Miracle-dz/UniFAR-FTUs huggingface dataset:
LightRNN: Memory and Computation-Efficient Recurrent Neural Networks

Recurrent neural networks (RNNs) have achieved state-of-the-art performances in many natural language processing tasks, such as language modeling and machine translation. However, when the vocabulary is large, the RNN model will become very big (e.g., possibly beyond the memory capacity of a GPU device) and its training will become very inefficient. In this work, we propose a novel technique to tackle this challenge. The key idea is to use 2-Component (2C) shared embedding for word representations. We allocate every word in the vocabulary into a table, each row of which is associated with a vector, and each column associated with another vector. Depending on its position in the table, a word is jointly represented by two components: a row vector and a column vector. Since the words in the same row share the row vector and the words in the same column share the column vector, we only need $2 \sqrt{|V|}$ vectors to represent a vocabulary of $|V|$ unique words, which are far less than the $|V|$ vectors required by existing approaches. Based on the 2-Component shared embedding, we design a new RNN algorithm and evaluate it using the language modeling task on several benchmark datasets. The results show that our algorithm significantly reduces the model size and speeds up the training process, without sacrifice of accuracy (it achieves similar, if not better, perplexity as compared to state-of-the-art language models). Remarkably, on the One-Billion-Word benchmark Dataset, our algorithm achieves comparable perplexity to previous language models, whilst reducing the model size by a factor of 40-100, and speeding up the training process by a factor of 2. We name our proposed algorithm \emph{LightRNN} to reflect its very small model size and very high training speed.
Social tillid i Danmark

TIiliden til andre, eller den sociale tillid, er i komparative undersøgelser en indikator for en demokratisk politisk kultur. Individuel social tillid er positivt forbundet med social status og deltagelse i netværker og negativt med autoritære værdier, deriblandt konformistisk børneop­ dragelse og national forskansning. På trods af modstanden mod indvandrere og flygtninge er andelen med social tillid vokset i Danmark fra 51 til 7 4 pct. over en tyveårs periode, et niveau og en udvikling der næsten er enestående.
Understanding and combating mission drift in social enterprises

Purpose – The aim of this paper is to develop a better understanding of the pressures that can cause mission drift among social enterprises and some of the steps that social enterprises can take to combat these pressures. Design/methodology/approach – The paper is conceptual in nature. It draws on resource dependency theory, institutional theory and various extant empirical studies to develop an understanding of the causes of mission drift. This analysis is then used to examine the practical steps that social enterprises can take to combat mission drift. Findings – The paper highlights how high dependence on a resource provider and the demands of “competing” institutional environments can lead to mission drift. Based on this analysis, the paper sets out various governance mechanisms and management strategies that can be used to combat mission drift. Practical implications – The paper sets out practical steps social enterprises can take to try to prevent mission drift. While governance mechanisms provide i.
A DEVS-scheme simulation of an electronic meeting system

Electronic Meeting Systems (EMS) facilitate group meetings by providing automated support for communicating, decison-making, and consensus-building. This paper presents an approach for building EMS through a quantitative description of two well-known approaches: Electronic Brainstorming and the Nominal Group Technique. A DEVS-Scheme simulation of these two tools provides an additional conceptual foundation for the construction of EMS tools.
CONTROL DESIGN FOR DISTRIBUTED-PARAMETER SYSTEMS VIA PARAMETRIZATION

Abstract A methodology, called by the name parametrization, is presented here for calculating open-loop controls for linear distributed-parameter systems. It is based on the theory of certain type of pseudo-differential operators (PDO). These operators have features which are useful from practical and computational viewpoints. The operators form an algebra, and their inverses belong to the calculus, too. Boundary conditions always present in real-life problems are naturally included in the operator structures. Consequently, their defining elements, so-called symbols, have transfer function like properties. However, more complicated than only rational symbols are included in the calculus.
A Review of Consistency and Convergence of Posterior Distribution

In this article, we review two important issues, namely consistency and convergence of posterior distribution, that arise in Bayesian inference with large samples. Both parametric and non-parametric cases are considered. In this article we address the issues of consistency and convergence of posterior distribution. This review is aimed for non-specialists. Technical conditions (like measurability) and mathematical expressions are avoided as far as possible. No proof of the results mentioned are given here. Unsatissed readers are encouraged to look at the references mentioned. The list of the references is certainly not exhaustive, but other references may be found from the mentioned ones. A general reference on the topic of Bayesian asymptotics is Ghosh and Ramamoorthi 36]. In Bayesian analysis, one starts with a prior knowledge (sometimes imprecise) expressed as a distribution on the parameter space and updates the knowledge according to the posterior distribution given the data. It is therefore of utmost importance to know whether the updated knowledge becomes more and more accurate and precise as data are collected indeenitely. This requirement is called the consistency of the posterior distribution. Although it is an asymptotic property, consistency is one of the benchmarks since the violation of consistency is clearly undesirable and one may have serious doubts against inferences based on an inconsistent posterior distribution. The above formulation of consistency is from the point of view of a classical Bayesian who believes in an unknown true model. Subjective Bayesians do not believe in such true models and thinks only in terms of the predictive distribution of a future observation. Nevertheless, consistency is important to subjective Bayesians also. Blackwell and Dubins 7] and Diaconis and Freedman 16] show that consistency is equivalent to intersubjective agreement, which means that two Bayesian will ultimately have very close predictive distributions. To deene consistency, we consider a sequence of statistical experiments indexed by a parameter taking values in a parameter space. The parameter space need not be a subset of a Euclidean space, so that non-parametric problems are also included. The observation at the nth stage is denoted by X is a probability P (n) controlled by the parameter. By a prior distribution, we mean a probability distribution on. The set of all priors will be denoted by M. A prior gives rise to a joint distribution of (; X
A Rigid Map Neural Network for Anatomical Joint Constraint Modelling

Accurate individual anatomical joint models are becoming increasingly important for both realistic animation and diagnostic medical applications. A number of recent approaches have exploited unit quaternions to eliminate singularities when modelling orientations between limbs at a joint. This has resulted in the development of unit quaternion based joint constraint validation and correction methods. A number of machine learning approaches have been applied to this problem. Recent work has demonstrated the use of Kohonen's Self Organizing Maps (SOMs) to model regular conical constraints on the orientation of the limb. In this paper we investigate a derivative of the SOM, the Rigid Map, applied in the same context.
4-2 Compressor Design with New XOR-XNOR Module

In this paper, a low-power high speed 4-2 compressor circuit is proposed for fast digital arithmetic integrated circuits. The 4-2 compressor has been widely employed for multiplier realizations. Based on a new exclusive OR (XOR) and exclusive NOR (XNOR) module, a 4-2 compressor circuit has been designed. Proposed circuit shows power consumption variation in the range of 718.72 pW to 3357.40 pW. Maximum output delay of the circuit presents variation in the range of 43.83 ps to 27.74 ps. Further, power-delay product (PDP) of circuit is varying from 315.01×10-22(J) to 931.34×10-22(J) with change in supply voltage from 1.8V to 3.3V. Power consumption, delay and PDP of proposed 4-2 compressor circuit have been compared with earlier reported circuits and proposed circuit is proven to have the minimum power consumption and the lowest delay. Simulations have been performed by using SPICE based on TSMC 0. 18μm CMOS technology.
DNA compaction by the bacteriophage protein Cox studied on the single DNA molecule level using nanofluidic channels

The Cox protein from bacteriophage P2 forms oligomeric filaments and it has been proposed that DNA can be wound up around these filaments, similar to how histones condense DNA. We here use fluorescence microscopy to study single DNA–Cox complexes in nanofluidic channels and compare how the Cox homologs from phages P2 and WΦ affect DNA. By measuring the extension of nanoconfined DNA in absence and presence of Cox we show that the protein compacts DNA and that the binding is highly cooperative, in agreement with the model of a Cox filament around which DNA is wrapped. Furthermore, comparing microscopy images for the wild-type P2 Cox protein and two mutants allows us to discriminate between compaction due to filament formation and compaction by monomeric Cox. P2 and WΦ Cox have similar effects on the physical properties of DNA and the subtle, but significant, differences in DNA binding are due to differences in binding affinity rather than binding mode. The presented work highlights the use of single DNA molecule studies to confirm structural predictions from X-ray crystallography. It also shows how a small protein by oligomerization can have great impact on the organization of DNA and thereby fulfill multiple regulatory functions.
A Study on Instruction-set Selection Using Multi-application Based Application Specific Instruction-set Processors

Efficiency in embedded systems is paramount to achieve high performance while consuming less area and power. Processors in embedded systems have to be designed carefully to achieve such design constraints. Application Specific Instruction set Processors (ASIPs) exploit the nature of applications to design an optimal instruction set. Despite being not general to execute any application, ASIPs are highly preferred in the embedded systems industry where the devices are produced to satisfy a certain type of application domain/s (either intra-domain or inter-domain). Typically, ASIPs are designed from a base-processor and functionalities are added for applications. This paper studies the multi-application ASIPs and their instruction sets, extensively analyzing the instructions for inter-domain and intra-domain designs. Metrics analyzed are the reusable instructions and the extra cost to add a certain application, together with the hardware synthesis numbers, such as area, timing and delay. A wide range of applications from various application benchmarks (BioPerf, CommBench, MediaBench, MiBench and SPEC2006) and domains are analyzed for three different architectures (LEON2, PISA and ARM-Thumb). Processors are generated for these architectures for different configurations to analyze and synthesize. Our study shows that the intra-domain applications contain larger number of common instructions, whereas the inter-domain applications have very less common instructions, regardless the kind of architecture (and therefore the ISA).
Influence of ovarian manipulation on reproductive endocrinology in polycystic ovarian syndrome and regularly cycling women.

OBJECTIVE Little is known about the function of the ovarian neuronal network in humans. In many species, copulation influences endocrinology through this network. As a first step, the possible influence of ovarian mechanical manipulation on pituitary and ovarian hormones was evaluated in polycystic ovarian syndrome (PCOS) and regularly cycling women. DESIGN Prospective case-control study (2008-2010). METHODS Ten PCOS women (Rotterdam criteria) undergoing ovulation induction with recombinant-FSH and ten normal ovulatory controls were included in an academic fertility clinic. In the late follicular phase blood was drawn every 10 min for 6 h. After 3 h the ovaries were mechanically manipulated by moving a transvaginal ultrasound probe firmly over each ovary ten times. Main outcome measures were LH and FSH pulsatility and ovarian hormones before and after ovarian manipulation. RESULTS All PCOS patients showed an LH decline after the ovarian manipulation (before 13.0 U/l and after 10.4 U/l, P<0.01), probably based on a combination of a longer LH pulse interval and smaller amplitude (P=0.07). The controls showed no LH change (before 9.6 U/l and after 9.3 U/l, P=0.67). None of the ovarian hormones (estradiol, progesterone, anti-Müllerian hormone, inhibin B, androstenedione and testosterone) changed in either group. CONCLUSIONS Ovarian mechanical manipulation lowers LH secretion immediately and typically only in preovulatory PCOS patients. The immediate LH change after the ovarian manipulation without any accompanying ovarian hormonal changes point to nonhormonal communication from the ovaries to the pituitary. A neuronal pathway from the ovaries communicating to the hypothalamic-pituitary system is the most reasonable explanation.
Design of Dual-Frequency CPW-fed Monopole Antenna for Wireless Application

A Novel and simple monopole antenna with a T-shape (gap) coplanar waveguide (CPW)-fed has been proposed in this paper. The antenna comprises of a rectangular single-step patch with a filter properties has been designed. A new coupling structure having a closed loop step-impedance resonator embedded with a uniform resonators and a modified ground plane (slots) is capable of generating dual band monopole antenna. The antenna was designed to operate at two resonating frequencies 3.5 and 5 GHz which covers a frequency bands from (3.2-3.5GHz) and (4.7-5.6GHz) respectively. A good monopole-like radiation pattern and gain over the operating bands have been obtained.
Circumventing Cheating on Power Auctioning in Resource Constrained Micro-Grids

Decentralized Continuous Double Auctioning offers a flexible marketing approach to power distribution in resource constrained (RC) smart micro-grids. Grid participants (buyers and sellers) can obtain power at a suitable price both at on or off-peak periods. Decentralized CDA schemes are however vulnerable to two attacks, namely - 'Victim Strategy Downgrade' and 'Collusion'. Both attacks foil the CDA scheme by allowing an individual to gain surplus energy that leads to low allocative efficiency, which is undesirable for maintaining grid stability and reliability. In this paper we propose a novel scheme to circumvent power auction cheating attacks. Our scheme works by employing an exception handling mechanism that employs cheating detection and resolution algorithms. Our correctness and complexity analysis demonstrates that the solution is both sound and performance efficient under resource constrained conditions.
A Distance Measure for Video Sequences

Video is a unique multimedia data type, in that it comes with distinguished spatio-temporal constraints. Content-based video retrieval thus requires methods for video sequence-to-sequence matching, incorporating the temporal ordering inherent in a video sequence, without losing sight of the visual nature of the information in the sequence. Such methods will require reliable measures of similarity between the video sequences. In this paper, we formulate the problem of video sequence-to-sequence matching as a pattern-matching problem and propose the vstring edit distance as a suitable distance measure for video sequences.
SOPS: A System for Efficient Processing of Spatial-Keyword Publish/Subscribe

Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale. These geo-textual data cover a wide range of topics. Users are interested in receiving up-to-date geo-textual objects (e.g., geo-tagged Tweets) such that their locations meet users' need and their texts are interesting to users. For example, a user may want to be updated with tweets near her home on the topic "dengue fever headache". [email protected] this demonstration, we present SOPS, the S patial-Keyw o rd P ublish/ S ubscribe System, that is capable of efficiently processing spatial keyword continuous queries. SOPS supports two types of queries: (1) B oolean R ange C ontinuous (BRC) query that can be used to subscribe the geo-textual objects satisfying a boolean keyword expression and falling in a specified spatial region; (2) T empor a l S patial- K eyword Top-k Continuous (TaSK) query that continuously maintains up-to-date top-k most relevant results over a stream of geo-textual objects. SOPS enables users to formulate their queries and view the real-time results over a stream of geo-textual objects by browser-based user interfaces. On the server side, we propose solutions to efficiently processing a large number of BRC queries (tens of millions) and TaSK queries over a stream of geo-textual objects.
Effects of dynamic resistance training on fascicle lengthand isometric strength

Abstract The aims of this study were to assess changes in muscle architecture, isometric and dynamic strength of the leg extensor muscles, resulting from dynamic resistance training, and the relationships between strength and muscle architecture variables. The participants (n = 30) were randomly assigned to one of two groups. The training group (n = 16; age 21.8 ± 2.3 years, body mass 74.8 ± 9.2 kg, height 1.75 ± 0.08 m) performed dynamic resistance training for 13 weeks. The control group (n = 14; age 19.9 ± 1.5 years, body mass 74.0 ± 8.5 kg, height 1.76 ± 0.05 m) did not perform any resistance training. Maximal dynamic and isometric strength were tested in both groups, before and after the training period. The members of the training group used the free-weight squat lift (90°) as their training exercise. The concentric phase of the squat was performed explosively. Skeletal muscle architecture of the vastus lateralis was visualized using ultrasonography. At the end of the study, significant increases in vastus lateralis muscle thickness (+6.9%, P < 0.001), fascicle length (+10.3%, P < 0.05), one-repetition maximum (+8.2%, P < 0.05), rate of force development (+23.8%, P < 0.05) and average force produced in the first 500 ms (+11.7%, P < 0.05) were seen only in the training group. Adaptations to the muscle architecture in the training group limited the loss of fibre force, and improved the capacity for developing higher velocities of contraction. The architectural changes in the training group were similar to those seen in studies where high-speed training was performed. In conclusion, dynamic resistance training with light loads leads to increases in muscle thickness and fascicle length, which might be related to a more efficient transmission of fibre force to the tendon.
A Feature Space View of Spectral Clustering

The transductive SVM is a semi-supervised learning algorithm that searches for a large margin hyperplane in feature space. By withholding the training labels and adding a constraint that favors balanced clusters, it can be turned into a clustering algorithm. The Normalized Cuts clustering algorithm of Shi and Malik, although originally presented as spectral relaxation of a graph cut problem, can be interpreted as a relaxation on clustering with transductive SVMs. Using this interpretation of Normalized Cuts, we identify some of its weaknesses, and propose a correction on it.
Adaptive randomized algorithm for finding eigenvector of stochastic matrix with application to PageRank

The problem of finding the eigenvector corresponding to the largest eigenvalue of a stochastic matrix has numerous applications in ranking search results, multi-agent consensus, networked control and data mining. The well-known power method is a typical tool for its solution. However randomized methods could be competitors vs standard ones; they require much less calculations for one iteration and are well-tailored for distributed computations. We propose a novel adaptive randomized algorithm and provide an explicit upper bound for its rate of convergence O(√lnN/n), where N is the dimension and n is the number of iterations. The bound looks promising because √lnN is not large even for very high dimensions. The proposed algorithm is based on the mirror-descent method for convex stochastic optimization.
Barrier Coverage with Mobile Sensor Network

In order to save the mobile sensor network energy and improve the barrier coverage with mobile sensor network to adapt to the environment. The virtual force principle is applied in low power RF (Radio Frequency) wake-up mobile sensor nodes and obstacles. Some of sensor nodes are in the state of work, the others are dormant. When the sensor network is damaged, the dormant sensor nodes can be waked up timely and mobile to the damage place to restore the barrier coverage. Analysis by simulation, it can effectively save the network energy consumption, improve the service life of the network and the network capacity to adapt to the environment.
Advances in BDD reduction usingParallel Genetic

Binary Decision Diagrams (BDDs) have proved to be a powerful representation for Boolean functions. Particularly, they are a very useful data structure for the symbolic model checking of digital circuits and other nite state systems, as well as other problems. Nevertheless, the size of the BDD representation of these functions is highly dependent on the order of the function arguments, also called variables, and to nd such good ordering is an NP-Complete problem. Many heuristics have been proposed to solve this problem, as the depth-rst traversal algorithm, one of the best known techniques, and the genetic algorithm found in 6]. In this paper, we present a improvement to them, through a parallel genetic algorithm, and compare its experimental results with those obtained from an interleaving-based implementation of the depth-rst traversal algorithm, applying them to the ISCAS85 benchmark circuits.
An overview of sports friendship quality of teenagers abroad

There are 12 positive factors and 4 negative factors in sports friendship quality.Sports friendship quality measuring tools include the friendship quality measuring form and the sports friendship quality measuring form.Sports friendship quality processes include the establishment stage,development stage and finish stage.There are differences of age and gender in sports friendship quality.The researchers failed to classify sports friendship quality based on different levels of teenagers in sports activities,i.e.they failed to thoroughly probe into sports friendship quality issues existing in teenager sports groups with different competitive levels and under different organizations.The relation between multiple motives(pleasure,promise and competition) under the influence of sports friendship quality should be further studied,and the vertical study of sports friendship quality and its stability should be carried out.