Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing human-swarm interactions using control Lyapunov functions and optimal control

A number of different interaction modalities have been proposed for human engagement with networked systems. In this paper, we establish formal guarantees for whether or not a given human-swarm interaction (HSI) strategy is appropriate for achieving particular multi-robot tasks, such as guiding a swarm of robots into a particular geometric configuration. In doing so, we define what it means to impose an HSI control structure on a multi-robot system. Control Lyapunov functions are used to establish feasibility for a user to achieve a particular geometric configuration with a multi-robot system under some selected HSI control structure. Several examples of multi-robot systems with unique HSI control structures are provided to illustrated the use of CLFs to establish feasibility. Additionally, we also uses these examples to illustrate how to use optimal control tools to compute three metrics for evaluating an HSI control structure: attention, effort, and scalability.
Optimal SOC limit estimation of ESS considering renwable energy sources

There have been increasing concerns about the ESS, in order effectively to deal with the volatility of the system. For those with renewable energy, resulting in the uncertainty of power output, the ESS can prevent possible negative outcomes from a sudden change of load in a short time and simultaneously reinforce electricity supply. In addition, considering the facilities in which the system is surrounded and the purpose of the installation, the accurate SOC of the ESS is determined, and it results in an increase of the efficiency of power supply and the reliability. In this paper, the efficiency for renewable energy is enhanced and at the same time, the ESS with the UPS features is adopted, so as to perform for unplanned blackout. In doing so, the operation algorithm of the ESS based upon renewable energy resources is suggested and the optimal SOC limit is also assessed. In the end, by estimating the reliability of the ESS that involves the UPS system, the quantitative comparison will be made between the existing system and the new system.
Vocabularies of Organizing: How Language Links Culture, Cognition, and Action in Organizations

Linking sociological theories of vocabularies and institutions with Neo-Whorfian perspectives from cognitive science, this paper develops a theoretical framework and propositions on how specialized vocabularies structure cognition and action in organizations. We propose that vocabularies of organizing are socially constructed systems of linguistic categories that provide organizational members with cultural systems to classify organizational practices. We identify five principles to capture vocabularies' effects: social construction, embodiment in organizational practices, modularity, theorization, and attentional selectivity. This perspective highlights the interrelationships between words and how cultural systems generate logics of action at the individual level and institutional logics at the macro-social level.
A Framework of Artificial Immune System in Writer Identification

Artificial Immune Systems (AIS) is an emerging computer science technique which is inspired from biological process and has a nonlinear classification property along with biological property such as Negative Selection (NS). AIS has been proved as one of the mechanism that has a good potential in solving complex problem such as pattern recognition. Meanwhile, handwritten writer identification is one of the most popular areas of research in pattern recognition due to its immense potential on commercial perspective. Due to the importance and increasing interest in bio-inspired computing, this paper proposed AIS framework for writer identification. However, early findings on data iris and pendigits show that the proposed framework is convincing with an accuracy of more than 80.0% with various matching techniques.
Find you from your friends: Graph-based residence location prediction for users in social media

As a bridge between social media and physical space, location information will potentially make the internet smarter, and release the real power of social media to address the serious and significant problems in the real world. However, in terms of privacy and security, most of the users are unwilling to make their locations public. To address the problem, an algorithm is necessary to predict the users' residence locations based on the public profiles. We define location propagation probability of users, leverage a semi-supervised learning algorithm, and introduce a novel method of location propagation to predict users' residence locations based on users' social relationships, textual and visual contents and a small amount of known users' residence locations. The experimental results on a large scale real data set in Tencent Weibo demonstrate that our location propagation algorithm outperforms the state-of-the-art approaches in both accuracy and scalability.
Sustainable Development Strategies for Product Innovation and Energy Efficiency

The interaction between product innovation and companies’ activities aimed at improving the energy efficiency of production facilities has been relatively little studied, but is of great relevance to society and companies given the strong focus of governments on grand challenges like climate change, green innovation technologies, and environmental problems in general. This paper utilizes the 2009 European Manufacturing Survey for the Danish sub-sample including 335 manufacturing firms. Through factor analysis, this paper confirms three main areas of focus of new product development: efficiency considerations, market attention, and greening of innovation. Logistic regression analysis demonstrates that while market attention is important for the development of new products, green aspects of innovation and efficiency considerations are important for production companies wanting to improve their energy efficiency. When these models are combined, the results highlight that energy efficiency moderates the effect of market attention to new product development. This paper therefore finds that aligning product innovation and energy efficiency is a complex and intertwined process – focusing on one may have indirect detrimental effects on the other. These results point to the conclusion that researchers and practitioners in innovation management have to consider more carefully the specificities and interactions of different types of products and process innovations and their environmental implications, and must formulate new, more sustainable managerial practices combining energy efficiency and product innovation. Copyright © 2013 John Wiley & Sons, Ltd and ERP Environment
Consensus control for nonlinear multi-agent systems subject to deception attacks

This paper deals with the consensus control problem for a class of discrete time-varying stochastic multi-agent systems with stochastic nonlinearities and deception attacks. A novel definition of quasi-consensus is proposed to reflect the consensus process where, at each time instant, all the agents are constrained to stay within a certain ellipsoidal region. The measurement output available for the controller is not only from the individual agent itself but also from its neighboring ones according to the given topology. A new deception attack model is proposed, where the attack signals are injected by the adversary to the measurement data during the process of information transmission via the communication network. By using a set of recursive matrix inequalities, sufficient conditions are derived for the existence of the desired control scheme for achieving the quasi-consensus. Subsequently, an optimization problem is formulated to seek the locally best consensus performance.
Pension Reform, Ownership Structure, and Corporate Governance: Evidence from Sweden

Sweden offers a unique natural experiment to analyze the microeconomic effects of institutionalized saving on ownership structure, corporate governance and performance of listed companies. First, the Swedish pension reform increased the participation of pension funds in the domestic stock market and caused a significant reshuffling in the ownership of the existing pension funds. Second, the availability of detailed data on firm ownership allows us to document the effects of the pension reform. We show that the effects of institutional investment on firm performance depend on the industry structure of pension funds. In particular, we find that firm performance improves if large independent private pension funds and public pension funds increase their equity stakes in the firm, but not if smaller pension funds and pension funds related to financial institutions and industrial groups increase their shareholdings. Additionally, controlling shareholders appear reluctant to relinquish control and the control premium increases if public pension funds acquire shares.
Formation of cristae and crista junctions in mitochondria depends on antagonism between Fcj1 and Su e/g

Crista junctions (CJs) are important for mitochondrial organization and function, but the molecular basis of their formation and architecture is obscure. We have identified and characterized a mitochondrial membrane protein in yeast, Fcj1 (formation of CJ protein 1), which is specifically enriched in CJs. Cells lacking Fcj1 lack CJs, exhibit concentric stacks of inner membrane in the mitochondrial matrix, and show increased levels of F1FO–ATP synthase (F1FO) supercomplexes. Overexpression of Fcj1 leads to increased CJ formation, branching of cristae, enlargement of CJ diameter, and reduced levels of F1FO supercomplexes. Impairment of F1FO oligomer formation by deletion of its subunits e/g (Su e/g) causes CJ diameter enlargement and reduction of cristae tip numbers and promotes cristae branching. Fcj1 and Su e/g genetically interact. We propose a model in which the antagonism between Fcj1 and Su e/g locally modulates the F1FO oligomeric state, thereby controlling membrane curvature of cristae to generate CJs and cristae tips.
High-Precision Abductive Mapping of Multilingual Metaphors

Metaphor is a cognitive phenomenon exhibited in language, where one conceptual domain (the target) is thought of in terms of another (the source). The first level of metaphor interpretation is the mapping of linguistic metaphors to pairs of source and target concepts. Based on the abductive approach to metaphor interpretation proposed by Hobbs (1992) and implemented in the open-source Metaphor-ADP system (Ovchinnikova et al., 2014), we present work to automatically learn knowledge bases to support high-precision conceptual metaphor mapping in English, Spanish, Farsi, and Russian.
An Efficient Similarity Searching Scheme in Massive Databases

Locality sensitive hashing (LSH) is a method of performing probabilistic dimension reduction of high dimensional data. It is a popular technique for approximate nearest neighbor search. However, LSH needs large memory space and long processing time to achieve good performance when searching a massive dataset. In addition, it is not effective on locating similar data in a very high dimensional dataset. This paper proposes a new LSH-based similarity searching scheme, namely SMLSH. It intelligently combines a consistent hash function and min-wise independent permutations into LSH. SMLSH effectively classifies information according to the similarity with reduced memory space requirement and in a very efficient manner. It can quickly locate similar data in a massive dataset. Experiment results show that SMLSH is both time and space efficient in comparison with LSH. It yields significant improvements on the effectiveness of similar searching over LSH in a massive dataset.
Experimental Results for Four Work-Optimal PRAM Simulation Algorithms on Coated Meshes

In this paper we consider the eeect of overloading in four work-optimal PRAM simulation algorithms on coated meshes with P real processors. A coated mesh consists of a mesh connected routing machinery, and processor&memory pairs, which form a coat on the routing machinery. Previously work-optimal PRAM simulations, which ignore the eeect of overloading, has been presented for coated meshes, but their cost is relatively high (around 100). The algorithms we study here are based on greedy routing, sorting, improved virtual levelled network technique, and combining queues method. Our results show that overloading alone can be used to improve the simulation cost of all PRAM models on coated meshes to circa 10 (and even less) routing steps per P simulated PRAM processors.
Strategies for Preventing Homelessness

This report identifies six community-wide approaches to preventing homelessness, three focused on families, two focused on people with serious mental illness, and one focused on youth. It describes four elements common to successful programs: (1) the ability to target people seriously at risk of homelessness; (2) the motivation to invest resources for prevention; (3) mechanisms for maximizing resources by collaborating with non-housing agencies such as child welfare and mental health; and (4) leadership that sets goals, develops strategies, and uses data to track progress, provide feedback, and support improvements.
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Cooperative Multi-Robot Map-building based on Genetic Algorithms

The paper surveys two research fields of cooperative multi-robot map-building . One field is exploring region distribute method and another field is robot exploring navigation strategy. A cooperative multi-robot map-building approach based on Hilbert curve exploring method and cooperative multi-robot sub-region selected method based on genetic algorithms is presented Simulation experiments show that the approach not only can reduce the probability of repeatedly explore the same region but also can make the region selected for every robot is a optimized region for them.
Calculating Wikipedia Article Similarity Using Machine Translation Evaluation Metrics

Calculating the similarity of Wikipedia articles in different languages is helpful for bilingual dictionary construction and various other research areas. However, standard methods for document similarity calculation are usually very simple. Therefore, we describe an approach of translating one Wikipedia article into the language of the other article, and then calculating article similarity with standard machine translation evaluation metrics. An experiment revealed that our approach is effective for identifying Wikipedia articles in different languages that are covering the same concept.
Temperament as a Predictor of Infant Immunization Distress and Response to Treatment

There is a growing body of research on interventions to decrease infant distress during painful procedures, and distraction is a particularly practical option. However, the effectiveness data for distraction for infant pain relief are mixed. Inconsistencies in response to distraction might be explained by unique characteristics of the infant patient. Some researchers argue that temperament is the best predictor of differences observed between individuals and also the most sensitive to novel environmental factors such as exposure to pain. This study examined whether infants‟ temperament is predictive of response to immunization injection pain and whether temperament moderates the relation between a distraction intervention and infant distress. Data for this study came from two prior studies of healthy infants receiving immunizations (Cohen, 2002; Cohen et al., 2006). Participants included 252 healthy infants and toddlers who ranged from 1 to 22 months of age. Infants were randomly assigned to “typical care” condition or “distraction” condition. The period of time before, during, and after the injection was videotaped and observational coding was used to assess infant distress. Prior to the immunization, parents completed six pre-injection visual analogue scales about their child‟s temperament. An oblique rotation factor analysis was conducted with the temperament data and provided two temperament factors that map onto the „easy/difficult‟ and „time-to-warm-up‟ dimensions documented in the literature; these two factors were used for analyses. After controlling for site and gender, regression analyses revealed that neither easy/difficult temperament (p = .098,  = .109) nor time-to-warm-up temperament (p = .572,  = -.037) was predictive of distress. There was a significant treatment condition and time-to-warm-up temperament interaction, b = . 0011, SE = . 0005, p = . 0254, such that distraction decreased distress in infants that were slower to warm up, or warmed up neither slowly nor quickly. No other significant distraction x temperament interactions were found. Temperament was not found to impact infant distress during immunizations in this study but results speaking to whether temperament serves as a moderator of the relation between distraction and distress were mixed. Results suggest that temperament is a factor that warrants closer attention when examining how infants respond to interventions around pain. INDEX WORDS: Infants, Temperament, Procedural pain, Distraction, Immunizations TEMPERAMENT AS A PREDICTOR OF INFANT IMMUNIZATION DISTRESS AND RESPONSE TO TREATMENT
AN EXPERIMENTAL TESTBED TO ENABLE AUTO-DYNAMIC DIFFICULTY IN MODERN VIDEO GAMES

Providing gameplay that is satisfying to a broad player audience is an appealing goal to game developers. Considering the wide range of player skill, emotional motivators, and tolerance for frustration, it is simply impossible for developers to deliver a game with an appropriate level of challenge and difficulty to satisfy all players using conventional techniques. Auto-dynamic difficulty, however, is a technique for adjusting gameplay to better suit player needs and expectations that holds promise to overcome this problem. This paper presents an experimental testbed to enable auto-dynamic difficulty adjustment in games. Not only does this testbed environment provide facilities for conducting user studies to investigate the factors involved in auto-dynamic difficulty, but this testbed also provides support for developers to build new algorithms and technologies that use auto-dynamic difficulty adjustment to improve gameplay. Initial experiences in using this auto-dynamic difficulty testbed have been quite promising, and have demonstrated its suitability for the task at hand.
AIS Electronic Library (AISeL)

Collaborative filtering (CF) recommendation is a knowledge sharing technology for distribution of opinions and facilitating contacts in network society between people with similar interests. The main concerns of the CF algorithm are about prediction accuracy, speed of response time, problem of data sparsity, and scalability. In general the efforts of improving prediction algorithms and lessening response time are decoupled. We propose a three-step CF recommendation model which is composed of profiling, inferring and a final prediction step, while considering prediction accuracy and computing speed simultaneously. This model combines a CF algorithm with two machine learning processes, SOM (Self-Organizing Map) and CBR (Case Based Reasoning), by changing an unsupervised clustering problem into a supervised user preference reasoning problem, which is a novel approach for the CF recommendation field. This paper demonstrates the utility of the CF recommendation based on SOM cluster-indexing CBR, with validation against control algorithms through an open dataset of user preference.
Learning on the job: the application of machine learning within the speech decoder

The current approach to the training of large vocabulary continuous speech recognition (LVCSR) systems involves the use of large corpora of text and labelled audio recordings [1]. These resources are analysed and statistics extracted so that the recogniser can determine the likelihood that the observed signal would have been generated from each sentence it proposes. The analysis of corpora is performed off-line, using statistical language models of the text (often trigram models of words), and acoustic models of the signal (often hidden Markov models of phonemes). To this off-line processing, recent years have seen a growth in the use of methods of adaptation in which the general statistical models are tuned to the specific characteristics of a given speaker, a given acoustic environment or a given topic. These adaptation processes modify the stored characteristics of the language model and the acoustic model to improve the probability that the correct interpretation would have given rise to the observed signal. No one would argue that these components provide a perfect model of the true statistical distribution of words and sounds. Weaknesses in typical acoustic models include: crude modelling of the interdependencies between the acoustic forms of different phones no model of systematic pronunciation variation across different contexts or speakers
Probing neurochemical structure and function of retinal ON bipolar cells with a transgenic mouse

Retinal ON bipolar cells make up about 70% of all bipolar cells. Glutamate hyperpolarizes these cells by binding to the metabotropic glutamate receptor mGluR6, activating the G‐protein Go1, and closing an unidentified cation channel. To facilitate investigation of ON bipolar cells, we here report on the production of a transgenic mouse (Grm6‐GFP) in which enhanced green fluorescent protein (EGFP), under control of mGluR6 promoter, was expressed in all and only ON bipolar cells. We used the mouse to determine density of ON bipolar cells, which in central retina was 29,600 cells/mm2. We further sorted the fluorescent cells and created a pure ON bipolar cDNA library that was negative for photoreceptor unique genes. With this library, we determined expression of 27 genes of interest. We obtained positive transcripts for Go interactors: regulators of G‐protein signaling (RGS), Ret‐RGS1 (a variant of RGS20), RGS16, RGS7, purkinje cell protein 2 (PCP2, also called L7 or GPSM4), synembryn (RIC‐8), LGN (GPSM2), RAP1GAP, and Gβ5; cGMP modulators: guanylyl cyclase (GC) 1α1, GC1β1, phosphodiesterase (PDE) 1C, and PDE9A; and channels: inwardly rectifying potassium channel Kir2.4, transient receptor potential TRPC2, and sperm‐specific cation channels CatSper 2–4. The following transcripts were not found in our library: AGS3 (GPSM1), RGS10, RGS19 (GAIP), calbindin, GC1α2, GC1β2, PDE5, PDE2A, amiloride‐sensitive sodium channel ACCN4, and CatSper1. We then localized Kir2.4 to several cell types and showed that, in ON bipolar cells, the channel concentrates in their dendritic tips. The channels and modulators found in ON bipolar cells likely shape their light response. Additional uses of the Grm6‐GFP mouse are also discussed. J. Comp. Neurol. 510:484–496, 2008. © 2008 Wiley‐Liss, Inc.
Dissemination of Rat Cytomegalovirus through Infected Granulocytes and Monocytes In Vitro and In Vivo

ABSTRACT The role of leukocytes in the in vivo dissemination of cytomegalovirus was studied in this experiment. Rat cytomegalovirus (RCMV) could be transferred to rat granulocytes and monocytes by cocultivation with RCMV-infected fibroblasts in vitro. Intravenous injection of purified infected granulocytes or monocytes resulted in a systemic infection in rats, indicating that our model is a powerful tool to gain further insight into CMV dissemination and the development of new antivirals.