Miracle-dz/UniFAR-FTUs huggingface dataset:
Battery-Aware IT Control Method for Effective Battery Use During Power Outage

We propose a novel method of information technology (IT) control that makes highly effective use of batteries under conditions where IT systems are powered by batteries during power outages. The main feature of this method is that it both utilizes battery residue and the forecast duration of power outages taking battery characteristics into consideration. We made a prototype using actual batteries and evaluated their characteristics and that of the proposed approach. The new method achieved a 27% improvement in the measurement of the IT-used-energy/battery-used-energy (Qt=Qu) compared to the conventional method that only utilized battery residue.
Electrophysiological Evidence for Spatiotemporal Flexibility in the Ventrolateral Attention Network

Successful completion of many everyday tasks depends on interactions between voluntary attention, which acts to maintain current goals, and reflexive attention, which enables responding to unexpected events by interrupting the current focus of attention. Past studies, which have mostly examined each attentional mechanism in isolation, indicate that volitional and reflexive orienting depend on two functionally specialized cortical networks in the human brain. Here we investigated how the interplay between these two cortical networks affects sensory processing and the resulting overt behavior. By combining measurements of human performance and electrocortical recordings with a novel analytical technique for estimating spatiotemporal activity in the human cortex, we found that the subregions that comprise the reflexive ventrolateral attention network dissociate both spatially and temporally as a function of the nature of the sensory information and current task demands. Moreover, we found that together with the magnitude of the early sensory gain, the spatiotemporal neural dynamics accounted for the high amount of the variance in the behavioral data. Collectively these data support the conclusion that the ventrolateral attention network is recruited flexibly to support complex behaviors.
Diverse Consequences of Algorithmic Probability

We reminisce and discuss applications of algorithmic probability to a wide range of problems in artificial intelligence, philosophy and technological society. We propose that Solomonoff has effectively axiomatized the field of artificial intelligence, therefore establishing it as a rigorous scientific discipline. We also relate to our own work in incremental machine learning and philosophy of complexity.
Power Optimization in IDMA with SNR and Differential Evolutions

Interleave Division Multiple Access (IDMA) is a multiple access scheme where users are separated by the only means of interleavers. However, IDMA revealed to depend on power optimization because equal power repartition significantly deteriorates the performance when the system is heavy-loaded. Therefore, we propose the application of the genetic annealing Differential Evolution algorithm to SNR evolution for solving this optimum power allocation problem.
Inverse Game Theory

One of the central questions in game theory deals with predicting the behavior of an agent. Here, we study the inverse of this problem: given the agents’ equilibrium behavior, what are possible utilities that motivate this behavior? We consider this problem in arbitrary normal-form games in which the utilities can be represented by a small number of parameters, such as in graphical, congestion, and network design games. In all such settings, we show how to efficiently, i.e. in polynomial time, determine utilities consistent with a given correlated equilibrium. However, inferring both utilities and structural elements (e.g., the graph within a graphical game) is in general NP-hard. From a theoretical perspective our results show that rationalizing an equilibrium is computationally easier than computing it; from a practical perspective a practitioner can use our algorithms to validate behavioral models.
What a Legal CBR Ontology Should Provide

This paper discusses the state of the art in CBR ontologies from the perspective of one developing an improved system for case-based legal reasoning. The paper proposes three specific roles for a CBR ontology and illustrates them in the context of the intended output of the new system: a legal classroom discussion of how to decide a case featuring hypothetical reasoning and abstract analogies. The paper distills the ontological requirements for modeling the example’s case-based arguments and assesses whether current research can meet those requirements. The concrete example helps to focus on and define goals for improving CBR ontologies.
PRECISE FINGERPRINT ENROLMENT THROUGH PROJECTION INCORPORATED SUBSPACE BASED ON PRINCIPAL COMPONENT ANALYSIS (PCA)

Despite recent advances in the area of fingerprint identification, fingerprint enrolment continues to be a challenging pattern recognition problem. The first step to this problem is the enhancement of landmarks as well as precise minutiae points (ridge bifurcation and ridge ending), core, plain ridges from a print. Once enhanced, these fingerprint images are then ready to extract features and store into a database. Later these are compared to all sets on file in search of a match. The accurate fingerprint image is the basis for the entire identification and matching process. Various enhancement approaches have been proposed in the literature, each with its own merits and degree of success. The most common approach is to enhance and store the precise fingerprint image through normalization, orientation, frequencies calculation, contextual filtering and then binarisation and masking. Our emphasis in this paper is to enhance and store the fingerprint image accurately using Projection Incorporated Subspace based on Principal Component Analysis (PCA). In particular, we have implemented the methods based on eigenspace representations and neural network classifiers. Moreover, we present preliminary results of an attempt to mingle the outputs of these methods using a clustering algorithm unique to this type of problem.
A Novel and Lightweight System to Secure Wireless Medical Sensor Networks

Wireless medical sensor networks (MSNs) are a key enabling technology in e-healthcare that allows the data of a patient's vital body parameters to be collected by the wearable or implantable biosensors. However, the security and privacy protection of the collected data is a major unsolved issue, with challenges coming from the stringent resource constraints of MSN devices, and the high demand for both security/privacy and practicality. In this paper, we propose a lightweight and secure system for MSNs. The system employs hash-chain based key updating mechanism and proxy-protected signature technique to achieve efficient secure transmission and fine-grained data access control. Furthermore, we extend the system to provide backward secrecy and privacy preservation. Our system only requires symmetric-key encryption/decryption and hash operations and is thus suitable for the low-power sensor nodes. This paper also reports the experimental results of the proposed system in a network of resource-limited motes and laptop PCs, which show its efficiency in practice. To the best of our knowledge, this is the first secure data transmission and access control system for MSNs until now.
POLY-SIGE: A HIGH-Q STRUCTURAL MATERIAL FOR INTEGRATED RF MEMS

This paper presents new material data for single- and multi- layer CMOS compatible poly-SiGe films, including mechanical quality factor (Q), Young's modulus, and strain gradient. Using audio frequency folded-flexure comb-drive resonators, the mechanical quality factor of poly-SiGe was determined at 2µTorr pressure. As-deposited poly-SiGe has Q = 20,000 - 31,000. CMOS compatible rapid thermal annealing (RTA) at 525°C for 60 seconds results in a quality factor between 40,000 and 44,000. We have measured the highest Q factor yet reported for poly-SiGe (Qs 61,100), as a result of RTA at 600°C for one minute. The measured resonant frequencies of the resonators were used to back-calculate the Young's modulus of poly-SiGe: E = 155 ± 5GPa. The calculated elastic modulus is significantly higher than the metallurgical Young's modulus of 146GPa. The as-deposited strain gradient of the tri-layer poly-SiGe film was found to be 1.75·10 -4 µm -1 (curl-up). RTA at 600°C for one minute drops the tri-layer strain gradient to 2.67·10 -5 µm -1 (curl-up). The graded Ge content multi-layer film was observed to induce a larger normalized strain gradient.
Organic food and mothers: techniques of neoliberal governmentality and negotiation of multiple discourses of motherhood, risks, and organic food

This thesis is based on a fieldwork consisting of sixteen in-depth interviews with mothers having children younger than seven years old and a discourse analysis of comments and posts on a mother blog. It analyzes following questions: Do the motivations and practices of mothers for feeding their children organic differ from each other? , why and how? ; is it considered primarily as the duty of mothers and why? ; is organic nurturing of a child a distinctive practice? ; do varied forms of organic food experiences in the urban space contribute to the symbolic boundaries within these mothers? Research findings indicate that there are multiple discourses which circulate and constitute the basis of concerns and motivations of mothers for feeding their children organic. The study also reveals that mothers contribute to these discourses not only and simply by reproducing them but also negotiating, transforming and reshaping them as active agents through their own practices in which their own economic and cultural capital, and their social positioning play an important role. It explores their impact on the diversification of perspectives and experiences of organic feeding, and thus points out that these practices are not only gendered but also classed and distinctive. Also, the research elaborates the symbolic boundaries that these practices strengthen, not only by drawing attention to the socio-economic boundaries but also the moral boundaries that organic feeding experiences highlight. Finally, through this case, it demonstrates how managing food security for children becomes a technique of neoliberal governmentality for mothers as a privatized responsibility. It examines how the ideals of selfconscious and sensitive mothers intersect with the organic food and risk discourses, and how intense mothering performances and the affective burden of these ideals are experienced by women.
Efficient Point-Based Rendering Techniques for Haptic Display of Virtual Objects

Computer haptics, an emerging field of research that is analogous to computer graphics, is concerned with the generation and rendering of haptic virtual objects. In this paper, we propose an efficient haptic rendering method for displaying the feel of 3-D polyhedral objects in virtual environments (VEs). Using this method and a haptic interface device, the users can manually explore and feel the shape and surface details of virtual objects. The main component of our rendering method is the neighborhood watch algorithm that takes advantage of precomputed connectivity information for detecting collisions between the end effector of a force-reflecting robot and polyhedral objects in VEs. We use a hierarchical database, multithreading techniques, and efficient search procedures to reduce the computational time such that the haptic servo rate after the first contact is essentially independent of the number of polygons that represent the object. We also propose efficient methods for displaying surface properties of objects such as haptic texture and friction. Our haptic-texturing techniques and friction model can add surface details onto convex or concave 3-D polygonal surfaces. These haptic-rendering techniques can be extended to display dynamics of rigid and deformable objects.
Herschel observations of FIR emission lines in brightest cluster galaxies

The question of how much gas cools in the cores of clusters of galaxies has been the focus of many, multiwavelength studies in the past 30 years. In this letter we present the first detections of the strongest atomic cooling lines, [Cii], [Oi ]a nd [Nii] in two strong cooling flow clusters, A1068 and A2597, using Herschel-PACS. These spectra indicate that the substantial mass of cold molecular gas (>10 9 M� ) known to be present in these systems is being irradiated by intense UV radiation, most probably from young stars. The line widths of these FIR lines indicate that they share dynamics similar but not identical to other ionised and molecular gas traced by optical, near-infrared and CO lines. The relative brightness of the FIR lines compared to CO and FIR luminosity is consistent with other star-forming galaxies indicating that the properties of the molecular gas clouds in cluster cores and the stars they form are not unusual. These results provide additional evidence for a reservoir of cold gas that is fed by the cooling of gas in the cores of the most compact clusters and provide important diagnostics of the temperature and density of the dense clouds this gas resides in.
COMPUTER MODELLING OF HEAT AND MASS FLOW IN STEAMING GROUND AT KARAPITI THERMAL AREA , NEW ZEALAND

Heat and mass transfer in steaming ground have been modeled using the TOUGH2 geothermal simulator and the results compared with field data collected by Bromley and Hochstein (2001). They measured temperatures at several sites over periods of 4 to 7 days at the soil surface, and depths of 0.01 m, 0.05 m, 0.10 m, 0.15 m, and 0.20 m. Soil porosities and saturations were also measured. These data sets were processed to extract four key sub-sets of data that were then used to calibrate a TOUGH2 model for each site. Two of these data sets are the steady state temperature and gas saturation versus depth; and the other two involve parameters of the variation with depth of the transient, approximately sinusoidal, diurnal temperature, namely, amplitude decay and phase shift. Calibration of the TOUGH2 models provides information about soil properties and heat and mass flows at each site. Model calibration also indicates a suitable range of parameters for the van Genuchten-Mualem relative permeability and van Genuchten capillary functions (Mualem, 1976; van Genuchten, 1980).
Optimizing MBMS Power Allocation through HSDPA Transmissions

Multimedia Broadcast Multicast Service (MBMS) epitomizes the increasing popularity of enhanced end-user experience in Universal Mobile Telecommunications System (UMTS), since it allows the economical delivery of multimedia services to a large number of users. MBMS multicast supports both Point-to-Point (PTP) and Point-to-Multipoint (PTM) modes in order to confront the strict resource limitations in wireless environments and improve efficiency during data transmission. The aim of this paper is to highlight the performance enhancements of MBMS multicasting over the High Speed Downlink Packet Access (HSDPA) and underline the need for its integration in MBMS specifications. HSDPA can play an instrumental role in positioning MBMS services as a key enabler for true Mobile Broadband. Under this prism, we investigate the provision of MBMS services over HSDPA, through a direct comparison between HSDPA and Release ’99 bearers. Since downlink transmission power is the most limited resource in UMTS networks, the evaluation is performed via an analytical dimensioning of the MBMS transmission power both in macrocells and microcells. Simulation results reveal that HSDPA can significantly optimize MBMS power allocation, bring more capacity and, consequently, enable the mass-market delivery of rich multimedia services in mobile networks.
How Does AES Work ?

Joshua Brown, Adam Mikeal, and Alysha Clark provided substantial feedback that greatly enhanced the value and clarity of the information in this article. Abstract Two of the largest Massive Open Online Course (MOOC) organizations have chosen different methods for the way they will score and provide feedback on essays students submit. EdX, MIT and Harvard’s non-profit MOOC federation, recently announced that they will use a machine-based Automated Essay Scoring (AES) application to assess written work in their MOOCs. Coursera, a Stanford startup for MOOCs, has been skeptical of AES applications and therefore has held that it will use some form of human-based “calibrated peer review” to score and provide feedback on student writing. This essay reviews the relevant literature on AES and UCLA’s Calibrated Peer ReviewTM (CPR) product at a high level, outlines the capabilities and limitations of both AES and CPR, and provides a table and framework for comparing these forms of assessment of student writing in MOOCs. Stephen Balfour is an instructional associate professor of psychology and the Director of Information Technology for the College of Liberal Arts at Texas A&M University.
GCplace: geo-cloud based correlation aware data replica placement

Cross datacenter data replication has been widely used in geo-cloud environment due to its ability to increase application's availability and improve the performance. However, with the large scale of cloud, it is difficult to determine the location of replicas among datacenters in order to minimize overall user access latency. The data correlation between each other makes replica placement problem more complex. To address these large scale and data correlation issues, we propose a two-step approach called GCplace. Before applying GCplace, a network coordinate system is used to predict the latency between all users and datacenter nodes. In the first step of GCplace, we introduce a stream based similarity clustering, which uses a small number of micro clusters to represent huge number of users and thus significantly reducing the cost of replica placement algorithm. In the second step, an iterative algorithm is proposed to get an approximation solution. We evaluated our approach by using a large scale real network latency dataset. Comprehensive experiments show that GCplace can reduce average user access latency significantly.
Genre Specific Aspect Based Sentiment Analysis of Movie Reviews

The opinion conveyed by the user towards a movie can be understood by doing Sentiment Analysis on the movie review. In the current work we focus on Genre Specific Aspect Based Sentiment Analysis of Movie Reviews. Using the aforementioned dataset and considering movie genres like action, comedy, crime, drama and horror, we develop a fine grained unsupervised analysis model using lexicons that are context specific to each genre under consideration.
Service cooperation in PaaS platform based on planning method

Platform-as-a Service (PaaS) provides a new pattern of software design, development, testing, deployment and hosting for organizations such as ISV, business department and so on. When the PaaS platform brings together lots of software services from various organizations; it's a challenging work to construct dynamically and intelligently new application with these service resources to meet application request. This paper pays more attention on application cooperation, namely business service process cooperation due to business process is the main form of application, in PaaS Platform based on planning method. Our approach comprises the following steps: construct abstract business process for cooperation based on the hierarchical task network planning and semantic model of service cooperation; construct executable serviceflow based on candidate services and use graph planning to verify dataflow in executable serviceflow. This approach can ensures not only the semantic consistency between the business objectives and business process logic, but also the dataflow consistency in process. This approach can provide more available executable serviceflow for business cooperation of different organizations in PaaS Platform. The correctness and necessity of this approach are verified through experiments and some cases.
Evolving ensemble of classifiers in random subspace

Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the diversity for the ensemble selection could be very time consuming. We propose compound diversity functions as objective functions for a faster and more effective GA searching. Classifiers selected by GA are combined by a proposed pairwise confusion matrix transformation, which offer strong performance boost for EoCs.
Query Answering under Matching Dependencies for Data Cleaning: Complexity and Algorithms

Matching dependencies (MDs) have been recently introduced as declarative rules for entity resolution (ER), i.e. for identifying and resolving duplicates in relational instance $D$. A set of MDs can be used as the basis for a possibly non-deterministic mechanism that computes a duplicate-free instance from $D$. The possible results of this process are the clean, "minimally resolved instances" (MRIs). There might be several MRIs for $D$, and the "resolved answers" to a query are those that are shared by all the MRIs. We investigate the problem of computing resolved answers. We look at various sets of MDs, developing syntactic criteria for determining (in)tractability of the resolved answer problem, including a dichotomy result. For some tractable classes of MDs and conjunctive queries, we present a query rewriting methodology that can be used to retrieve the resolved answers. We also investigate connections with "consistent query answering", deriving further tractability results for MD-based ER.
Trans-synaptic modulation of histamine H-1 receptor development in rat brain

To determine whether neuronal histamine influences development of histamine H-1 receptors in the rat brain, neonates were given diphenhydramine, an H-1 antagonist, daily for the first 21 days of postnatal life. In control rats, specific H-1 binding of [3H]mepyramine in whole brain was low at birth and increased progressively toward adult levels by the end of the 3rd week. Animals treated with diphenhydramine showed marked elevations in binding as early as 4 days postnatally and the differences persisted throughout the experimental period. The increased binding in treated rats was specific to treatment with H-1 antagonists (diphenhydramine, mepyramine) as opposed to an H-2 antagonist (cimetidine); the alteration reflected enhancement of the number of binding sites without a change in Kd, a finding indicative of H-1 receptor supersensitivity. Similar results were seen in the hypothalamus, an area rich in neuronal histaminergic projections. Levels of histamine in the hypothalamus were unaffected by diphenhydramine administration until the end of the 3rd week, at which time, increases were noted. After the loading of the hypothalamus with [3H]histamine, release of label by K+ depolarization in vitro (an indirect index of release from the neuronal histamine pool) was readily obtained at all ages and was unaffected by diphenhydramine administration. Diphenhydramine did not alter histamine levels in brain regions in which most of the histamine is non-neuronal. These studies suggest that, even early in the ontogenesis of histaminergic synapses, a sufficient proportion of releasable histamine is associated with histaminergic neurons to enable trans-synaptic modulation of development of histaminergic H-1 receptors; consequently, blockade of these receptors with diphenhydramine results in supersensitivity even at the earliest stages of development.
Report on Demonstration Scenario Specifications

: This deliverable belongs to Task 7.5, which was added to the annex of the project after the first review, appropriate to the recommendations of the reviewers. In this report, specifications of the demonstrator scenarios are discussed. Four representative areas for haptic feedback are selected and demonstration scenarios are created appropriate to these areas. The demonstrators are divided into four groups, namely Soft Tissue Interaction Simulators , Haptic Texture and Pattern Demonstrators , Rigid Haptic Prototyping Demonstrators