Miracle-dz/UniFAR-FTUs huggingface dataset:
Research and application of hybrid intelligent control for coke oven heating process

Coke oven heating temperature was reflected by flue temperature and adjusted by gas flow. Aiming at the coke oven heating process characteristics of great inertia, pure time-delay, strong non-linear and time changeable, the control method of combining the intermittent heating control with the heating gas flow adjustment was adopted. Hybrid intelligent control strategy and model of coke oven heating process were established, which combined two feedback control, one feedforward control and fuzzy control. Energy-required prediction feed-forward model was built to give the initial gas flow. Carbonization index feedback model was proposed to revise the goal flue temperature in order to control coking process. Flue temperature soft measurement model based on linear regression and neural network was built to supply temperature feedback control. According to artificial experience and actual condition in the plant, fuzzy controller was designed. The proper amount of stopping heating time and heating gas flow were computed taking the operation condition of coke oven into account. The practical running results indicate that the system can achieve intelligent control of coke oven heating process, satisfy the actual production need, and has great practical value.
Improving Quality of Clustering using Cellular Automata for Information retrieval

Clustering has been widely applied to Information Retrieval (IR) on the grounds of its potential improved effectiveness over inverted file search. Clustering is a mostly unsupervised procedure and the majority of the clustering algorithms depend on certain assumptions in order to define the subgroups present in a data set . A clustering quality measure is a function that, given a data set and its partition into clusters, returns a non-negative real number representing the quality of that clustering. Moreover, they may behave in a different way depending on the features of the data set and their input parameters values. Therefore, in most applications the resulting clustering scheme requires some sort of evaluation as regards its validity. The quality of clustering can be enhanced by using a Cellular Automata Classifier for information retrieval. In this study we take the view that if cellular automata with clustering is applied to search results (query-specific clustering), then it has the potential to increase the retrieval effectiveness compared both to that of static clustering and of conventional inverted file search. We conducted a number of experiments using ten document collections and eight hierarchic clustering methods. Our results show that the effectiveness of query-specific clustering with cellular automata is indeed higher and suggest that there is scope for its application to IR.
Modeling of Lexical Relations Between Topics Retrieved from DBLP Journals

In this paper we present a method for getting topics from aims and scopes in DBLP journals and following construction of their hierarchical order. We focused on semantic relations between topics. Our method is fully automatic but manual cleaning of topic database would lead to much better accuracy. Another purpose of our work is to provide similar system to ACM classification system. We want to provide better, newer and fully automatic system contrary to ACM.
Affordance-Based Reasoning in Robot Task Planning

Humans are able to come up with plans to achieve their goals, and to adapt these plans to changes in their environment, ﬁnding ﬁxes, alternatives and taking advantages of opportunities without much deliberation. For example, they may use a tea kettle to water the plants, or a mug instead of a glass. Despite decades of research, artiﬁcial agents are not as robust or as ﬂexible. In this work, we introduce three reasoning phases that use af-fordances to enable such robustness and ﬂexibility in robot task planning. The ﬁrst phase generates a focused planning problem. The second phase expands the domain where necessary while the third and ﬁnal reasoning phase uses affordances during plan execution and monitoring. This is accomplished by combining Hierarchical Task Network planning, description logics, and a robust execution/monitoring system.
A Vesicular Stomatitis Virus Replicon-Based Bioassay for the Rapid and Sensitive Determination of Multi-Species Type I Interferon

Type I interferons (IFN) comprise a family of cytokines that signal through a common cellular receptor to induce a plethora of genes with antiviral and other activities. Recombinant IFNs are used for the treatment of hepatitis C virus infection, multiple sclerosis, and certain malignancies. The capability of type I IFN to suppress virus replication and resultant cytopathic effects is frequently used to measure their bioactivity. However, these assays are time-consuming and require appropriate biosafety containment. In this study, an improved IFN assay is presented which is based on a recombinant vesicular stomatitis virus (VSV) replicon encoding two reporter proteins, firefly luciferase and green fluorescent protein. The vector lacks the essential envelope glycoprotein (G) gene of VSV and is propagated on a G protein-expressing transgenic cell line. Several mammalian and avian cells turned out to be susceptible to infection with the complemented replicon particles. Infected cells readily expressed the reporter proteins at high levels five hours post infection. When human fibroblasts were treated with serial dilutions of human IFN-β prior to infection, reporter expression was accordingly suppressed. This method was more sensitive and faster than a classical IFN bioassay based on VSV cytopathic effects. In addition, the antiviral activity of human IFN-λ (interleukin-29), a type III IFN, was determined on Calu-3 cells. Both IFN-β and IFN-λ were acid-stable, but only IFN-β was resistant to alkaline treatment. The antiviral activities of canine, porcine, and avian type I IFN were analysed with cell lines derived from the corresponding species. This safe bioassay will be useful for the rapid and sensitive quantification of multi-species type I IFN and potentially other antiviral cytokines.
Under Consideration for Publication in Theory and Practice of Logic Programming Detection and Exploitation of Functional Dependencies for Model Generation

Recent work in Answer Set Programming has integrated ideas from Constraint Programming. This has led to a new eld called ASP Modulo CSP (CASP), in which the ASP language is enriched with constraint atoms representing constraint satisfaction problems. These constraints have a more compact grounding and are handled by a new generation of search algorithms. However , the burden is on the modeler to exploit these new constructs in his declarative problem specications. Here, we explore how to remove this burden by automatically generating constraint atoms. We do so in the context of FO(·) IDP , a knowledge representation language that extends rst-order logic with, among others, inductive denitions, arithmetic and aggregates. We uncover functional dependencies in declarative problem specications with a theorem prover and exploit them with a transformation that introduces functions. Experimental evaluation shows that we obtain more compact groundings and better search performance.
New Compression Techniques for Content-based Retrieval 1

Due to the proliferation of multimedia information over the internet, users are confronted with large amounts of content from many sources around the world. Techniques that enable users to efficiently search and exchange information are greatly needed. Content-based retrieval system was proposed to automatically annotate and index the multimedia information by their own audio/visual contents instead of text-based keywords that were manually entered. Most of current content-based retrieval systems are designed in a centralized fashion where feature extraction, indexing and querying are all done in a single database server. This paradigm faces problems of intensive computation and difficulty to scale up.
Perception of non-verbal emotional listener feedback

This paper reports on a listening test assessing the perception of short non-verbal emotional vocalisations emitted by a listener as feedback to the speaker. We clarify the concepts backchannel and feedback, and investigate the use of affect bursts as a means of giving emotional feedback via the backchannel. Experiments with German and Dutch subjects confirm that the recognition of emotion from affect bursts in a dialogical context is similar to their perception in isolation. We also investigate the acceptability of affect bursts when used as listener feedback. Acceptability appears to be linked to display rules for emotion expression. While many ratings were similar between Dutch and German listeners, a number of clear differences was found, suggesting language-specific affect bursts.
Opus: University of Bath Online Publication Store the Optimized String Dynamic Photovoltaic Array

from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. This version is made available in accordance with publisher policies. Please cite only the published version using the reference above. Abstract—This paper presents a novel system for producing the optimum power output from photovoltaic arrays using dynamic cell reconfiguration. The proposed approach is the first in the literature that creates multi-cell sub-strings using individual cells that have been characterized and categorized ensuring maximum power extraction for a given irradiance profile. This optimized and decentralized PV architecture can produce significantly more power than a static equivalent (by an average of 22.6%) and also compared to an alternative irradiance equalized dynamic photovoltaic array (IEq-DPVA) (by an average of 13.7%)). The paper identifies the hardware requirements to produce such a system and it describes an algorithm that performs the optimized string reconfiguration strategy. Finally, a simulator programmed in MATLAB is used to compare the performance of the optimized string DPVA (OS-DPVA) against an Irradiance equalized DPVA in a series of flexibility tests.
A Connectionist Model for Part of Speech Tagging

AutoTutor is a fully automated tutoring system that attempts to comprehend learner contributions and formulate appropriate dialogue moves. This paper reports the mechanisms and performance of one of AutoTutor’s language modules, the word tagging module. AutoTutor’s word tagging module determines the part of speech tag for every word in the learner’s contributions. It uses a two part procedure: it first consults a lexicon to identify the set of possible tags for each word, then it uses a neural network to select a single tag for each word. Performance assessments were made on a corpus of oral tutorial dialogue, as opposed to well-formed printed text. The lexicon provided the correct tag, as one member of a set, for 97% of the words and 91.6% of the neural network’s first-choice tags matched assignments by humans.
Proactive market orientation and innovation in India: The moderating role of intrafirm causal ambiguity

Abstract Despite the implication of organizational resources and the resource-based view of the firm, the market orientation literature has not examined associated constructs. Additionally, while it is recognized that emerging economies (e.g., India) are key drivers of economic growth, this literature has not paid sufficient attention to such markets, with few exceptions. We examine the impact of proactive market orientation on innovation capability, and performance in a sample of predominantly service firms, in a culture characterized by high power distance and low uncertainty avoidance. We contribute by conceptualizing and demonstrating the moderating impact of intrafirm causal ambiguity, drawn from resource-based theories of the firm. Based on Structural Equation Modelling analysis of responses to a survey of marketing managers, we find that intra-firm causal ambiguity moderates the proactive market orientation-innovation capability relationship, while this strategic orientation is linked to business performance through innovation. We discuss these findings, limitations, implications, and directions for future research.
An intelligent SA-adaptive interface to aid supervisory control of a UAV swarm

Building and maintaining Situation Awareness (SA) during supervisory control of a swarm of highly automated Unmanned Aerial Vehicles (UAV) is a complex and visually demanding process, which is often affected by weak scanning behaviors of the human operators. As a consequence severe errors, such as incorrect decisions, are likely to occur. This paper presents an Intelligent SA-Adaptive Interface (ISAAI) for supervisory control of a UAV swarm, which aims at optimizing the scanning behavior of a human operator with regard to his/her actual SA-needs. Therefore, the ISAAI integrates an eye movement based technique to assess human operator SA during mission execution and a technique for guiding visual attention to relevant but unattended information.
Torque quality assessment and sizing optimization for surface mounted permanent magnet machines

Torque quality assessment and optimization methods are presented in this paper. General purpose sizing equations are obtained and sizing optimization of the slotless TORUS machine is shown for maximum power density or efficiency points. For pulsating torque analysis, general instantaneous electromagnetic torque equation and torque ripple factor (TRF) analysis are carried out. Besides, stator winding distribution factor and rotor PM skew factor, excitation field form factor to indicate the excitation field harmonics, open slot factor to indicate the slot effect based on the calculation of airgap permeance are introduced for nonslotted and slotted axial flux surface mounted PM machines. Based on the above analysis, optimum design can be achieved for minimum ripple torque. On the other hand, cogging torque can be canceled using nonslotted structure. A slotless TORUS machine is used as a sample application for the torque ripple minimization in the paper. Furthermore, 2D and 3D finite element analysis (FEA) of both nonslotted and slotted surface mounted PM TORUS type (axial flux external rotor internal stator) structure, AFIR type (axial flux internal rotor external stator) structure and RFSM (radial flux internal rotor external stator) type structures are investigated for an insight into pulsating torques, ripple torques and cogging torques. The results obtained from both TRF analysis and 2D/3D FEA are illustrated in the paper.
An Extended RBAC Model for Uniform Implementation of Role Hierarchy and Constraint

Role based access control (RBAC) has been widely adopted as a policy neutral access control model by many IT corporations. RBAC96, which is the most famous family of RBAC models, provides a common frame reference for related research and development. Many properties proposed in the family, e.g. limited inheritance, mutually exclusive roles, cardinality, and interaction, have been separately discussed in the previous work. In this paper, an extended RBAC model implementing those properties is proposed to provide an approach for implementing RBAC3. The extended RBAC model is based on deputy mechanism and is called deputy-based access control (DBAC). Since the private role hierarchy and constraint can be uniformly handled in DBAC, a flexible and powerful access control system can be implemented.
Differences of Opinion, Short-Sales Constraints, and Market Crashes

We develop a theory of market crashes based on differences of opinion among investors. Because of short-sales constraints, bearish investors do not initially participate in the market and their information is not revealed in prices. However, if other previously bullish investors bail out of the market, the originally bearish group may become the marginal "support buyers," and more will be learned about their signals. Thus accumulated hidden information comes out during market declines. The model explains a variety of stylized facts about crashes and also makes a distinctive new prediction--that returns will be more negatively skewed conditional on high trading volume. Copyright 2003, Oxford University Press.
Mammalian cells express three distinct dynein heavy chains that are localized to different cytoplasmic organelles

We describe two dynein heavy chain (DHC)-like polypeptides (DHCs 2 and 3) that are distinct from the heavy chain of conventional cytoplasmic dynein (DHC1) but are expressed in a variety of mammalian cells that lack axonemes. DHC2 is a distant member of the "cytoplasmic" branch of the dynein phylogenetic tree, while DHC3 shares more sequence similarity with dynein-like polypeptides that have been thought to be axonemal. Each cytoplasmic dynein is associated with distinct cellular organelles. DHC2 is localized predominantly to the Golgi apparatus. Moreover, the Golgi disperses upon microinjection of antibodies to DHC2, suggesting that this motor is involved in establishing proper Golgi organization. DCH3 is associated with as yet unidentified structures that may represent transport intermediates between two or more cytoplasmic compartments. Apparently, specific cytoplasmic dyneins, like individual members of the kinesin superfamily, play unique roles in the traffic of cytomembranes.
An ideal ANFIS-based approach for classification of biomedical signals employing wavelet sub-band energy-based characteristics feature

There is a critical linkage of the error detection and classification of various biomedical signals with the diagnosis of different abnormalities. In this paper, basing on the characteristic features of wavelet sub-band energy coefficient, an ideal approach has been implemented for ECG and EEG classification. The ECG and EEG signals are pre-processed using adaptive filter and further are decomposed into time-frequency representation by the use of wavelet transformation. These extracted wavelet coefficients are helpful in calculating certain statistical parameters. For the differentiation between normal and abnormal beats, the types of EEG and ECG beats are taken into consideration. For this classification, Adaptive Neuro-Fuzzy Inference System (ANFIS) is used. The real time signals are obtained from medical and diagnostic centers for the analysis purposes.
Identification of the Rps28 binding motif from yeast Edc3 involved in the autoregulatory feedback loop controlling RPS28B mRNA decay

In the yeast Saccharomyces cerevisiae, the Edc3 protein was previously reported to participate in the auto-regulatory feedback loop controlling the level of the RPS28B messenger RNA (mRNA). We show here that Edc3 binds directly and tightly to the globular core of Rps28 ribosomal protein. This binding occurs through a motif that is present exclusively in Edc3 proteins from yeast belonging to the Saccharomycetaceae phylum. Functional analyses indicate that the ability of Edc3 to interact with Rps28 is not required for its general function and for its role in the regulation of the YRA1 pre-mRNA decay. In contrast, this interaction appears to be exclusively required for the auto-regulatory mechanism controlling the RPS28B mRNA decay. These observations suggest a plausible model for the evolutionary appearance of a Rps28 binding motif in Edc3.
Informational Cascades vs . Network Externalities : An Empirical Investigation of Herding on Software Downloading

Herd behavior, i.e. everyone is doing what everyone else is doing (Banerjee 1992), portrays various social and economic situations where individuals are markedly influenced by the decisions of others, such as in financial investment, technology adoption, firms’ strategic decisions, political voting, and dining and fashion trends. When there are two restaurants next to each other, customers often pick the one with more seats occupied. Despite mediocre reviews, a New York Times bestseller can be sold well enough to continue as a bestseller (Bikhchandani et al. 1998).
Forgive Us Our Trespasses: Priming a Forgiving (But Not a Punishing) God Increases Unethical Behavior

Religious people differ in how punishing or forgiving they see their Gods. Such different beliefs may have distinct consequences in encouraging people to act in normative ways. Though a number of priming studies have shown a positive causal relationship between religion and normative behavior, few have primed different aspects of religion, and none has examined the punishing/forgiving dimension. In 3 experiments, Christians instructed to read and write about a forgiving God stole more money (Experiments 1 and 2) and cheated more on a math assignment (Experiment 3) than those who read and wrote about a punishing God, a forgiving human, a punishing human, or those in a control condition. These studies present a more complex and nuanced picture of the important relationship between religion and normative behavior.
Exploiting User Centered Design Approach and Interactivity in Web Based Software Developing

Human computer interaction (HCI) and software engineering approaches are always taken into the account together in order to make the well-organized software. Interactive design is the significant part of new media which has been proposed to the world for the past decades, and it is a very proficient technique. Interactive maps add more dimensions of information; they become a more and more helpful tools and resources. This research clarifies the idea of how we can smooth the progress of presenting and communicating the essential information using interactive manner. The interactive map of Bangkok underground train and sky train navigation routes map was developed as the case study using user-centered design (UCD) methodology as the fundamental developing processes. The main objective of the work is to develop the friendly and usable web based software that reduce the confusion and help users save times. The software developing processes in this work tend to focus on the users. And also the essential idea of the research is to take the uses and gratification communication theory of the users into account with the intention of providing what user requires by finding the real users’ requirements. This means the user can control software according to their needs and software act or response according to user’s requests. The paper mentions the role of communication theory, human computer interaction, and user-centered design software developing.
Bayesian function estimation using continuous wavelet dictionaries

We present a Bayesian approach for nonparametric curve estimation based on a continuous wavelet dictionary, where the unknown function is modeled by a random sum of wavelet functions at arbitrary locations and scales. By avoiding the dyadic constraints for orthonormal wavelet bases, the continuous overcomplete wavelet dictionary has greater flexibility to adapt to the structure of the data, and leads to sparse representations. The price for this flexibility is the computational challenge of searching over an infinite number of potential dictionary elements. We develop a reversible jump Markov Chain Monte Carlo algorithm which utilizes local features in the proposal distributions and leads to better mixing of the Markov chain. Performance comparison in terms of sparsity and mean square error is carried out on standard wavelet test functions. Results on a non-equally spaced example show that our method compares favorably to methods using interpolation or imputation.