Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a non-probabilistic approach to hybrid geometry-topological SLAM

This article introduces a new approach to Simultaneous Localization and Mapping (SLAM) which pursues robustness and accuracy in large-scale environments. Unlike most successful works on SLAM, we use non-probability method to build the local geometry map, and let the loop closure data fusion module to deal with the inconsistency of global map which is the most difficult problem in SLAM. We also design other modules which are involved in our framework. In the Map partition module, we present a novel concept, which is called reinforced Sensed-Space Overlap, and use it in graph-based segmentation of the local region segmentation algorithm. The assumption-proven strategies were used in the loop closure data fusion module. In the meantime, two different algorithms were presented. The performance of framework and each module are testified by the experimental results.
Living With a Lifetime Store

Storage trends have brought us to the point where it is affordable to keep a complete digital record of one’s life. The MyLifeBits system is designed to store and manage a lifetime’s worth of data. To experiment with a lifetime store, we have digitized everything possible from Gordon Bell’s life. These are added to his existing digital assets. We also continue to add new digital capture such as web pages, telephone, radio and television. In this paper we explain the key requirements of a lifetime store. We show how typed links and database features are keys to the usefulness of such a system.
Feasibility of random basis function approximators for modeling and control

We discuss the role of random basis function approximators in modeling and control. We analyze the published work on random basis function approximators and demonstrate that their favorable error rate of convergence O(1/n) is guaranteed only with very substantial computational resources. We also discuss implications of our analysis for applications of neural networks in modeling and control.
2D meets 3D: a human-centered interface for visual data exploration

There is still a controversial debate on the usefulness of 3D user interfaces. Most of the time, 2D metaphors are force-fitted to establish a rich set of functionality. With the aim of shifting the 20-year-old 2D WIMP (windows, icons, menus, and pointing device) paradigm towards a more natural and intuitive 3D user interface, we have developed a hybrid 2D + 3D prototype targeted at immersive environments. Our complementary display and interaction environment combines visual design techniques with mixed-mode interaction to support typical tasks of information workers to the greatest potential. To achieve this, we match visualization and interaction metaphors by the principle of dimensional congruence. This results in a sophisticated and more intuitive user interface. An ongoing evaluation gives encouraging feedback and shows that even non-expert users can efficiently work with the system.
Power Optimization of LNA for LTE Receiver

In the up-coming wireless standards, focus is not only for improving the quality of service but also towards finding the integrated solution for all the existing standards. In this regard, system-on-chip (SOC) must have the ability to process multi-mode and multi-band signals without any relaxation in their energy consumption. Hence in circuit realization, transceivers' SOCs may require multiple LNAs (low-noise amplifier), key component of receiver, where the power requirement of individual amplifier is critical in-order to elongate the battery life. In this paper, the power of LNA is optimized based on the sensitivity requirement of the receiver. Accordingly, the LTE receiver performance assessment is carried out to find the maximum noise limitation of the LNA. For meeting the receiver noise performance, a sub-threshold LNA is implemented that consumes a total power of 706 uW with an affordable 2 dB noise figure (NF). The resulting LNA is implemented in 65nm technology and it is compensated against process variations. The low power LNA achieves about S21 of 12.9 dB in typical corner case and undergoes only a maximum change around +/-3.4% when all the corners are considered. Comparison with other microwatt LNAs, shows that presented amplifier offers the best NF with a moderate figure of merit (FOM).
TagEz: Flickr Tag Recommendation

User tagging of multimedia has emerged as the pre-mier organizational tool for large sets of rapidly growing information. We present a tag prediction system for images on Flickr which combines both linguistic and vision features. We describe methods for building language models of tags on Flickr, similar in spirit to traditional language modeling in the NLP community. We evaluate our system against held-out Flickr data, and achieve competitive performance.
A low magnetic bias sub-millimetre wave semiconductor junction circulator

This paper presents a design for a semiconductor junction circulator to work in the sub-millimetre wave frequency range. An InSb disk is modelled for a low steady applied axial magnetic field. An approach was utilised to design the circulator with minimum required magnetic biasing by exploiting a frequency range above the extraordinary wave resonant frequency. Circulation at frequency of 650GHz with about 9% 10dB bandwidth was predicted using an applied magnetic field as low as 0.2T. The Green's function description is verified using a commercially available electromagnetic simulation package with resultant electromagnetic field patterns given.
Variational methods for Reinforcement Learning

We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transition matrix is obtained from which the optimal decision policy is formed. The classical maximum likelihood point estimate of the transition model does not reect the uncertainty in the estimate of the transition model and the resulting policies may consequently lack a sucient degree of exploration. We consider a Bayesian alternative that maintains a distribution over the transition so that the resulting policy takes into account the limited experience of the environment. The resulting algorithm is formally intractable and we discuss two approximate solution methods, Variational Bayes and Expectation Propagation.
Effect of Nitrate on Nodule and Root Growth of Soybean (Glycine max (L.) Merr.)

The application of combined nitrogen, especially nitrate, to soybean plants is known to strongly inhibit nodule formation, growth and nitrogen fixation. In the present study, we measured the effects of supplying 5 mM nitrate on the growth of nodules, primary root, and lateral roots under light at 28 °C or dark at 18 °C conditions. Photographs of the nodulated roots were periodically taken by a digital camera at 1-h intervals, and the size of the nodules was measured with newly developed computer software. Nodule growth was depressed approximately 7 h after the addition of nitrate under light conditions. The nodule growth rate under dark conditions was almost half that under light conditions, and nodule growth was further suppressed by the addition of 5 mM nitrate. Similar results were observed for the extending growth rate of the primary root as those for nodule growth supplied with 5 mM nitrate under light/dark conditions. In contrast, the growth of lateral roots was promoted by the addition of 5 mM nitrate. The 2D-PAGE profiles of nodule protein showed similar patterns between the 0 and 5 mM nitrate treatments, which suggested that metabolic integrity may be maintained with the 5 mM nitrate treatment. Further studies are required to confirm whether light or temperature condition may give the primary effect on the growth of nodules and roots.
Finite state machine for mutation

In this paper an attempt has been made to represent biological mutational activities through sequential mathematical machines. Begin with a brief theory of finite state sequential ma- chines genetic sequences are presented in a systematic manner. A mutator has been shown as a variety of finite state machines. The mutation is studied systematically and an automaton have been constructed with the biological sequences. It has also been shown that the automaton constructed is the minimal state automaton. DNA sequences are represented as regular expressions. A case study with FMR-1 gene is presented as an illustration.
Study on Faulty Phase Selection Based on the Wavelet Power Spectrum Entropy and LIBSVM

Fault phase selection is studied in this paper based on the wavelet power spectrum entropy and LIBSVM for transmission line. First, MATLAB is used to simulate five fault types and obtain a variety of fault voltage waveforms. Second, the simulation waveform is transformed to extract the energy spectrum entropy which is pretreatment to greatly reduce the number of data dimensions and effectively optimize the input data of LIBSVM. Finally, LIBSVM is used to select fault phase, experimental results show that the method is very effective.
Estimation of Super-Resolved Video Dynamics

In this work, we propose an efficient methodology for video super-resolution, that is, the recovery of a sequence of high-resolution images from its low-resolution counterpart. The optimization problem associated to video super-resolution has several specificities which makes it particularly challenging. A first barrier is the high-dimensionality of the problem, which derives from the extra temporal dimension and the unknown parametrization of the dynamical model characterizing the video. A second obstacle is the non-differentiability and the non-convexity of some of the terms of the cost function: the non-differentiability stems from the use of regularization terms of the state of the art (e.g., to enforce sparsity) whereas the non-convexity appears as soon as the motion describing the video is unknown. In this paper, we propose an overall algorithmic framework to address the video super-resolution problem. Our approach is based on fast gradient evaluation methods and modern optimization techniques for non-differentiable/non-convex problems. As a consequence, unlike previous work in the field, we show that there exists a provably-convergent method estimating both the high-resolution image sequence and the underlying motion with a complexity linear in the problem dimensions. We assess the proposed optimization methods on videos of the MPI Sintel data set, known to be a challenging optical-flow benchmark.
Empirical investigation of web design attributes affecting brand perception

The web has become a mainstream communication tool used by companies, institutions, celebrities, and politicians to establish, reinforce, or repurpose their brand, almost bypassing more conventional branding media. In this scenario, understanding the effects of the different design qualities of a website on users' attitude towards the brand is of major importance. This paper contributes to the exploration of this issue by presenting a wide empirical study that investigates the degree to which users' perception of a brand is affected by different design aspects of a website, namely usability, aesthetics, and communicability. The results of this multidimensional analysis have implications on HCI research and practice, as they provide empirically founded guidelines to prioritize design choices in relationship to branding goals.
Smart Phone Based Indoor Pedestrian Localization System

Indoor Positioning Systems (IPSs) are emerging computing systems that can locate objects or people inside indoor environment. This technology shows assurance for future mobile apps that can be used in malls, museums, hospitals, airports and college campuses for self localization. Despite advances in Global Positioning System (GPS) technology, indoor spaces are still out of reach of satellites. GPS signals are not designed to penetrate most construction materials. An IPS relies on nearby anchors or landmarks, and uses various sensing schemes including artificial vision, Wi-Fi, Bluetooth, Camera images etc. In this paper, we present a system that leverages the camera and Wi-Fi present in the smart phones carried by users, to track them as they traverse in indoor environments. It makes use of a radio map of an indoor environment. A significant challenge that our system surmounts is to estimate user's position without any prior user-specific knowledge, such as the user's initial location. The results obtained after conducting simulations demonstrate the validity and suitability of the proposed algorithm to provide a high performance level in terms of positional accuracy and scalability.
Web-Based Technical Appendix to The Uneven Pace of Deindustrialization in the OECD

Throughout the OECD, the period since the 1970s saw a secular decline in manufacturing's share of GDP and a secular rise in the share of services. Despite this being a central feature of growth, the economic forces behind deindustrialization and the reasons why its pace varied so markedly across OECD countries are not well understood. Adopting an econometric approach founded in neoclassical production theory, we provide empirical evidence on how changes in technology, relative prices and factor endowments (in particular, educational attainment) interacted with national labour market institutions. We show how higher employment protection slowed structural change. The views expressed are those of the authors alone and should not be attributed to any institution to which the authors are affiliated. We are grateful Vignoles, conference and seminar participants for helpful comments. We would also like to thank Webb for their help with the data. We are grateful to Martin Stewart for research assistance. All opinions, results, and any errors are the authors' responsibility alone.
Output, Input and Incentives Measurement for Non-market Activity The case of Italian Revenue Agency

The Italian Revenue Agency (hereinafter Agency) is a new Government body, founded in 2001, and it has the strategic objective of maintaining and encouraging taxpayers in their willingness to comply with their tax duties as laid down by law. It works in a self-government framework, regulated by an annual agreement with the Ministry of Economy, who sets the aims to be reached and the related budget. The Agency has two main goals: improving the quality of provided services and the efficiency in its production process. In order to achieve these two goals, analytic tools are now needed to monitor the input, output and productivity over time.
Aggregate R&D Expenditure and Endogenous Economic Growth

The aim of this paper is to theoretically and empirically analyze the role that aggregate R&Dexpenditures play in economic growth. We introduce a technology of innovation based on R&Dexpenditures instead of labor to see how this consideration generates sustainable growth determined endogenously, even if population growth does not exist. Therefore, it seems relevant to analyze the effects of different fiscal policies. For the empirical analysis we make use of an econometric model obtained from the decentralized equilibrium. More precisely, the specification is obtained using the free-entry condition that the competitive equilibrium states for the R&D-activity and the policy function defining the dynamic evolution of patentees' price.
Internet Threat Detection, Prediction and Relevant Reaction System for Pattern-freeWorm

With the development of Internet technology, the popularity of the malicious threat has grown beyond our imagination. The emergence of intelligent, sophisticated attack techniques makes the Internet services more vulnerable than ever, which become an important business technology in e-commerce. Many techniques have been proposed to detect (Zou et al., 2003; Lakhina and Diot, 2005; and Krishnamurthy et al., 2003), predict (Kai-Gui Wu, 2006 and Songjie Wei and Kirkovic, 2005) and react (Castaneda and Xuy, 2004 and Williamson, 2002) the malicious worm traffic, yet have limitations. In this paper, we proposed Internet threat detection, prediction and relevant reaction system for pattern-free worm. Our proposed system allows the system to detect, predict, react using grouping traffic characteristics. According to the proposed system, traffic factors generated by respective worms using k-means algorithms are grouped into N groups so that a great of Information may be effectively understood and a worm generated afterward is involved with characteristics of relevant group using cosine similarity for prediction and reaction.
A Novel High-Content Flow Cytometric Method for Assessing the Viability and Damage of Rat Retinal Ganglion Cells

Purpose The aim of the study was to develop a high-content flow cytometric method for assessing the viability and damage of small, medium, and large retinal ganglion cells (RGCs) in N-methyl-D-aspartic acid (NMDA)-injury model. Methods/Results Retinal toxicity was induced in rats by intravitreal injection of NMDA and RGCs were retrogradely labeled with Fluoro-Gold (FG). Seven days post-NMDA injection, flatmount and flow cytometric methods were used to evaluate RGCs. In addition, the RGC area diameter (D(a)) obtained from retinal flatmount imaging were plotted versus apparent volume diameter (D(v)) obtained from flow cytometry for the same cumulative cell number (sequentially from small to large RGCs) percentile (Q) to establish their relationship for accurately determining RGC sizes. Good correlation (r = 0.9718) was found between D(a) and apparent D(v). Both flatmount and flow cytometric analyses of RGCs showed that 40 mM NMDA significantly reduced the numbers of small and medium RGCs but not large RGCs. Additionally, flow cytometry showed that the geometric means of FG and thy-1 intensities in three types of RGCs decreased to 90.96±2.24% (P<0.05) and 91.78±1.89% (P>0.05) for small, 69.62±2.11% (P<0.01) and 69.07±2.98% (P<0.01) for medium, and 69.68±6.48% (P<0.05) and 69.91±6.23% (P<0.05) for large as compared with the normal RGCs. Conclusion The established flow cytometric method provides high-content analysis for differential evaluation of RGC number and status and should be useful for the evaluation of various models of optic nerve injury and the effects of potential neuroprotective agents.
Flying Off Course: The Economics of International Airlines

Characteristics and trends in airline operations the regulation of international air transport deregulation and its impact on the industry deregulation and Europe - 1992 and all that the structure of airline costs determinants of airline costs big is beautiful - the benefits of scale in airline operations the economics of passenger charters airline marketing and product planning the nature of passenger demand forecasting demand pricing policies and fare structures the economics of air freight future prospects. Appendices: freedom of the air definition of airline terms.
Two Novel Structures for Tunable MEMS Capacitor with RF Applications

Abstract—Two novel structures for high-Q MEMS tumble capacitors are presented. The proposed designs include full plate as well as the comb structured capacitors. They can be fabricated employing surface micromachining technology which is CMOS-compatible. The structures do not require the cantilever beams which introduce considerable series resistance to the capacitor and decrease the quality factor. Therefore, our proposed structures achieve better Q in a smaller die area. The simulated results for 1 pF full plate capacitor shows a tuning range of 42% and a Q of 47 at 1 GHz. However, with the same initial capacitance, but the comb structure, the tuning range is increased to 43% but the Q is decreased to 45 at 1 GHz. The simulated Pull-in voltage with no residual stress is 3.5 V for both capacitors. The S11 responses are reported for a frequency range from 1 up to 4 GHz.
Phonetic classification of timit segments preprocessed with lyon's cochlear model using a supervised/unsupervised hybrid neural network

We report results on vowel and stop consonant recognition with tokens extracted from the TIMIT database. Our current system diiers from others doing similar tasks in that we do not use any speciic time normalization techniques. We use a very detailed biologically motivated input representation of the speech tokens-Lyon's cochlear model as implemented by Slaney 20]. This detailed, high dimensional representation, known as a cochleagram, is classi-ed by either a back-propagation or by a hybrid super-vised/unsupervised neural network classiier. The hybrid network is composed of a biologically motivated unsuper-vised network and a supervised back-propagation network. This approach produces results comparable to those obtained by others without the addition of time normaliza-tion.
Design of the portable instrument for bioelectrical impedance

Bioelectrical impedance is a body's important parameter, which, to a certain degree, reflects the physiological state of the human body. According to the shortage that traditional five-segments model of human body impedance can't satisfy the needs of figuring out human trunk subdivision impedance, the exiting solution of eight-segments bioelectrical impedance module is premised on the basis of symmetrical limbs (symmetrical limbs is not existed in fact). Therefore, an asymmetrical model for measuring the impedance of eight-segments of human body is proposed, two solving equations are used to supplement the impedance relation of the left and right upper limbs and the impedance of the left and right lower limbs by using the five-segments impedance model, solving the problem in the asymmetric eight-segments impedance model,where the resistance is hard to work out. Based on this theory, a portable eight-segments body impedance instrument is designed, an integral design of this instrument is introduced and a contrast experiment with the InBody770 instrument is designed. The results show that the accuracy of the measuring instrument is close to the InBody770 instrument, which meets the needs of measuring the subdivision impedance in human trunk part.
Permutation techniques based on discrete chaos and their utilization in image encryption

To achieve the Shannon's confusion and diffusion properties, an image encryption algorithm should include permutations and substitutions. This paper presents three different permutation techniques based on discrete chaotic maps. The permutation techniques are, then, evaluated using two measures: the average distance one pixel moved and the average distance between two adjacent pixels. The evaluation is performed for different matrix sizes and considers the scrambling efficiency and the execution time ratios. Furthermore, each of the permutation techniques is used in a simple encryption system and the encrypted images are evaluated using correlation coefficients, differential attack measures, the NIST statistical test suite and sensitivity analysis where promising encryption results are obtained.
An Automatic System Of Segmentation, Recognition And Detection For Any Image By UML

Unified Modeling Language, a standard language for designing and documenting a system in an object-oriented manner. UML is not a programming language it is basically a modeling language it’s a language by which Technical architects can communicate with developers. It’s a blue print of our source code. In Our Paper UML model has been designed for the compression of any image using transform method because compressed image take a very less transmission time for sending image from one node to another node and at receiving end after decompression re find the original image. The class diagram and sequence diagram for the compression of an image are depicted in this paper. Some run length coding technique is also reported in this paper with activity diagram.