Miracle-dz/UniFAR-FTUs huggingface dataset:
Behavior-Based online Incentive Mechanism for Crowd Sensing with Budget Constraints

Crowd sensing is a new paradigm which leverages the ubiquity of sensor-equipped mobile devices to collect data. To achieve good quality for crowd sensing, incentive mechanisms are indispensable to attract more participants. Most of existing mechanisms focus on the expected utility prior to sensing, ignoring the risk of low quality solution and privacy leakage. Traditional incentive mechanisms such as the Vickrey-Clarke-Groves (VCG) mechanism and its variants are not applicable here. In this paper, to address these challenges, we propose a behavior based incentive mechanism for crowd sensing applications with budget constraints by applying sequential all-pay auctions in mobile social networks (MSNs), not only to consider the effects of extensive user participation, but also to maximize high quality of the context based sensing content submission for crowd sensing platform under the budget constraints, where users arrive in a sequential order. Through an extensive simulation, results indicate that incentive mechanisms in our proposed framework outperform the best existing solution.
An effect of variable distance on IP camera performance implemented on WLAN robot

IEEE 802.11n improves upon the previous 802.11 standards by adding multiple-input multiple-output antennas (MIMO). , which operates at a maximum data rate from 54 to 600 Mbit/sec. Nowadays, WLAN robot is becoming popular. IP camera implemented on the WLAN robot consumes a high bandwidth usage, which is needed to investigated. Traffic characteristic of IP camera over IEEE 802.11 is also rarely studied. In this paper, Two IP cameras throughput on WLAN robot is observed. Traffic characteristic of IP camera in terms of packet size and packet volume (pps) is also analyzed. Additionally, the performance comparison of IEEE802.11 devices is also presented. The experimental results show the limitation of using IEEE 802.11 devices in the remote controlling robot on both curved and straight road. WLAN signal is not smooth proved by RTT mdev. Traffic characteristic of IP camera is useful for traffic simulation.
European Union Intergovernmental Conferences: Domestic preference formation, transgovernmental networks and the dynamics of compromise

1. EU Intergovernmental Conferences 2. Theorizing EU Constitutionalization 3. Research Design: A Quantitative Case Study 4. The Agenda: Notes, Issues, and Issue Groups 5. The Domestic Game 6. Transgovernmental Networks in Semi-permeable Governments 7. Signals and Concessions 8. Conclusion
Adolescent Toluene Inhalation in Rats Affects White Matter Maturation with the Potential for Recovery Following Abstinence

Inhalant misuse is common during adolescence, with ongoing chronic misuse associated with neurobiological and cognitive abnormalities. While human imaging studies consistently report white matter abnormalities among long-term inhalant users, longitudinal studies have been lacking with limited data available regarding the progressive nature of such abnormalities, including the potential for recovery following periods of sustained abstinence. We exposed adolescent male Wistar rats (postnatal day 27) to chronic intermittent inhaled toluene (3,000 ppm) for 1 hour/day, 3 times/week for 8 weeks to model abuse patterns observed in adolescent and young adult human users. This dosing regimen resulted in a significant retardation in weight gain during the exposure period (p<0.05). In parallel, we performed longitudinal magnetic resonance imaging (T2-weighted) and diffusion tensor imaging prior to exposure, and after 4 and 8 weeks, to examine the integrity of white matter tracts, including the anterior commissure and corpus callosum. We also conducted imaging after 8 weeks of abstinence to assess for potential recovery. Chronic intermittent toluene exposure during adolescence and early adulthood resulted in white matter abnormalities, including a decrease in axial (p<0.05) and radial (p<0.05) diffusivity. These abnormalities appeared region-specific, occurring in the anterior commissure but not the corpus callosum and were not present until after at least 4 weeks of exposure. Toluene-induced effects on both body weight and white matter parameters recovered following abstinence. Behaviourally, we observed a progressive decrease in rearing activity following toluene exposure but no difference in motor function, suggesting cognitive function may be more sensitive to the effects of toluene. Furthermore, deficits in rearing were present by 4 weeks suggesting that toluene may affect behaviour prior to detectable white matter abnormalities. Consequently, exposure to inhalants that contain toluene during adolescence and early adulthood appear to differentially affect white matter maturation and behavioural outcomes, although recovery can occur following abstinence.
Learning overcomplete dictionaries with ℓ0-sparse Non-negative Matrix Factorisation

Non-negative Matrix Factorisation (NMF) is a popular tool in which a `parts-based' representation of a non-negative matrix is sought. NMF tends to produce sparse decompositions. This sparsity is a desirable property in many applications, and Sparse NMF (S-NMF) methods have been proposed to enhance this feature. Typically these enforce sparsity through use of a penalty term, and a ℓ1 norm penalty term is often used. However an ℓ1 penalty term may not be appropriate in a non-negative framework. In this paper the use of a ℓ0 norm penalty for NMF is proposed, approximated using backwards elimination from an initial NNLS decomposition. Dictionary recovery experiments using overcomplete dictionaries show that this method outperforms both NMF and a state of the art S-NMF method, in particular when the dictionary to be learnt is dense.
A Twofold Spline Approximation for Finite Horizon LQG Control of Hereditary Systems

In this paper an approximation scheme is developed for the solution of the linear quadratic Gaussian (LQG) control on a finite time interval for hereditary systems with multiple noncommensurate delays and distributed delay. The solution here proposed is achieved by means of two approximating subspaces: the first one to approximate the Riccati equation for control and the second one to approximate the filtering equations. Since the approximating subspaces have finite dimension, the resulting equations can be implemented. The convergence of the approximated control law to the optimal one is proved. Simulation results are reported on a wind tunnel model, showing the high performance of the method.
From Needs Assessment to Communities of Practice for Online Continuing-Education Programming.

This study identifies the professional development needs of instructors teaching online using quantitative and qualitative methods. Twenty-six participants from a convenience sample at the University of Colorado, Boulder’s Division of Continuing Education (CE) were surveyed in a Faculty Needs Assessment (FNA) that was open to participants from September to October of 2013, and six of those participants self-selected into an open focus group interview in November 2013. Survey participants were asked questions about skills and knowledge gaps, learning preferences, and other support needed to help advance their professional development. Focus group participants were interviewed to provide further detail about the themes that emerged from the survey. The findings revealed specific pedagogy and technology training needs, platform preferences for the delivery of training and community engagement, and barriers to professional development. The results of the study provide direction on designing a learning and performance strategy to meet instructors’ professional development needs.
Prediction of the Influence of Induced Stresses in Silicon on CMOS Performance in a Cu-Through-Via Interconnect Technology

One approach to 3D chip stacking and integration is to process filled Cu-vias into the Si and to attach them to a next level die by means of thermocompression bonding. This results in induced stresses in the silicon due to the large CTE disparity between copper and silicon, and also from the force applied during thermocompression bonding. These stresses can have an impact on the performance of the transistors and may as well result in die fracture. This paper studies these stresses through Finite Element modeling. We found that the keep-away- zone of the transistors from the copper via where transistor performance is impacted by the through-Si interconnect proximity, is proportional to the via diameter. The bonding temperature is found to be the main cause for the induced stresses during the thermocompression bonding process. The induced stresses in silicon decrease with decreasing the silicon thickness.
Understanding developers' natural language queries with interactive clarification

When performing software maintenance tasks, developers often need to understand a series of background knowledge based on information distributed in different software repositories such as source codes, version control systems and bug tracking systems. An effective way to support developers to understand such knowledge is to provide an integrated knowledge base and allow them to ask questions using natural language. Existing approaches cannot well support natural language questions that involve a series of conceptual relationships and are phrased in a flexible way. In this paper, we propose an interactive approach for understanding developers' natural language queries. The approach can understand a developer's natural language questions phrased in different ways by generating a set of ranked and human-readable candidate questions and getting feedback from the developer. Based on the candidate question confirmed by the developer, the approach can then synthesize an answer by constructing and executing a structural query to the knowledge base. We have implemented a tool following the proposed approach and conducted a user study using the tool. The results show that our approach can help developers get the desired answers more easily and accurately.
CRF based Name Entity Recognition (NER) in Manipuri: A highly agglutinative Indian Language

This paper deals about the Name Entity Recognition (NER) of Manipuri, a highly agglutinative Indian Language. This language is an Eight Scheduled Language of Indian Constitution. NER plays an important role in the applications of Natural Language Processing like Machine Translation, Part of Speech tagging, Information Retrieval, Question Answering etc. Feature selection is an important factor in recognition of Manipuri Name Entity using Conditional Random Field (CRF). This model proved to have a Recall of 81.12%, Precision of 85.67% and F-Score of 83.33%.
Invention and Development of Diffusion Tensor MRI (DT-MRI or DTI) at the NIH

At the time of the invention of DT-MRI (or DTI), I was employed as a Staff Fellow (a postdoctoral fellow position) in the Mechanical Engineering Section (MES) of the Biomedical Engineering and Instrumentation Branch (BEIB) in the Intramural Research Program (IRP) of the National Center for Research Resources (NCRR) of the National Institutes of Health (NIH). (People in the federal government like acronyms! ) This was my fi rst postdoctoral position after having graduated from Harvard University’s Division of Applied Sciences, where I had studied biofl uid and continuum mechanics, and applied mathematics. Initially, my research activities within BEIB focused on “biomimetics,” specifi cally, the development of models and model systems that mimic more complex biological ones; and studying the response of tissues to impressed mechanical and electric fi elds. By the early 1990s, my two primary projects involved understanding the physical basis of electromagnetic stimulation (i.e., “magnetic stimulation”) of the peripheral (PNS) and central nervous systems (CNS), and understanding the mechanical effects (swelling and consolidation) in the brain during drug infusion. Bradley Roth (a talented biophysicist and fellow Staff Fellow in the BEIB) and I had developed a mathematical model of magnetic stimulation to explain how induced electromagnetic fi elds in neural tissue can cause depolarizing or hyperpolarizing transmembrane currents in long axons in the PNS. In one of our papers (Basser and Roth, 1991 ), we described an axon’s trajectory or path as a 3D space curve — a concept that later resurfaced in DTI tractography (Basser, 1998 ) — while considering the case of magnetic stimulation of an axon whose path is kinked or sinuous. Developing these models of magnetic stimulation led me to realize that we would never be able to determine the action of induced electromagnetic fi elds on nerves in the CNS or the PNS if we 1) didn’t know the coordinates and trajectories of the nerve pathways of interest, and 2) more generally, didn’t know the anisotropic and heterogeneous electrical properties (i.e., the Summay box
A Hierarchical Online Classifier for Patent Categorization

Patent categorization (PC) is a typical application area of text categorization (TC). TC can be applied in different scenarios at the work of patent offices depending on at what stage the categorization is needed. This is a challenging field for TC algorithms, since the applications have to deal simultaneously with large number of categories (in the magnitude of 1000–10000) organized in hierarchy, large number of long documents with huge vocabularies at training, and they are required to work fast and accurate at on-the-fly categorization. In this paper we present a hierarchical online classifier, called HITEC, which meets the above requirements. The novelty of the method lies in the taxonomy dependent architecture of the classifier, the applied weight updating scheme, and in the relaxed category selection method. We evaluate the presented method on two large English patent application databases, the WIPO-alpha and the Espace A/B corpora. We also compare the method to other TC algorithms on these collections, and show that it outperforms them significantly.
Semantic Gossiping: Coping with Heterogeneous Semantic Knowledge Management Systems in the Large

With the creation and wide adoption of Semantic Web standards like RDF or OWL, a new breed of semantic networks is about to appear. For the first time, we can expect large numbers of knowledge management systems to interoperate using common languages to express the semantics of the data they share or seek. We however foresee semantic heterogeneity to surface once more as a key problem in information integration, given the scale and variety of the systems we are dealing with: Indeed, we realistically cannot expect common global upper-ontologies to capture with sufficient adequacy the requirements of all the different parties in our heterogeneous environment. Custom ontologies will be developed for various application needs, thus endangering global semantic interoperability by introducing local concepts and properties. Also, the situation is somewhat complicated by the fact that ontologies will not be static in such environments, but will tend to evolve, appear or disappear dynamically as systems join and leave the network. Cleary, there is a need and potential to develop new semantic integration techniques here, since traditional approaches can neither cope with the scale, nor with the dynamicity of such environments. Observing that fostering semantic interoperability requires some form of agreement or consensus among information sharing parties we focus on mechanisms for establishing such agreements in the large. Unlike traditional approaches, like database schema integration or ontology engineering, we do not require the agreements to be static, global or even accurate. Rather, we consider the existence of mutual local agreements only, and expect global semantic properties to emerge from the continuous interactions of autonomous entities in a self-organizing manner. Establishing semantic interoperability in the large can be understood as studying the dynamics of a complex, self-organizing system. Local communication and decision-making of information sharing agents generate the dynamics of this system. When agents locally reach acceptable agreements that are as consistent as possible with the information they receive, the global system reaches a state that embodies what we call the global semantic agreement. Since this state emerges from the dynamics of a complex system, we call the resulting global semantic agreement also the emergent semantics of the semantic interoperability system.
Unsupervised image categorization with improved spectral clustering

This paper presents an approach for unsupervised image categorization which can be used in non-label image library. We extract the basic feature from image, and by using bag of words model and spatial pyramid matching we manage to improve image descriptor performance. To get better clustering performance we propose an improved spectral clustering approach and use it to achieve our image categorization object. We test our approach on two widely used image datasets. Furthermore we compare our approach to several methods and experimental results show that our approach is effective.
Initiation, Propagation, and Termination of Epileptiform Activity in Rodent Neocortex In Vitro Involve Distinct Mechanisms

Waves of epileptiform activity in neocortex have three phenomenological stages: initiation, propagation, and termination. We use a well studied model of epileptiform activity in vitro to investigate directly the hypothesis that each stage is governed by an independent mechanism within the underlying cortical circuit. Using the partially disinhibited neocortical slice preparation, activity is induced and modulated using neurotransmitter receptor antagonists and is measured using both intracellular recordings and a linear array of extracellular electrodes. We find that initiation depends on both synaptic excitation and inhibition and entails a slow process of recruitment at discrete spatial locations within cortical layer 5 but not layer 2/3. Propagation depends on synaptic excitation but not inhibition and is a fast process that involves neurons across the spatial extent of the slice and in all cortical layers. Termination is modulated by synaptic excitation and inhibition. In space, termination occurs reliably at discrete locations. In time, termination is characterized by a strong depolarizing shift (block) and recovery of neurons in all cortical layers. These results suggest that the phenomenological stages of epileptiform events correspond to distinct mechanistic stages.
Research on the Information Integrated Model of ERP and ABC in the Environment of Project Manufacturing

Focused on the issues of the project manufacturing enterprise without considering the proportion of overhead increased evidently in products total cost, still adopting traditional costing accounting methods may cause the cost information of project to distort and make a biased strategy decisions. According to analyze the feature of ERP system and the basic principle of activity-based costing (ABC), summarized the theoretical foundation of integrating ERP and ABC, and made the basic model which integrated ERP with ABC. Eventually, with considering the feature of ERP system in project manufacturing enterprise and the basic model, constructed the information integrated model of ERP and ABC in the environment of project manufacturing.
FINDING THE PROBLEM : THE FOUNDATION OF THE REQUIREMENTS ENGINEERING PROCESS

This paper examines the cognitive processes involved in problem finding as part of the Requirements Engineering (RE) process. It describes intensive field research that provided rich understanding of the practices of systems analysts. The paper makes three contributions to cognitive research in Information Systems. Firstly, three characteristics of analysts’ problem finding in the early stages of the RE process are identified. Some of these observations have been noted previously in other domains. However, it is the combination of characteristics that typifies problem finding in the RE process. The importance of these characteristics is demonstrated through a comparison of the practices of an expert and a novice analyst. Secondly, observation of analysts’ exploration of the problem space has led to an revised definition of opportunism that is applicable to problem finding. Thirdly, empirically-based understanding of the cognitive processes involved in problem finding provides for practical improvements to the early stages of the RE process. The paper concludes with suggestions for training, supporting and managing analysts during their problem finding activities.
A taxonomy of routing protocols for wireless sensor networks

Wireless sensor networks are large scale networks consisting of a large number of tiny sensor nodes and a few base stations, which communicate using multi-hop wireless communications. The design of energy efficient routing protocols for such networks is a challenging task, which has been in the focus of the sensor network research community in the recent past. This effort resulted in a huge number of sensor network routing protocols. The proposed protocols show a high variety, which stems from the diverse requirements of the various envisioned application scenarios. In this work, we propose a taxonomy of sensor network routing protocols, and classify the mainstream protocols proposed in the literature using this taxonomy. We distinguish five families of protocols based on the way the next hop is selected on the route of a message, and briefly describe the operation of a representative member from each group.
Hydraulic constraints in the functional scaling of trees.

I conducted a literature survey to assess the available information on relationships between size--expressed in terms of diameter and dry biomass--and hydraulic efficiency of woody structures at different scales, from stem segments to whole trees. Three data sets were constructed: the first described the relationship between segment diameter and hydraulic conductivity (k(h); kg m s(-1) MPa(-1)) in four species; the second, for the same four species, described the intraspecific trajectories of change in total hydraulic conductance (G; kg s(-1) MPa(-1)) during ontogeny, i.e., from saplings to mature trees, thereby providing a comparison between allometric scaling laws at the scales of segments and whole trees; the third comprised pooled means for nine species that described the interspecific trajectory of change in G with tree size. The scaling coefficients obtained were compared with predictions made with an architectural fractal-like model incorporating tissue-specific hydraulic architecture parameters (West et al. 1999). When data on segment k(h) were examined, the fractal-like model closely predicted the scaling of k(h) with segment diameter in four species. However, the model failed to predict accurately in all species the intraspecific scaling at the branch and whole-tree levels, and consistently overestimated the scaling coefficients. The results suggest that ontogenetic changes in tree size during the life cycle of one tree may result in tradeoffs between optimal hydraulic supply to the existing leaf area and maintenance costs of the supporting xylem tissue. The model of West et al. (1999) may be useful for understanding broad interspecific patterns, but not for understanding more subtle ontogenetic changes.