Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Two-Switch-Based Switched Reluctance Motor Drive for Low-Cost High-Volume Applications

This paper presents a low-cost energy-efficient variable-speed drive for high-volume applications, such as home appliances, fans, and hand tools. A new low-cost power converter is proposed, and the drive system is realized using a two-phase switched reluctance motor and the proposed converter. The motor is capable of self-starting at any rotor position and four-quadrant operation. The converter is unique in that it has two capacitors for the energization of each phase and uses the main phase winding as energy storage for the secondary capacitor C2. The converter employs a single-switch-per-phase configuration, hence requiring only two controllable switching devices in total. The converter is inherently suited for two-phase motors having asymmetric stator phases to realize self-starting and speed reversal. Simple starting and C2 voltage control schemes are presented. This paper describes the analysis, modeling, control algorithm, and design considerations for a prototype drive system. Experimental verification and correlation with simulation results are presented. The proposed drive system offers a low-cost brushless variable-speed drive that is a potential alternative for conventional brush-commutator motors in high-volume applications.
Detecting and Blocking False Sentiment Propagation

Sentiment detection of a given expression involves interaction with its component constituents through rules such as polarity propagation, reversal or neutralization. Such compositionality-based sentiment detection usually performs better than a vote-based bag-ofwords approach. However, in some contexts, the polarity of the adjectival modifier may not always be correctly determined by such rules, especially when the adjectival modifier characterizes the noun so that its denotation becomes a particular concept or an object in customer reviews. In this paper, we examine adjectival modifiers in customer review sentences whose polarity should either be propagated (SHIFT) or not (UNSHIFT). We refine polarity propagation rules in the literature by considering both syntactic and semantic clues of the modified nouns and the verbs that take such nouns as arguments. The resulting rules are shown to work particularly well in detecting cases of ‘UNSHIFT’ above, improving the performance of overall sentiment detection at the clause level, especially in ‘neutral’ sentences. We also show that even such polarity that is not propagated is still necessary for identifying implicit sentiment of the adjacent clauses.
Survey of Reasoning using Neural networks

Reason and inference require process as well as memory skills by humans. Neural networks are able to process tasks like image recognition (better than humans) but in memory aspects are still limited (by attention mechanism, size). Recurrent Neural Network (RNN) and it's modified version LSTM are able to solve small memory contexts, but as context becomes larger than a threshold, it is difficult to use them. The Solution is to use large external memory. Still, it poses many challenges like, how to train neural networks for discrete memory representation, how to describe long term dependencies in sequential data etc. Most prominent neural architectures for such tasks are Memory networks: inference components combined with long term memory and Neural Turing Machines: neural networks using external memory resources. Also, additional techniques like attention mechanism, end to end gradient descent on discrete memory representation are needed to support these solutions. Preliminary results of above neural architectures on simple algorithms (sorting, copying) and Question Answering (based on story, dialogs) application are comparable with the state of the art. In this paper, I explain these architectures (in general), the additional techniques used and the results of their application.
Mobile landmark guide system based on LOD and SURF

In this paper, we present a mobile collaborative outdoor augmented reality system. The system will provide a user who captures image of a building facade with related introduction. The proposed system mainly consists of two major parts - annotation module and AR browsing module. Annotation module works with existing standards and linked data to allow users create annotations of the building. Annotation data in our system which only contains URI and metadata, such cluster ID, cluster centroid and the image feature vectors. When user using the system browsing the landmark in outdoor, the system first recognize the landmark and calculate the camera pose from the matching, and then the related introduction is retrieved from linked data through its URI. Experiments show that the proposed augmented reality system is efficient and robust in many cases.
THE DEVELOPMENT OF NEW CODED TARGETS FOR AUTOMATED POINT IDENTIFICATION AND NON CONTACT 3D SURFACE MEASUREMENTS

The central task of close-range photogrammetry is the solution of correspondence problem, i.e. determination of image coordinates for given space point for two and more images. The paper presents the results of developing and testing new coded targets for automated identification and coordinates determination of marked points. The developed coded targets are independent to location and rotation, provide the possibility of reliable detection and localisation in textured image and precise centre coordinates calculation. The coded targets have been used for automated 3D coordinates measurements by photogrammetric station of State Research Institute for Aviation System. The methodics of automated identification and 3D measurements technique are given. Also the estimations of system performance and measurements accuracy and approaches to high accuracy achievement are presented.
Fuzzy Self-Localization using Natural Features on an AIBO Robot in Robocup

In current RoboCup four-legged league the robots rely only on coloured landmarks for localisation. It is intended to remove these landmarks in a few years, as happened in other leagues. The odometry of four-legged robots is extremely unreliable and there is a high uncertainty in robot motion. Therefore, sensor-based localization is necessary. We propose to extend our previous technique for fuzzy selflocalization based on landmars, by including observations of the corners between the field lines. We show experimental tests in a simulator using only the field lines and the two nets.
Development of a Multipurpose GATEWAY-Based Lentiviral Tetracycline-Regulated Conditional RNAi System (GLTR)

RNA interference (RNAi) has become an essential technology for functional gene analysis. Its success, however, depends on the effective expression of RNAi-inducing small double-stranded interfering RNA molecules (siRNAs) in target cells. In many cell types, RNAi can be achieved by transfection of chemically synthesised siRNAs, which results in transient knockdown of protein expression. Expression of double-stranded short hairpin RNA (shRNA) provides another means to induce RNAi in cells that are hard to transfect. To facilitate the generation of stable, conditional RNAi cell lines, we have developed novel one- and two-component vector GATEWAY-compatible lentiviral tetracycline-regulated RNAi (GLTR) systems. The combination of a modified RNA-polymerase-III-dependent H1 RNA promoter (designated ‘THT’) for conditional shRNA expression with different lentiviral delivery vectors allows (1) the use of fluorescent proteins for colour-coded combinatorial RNAi or for monitoring RNAi induction (pGLTR-FP), (2) selection of transduced cells (pGLTR-S), and (3) the generation of conditional cell lines using a one vector system (pGLTR-X). All three systems were found to be suitable for the analysis of essential genes, such as CDC27, a component of the mitotic ubiquitin ligase APC/C, in cell lines and primary human cells.
A Multiresolution Gaussian Process Model for the Analysis of Large Spatial Datasets

We develop a multiresolution model to predict two-dimensional spatial fields based on irregularly spaced observations. The radial basis functions at each level of resolution are constructed using a Wendland compactly supported correlation function with the nodes arranged on a rectangular grid. The grid at each finer level increases by a factor of two and the basis functions are scaled to have a constant overlap. The coefficients associated with the basis functions at each level of resolution are distributed according to a Gaussian Markov random field (GMRF) and take advantage of the fact that the basis is organized as a lattice. Several numerical examples and analytical results establish that this scheme gives a good approximation to standard covariance functions such as the Matérn and also has flexibility to fit more complicated shapes. The other important feature of this model is that it can be applied to statistical inference for large spatial datasets because key matrices in the computations are sparse. The computational efficiency applies to both the evaluation of the likelihood and spatial predictions.
Functional Complexity Can Mitigate Performance Trade-Offs

Trade-offs are believed to impose major constraints on adaptive evolution, and they arise when modification of a trait improves one aspect of performance but incurs a cost in another. Here we show that performance costs that result from competing demands on one trait can be mitigated by compensatory changes in other traits, so long as performance has a complex basis. Numerical simulations indicate that increases in the number of traits that determine performance decrease the strength of performance trade-offs. In centrarchid fishes, multiple traits underlie suction feeding performance, and experimental data and hydrodynamic modeling show that combinations of traits evolve to increase the ability to feed on attached prey while mitigating costs to performance on evasive prey. Diet data for centrarchid species reveal a weak trade-off between these prey types, corroborating the results based on hydrodynamic modeling and suggesting that complexity in the functional basis of suction feeding performance enhances trophic diversification. Complexity may thus permit the evolution of combinations of high-performance behaviors that appear to violate underlying trade-offs, such as the ability to exert high suction forces with large gape. This phenomenon may promote morphological, functional, and ecological diversification in the face of the myriad selective demands organisms encounter.
Dose-Dependent Differential Regulation of Cytokine Secretion from Macrophages by Fractalkine1

Although expression of the fractalkine (CX3CL1, FKN) is enhanced in inflamed tissues, it is detected at steady state in various organs such as the intestine, and its receptor CX3CR1 is highly expressed in resident-type dendritic cells and macrophages. We hypothesized that FKN might regulate the inflammatory responses of these cells. Therefore, murine macrophages were pretreated with FKN and then stimulated with LPS. We found that macrophages pretreated with 0.03 nM FKN but not with 3 nM FKN secreted 50% less TNF-α than did cells treated with LPS alone. Cells treated with 0.03 nM FKN and LPS also showed reduced phosphorylation of ERK1/2 and reduced NF-κB p50 subunit. Interestingly, the p65 subunit of NF-κB was translocated to the nuclei but redistributed to the cytoplasm in the early phase by forming a complex with peroxisome proliferator-activated receptor (PPAR) γ. Exogenous 15-deoxy-Δ(12,14)-prostaglandin J2, a natural ligand for PPAR-γ, also induced redistribution of p65 with decreased TNF-α secretion after LPS challenge. Pretreatment with 0.03 nM but not 3 nM FKN increased the cellular levels of 15-deoxy-Δ(12,14)-prostaglandin J2 as well as mRNA of PPAR-γ. Requirement of PPAR-γ for the effect of 0.03 nM FKN was confirmed by small interfering RNA of PPAR-γ. In contrast, pretreatment with 3 nM FKN induced higher levels of IL-23 compared with cells pretreated with 0.03 nM FKN and produced TNF-α in a CX3CR1-dependent manner. These dose-dependent differential effects of FKN establish its novel role in immune homeostasis and inflammation.
Towards a Probabilistic Taxonomy of Many Concepts

Knowledge is indispensable to understanding. The ongoing information explosion highlights the need to enable machines to better understand electronic text in natural human language. The challenge lies in how to transfer human knowledge to machines. Much work has been devoted to creating universal ontologies for this purpose. However, none of the existing ontologies has the necessary depth and breadth to offer “universal understanding. ” In this paper, we present a universal, probabilistic ontology that is more comprehensive than any of the existing ontologies. It contains 2.7 million concepts harnessed automatically from a corpus of 1.68 billion web pages and two years’ worth of search log data. Unlike traditional knowledge bases that treat knowledge as black and white, it enables probabilistic interpretations of the information it contains. The probabilistic nature then enables it to incorporate heterogeneous information in a natural way. We present details of how the core ontology is constructed, and how it models knowledge’s inherent uncertainty, ambiguity, and inconsistency. We also discuss potential applications, e.g., understanding user intent, that can benefit from the taxonomy.
Integration of Transcriptional and Posttranslational Regulation in a Glucose Signal Transduction Pathway in Saccharomyces cerevisiae

ABSTRACT Expression of the HXT genes encoding glucose transporters in the budding yeast Saccharomyces cerevisiae is regulated by two interconnected glucose-signaling pathways: the Snf3/Rgt2-Rgt1 glucose induction pathway and the Snf1-Mig1 glucose repression pathway. The Snf3 and Rgt2 glucose sensors in the membrane generate a signal in the presence of glucose that inhibits the functions of Std1 and Mth1, paralogous proteins that regulate the function of the Rgt1 transcription factor, which binds to the HXT promoters. It is well established that glucose induces degradation of Mth1, but the fate of its paralogue Std1 has been less clear. We present evidence that glucose-induced degradation of Std1 via the SCFGrr1 ubiquitin-protein ligase and the 26S proteasome is obscured by feedback regulation of STD1 expression. Disappearance of Std1 in response to glucose is accelerated when glucose induction of STD1 expression due to feedback regulation by Rgt1 is prevented. The consequence of relieving feedback regulation of STD1 expression is that reestablishment of repression of HXT1 expression upon removal of glucose is delayed. In contrast, degradation of Mth1 is reinforced by glucose repression of MTH1 expression: disappearance of Mth1 is slowed when glucose repression of MTH1 expression is prevented, and this results in a delay in induction of HXT3 expression in response to glucose. Thus, the cellular levels of Std1 and Mth1, and, as a consequence, the kinetics of induction and repression of HXT gene expression, are closely regulated by interwoven transcriptional and posttranslational controls mediated by two different glucose-sensing pathways.
Real Scene Graphics Symbol Recognition

A common problem encountered in recognizing symbols in real-scene images is the perspective deformation. A character recognition method resistant to perspective deformation has been proposed in [4]. Particularly, a symbol is represented by a sequence of cross ratio spectra, in which 3D perspective deformation is modeled as a 1D uneven stretching. Dynamic Time Warping algorithm is employed to compare the similarity of spectrum sequences and to find the pixel-level correspondence between two symbols. In this paper, this method is employed to recognize real-scene symbols. The experiment shows that this method outperforms SIFT and Shape Context when recognizing symbols with severe perspective.
Low Complexity Scheduling Algorithms for Downlink Zero-Forcing Beamforming Systems

In this paper, the downlink zero-forcing beamforming strategy under perfect channel state information at the transmitter (CSIT) for the case of random packet arrivals is investigated. Under this setting, the relevant fairness criterion is the stabilization of all buffer queues which guarantees a bounded average delay for all users. In case of queue stability is the goal, it can be shown that allocating resources to maximize a queue-length-weighted sum of the rates which are feasible in the current time slot is a stabilizing policy. However, the high complexity of user selection or the feasible rates determination for optimal scheme may prevent the real-time scheduling operation. Two simplified algorithms were provided taking the channel state, queue state and orthogonality into to account. In particular, we pick the first user with the largest product between channel gain and queueing lengths, and select the remaining Nt-1 users to form the user set based on the greedy user selection method or takeing channel orientations into account as well. Simulation results show that the average delay performance of the simplified algorithms are reduced by less than 10% compared to optimal schemes.
Anisotropic materials appearance analysis using ellipsoidal mirror

Many real-world materials exhibit significant changes in appearance when rotated along a surface normal. The presence of this behavior is often referred to as visual anisotropy. Anisotropic appearance of spatially homogeneous materials is commonly characterized by a four-dimensional BRDF. Unfortunately, due to simplicity most past research has been devoted to three dimensional isotropic BRDFs. In this paper, we introduce an innovative, fast, and inexpensive image-based approach to detect the extent of anisotropy, its main axes and width of corresponding anisotropic highlights. The method does not rely on any moving parts and uses only an off-the-shelf ellipsoidal reflector with a compact camera. We analyze our findings with a material microgeometry scan, and present how results correspond to the microstructure of individual threads in a particular fabric. We show that knowledge of a material’s anisotropic behavior can be effectively used in order to design a material-dependent sampling pattern so as the material’s BRDF could be measured much more precisely in the same amount of time using a common gonioreflectometer.
Will It Spread or Not? The Effects of Social Influences and Network Topology on Innovation Diffusion

Innovation diffusion theory suggests that consumers differ concerning the number of contacts they have and the degree and the direction to which social influences determine their choice to adopt. To test the impacts of these factors on innovation diffusion, in particular the occurrence of hits and flops, a new agent-based model for innovation diffusion is introduced. This model departs from existing percolation models by using more realistic agents (both individual preferences and social influence) and more realistic networks (scale free with cost constraints). Furthermore, it allows consumers to weight the links they have, and it allows links to be directional. In this way this agent-based model tests the effect of VIPs who can have a relatively large impact on many consumers. Results indicate that markets with high social influence are more uncertain concerning the final success of the innovation and that it is more difficult for the innovation to take off. As consumers affect each other to adopt or not at the beginning of the diffusion, the new product has more difficulties to reach the critical mass that is necessary for the product to take off. In addition, results of the simulation experiments show under which conditions highly connected agents (VIPs) determine the final diffusion of the innovation. Although hubs are present in almost any network of consumers, their roles and their effects in different markets can be very different. Using a scale-free network with a cut-off parameter for the maximum number of connections a hub can have, the simulation results show that when hubs have limits to the maximum number of connections the innovation diffusion is severely hampered, and it becomes much more uncertain. However, it is found that the effect of VIPs on the diffusion curve is often overestimated. In fact when the influence of VIPs on the decision making of the consumers is strengthened compared with the influence of normal friends, the diffusion of the innovation is not substantially facilitated. It can be concluded that the importance of VIPs resides in their capacity to inform many consumers and not in a stronger persuasive power.
eGov website evolution study within strategic planning

Public administration has been looking for new guarantees of visibility and transparency for the implementation of public policies. In this paper, the experience is reported of a supervising institution, the Mato Grosso State Audit Court - TCE-MT that, when realigning its strategic planning in 2005, realized the need to install tools that confirm the accomplishment of its mission of supervising and orienting public managers with a closer approach to society. For this, and to strengthen communication with the general public, a constant website evaluation process has begun so that the TCE-MT would be able to fulfill the purpose of informing and ensuring transparency of its acts and of those under its jurisdiction, with the objective of getting the public interested in following the results of public policies. This meant it was important for the institution to have very clear web concepts, communication policies and strategic information management, including setting parameters with the electronic government concepts, and thus formulate its first website planning, aligned with the objectives of long term Institutional Planning. Therefore, this study shows the alignment of the institution's strategic planning to the website's technological evolution throughout the biennia in accordance with the electronic government guidelines.
Design of an Ultra Low-Power RFID Baseband Processor Featuring an AES Cryptography Engine

Cheap passive radio frequency identification (RFID) tags operating in ultra high frequency (UHF) bands are fostering innovation in several field such as building access control, goods tracking, supply chains management and automatic product checkout. RFID transponders can also be coupled to tiny sensors, enabling non invasive monitoring of environmental and personal parameters. To ensure the privacy of highly sensitive data, encryption and authentication capabilities should be embedded in RFID devices, in a fashion compatible with tight power budgets of wireless devices. In this contribution, a baseband-processor is introduced, which complies with ISO 18000-6C (EPC Class1 Gen2) protocol and integrates AES primitives aimed at secure data transmission. Performance of passive RFID devices is limited by the available power, harvested from the incoming radiation. Power-saving strategies are devised, both at the system and the circuit levels. A set of standard cells has been designed, suitable for near-threshold voltage operations. Physical implementation on CMOS 0.18um technology has been carried out and the chip has being fabricated.
Optimization of the Medium for the Production of Extracellular Amylase by the Pseudomonas stutzeri ISL B5 Isolated from Municipal Solid Waste

The management of municipal solid waste is one of the major problems of the present world. The use of microbial enzymes for sustainable management of the solid waste is the need of the time. In the present study, we have isolated a potent amylase producing strain (ISL B5) from municipal solid waste. The strain was identified as Pseudomonas stutzeri (P. stutzeri) both biochemically and by 16S rDNA sequencing. The optimization studies revealed that the strain ISL B5 exhibited maximum activity in the liquid media containing 2% starch (2.77 U/ml), 0.8% peptone (2.77 U/ml), and 0.001% Ca2+ ion (2.49 U/ml) under the pH 7.5 (2.59 U/ml), temperature 40°C (2.63 U/ml), and 25 h of incubation period (2.49 U/ml). The highest activity of crude enzyme has also been optimized at the pH 8 (2.49 U/ml).