Miracle-dz/UniFAR-FTUs huggingface dataset:
Academic Challenge: Its Meaning for College Students and Faculty

Academic challenge is seldom clearly defined. The authors’ center for teaching and learning collaborated with a faculty member to investigate the perceived meaning of academic challenge among faculty and student samples at a small liberal arts institution. Participants completed a questionnaire designed to reflect those perceived meanings. Qualitative and quantitative analyses revealed contextualized information and suggested that students’ perceptions are structured differently from faculty members’ perceptions. The amount of time spent on academics was more centrally positioned in the students’ perceptions than in the faculty members’. Future research approaches and directions for centers for teaching and learning are suggested.
Low power realization of finite state machines—a decomposition approach

We present in this article a new approach to the synthesis problem for finite state machines with the reduction of power dissipation as a design objective. A finite state machine is decomposed into a number of coupled submachines. Most of the time, only one of the submachines will be activated which, consequently, could lead to substantial savings in power consumption. The key steps in our approach are: (1) decomposition of a finite state machine into submachines so that there is a high probability that state transitions will be confined to the smaller of the submachines most of the time, and (2) synthesis of the coupled submachines to optimize the logic circuits. Experimental results confirmed that our approach produced very good results (in particular, for finite state machines with a large number of states.)
Guest editorial: special issue on on-chip inductance in high-speed integrated circuits

HE appropriate interconnect model has changed several times over the past two decades due to aggressive technology scaling. New, more accurate interconnect models were introduced when parasitic effects that were negligible in earlier technologies, could no longer be ignored. Currently, RC models are used to analyze high resistance nets while capacitive models are used for less resistive interconnects. However, on-chip inductance is becoming increasingly important since integrated circuits now operate at frequencies where the inductive impedance of thick wide wires is comparable to wire resistance and line lengths are long enough, relative to signal rise times, for transmission line behavior to become significant. Furthermore, this trend shows every indication of spreading beyond the relatively few lines it now affects. Operating frequencies that have increased dramatically over the past decade, are expected to maintain the same rate of increase over the next decade approaching 10 GHz by the year 2012. The use of thick upper level metals, large die sizes, and low resistance copper interconnect—already used in many commercial CMOS technologies, will likewise continue. Finally, because large die sizes enable more system integration, the use of long thick wide wires, once largely devoted to global clock distribution networks, will spread to critical data-buses and control lines. This special issue deals with the design and analysis of integrated circuits including parasitic on-chip inductance. It does not deal with intentionally designed structures like the spiral inductors used in RF circuits and LC tank oscillators. As evidence that the subject material is still under investigation, the papers in this special issue do not present a unified approach to modeling parasitic inductance. The most notable difference centers around the use of 2-D (or loop inductance) models versus more general 3-D inductance models, and at the center of this debate is the question of current loops formed by return currents. The 3-D model advocates take the position that the return current paths are fundamentally unknown and present sophisticated analysis methods to cope with the increased complexity of 3-D models. The 2-D advocates insist that the return currents are equal and opposite to the interconnect currents and can therefore, employ simpler models. While this debate is apparent in the second paper which favors 2-D models and the third, fourth, and sixth papers which favor 3-D models, several other papers also imply a preference by presenting analytical methods that are suitable to 2-D models only. The paper summary below highlights when notable, the authors stated or implied preference to 2-D or 3-D models. In the first paper, Ismail presents several analytical methods for including inductive effects in both timing and noise analysis. The analytical models he presents are only applicable to
Battery-based intrusion detection a first line of defense

This paper proposes a first line of defense early warning system via a host-based form of intrusion detection that can alert security administrators to protect their corporate network(s). This innovative technique operates through the implementation of battery-based intrusion detection (B-bid) on mobile devices by correlating attacks with their impact on device power consumption using a rule-based host intrusion detection engine (HIDE). HIDE monitors power behavior to detect potential intrusions by noting irregularities of power consumption and works in conjunction with a host analysis signature trace engine (HASTE) to provide protection to both mobile hosts and, by extension, their affiliated network.
Conservation practice as primitive accumulation

Protected areas appear to be examples of Marx's primitive accumulation, complete with acts of enclosure, dispossession, dissolution of the commons and accumulation. There are limits to these parallels, however. Though primitive accumulation generally involves the enclosure of a commons in favor of private property, protected areas generally create public, not private property. Protected areas that limit extraction are not being commodified, but are being taken out of the market. This paper shows that arguments against the parallels between primitive accumulation and the creation of protected areas may be confounded bythe realities of conservation practice. The violent acts of enclosure and dispossession related to the creation of protected areas may lead to private benefit, and expand the conditions under which capitalist production can expand and continue. I show the mechanisms by which enclosure and dispossession take place, the consequences of these actions, as well as the acts of resistance against them.
A Terrain Model Simplification Method Based on Adaptive Threshold Selection

This paper presents a fast simplification strategy for the terrain model based on identifying the terrain features. In this strategy, the original data is organized on a hierarchical structure with multi-resolution, which reduced effectively the range of searching feature points. Thus, the feature points can be selected fast according to our rules. Taking the feature points as the centers, we can obtain the feature areas by using the proposed division algorithm. The aim is to provide the criterion for the error evaluation and the threshold enactment. Based on the feature areas, we proposed the multi-threshold algorithm, which improved the precision and the self-adaptability of the result model greatly. Finally, many experiments have been conducted on the various benchmark data, which shows that our method is very efficient and the result model can preserve the detailed features with a quite high precision even as the simplification ratio is very high.
On the Assumptions about Network Dynamics in Distributed Computing

Besides the complexity in time or in number of messages, a com mon approach for analyzing distributed algorithms is to look at the assumptions they ma ke on the underlying network. We investigate this question from the perspective of network dynamics. In p articular, we ask how a given property on the evolution of the network can be formally proven as necess ary or sufficient for a given algorithm. The main contribution of this paper is to propose the combinatio n of two existing tools in this direction: local computationsby means of graph relabelings , andevolving graphs . Such a combination makes it possible to express fine-grained properties on the network dynamics, th en examine what impact those properties have on the possible outcomes of an execution. We illustrate the u se of this framework through the analysis of three simple algorithms, then discuss general implication s of this work, which include (i) the possibility to compare distributed algorithms on the basis of their topolo gical requirements, (ii) a formal classification of dynamic networks based on these requirements, and (iii) t he potential for mechanization induced by our framework, which we believe opens a path towards automated a nalysis and decision support in dynamic networks.
Efficient, Modular Metadata Management with Loris

With the amount of data increasing at an alarming rate, domain-specific user-level metadata management systems have emerged in several application areas to compensate for the shortcomings of file systems. Such systems provide domain-specific storage formats for performance-optimized metadata storage, search-based access interfaces for enabling declarative queries, and type-specific indexing structures for performing scalable search over metadata. In this paper, we highlight several issues that plague these user-level systems. We then show how integrating metadata management into the Loris stack solves all these problems by design. In doing so, we show how the Loris stack provides a modular framework for implementing domain-specific solutions by presenting the design of our own Loris-based metadata management system that provides 1) LSM-tree-based metadata storage, 2) an indexing infrastructure that uses LSM-trees for maintaining real-time attribute indices, and 3) scalable metadata querying using an attribute-based query language.
Classification of left/right hand movement from EEG signal by intelligent algorithms

Brain Computer interface (BCI) shown enormous ability to advance the human way of life. Furthermore its application is also targeting the disabled ones. In this research, we have implemented a new approach to classify EEG signals more efficiently. The dataset used for this purpose is from BCI competition-II 2003 named Graz database. Initial processing of the EEG signals has been carried out on 2 electrodes named C3 & C4; after that the bi-orthogonal wavelet coefficients, Welench Power Spectral Density estimates and the average power were used as a feature set for classification. We have given a relative study of currently used classification algorithms along with a new approach for classification i.e. Self-organizing maps (SOM) based neural network technique. It is used to classify the feature vector obtain from the EEG dataset, into their corresponding classes belong to left/right hand movements. Algorithms have been implemented on both unprocessed features and processed reduced feature sets. Principal component Analysis (PCA) has been used for feature reduction. Measured data revealed that the maximum classification accuracy of 84.17% on PCA implemented reduce feature set has been achieved using SOM based classifier. Furthermore, the classification accuracy has been increased about 2% by simply using bi-orthogonal Wavelet transform rather than Daubechies wavelet transform.
Phase behavior of C18 monoglyceride in hydrophobic solutions

We apply a set of different techniques to analyze the physical properties and phase transitions of monoglycerides (MGs) in oil. In contrast to many studies of MGs in water or aqueous systems, we find a significant difference in the phase structure at different concentrations and temperatures. By adding small quantities of water to our base MG/oil systems we test the effect of hydration of surfactant head-groups, and its effect on the phase behavior. The phase diagrams are determined by calorimetry and their universal features are recorded under different conditions. Two ordered phases are reported: the inverse lamellar gel phase and the sub-alpha crystalline gel phase. This sequence is very different from the structures in MG/water; its most striking feature is the establishing of a 2D densely packed hexagonal order of glycerol heads in the middle of inverse lamellar bilayers. Rheology was examined through temperature scans to demonstrate the gelation phenomenon, which starts from the onset of the lamellar phase during the cooling/ordering process.
On the possibility of a helium white dwarf donor in the presumed ultracompact binary 2S 0918-549

2S 0918–549 is a low-mass X-ray binary (LMXB) with a low optical to X-ray flux ratio. Probably it is an ultracompact binary with an orbital period shorter than 60 min. Such binaries cannot harbor hydrogen rich donor stars. As with other (sometimes confirmed) ultracompact LMXBs, 2S 0918–549 is observed to have a high neon-to-oxygen abundance ratio (Juett et al. 2001, ApJ, 560, L59) which has been used to argue that the companion star is a CO or ONe white dwarf. However, type-I X-ray bursts have been observed from several of these systems implying the presence of hydrogen or helium on the neutron star surface. In this paper, we argue that the companion star in 2S 0918–549 is a helium white dwarf. We first present a type-I X-ray burst from 2S 0918–549 with a long duration of 40 min. We show that this burst is naturally explained by accretion of pure helium at the inferred accretion rate of ~$ 0.01$ times the Eddington accretion rate. At higher accretion rates of ~$ 0.1$ Eddington, hydrogen is required to explain long duration bursts. However, at low rates the long duration is due to the large amount of helium that accumulates prior to the burst. We show that it is possible to form a helium white dwarf donor in an ultracompact binary if accretion starts during the first ascent of the giant branch, when the core is predominantly made of helium. Furthermore, this scenario naturally explains the high neon-to-oxgen ratio, without requiring a CO or ONe white dwarf companion. The only observational aspect of 2S 0918–549 that we cannot explain is the absence of helium lines in the optical spectrum. Model calculations of optical accretion disk spectra need to be carried out in order to obtain limits on the helium abundance.
Rat anterodorsal thalamic head direction neurons depend upon dynamic visual signals to select anchoring landmark cues

Head direction cells, which are functionally coupled to ‘place’ cells of the hippocampus, a structure critically involved in spatial cognition, are likely neural substrates for the sense of direction. Here we studied the mechanism by which head direction cells are principally anchored to background visual cues [M.B. Zugaro et al. (2001) J. Neurosci. , 21, RC154,1–5]. Anterodorsal thalamic head direction cells were recorded while the rat foraged on a small elevated platform in a 3‐m diameter cylindrical enclosure. A large card was placed in the background, near the curtain, and a smaller card was placed in the foreground, near the platform. The cards were identically marked, proportionally dimensioned, subtended the same visual angles from the central vantage point and separated by 90°. The rat was then disoriented in darkness, the cards were rotated by 90° in opposite directions about the center and the rat was returned. Preferred directions followed either the background card, foreground card or midpoint between the two cards. In continuous lighting, preferred directions shifted to follow the background cue in most cases (30 of the 53 experiments, Batschelet V‐test, P < 0.01). Stroboscopic illumination, which perturbs dynamic visual signals (e.g. motion parallax), blocked this selectivity. Head direction cells remained equally anchored to the background card, foreground card or configuration of the two cards (Watson test, P > 0.1). This shows that dynamic visual signals are critical in distinguishing typically more stable background cues which govern spatial neuronal responses and orientation behaviors.
Explicit computations of Serre's obstruction for genus-3 curves and application to optimal curves

Let k be a field of characteristic other than 2. There can be an obstruction to a principally polarized abelian threefold ( A , a ) over k , which is a Jacobian over , being a Jacobian over k ; this can be computed in terms of the rationality of the square root of the value of a certain Siegel modular form. We show how to do this explicitly for principally polarized abelian threefolds which are the third power of an elliptic curve with complex multiplication. We use our numerical results to prove or refute the existence of some optimal curves of genus 3.
Simple-to-use, Secure-by-design Networking in Ethos

We describe networking in Ethos, a clean-slate operating system we designed to meet the security requirements which arise on the Internet. Through careful layering, Ethos makes network encryption, authentication, and authorization protections compulsory. This means that application developers can neither avoid nor incorrectly use them, and system administrators need not audit their use. We show through a case study how Ethos reduces application complexity and makes it easier to write and deploy robust applications.
Ja n 20 02 The Most Luminous Galaxies

Ultraluminous galaxies in the local universe (z≤0.2) emit the bulk of their energy in the mid and far-infrared. The multiwavelength approach to these objects has shown that they are advanced mergers of gas-rich spiral galaxies. Galaxy-galaxy collisions took place on all cosmological time-scales, and nearby mergers serve as local analogs to gain insight into the physical processes that lead to the formation and trans-formation of galaxies in the more distant universe. Here I review multiwavelength observations –with particular emphasis on recent results obtained with ISO– of mergers of massive galaxies driving the formation of: 1) luminous infrared galaxies, 2) elliptical galaxy cores, 3) luminous dust-enshrouded extranuclear starbursts, 4) symbiotic galaxies that host AGNs, and 5) tidal dwarf galaxies. The most important implication for studies on the formation of galaxies at early cosmological timescales is that the distant analogs to the local ultraluminous infrared galaxies are invisible in the ultraviolet and optical wavelength rest-frames and should be detected as sub-millimeter sources with no optical counterparts.
X-ray Variability of Blazars

Abstract Critical progress in our understanding of high energy emission from AGN has been determined in the last 10 years by X-ray monitoring campaigns with many space missions, notably ROSAT, ASCA, RXTE, BeppoSAX, and XMM, often in conjunction with observations at other frequencies. The emphasis of the present review is on recent findings about X-ray variability of blazars. Among AGN, these exhibit the largest amplitude variations of the X-ray emission, often well correlated with variations at higher energies (GeV and TeV radiation). The accurate sampling of the X-ray spectra over more than three decades in energy, made possible by the wide energy range of BeppoSAX, has also shown strong spectral variability in blazar active states, suggesting extreme electron energies and leading to the identification of a class of ‘extreme synchrotron’ sources.
A Combined Color, Texture and Edge Features Based Approach for Identification and Classification of Indian Medicinal Plants

This paper presents a method for identification and classification of images of medicinal plants such as herbs, shrubs and trees based on color and texture feature using SVM and neural network classifier. The tribal people in India classify plants according to their medicinal values. In the system of medicine called Ayurveda, identification of medicinal plants is considered an important activity in the preparation of herbal medicines. Ayurveda medicines have become alternate for allopathic medicine. Hence, leveraging technology in automatic identification and classification of medicinal plants has become essential. Plant species belonging to different classes such as Papaya, Neem, Tulasi, Aloe and Garlic are considered in this work. This paper presents edge and color descriptors that have low-dimension, effective and simple. In addition, the rotation invariant texture descriptors namely, directional difference and the gradient histogram are used. These features are obtained from 900 images of medicinal plants and used to train and test the image samples of three classes with SVM and radial basis exact fit neural network (RBENN). The classification accuracies for color, edge texture features are 74% and 80% respectively. The accuracy is improved to 90% with combined color and texture features. The results are encouraging for tree image plants than herbs and shrubs due to distinguishing feature of stem.
Modelling expressive performance using consistent evolutionary regression trees

We present an evolutionary approach for building regression tree based models in the context of expressive music performance. We first review the benefits of using evolutionary computation techniques in this context. We then use the strongly-typed genetic programming framework and define the types and constraints that are needed for evolving efficiently multi-dimensional regression trees, and present two fitness functions for modelling expressive performance local timing. While the first fitness measurement is purely error-driven, the second also takes into account the balance of the evolved tree in terms of input space representation. Finally, we present the results of both learning and generalization experiments. For these experiments, we use a database of saxophone performance timing extracted from a set of acoustic recordings of jazz standards. The whole system is built into the Open Beagle [5] evolutionary computation framework.
A Faster Method for Tracking and Scoring Videos Corresponding to Sentences

Prior work presented the sentence tracker, a method for scoring how well a sentence describes a video clip or alternatively how well a video clip depicts a sentence. We present an improved method for optimizing the same cost function employed by this prior work, reducing the space complexity from exponential in the sentence length to polynomial, as well as producing a qualitatively identical result in time polynomial in the sentence length instead of exponential. Since this new method is plug-compatible with the prior method, it can be used for the same applications: video retrieval with sentential queries, generating sentential descriptions of video clips, and focusing the attention of a tracker with a sentence, while allowing these applications to scale with significantly larger numbers of object detections, word meanings modeled with HMMs with significantly larger numbers of states, and significantly longer sentences, with no appreciable degradation in quality of results.
Governance of public corporations: Profits and the public benefit

Until recently, changes in the governance of publicly-owned enterprises could be seen as a move along a spectrum which led inevitably to privatisation. The general rejection of privatisation as a policy, and increasing demands for systems of corporate governance that take account of social interests broader than those encompassed in the maximisation of shareholder value subject to legal and regulatory constraints, have created new challenges for governments and for managers of publicly-owned enterprises.