method to evaluate the blood cell damage and investigate the real-time characteristics of blood flow patterns in vitro using rheometer and bionic microfluidic devices. The variation of plasma free hemoglobin (PFH) and lactic dehydrogenase (LDH) in the rheometer test showed that high shear stress was the main factor causing erythrocyte membrane injury, while the long-term exposure of high shear stress further aggravated this trauma. Following this rheometer test, the damaged erythrocytes were collected and injected into a bionic microfluidic device. The captured images of bionic microfluidic device tests showed that with the increase of shear stress suffered by the erythrocyte, the migration rate of damaged erythrocyte in bionic microchannel significantly decreased and, meanwhile, aggregation of erythrocyte was clearly observed. Our results indicate that mechanical shear stress caused by erythrocyte injury leads to thrombus formulation and adhesion in arterioles.
New 2-MHz Multiarray Borehole-Compensated Resistivity Tool Developed for MWD in Slim Holes

To address the increasing number of slim holes being drilled in the range of 5.75 in. to 6.75 in. , a mixed-borehole-compensated (MBHC) 2-MHz array resistivity tool with a 4.75-in. collar diameter is described for resistivity measurement-while-drilling (MWD) applications. MBHC is a unique technique developed to minimize the effects of borehole rugosity. The new MWD array resistivity tool makes multiple MBHC phase shift and attenuation resistivity measurements using five transmitter-to-receiver spacings. Five independent MBHC phase shift and attenuation measurements are made at 2 MHz. The five phase shift resistivities have similar vertical responses but with increasing radial depths of investigation. The five attenuation resistivities are also vertically similar but coarser and are radially deeper than the phase shift resistivities. This new array resistivity tool effectively exploits the technology and the interpretation methodology recently developed for wireline induction resistivities and the benefits of multispacing probes for formation evaluation. Most of the petrophysical applications developed in conjunction with the wireline resistivity AIT* Array Induction Imager Tool are illustrated from MWD array resistivity logs acquired while drilling.
Design of a fuzzy controller mixing analog and digital techniques

Analog circuits are attractive for fuzzy VLSI, as they allow an easy implementation of the arithmetic functions which are needed in a fuzzy controller. Analog circuits are efficient in areas allowing parallelism to be employed. However, they suffer from noise disturbances and interferences. Also, they are susceptible to process variations and mismatching. On the other hand, digital circuits are robust and easy to design and process. However, arithmetic functions (such as multiplication and division) require large digital circuits. To overcome the above-mentioned drawbacks, pulse stream techniques have been proposed. These techniques use digital signals to carry information and control analog circuitry. Among the existing pulse stream techniques, pulse width modulation (PWM) has been selected due to its simplicity. This paper presents the architecture of a fuzzy logic controller using PWM techniques. A prototype circuit is being designed using a standard CMOS process. <<ETX>>
Analysis and simulation of multiconductor transmission lines for high-speed interconnect and package design

The authors present a novel approach to the crosstalk analysis of high-speed interconnects which are modeled as multiconductor transmission lines. The method is applicable to the general problem of N coupled lossy and/or dispersive interconnects with arbitrary linear source/load impedances. Closed-form formulas for determining the voltage and current transfer functions are derived using the spectral domain modal analysis technique. The transfer function is expanded to its Taylor series form, and the inverse Fourier transform is applied to the significant terms in the series. As a result, analytical expressions of time-domain signal waveforms are obtained. Besides providing valuable insight into the coupling phenomenon, the formulas facilitate analytical computation of noise and waveform distortion due to crosstalk. <<ETX>>
Subscription merging in filter-based publish/subscribe systems

Filter-based publish/subscribe systems suffer from high subscription maintenance cost for each broker in the system stores a large number of subscriptions. Advertisement and covering are not sufficient to conquer such problem. Thus, subscription merging is proposed. However, current researches lack of an efficient and practical merging mechanism. In this paper, we propose a novel subscription merging mechanism. The mechanism is both time and space efficient, and can flexibly control the merging granularity. The merging mechanism has been verified through both theoretical and simulation-based evaluation.
A novel document ranking algorithm that supports mobile healthcare information access effectiveness

This study presented DROPT; an acronym for Document ranking Optmization algorithm approach, a new idea for the effectiveness of meaningful retrieval results from the information source. Proposed method extracted the frequency of query keyword terms that appears within the user context of Frequently Asked Questions (FAQ) systems on HIV/AIDS content related­ documents. The SMS messages were analyzed and then classified, with the aim of constructing a corpus of SMS related to HIV/AIDS. This study presented a novel framework of Information Retrieval Systems (IRS) based on the proposed algorithm. The developed DROPT procedure was used as an evaluation measure. This "Term Frequency-Inverse Document Frequency (TFIDF)" method was applied to obtain the experimental result that was found promising in ranking documents not only the order in which the relevant documents were retrieved, but also both the terms of the relevant documents in feedback and the terms of the irrelevant documents in feedback might be useful for relevance feedback, especially to define its fitness function (mean weight).
Use of Generalized Language Model for Question Matching

Question and answering service is one of the popular services in the World Wide Web. The main goal of these services is to find the best answer for user's input question as quick as possible. In order to achieve this aim, most of these use new techniques foe question matching. We have a lot of question and answering services in Persian web, so it seems that developing a question matching model might be useful. This paper introduces a new question matching model for Persian. This model is based on statistical language model and employs generalized bigram and trigram model. We also describe some results regarding the employment of natural language processing in question matching model. Most of the QA hence we considered an optimized implementation for the model. We evaluated our model with Rasekhoon question and answering archive which contains about 18000 pairs of questions and answers. The results showed the improvement of precision and recall measures through using this model.
Psycholinguistic perspectives on second language learning and bilingualism: The course and consequence of cross-language competition

Recent psycholinguistic research demonstrates that using a second language has consequences for the first language (e.g. Dussias, 2003; Van Hell & Dijkstra, 2002) and for domain-general cognitive processes (Bialystok, 2005). This work suggests that the language system is permeable, with cross-language exchange at every level of processing (Malt & Sloman, 2003). Critically, even proficient bilinguals appear unable to switch off the language not in use when they hear, read, or speak one language alone (e.g. Dijkstra, 2005; Kroll, Bobb, & Wodniecka, 2006; Marian & Spivey, 2003), creating cross-language competition. In this article, we describe research that considers how cross-language activation is modulated during spoken production and during the earliest stages of second language learning. We hypothesize that the open nature of the bilingual’s language system may create optimal conditions for new language learning and also for enhanced cognitive control that enables effective selection of the language to be spoken.
Effects of N-Terminal and C-Terminal Polyhistidine Tag on the Stability and Function of the Thermophilic P450 CYP119

Biocatalysts are sought-after in synthesis of pharmaceuticals and agrochemicals due to their high regioselectivity and enantioselectivity. Among biocatalysts, heme-containing cytochrome P450 (P450) oxygenases are an attractive target since they catalyze oxidation of “unactivated” carbon-hydrogen bonds with high efficiency. CYP119 is an acidothermophilic P450 from Sulfolobus acidocaldarius, which has the potential to be widely used as a biocatalyst since it shows activity at high temperatures and low pH. Polyhistidine tags (His-tags) are widely used to simplify purification of proteins. However, His-tags can cause changes to protein structure and function. Here, we demonstrate the effects of His-tags on CYP119. To this end, the His-tags were cloned at the N-terminus or C-terminus of the CYP119, and His-tagged proteins were expressed and isolated. The thermostability and peroxidase activity of His-tagged CYP119s were tested and compared to wild type CYP119. Results indicated that while addition of His-tags increased the yield and simplified isolation of CYP119, they also influenced the electronic structure of active site and the activity of the protein. We show that N-terminal His-tagged CYP119 has desirable properties and potential to be used in industrial applications, but mechanistic studies using this protein need careful interpretation since the His-tag affects electronic properties of the active site heme iron.
A multicasting extension to OIF UNI standard

This paper presents a multicasting extension to OIF User Network Interface (UNI) standard, which allows dynamically setup/teardown/graft/prune a transport network multicasting tree. Transport network multicasting tree means a point-to-multipoint connection that originates from an ingress Transport Network Element (TNE) port and end at multiple egress TNE ports across the transport network for transporting user services. A global multicasting tree ID is defined to identify the transport network multicasting tree. Without addition of any new abstract messages, we just add some new attributes to existing UNI abstract messages to implement the signaling actions needed to support optical multicasting. Experimental results show the performance of our proposal under different strategy.
A Review on the Studies of Air Flow Field and Fiber Formation Process during Melt Blowing

Melt blowing is an industrially important process in producing microfibrous nonwovens. Over the past decades, there has been a considerable amount of fundamental research on this technique, driven by the development of advanced materials in the areas of filtration, absorption, and isolation. This work presents a comprehensive overview of the research on the air flow field and fiber formation process. Specific attention is concentrated on experimental and numerical studies that have been applied. The measuring methods and devices, results of the air flow field characteristics, and the fibers motion patterns under different types of dies are summarized. It is concluded that the properties of resultant nonwovens are influenced by the air flow field and fiber formation process. These fundamental researches are significant for the melt blowing technique in controlling the manufacturing process, reducing energy consuming, and improving the product performance.
Unified Acoustic Modeling using Deep Conditional Random Fields

Acoustic models based on Deep Neural Networks (DNNs) lead to significant improvement in the recognition accuracy. In these methods, Hidden Markov Models (HMMs) state scores are computed using flexible discriminant DNNs. On the other hand, Conditional Random Fields (CRFs) are undirected graphical models that maintain the Markov properties of HMMs formulated using the maximum entropy (MaxEnt) principle. CRFs have limited ability to model spectral phenomena since they have single quadratic activation function per state. It is possible and natural to use DNNs to compute the state scores in CRFs. These acoustic models are known as Deep Conditional Random Fields (DCRFs). In this work, a variant of DCRFs is presented and connections with hybrid DNN/HMM systems are established. Under certain assumptions, both DCRFs and hybrid DNN/HMM systems can lead to exact same results for a phone recognition task. In addition, linear activation functions are used in the DCRFs output layer. Consequently, DCRFs and traditional DNN/HMM systems have the same decoding speed.
Optimizing sampling approaches along ecological gradients

Natural scientists and especially ecologists use manipulative experiments or field observations along gradients to differentiate patterns driven by processes from those caused by random noise. A well‐conceived sampling design is essential for identifying, analysing and reporting underlying patterns in a statistically solid and reproducible manner, given the normal restrictions in labour, time and money. However, a technical guideline about an adequate sampling design to maximize prediction success under restricted resources is lacking. This study aims at developing such a solid and reproducible guideline for sampling along gradients in all fields of ecology and science in general. We conducted simulations with artificial data for five common response types known in ecology, each represented by a simple function (no response, linear, exponential, symmetric unimodal and asymmetric unimodal). In the simulations, we accounted for different levels of random and systematic error, the two sources of noise in ecological data. We quantified prediction success for varying total sample size, number of locations sampled along a spatial/temporal gradient and number of replicates per sampled location. The number of replicates becomes more important with increasing random error, whereas replicates become less relevant for a systematic error bigger than 20% of total variation. Thus, if high levels of systematic error are indicated or expected (e.g. in field studies with spatial autocorrelation, unaccountable additional environmental drivers or population clustering), continuous sampling with little to no replication is recommended. In contrast, sampling designs with replications are recommended in studies that can control for systematic errors. In a setting that is characteristic for ecological experiments and field studies strictly controlling for undeterminable systematic error (random error ≥10% and systematic error ≤10% of total variation), prediction success was best for an intermediate number of sampled locations along the gradient (10–15) and a low number of replicates per location (3). Our findings from reproducible, statistical simulations will help design appropriate and efficient sampling approaches and avoid erroneous conclusions based on studies with flawed sampling design, which is currently one of the main targets of public criticism against science.
A Multimedia CELP/Subband Coder for ATM Networks

The transmission of compressed audio and video data over ATM packet networks is quickly becoming a practical way to implement a multimedia teleconferencing system. To reduce the required bit rate of the combined audio/video sequence to that of basic rate ISDN, we encode the video using a subband coder and encode the audio using a CELP coder. In this paper, we examine the effects that packet losses, and the variable delay and delay jitter of ATM networks have on our audio coding system. Results for a large time-bandwidth product network are presented. Specifically, ways to make the speech coding more robust to packet loss are examined.
Metadata Dictionary Database: A Proposed Tool for Academic Library Metadata Management

This article proposes a metadata dictionary (MDD) be used as a tool for metadata management. The MDD is a repository of critical data necessary for managing metadata to create “shareable” digital collections. An operational definition of metadata management is provided. The authors explore activities involved in metadata management in organizational settings and indicate how the MDD can support these activities. A detailed discussion of the metadata dictionary and its structure, benefits and challenges is provided.
Content-Boosted Collaborative Filtering

Most recommender systems use Collaborative Filtering or Content-based methods to predict new items of interest for a user. While both methods have their own advantages, individually they fail to provide good recommendations in many situations. Incorporating components from both methods, a hybrid recommender system can overcome these shortcomings. In this paper, we present an elegant and e ective framework for combining content and collaboration. Our approach uses a content-based predictor to enhance existing user data, and then provides personalized suggestions through collaborative ltering. We present experimental results that show how this approach, Content-Boosted Collaborative Filtering, performs better than a pure content-based predictor, pure collaborative lter, and a naive hybrid approach. We also discuss methods to improve the performance of our hybrid system.