Miracle-dz/UniFAR-FTUs huggingface dataset:
Intelligent Information Sharing Systems

Management in the 1990s Management in the 1990s is an industry and governmental agency supported research program. Its aim is to develop a better understanding of the managerial issues of the 1990s and how to deal most effectively with them, particularly as these issues revolve around anticipated advances in Information Technology. Assisting the work of the Sloan School scholars with financial support and as working partners in research are: The conclusions or opinions expressed in this paper are those of the author(s) and do not necessarily reflect the opinion of the Massachussetts Institute of Technology, the Management in the 1990s Research Program, or its sponsoring organizations. Crowston implemented and maintains the mail gateway between our system and the outside network world, Chee-Seng Chow helped implement the first version of the central mail sorter, and Constance Perin collaborated in some of the early studies of information sharing in organizations. We gratefully acknowledge all these contributions. Summary As it becomes both technically and economically feasible to send electronic messages and other documents to large numbers of possible recipients, the problem of deciding who should receive a particular piece of information will become increasingly important. This paper focuses on the application of techniques from artificial intelligence, user interface design, and organizational science to help people share interesting and relevant information without being inundated by the potentially vast amount of less useful information. 1 Much of the work that has been done on computer-mediated communication systems, such as electronic mail, computer conferencing, and electronic bulletin boards, has focused on technical capabilities and standards for transporting and storing messages. In this paper, we propose to shift our focus to a more general problem that we will refer to as the information sharing problem. The information sharing problem involves disseminating information such that the information reaches those people to whom it is valuable and yet does not interfere with the information processing of people who will find no value in its contents. We argue that this problem will become increasingly important with advances in communication technology and we will suggest three fundamental approaches to its solution. Our characterization of these approaches will be illustrated with (1) examples from a series of informal studies that we have conducted on how people share information in organizations, and (2) a description of an intelligent information sharing system, called the Information Lens, that we have developed. It is already a …
Low Power Bus Binding Exploiting Optimal Substructure

The earlier the stage where we perform low power design, the higher the dynamic power reduction we achieve. In this paper, we focus on reducing switching activity in high-level synthesis, especially, in the problem of functional module binding, bus binding or register binding. We propose an effective low power bus binding algorithm based on the table decomposition method, to reduce switching activity. The proposed algorithm is based on the decomposition of the original problem into sub-problems by exploiting the optimal substructure. As a result, it finds an optimal or close-to-optimal binding solution with less computation time. Experimental results show the proposed method obtains a solution 2.3-22.2% closer to optimal solution than one with a conventional heuristic method, 8.0-479.2 times faster than the optimal one (at a threshold value of 1.0E+9).
A high-level synthesis flow for the implementation of iterative stencil loop algorithms on FPGA devices

The automatic generation of hardware implementations for a given algorithm is generally a difficult task, especially when data dependencies span across multiple iterations such as in iterative stencil loops (ISLs). In this paper, we introduce an automatic design flow to extract parallelism from an ISL algorithm and perform a design space exploration to identify its best FPGA hardware implementation, in terms of both area and throughput. Experimental results show that the proposed methodology generates hardware designs whose performance is comparable to the one of manually-optimized solutions, and orders of magnitude higher than the implementations generated by commercial high-level synthesis tools.
Design of intelligent capabilities in SDN

Software-Defined Networking (SDN) is an innovative and programmable networking architecture, representing the direction of the future network evolution. In this paper, we propose an architecture to introduce traffic classification techniques into the OpenFlow-based SDN network, which enables the network to be application-aware, so the network could distinguish various applications flows and know the requirements of different flows. Our new architecture also take advantage of the new intelligence to make the network forward traffic flows based flows' demands on bandwidth and delay, which could improve Quality of Service (QoS) of applications and optimize resource allocation all over the network.
The assessment system of students' satisfaction in learning in China's HEIs

The research made sampling investigation in twelve universities in five cities: Beijing,Shanghai,Wuhan,Guangzhou,Xi'an.Adopting the methods of factor analysis and sorting,the research established an index system and assessment mode that could measure students' satisfaction quantitatively in China's HEIs(higher education institutiions). The research found that the important indexes that influence university students' satisfaction are: "campus environment and atmosphere","mechanism of student management","instruction facilities","logistic service","extracurricular activities","the professional quality of instructors","the management of curriculum","the service awareness of staff" and "personal development". Among them,"campus environment and atmosphere" and "the professional quality of instructors" account for the biggest weight,and therefore they should be where universities endeavor to improve students' satisfaction.
The Effect of Scattering on Pulsar Polarization Angle

The low-frequency profiles of some pulsars manifest temporal broadening due to scattering, usually accompanied by flat polarization position angle (PA) curves. Assuming that the scattering works on the 4 Stokes parameters in the same way, we have simulated the effect of scattering on polarization profiles and find that the scattering can indeed flatten the PA curves. Since the higher-frequency profiles suffer less from scattering, they are convolved with scattering models to fit the observed low-frequency profiles. The calculated flat PA curves exactly reproduce the corresponding observations.
An HCR System for Combinational Malayalam Handwritten Characters based on HLH Patterns

An efficient and robust algorithm for recognition of handwritten Malayalam characters is proposed in this study. Malayalam, also known as Kairali, is one of the four major Dravidian languages of Southern India. It consists of basically 15 vowels and 36 consonants. The existence of lot of their combinations and connected characters, the recognition poses a gargantuan challenge in front of us. Till now Malayalam lacks an efficient OCR which meets all conditions. The intertwined characters are very complex owing to the non-adherent styles in which they may be presented. Here we propose an algorithm which uses the inveterate characteristic features to recognize these characters with perceptive accuracy by utilizing the intensity variations in the way in which they may be written. This algorithm recognizes the antediluvian script of Malayalam characters which are connected in nature. Here the input is a 24-bit bmp image which can be enscribed using the Light pen. The output is editable version of the recognized Malayalam characters. In our study we have classified the connected characters into 3 categories. The algorithm is tested for 3 sets of samples ranging 402 letters in noiseless environment and produces accuracy of 92%. General Terms Algorithms
Equivalence of spectral projections in semiclassical limit and a vanishing theorem for higher traces in K-theory

Abstract In this paper, we study a refined L 2 version of the semiclassical approximation of projectively invariant elliptic operators with invariant Morse type potentials on covering spaces of compact manifolds. We work on the level of spectral projections (and not just their traces) and obtain information about classes of these projections in K-theory in the semiclassical limit as the coupling constant μ goes to zero. An important corollary is a vanishing theorem for the higher traces in cyclic cohomology for the spectral projections. This result is then applied to the quantum Hall effect. We also give a new proof that there are arbitrarily many gaps in the spectrum of the operators under consideration in the semiclassical limit.
DE-INTERLEAVED SUBSAMPLING ARCHITECTURE FOR HOMODYNE RECEIVERS

This paper presents a de-interleaved subsampling receiver architecture suitable for homodyne receivers. The proposed topology requires only a single branch to down-convert and extract the in- phase (I) and quadrature (Q) baseband signals. Using a single- branch receiver eliminates the I=Q mismatch issue of traditional direct down-conversion receivers. The simplicity of the proposed receiver architecture makes it an alternative solution for multi-band and multi- standard applications.
Coupled forest growth-hydrology modelling as an instrument for the assessment of effects of forest management on hydrology in forested catchments

The type and intensity of forest management di- rectly influences regional catchment hydrology. Future forest management must optimise the effects of its practices to achieve sustainable management. With scenario analysis of forestry practices, the effects of different forest utilisation strategies on the hydrology of forested catchments can be temporally and spatially quantified. The approach adopted in this study necessitated the de- velopment of an interactive system for the spatially dis- tributed modelling of hydrology in relation to forest stand development. Consequently, a forest growth model was used to simulate stand development assuming various forest man- agement activities. Selected simulated forest growth parame- ters were entered into the hydrological model to simulate wa- ter fluxes under different conditions of forest structure. The approach enables the spatially differentiated quantification of changes in the water regime (e.g. increased evapotranspira- tion). The results of hydrological simulations in the study area, the Oker catchment (northern Harz Mountains), show that forests contribute to the protection of water systems because they have a balancing effect on the hydrological regime. As scenario simulations also suggest, however, forestry prac- tices can also lead to substantial changes in water budgets of forested catchments. The preservation of the hydrological services of forests requires a sustainable and long-term forest conversion on the basis of current management directives for near natural silviculture. Management strategies on basis of moderate harvesting regimes are preferred because of their limited impact on the water budget.
Neo-digit functional reconstruction of mutilating hand injury using transplantation of multiple composite tissue flaps

Purpose:Functional reconstruction of mutilating hand injuries poses a challenge to the surgeon. We present our experience with use of multiple composite tissue flaps transplant for functional reconstruction of hand in patients with mutilating hand injuries. The associated merits and demerits of these surgical approaches are briefly discussed. Methods:From August 2004 to October 2014, functional reconstruction of hand with transplantation of multiple composite tissue flaps was performed in 8 patients. These included the toe with dorsal pedis artery flap, the reverse posterior interosseous artery flap, and the anterolateral thigh flap. Mean interval from injury to functional reconstruction was 10.6 days. Results:All transplanted skin flaps and reconstructed neofingers survived completely. Only 1 patient developed wound infection at the recipient site (hand), which resolved without any debridement or revision surgery. At the donor site (foot), partial skin necrosis was observed in 1 patient, which healed with local wound care. In other patients, all wounds healed without any complications. The average range of movement at the neofinger metacarpophalangeal and interphalangeal joints was 38° and 73°, respectively. None of the patients required revision surgery. Conclusion:Use of negative pressure wound therapy and multiple composite tissue flap transplantation appears to be an effective strategy for hand functional reconstruction in patients with mutilating hand injuries. Among the multiple composite tissue flaps, use of toe transplantation combined with reverse posterior interosseous artery flap appears to be the best option.
An Adaptive Steganography for 3D Point Cloud Models

This paper presents a new adaptive, high-capacity steganography for 3D point cloud models using self-similarity segmentation. Every embedding vertex of the model can adaptively embed variable σ (σ ≥ 3) bits using an adaptive space subdivision procedure which uses normal direction of vertexes to estimate the embedding capacity of every vertex with respect to human visual system. The scheme segments the 3D point cloud model to patches using self-similarity measures. The representative patches and similar patches are then taken as the reference patches and the message patches. Finally, every message point in the similar message patches which has the point-to-point correspondence with a reference point in the reference patch can adaptively embed at least three bits by shifting the message point from current point to the corresponding embedding position using space subdivision. Experimental results show that the proposed scheme is adaptive, has high capacity and low distortion, and is robust against uniform affine transformations such as transformation, rotation, scaling.
A Logical Information System Proposal for Browsing Terminological Resources

This article presents an automated construction of a logical information context from a terminological resource, available in xml ; we apply this to the resource FranceTerme and to Camelis tool and we discuss how the resulting context can be used with such a tool dedicated to logical contexts. The purpose of this development and the choices related to this experiment is twofold : to facilitate the use of a rich linguistic resource available as open-data in xml ; to test and envision a systematic transformation of such xml resources to logical contexts. A logical view of a context allows to explore information in a flexible way, without writing explicit queries, it may also provide insights on the quality of the data. Such a context can be enriched by other information (of diverse natures), it can also be linked with other applications (according to arguments supplied by the context).
Speculative Loop-Pipelining in Binary Translation for Hardware Acceleration

Multimedia and DSP applications have several computationally intensive kernels which are often off loaded and accelerated by application-specific hardware. This paper presents a speculative loop pipelining technique to overcome limitations of binary translation for hardware acceleration. Although many compilers have been developed at source level, it is desirable to translate the binary targeted to popular processors onto hardware for several practical benefits. However, the translated code can be less optimized. In particular, it is difficult to optimize memory accesses on binary to exploit pipeline parallelism since memory optimization techniques require perfect dependence information for correctness and efficiency. This information is not often available at binary level or even at the source level. Our technique synthesizes the pipeline with memory dependence speculation and postpones some phases of compilation by generating a small dependence analysis code or logic which makes use of runtime values. Such speculative optimization achieves the large amount of parallelism and does not depend on any user annotation. The experimental results show a promising speedup of up to 2.53 compared with the code in which memory accesses are not optimized in the pipeline fashion due to conservative memory analysis. In addition, we have evaluated our technique at hardware level implementation on FPGA devices and achieved comparable clock frequency and power consumption compared to a conservative method while achieving significant improvement in throughput.
Lattice Boltzmann model of anisotropic diffusion for image denoising

To overcome the inefficiency of the traditional numerical methods that implement the anisotropic diffusion model for image denoising, a novel lattice Boltzmann model of anisotropic diffusion is presented in this paper. In the model, the diffusion rate is adapted to the image itself and independently set for each direction of diffusion. The mass accumulation is calculated through a weighted summation of the particle distribution functions. Our method is stable with large iteration steps thus reducing the iteration steps greatly. The experiment results showed that compared to others, our approach performs better in terms of the resulting images as well as computing efficiency. In addition, our approach is easy for parallel implementation.
International Conference on Intelligent and Advanced Systems 2007 Front-end Estimation of Noise Power and Snr in Ofdm Systems

In this paper a front-end Noise Power and SNR estimation method based on one OFDM preamble is proposed and compared with previously published SNR estimators – none of which are front-end estimator. The estimator makes use of two identical halves property of time synchronization preamble used in OFDM systems and relies on autocorrelation of the same. The current estimator is compared with two existing SNR estimators, the Reddy estimator and Subspace based estimator in terms of normalized mean square error (NMSE) and estimated SNR. It is observed that current estimator gives SNR estimates better than Reddy and subspace estimators. The estimator performs SNR estimation at front-end of the receiver unlike all other estimators which perform SNR estimation at back-end of the receiver.
Relationship between serum 25-hydroxyvitamin D concentration and risks of metabolic syndrome in children and adolescents from Korean National Health and Nutrition Examination survey 2008-2010

Purpose Previous studies have revealed many inconsistent results regarding the relationship between vitamin D and metabolic syndrome. The purpose of our study was to investigate the association between serum 25-hydroxyvitamin D (25(OH)D) concentration and factors that characterize metabolic syndrome in Korean children and adolescents. Methods We analyzed data from 2,880 children and adolescents aged 10-18 years collected from the 2008-2010 Korean National Health and Nutrition Examination Survey. We investigated the data according to quartiles of 25(OH)D concentrations. Results Systolic blood pressure and diastolic blood pressure with adjustment for sex and age differed significantly between the serum 25(OH)D groups and exhibited negative trend as 25(OH)D concentrations increased. The number of subjects with metabolic syndrome was greater in the low 25(OH)D groups (I, II, and III quartile) than in the high 25(OH)D group (IV quartile) (P=0.029). BMI and waist circumference were lower in the high 25(OH)D group. Serum 25(OH)D concentration correlated negatively with homeostasis model assessment estimate of insulin resistance (ρ=-0.073, P<0.001) and correlated positively with quantitative insulin sensitivity check index (ρ=0.095, P<0.001). Conclusion Low serum 25(OH)D level is associated with an increase of insulin resistance and metabolic syndrome in children and adolescents.
Transformation-based learning meets frequent pattern discovery

Transformation-based learning (TBL) and frequent pattern discovery (FPD) are two popular research paradigms, one from the domain of empirical natural language processing , the second from the eld of data mining. This paper describes how Eric Brill's original TBL algorithm can be improved via incorporation of FPD techniques. The algorithm B-Warmr is presented that upgrades TBL to rst-order logic and speeds up the search for transformations, also in the original propositional case. We demonstrate some scaling properties of B-Warmr and discuss how the algorithm can be tuned to generate ((rst-order) decision lists. We also propose a new method, Disjunctive Transformation-Based Learning (DTBL) that combines the advantages of TBL and decision lists.
Followers or Phantoms? An Anatomy of Purchased Twitter Followers

Online Social Media (OSM) is extensively used by contemporary Internet users to communicate, socialize and disseminate information. This has led to the creation of a distinct online social identity which in turn has created the need of online social reputation management techniques. A significant percentage of OSM users utilize various methods to drive and manage their reputation on OSM. This has given rise to underground markets which buy/sell fraudulent accounts, `likes', `comments' (Facebook, Instagram) and `followers' (Twitter) to artificially boost their social reputation. In this study, we present an anatomy of purchased followers on Twitter and their behaviour. We illustrate in detail the profile characteristics, content sharing and behavioural patterns of purchased follower accounts. Previous studies have analyzed the purchased follower markets and customers. Ours is the first study which analyzes the anatomy of purchased followers accounts. Some of the key insights of our study show that purchased followers have a very high unfollow entropy rate and low social engagement with their friends. In addition, we noticed that purchased follower accounts have significant difference in their interaction and content sharing patterns in comparison to random Twitter users. We also found that underground markets do not follow their service policies and guarantees they provide to customer. Our study highlights the key identifiers for suspicious follow behaviour. We then built a supervised learning mechanism to predict suspicious follower behaviour with 88.2% accuracy. We believe that understanding the anatomy and characteristics of purchased followers can help detect suspicious follower behaviour and fraudulent accounts to a larger extent.
Massively multi-topology sizing of analog integrated circuits

This paper demonstrates a system that performs multi-objective sizing across 100,000 analog circuit topologies simultaneously, with SPICE accuracy. It builds on a previous system, MOJITO, which searches through 3500 topologies defined by a hierarchically-organized set of 30 analog blocks. This paper improves MOJITO's results quality via three key extensions. First, it enlarges the block library to enable symmetrical transconductance amplifiers and more. Second, it improves initial topology diversity via optimization-based constraint satisfaction. Third, it maintains topology diversity during search via a novel multi-objective selection mechanism, dubbed TAPAS. MO-JITO+TAPAS is demonstrated on a problem with 6 objectives, returning a tradeoff holding 17438 nondominated designs. The tradeoff is comprised of 152 unique topologies that include the newly-introduced topologies. 59 designs across 12 topologies designs outperform an expert-designed reference circuit.