Miracle-dz/UniFAR-FTUs huggingface dataset:
A new method for construction filed association terms using co-occurrence words and declinable words information

Readers can know the subject of many document fields by reading only some specific words called field association (FA) terms. It is very important to construct these FA terms to decide correctly the document fields from few word information in part of the file. The field can be decided efficiently if the number of these FA terms is many and the frequency rate is high. If the number of level 1 (words that directly connect to terminal fields) FA words is limited, old methods cannot determine the documents filed easily and fast, specially when there is a small number of corpus documents. This paper proposes a new method for deciding FA terms using the weight of co-occurrence words and declinable words which are related to the narrow association category with eliminating FA terms' ambiguity. Moreover, efficient FA terms are difficult to be extracted only by the information of the frequency of them. This paper proposes a new efficient method using new co-occurrence word weighting which makes precision and recall higher than the case of degree of frequency.
Neural network models of managerial judgment

An experiment is presented which compares actual managerial decision-making, decisions based on neural network models, and decisions based on linear regression rules. Since neural networks are thought to be superior in the case of more complex decisions, two level of environmental complexity are also introduced into the study. The study makes use of data from subjects making a production-scheduling decision. The subject's behavior is modeled with linear decision rules and several neural network models. The results for the experiment are not included in the paper because analysis was incomplete. <<ETX>>
Learning from Examples Via Self-Explanations

Abstract : This paper summarizes the results of our investigation of: 1) how students learn to solve simple mechanics problems; 2) what is learned when they study worked-out examples in the text; and 3) how they use what has been learned from the examples while solving problems. We also provide justifications for why mechanics problems were chosen, why we examined learning from examples, and how we can capture the understanding of examples by asking students to generate explanations. The underlying assumption of our research is that differences in students' abilities to learn to solve problems arise from the degree to which they have encoded the relevant knowledge from the text, and use this knowledge to parse and understand the worked-out examples. We found that not only do the good students, those who subsequently had greater success at solving the end-of- the-chapter problems, generate a greater amount of explanations, but moreover, the quality of their explanations was better in that it explicated the tacit knowledge, as well as related the example statements to principles and concepts introduced in the text. Good students were also more accurate at monitoring their comprehension of the example statements. Accuracy was important because awareness of misunderstanding usually led to episodes of self-explanations. Worked-out examples were also used in different ways by good and poor students. Keywords: Individual differences.
Run-to-run Optimization for Fed-batch Fermentation Process with Swarm Energy Conservation Particle Swarm Optimization Algorithm

为喂批发酵过程的反复的优化策略被把 run-to-run 优化与群精力保存粒子群优化(SEC-PSO ) 相结合介绍。 SEC-PSO，与精力保存的概念被设计，能解决早熟的集中的问题经常由根据群的精力把它的人口划分成几亚群在标准 PSO 算法出现了并且为参数鉴定和操作条件优化在优化策略被使用。 run-to-run 优化利用喂批过程的重复性质以便与不精密的过程模型和不稳定的过程状态一起处理喂批发酵过程的最佳的问题。 运动模型参数，在下一跑的操作条件优化使用，被在 run-to-run 优化从真实喂批过程获得的精明的时间系列数据调整。 模拟结果证明策略能动态地调整它的运动模型并且有效地克服喂批过程的不稳定性。 有 SEC-PSO 的 Run-to-run 策略为喂批发酵过程的优化提供一个有效方法。
Effects of Age and Training on World Wide Web Navigation Strategies

The present study examined the effects of age and type of training on efficiency and preferences in a World Wide Web search activity. Older and younger participants received a hands-on Web navigation tutorial or a verbal description of available navigation tools. Participants then searched a 19-page Web site for the answers to nine questions. Older participants were able to complete most of the nine search tasks, but followed more links and scrolled more pages to find the required information than did younger adults. Factors in this inefficiency were patterns of returning to the home page while searching and revisiting previously viewed pages during a single task. Hands-on training was associated with increased use of the more efficient navigation tools. Older adults, especially those who received hands-on training, were more likely to use the “site map” and “index tabs” than were younger adults. Implications for training and Web site design are discussed.
Deca­aqua­dioxobis[μ3-N-(phosphono­meth­yl)imino­diacetato]dimanganesedivanadium dihydrate

The crystal structure of the title compound, [Mn2V2(C5H6NO7P)2O2(H2O)10]·2H2O, contains a centrosymmetric dimeric [V2O2(pmida)2]4− unit [where H4pmida is N-(phosphono­meth­yl)imino­diacetic acid] connecting two neighbouring Mn2+ cations through the phospho­nate groups. The crystal structure is characterized by the presence of an extensive network of strong and highly directional O—H⋯O hydrogen bonds, involving the water mol­ecules (coordinated and uncoordinated) and the functional groups of pmida4−.
Characterization of a dedicated double loop, endoluminal coil for anal sphincter MR imaging at 1.5 T and 3 T

MRI has proven its usefulness in the prediction of surgical anterior anal repair that cannot be done with the reference endosonographic exam. Conventional endorectal coils are often based on a single loop coil design and do not possess satisfactory radial uniformity which could impede the correct assessment of the anal sphincter. In this study, several double loop endorectal coils were designed, built, and assessed in simulations, on phantoms and in vivo. The optimum was found for a 50°–70° double loop endorectal coil which presents a better radial uniformity especially at close distance from the coil where the SNR is the highest. First in vivo experiments proved enhanced readability of the MR exam for the radiologist. © 2014 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 44B: 39–49, 2014
A quantitative, parametric model of musical tension

This thesis presents a quantitative, parametric model for describing musical tension. While the phenomenon of tension is evident to listeners, it is difficult to formalize due to its subjective and multi-dimensional nature. The model is therefore derived from empirical data. Two experiments with contrasting approaches are described. The first experiment is an online test with short musical excerpts and multiple choice answers. The format of the test makes it possible to gather large amounts of data. The second study requires fewer subjects and collects real-time responses to musical stimuli. Both studies present test subjects with examples that take into account a number of musical parameters including harmony, pitch height, melodic expectation, dynamics, onset frequency, tempo, and rhythmic regularity. The goal of the first experiment is to confirm that the individual musical parameters contribute directly to the listener’s overall perception of tension. The goal of the second experiment is to explore linear and nonlinear models for predicting tension given descriptions of the musical parameters for each excerpt. The resulting model is considered for potential incorporation into computerbased applications. Specifically, it could be used as part of a computer-assisted composition environment. One such application, Hyperscore, is described and presented as a possible platform for integration. Thesis supervisor: Tod Machover Title: Professor of Music and Media
Meeting decision detection : multimodal information fusion for multi-party dialogue understanding

Modern advances in multimedia and storage technologies have led to huge archives of human conversations in widely ranging areas. These archives offer a wealth of information in the organization contexts. However, retrieving and managing information in these archives is a time-consuming and labor-intensive task. Previous research applied keyword and computer vision-based methods to do this. However, spontaneous conversations, complex in the use of multimodal cues and intricate in the interactions between multiple speakers, have posed new challenges to these methods. We need new techniques that can leverage the information hidden in multiple communication modalities – including not just “what” the speakers say but also “how” they express themselves and interact with others. In responding to this need, the thesis inquires into the multimodal nature of meeting dialogues and computational means to retrieve and manage the recorded meeting information. In particular, this thesis develops the Meeting Decision Detector (MDD) to detect and track decisions, one of the most important outcomes of the meetings. The MDD involves not only the generation of extractive summaries pertaining to the decisions (“decision detection”), but also the organization of a continuous stream of meeting speech into locally coherent segments (“discourse segmentation”). This inquiry starts with a corpus analysis which constitutes a comprehensive empirical study of the decision-indicative and segment-signalling cues in the meeting corpora. These cues are uncovered from a variety of communication modalities, including the words spoken, gesture and head movements, pitch and energy level, rate of speech, pauses, and use of subjective terms. While some of the cues match the previous findings of speech segmentation, some others have not been studied before. The analysis also provides empirical grounding for computing features and integrating them into a computational model. To handle the high-dimensional multimodal feature space in the meeting domain, this thesis compares empirically feature discriminability and feature pattern finding criteria. As the different knowledge sources are expected to capture different types of features, the thesis also experiments with methods that can harness synergy between the multiple knowledge sources. The problem formalization and the modeling algorithm so far correspond to an optimal setting: an off-line, post-meeting analysis scenario. However, ultimately the MDD is expected to be operated online – right after a meeting, or when a meeting is still in progress. Thus this thesis also explores techniques that help relax the optimal setting, especially those using only features that can be generated with a higher
FIR filtering using CMOS switched-current techniques

The design of high-speed FIR (finite impulse response) filters using switched-current technology is considered. By using current to represent signals, an FIR filter has been implemented using building blocks developed from switched-current circuits. It has been fabricated using the MOSIS 2- mu m CMOS technology, and can operate at a sampling frequency over 10 MHz. <<ETX>>
Android-based automatic speech recognitionfront end to access Web APIs

An automatic speech-recognition (ASR) front-end was implemented on Android platform to access RESTful API. The purpose was retrieving information from the Internet using speech as primary input. The Android application uses an ASR front-end to recognize uttered words and transform them into text patterns. Then it exploits on board GPS data and RESTful Twitter API to find twits containing the recognized text and coming from users located in a certain area around the device. Implementations of the same algorithm in C and in Java were compared, and performance on the Android platform was evaluated.
A skeleton middleware for the parallel program

We propose an approach to the design of distributed parallel computing systems based on the concept of reflective middleware, skeleton parallel programming and object-oriented software engineering. In the approach, the programmer does not need to be bothered by the architectural details. Furthermore, the approach provides support for the mostly used parallel paradigms, which will ease the onerous work for the programmer to construct the parallelism. It offers a method for the user to map the programming design seamlessly to the real environment.
Software Component Retrieval by Composition Using Semantic Properties

Abstract Retrieving software components by composition helps the user build a new component by reusing the existing components even when there is no single component in the component reuse library that meets the user's requirements. However, the number of possible compositions tends to be extremely large. In this article we present a method of retrieval-by-composition in which the user provides a composition structure for the desired component and the retrieval system retrieves all possible compositions of components that fit into that composition structure. In our method, a set of simple semantic properties including demand, transmission, and length properties about the desired component is used to reduce the number of possible compositions. The semantic properties of internal composing components are automatically inferred based on the semantic property of the desired component and the composition structure. We implement a prototype semantic property-based retrieval by composition system in which the user can visually construct composition structures.
Different roles of evaluation in information systems research

Evaluation of information systems (IS) has come to be an important topic for study as well as practice. IS scholars perform studies of how to evaluate IS and different IS related phenomena, like e.g. methods and strategies. Evaluation is also used as a research approach in many IS research studies. However, the use and interest of evaluation seem to be rather fragmented and diversified in the IS field. The purpose of this paper is to bring more structure to evaluation in IS research. Based on a review of literature on evaluation in IS research and on evaluation research in general a conceptualisation of evaluation in IS is presented. This consists of 1) a conceptual practice model of evaluation (including generic questions for the design of evaluation) and 2) a classification of different roles of IS evaluation research. This classification consists of three main research types: 1) research about evaluation, 2) research through evaluation and 3) research about evaluation research. The second research type has been divided into three sub-classes: 2a) research through evaluation as main strategy, 2b) research through evaluation as companion strategy and 2c) research through evaluation as re-use strategy. The different research types have been characterized and exemplified.
A new neural associative memory with learning

A new learnable associative neural memory has been designed, analyzed, and implemented. The chip implementation is made by using the CMOS current-mode circuits with analog current multiplier and divider. This neural memory can automatically learn and correlative things and has an on-chip ratio-type memory. It can be refreshed by reminding. An experimental three-neuron-net chip was fabricated on a 5-mm*5-mm chip. Experimental results are presented. <<ETX>>
Early wirability checking and 2D congestion-driven circuit placement

An effective congestion-driven placement algorithm that uses initial global routing model for congestion analysis and optimization is proposed. The approach has been used for rescuing many difficult chip designs when intensive rip-up and remote technique could not complete the wiring. It is demonstrated that the congestion cost evaluation step of the algorithm can be used as an accurate early wirability checking utility. <<ETX>>
Automatic defect classification for integrated circuits

While initial detection of defects is the most critical function of inspection, automatic classification of detected defects is becoming increasingly desirable. The key to better process control is reliable process measurement. The classification of defects provides valuable process diagnosis information. The hope is that machines can perform this task more reliably than humans. However, there are many problems in automating defect classification, and many of these are related to the central problems in artificial intelligence, such as knowledge representation, inferencing, and dealing with uncertainty. In this paper we pay special attention to the issues arising in the Automatic Defect Classification (ADC) of integrated circuits. We first discuss technical and system requirements, followed by an outline of the technical challenges to be overcome to develop flexible and powerful ACD tools which can be quickly customized on a user level for diverse applications.
Does the choice of stimulus affect the complexity of children's oral narratives?

There is a lack of normative information that accounts for differences that may result from use of different story stimuli in oral narrative assessment. In this study, story generations in response to a complex wordless picture book and a single-scene picture were compared in a group of sixteen 5-year-old children with normally developing language, using a story grammar analysis. The effect of stimulus was significant, with the children producing longer, more informative and more complex stories for a complex wordless picture book than for a single-scene picture. The implications for clinicians assessing oral narrative skills are discussed.
Social Media & Mobile Internet Use among Teens and Young Adults. Millennials.

This publication is part of a Pew Research Center report series that looks at the values, attitudes and experiences of America's next generation: the Millennials. Find out how today's teens and twentysomethings are reshaping the nation at: Since 2006, blogging has dropped among teens and young adults while simultaneously rising among older adults. As the tools and technology embedded in social networking sites change, and use of the sites continues to grow, youth may be exchanging 'macro‐blogging' for microblogging with status updates. Blogging has declined in popularity among both teens and young adults since 2006. Blog commenting has also dropped among teens.  14% of online teens now say they blog, down from 28% of teen internet users in 2006.  This decline is also reflected in the lower incidence of teen commenting on blogs within social networking websites; 52% of teen social network users report commenting on friends' blogs, down from the 76% who did so in 2006.  By comparison, the prevalence of blogging within the overall adult internet population has remained steady in recent years. Pew Internet surveys since 2005 have consistently found that roughly one in ten online adults maintain a personal online journal or blog. While blogging among adults as a whole has remained steady, the prevalence of blogging within specific age groups has changed dramatically in recent years. Specifically, a sharp decline in blogging by young adults has been tempered by a corresponding increase in blogging among older adults.  In December 2007, 24% of online 18‐29 year olds reported blogging, compared with 7% of those thirty and older.  By 2009, just 15% of internet users ages 18‐29 maintain a blog—a nine percentage point drop in two years. However, 11% of internet users ages thirty and older now maintain a personal blog. Both teen and adult use of social networking sites has risen significantly, yet there are shifts and some drops in the proportion of teens using several social networking site features.  73% of wired American teens now use social networking websites, a significant increase from previous surveys. Just over half of online teens (55%) used social networking sites in November 2006 and 65% did so in February 2008.  As the teen social networking population has increased, the popularity of some sites' features has shifted. Compared with SNS activity in February 2008, a smaller proportion of teens in mid‐ 2009 were …
Hardware Support for Dynamic Access Ordering: Performance of Some Design Options

Hardware Support for Dynamic Access Ordering: Performance of Some Design Options Sally A. McKee Department of Computer Science University of Virginia Charlottesville, VA, 22903 mckee@virginia.edu Memory bandwidth is rapidly becoming the performance bottleneck in the application of high performance microprocessors to vector -like algorithms, including the “grand challenge” scientific problems. Caching is not the sole solution for these applications due to the poor temporal and spatial locality of their data accesses. Moreover , the nature of memories themselves has changed. Achieving greater bandwidth requires exploiting the characteristics of memory components “on the other side of the cache” — they should not be treated as uniform access-time RAM. This paper describes the use of hardware-assisted acc ss ordering on a uniprocessor system. Our technique combines compile-time detection of memory access patterns with a memory subsystem that decouples the order of requests generated by the processor from that issued to the memory system. This decoupling permits the requests to be issued in an order that optimizes use of the memory system. We present numerous simulation results showing significant speedup on important scientific kernels.
Multi-rate encoding of a video sequence in the DCT domain

In today's streaming servers, video sequences are offered to users at different fixed bit rates. This paper presents an efficient approach for simultaneous encoding of a video sequence at multiple bit rates. In this encoder, motion estimation is performed only once for the reference stream. We also take the DCT out of the encoding loop so that it is only computed once per frame. As a result, no iDCT has to be computed at the encoder. However, motion compensation is performed in the DCT domain, and drift error can be introduced adaptively to reduce the computational cost of the DCT-domain motion compensation. Results show that significant computational reduction can be achieved with less than 0.3 dB loss in PSNR when compared to independently encoding the video sequence at multiple rates.
Brain and brain-heart Granger causality during wakefulness and sleep

In this exploratory study we apply Granger Causality (GC) to investigate the brain-brain and brain-heart interactions during wakefulness and sleep. Our analysis includes electroencephalogram (EEG) and electrocardiogram (ECG) data during all-night polysomnographic recordings from volunteers with apnea, available from the Massachusetts General Hospital’s Computational Clinical Neurophysiology Laboratory and the Clinical Data Animation Laboratory. The data is manually annotated by clinical staff at the MGH in 30 second contiguous intervals (wakefulness and sleep stages 1, 2, 3, and rapid eye movement (REM). We applied GC to 4-s non-overlapping segments of available EEG and ECG across all-night recordings of 50 randomly chosen patients. To identify differences in GC between the different sleep stages, the GC for each sleep stage was subtracted from the GC during wakefulness. Positive (negative) differences indicated that GC was greater (lower) during wakefulness compared to the specific sleep stage. The application of GC to study brain-brain and brain-heart bidirectional connections during wakefulness and sleep confirmed the importance of fronto-posterior connectivity during these two states, but has also revealed differences in ipsilateral and contralateral mechanisms of these connections. It has also confirmed the existence of bidirectional brain-heart connections that are more prominent in the direction from brain to heart. Our exploratory study has shown that GC can be successfully applied to sleep data analysis and captures the varying physiological mechanisms that are related to wakefulness and different sleep stages.