Miracle-dz/UniFAR-FTUs huggingface dataset:
I/O performance of mobile devices over different storage media and block sizes

The increase in the use of handheld devices such as technologically enhanced mobile phones (smart phones), Personal Digital Assistance (PDA), palmtops, and very high end digital cameras, has brought in a new set of performance issues while accessing large volumes of datasets. Although much research work focuses towards the novel applications there is less concern about the performance of the device. During the last decade the rapid development of technologies has leveraged the power of storage and access capabilities. Therefore, it is significant to analyze the I/O performances of different storage devices utilized for mobile devices. A crucial factor in this connection is consideration towards the performance of algorithms for data access latency. To minimize data access time, it is significant to consider data access pattern, and the specific native characteristics of the storage media. This paper contributes towards identifying the specific characteristics over different Storage Media.
Demo Abstract: MOS: A Bandwidth-Efficient Cross-Platform Middleware for Publish/Subscribe

Shared dictionary compression is known as an efficient compression method for pub/sub. In practice, bandwidth reductions of more than 80% are achievable for JSON or XML data formats. Compared to other compression techniques such as GZip or Deate, a dictionary is needed to compress and decompress messages. Generating a dictionary is a CPU-expensive task and sharing it introduces bandwidth overheads. Furthermore, the dictionary is continuously maintained to keep the compression performance high. We developed MOS: a cross-platform middleware for managing shared dictionary compression in pub/sub. This includes dictionary propagation, compression/decompression, and periodic maintenance. We provide a developer API to interact with the MQTT-based pub/sub infrastructure. Our demo shows an example application built on top of MOS which shows the performance of the shared dictionary compression scheme.
Feature extraction via dynamic PCA for epilepsy diagnosis and epileptic seizure detection

Feature extraction is an important technique for complex, multivariate data containing various attributes. In this paper, we propose new detection schemes to help diagnosing epilepsy and detecting the onset of epileptic seizures. These schemes are based on the dynamic principle component analysis (PCA) approach and on partially extracted features. We propose a detection performance measure for evaluation of performance of the detection schemes. We also introduce a method for determining the threshold of the PC classifier using the normalized partial energy sequence of the extracted features of the training data set. We use partially extracted features to act as a classifier to help diagnosing epilepsy and detecting the onset of epileptic seizures. A publicly available EEG database is employed to evaluate our detection schemes. Our study shows that the proposed detection schemes are very promising in assisting diagnosis of epilepsy and for epileptic seizure detection.
The Stability of Distinctive Vowel Lengthin Thai

Many languages have phonological distinctions of quantity in consonants or vowels or both. Among them, Italian is known for its word-medial intervocalic short and long consonants, while Pattani Malay (Abramson, 1987) has word-initial prevocalic short and long consonants. Swedish, some dialects of German, and Thai have short and long vowels. Finnish has a length distinction for both consonants and vowels. Such distinctive length in segments is to be distinguished, of course, from other communicatively relevant roles oftiming in speech, e.g., in stress and intonation. The obvious physical correlate of the length distinction in phonetic segments is relative duration. That is, in the simplest case, the articulatory configuration is held longer for the "long" segment than for the "short" one. Limiting our attention here to vowels, we note an important observation made by Daniel Jones (1950, p. 28): "In languages where vowel length is significant it very often happens that the quality of a long vowel is not quite the same as that of the corresponding short vowel. " Ilse Lehiste (1970, pp. 30-33) amplifies the point by commenting that in "quantity" languages some differences in the phonetic quality of short and long vowels can he observed, although such languages differ somewhat in the amount of correlation between length and quality. To the
On the $b$-Independence Number of Sparse Random Graphs

Let graph $G=(V,E)$ and integer $b\geq 1$ be given. A set $S\subseteq V$ is said to be $b$-independent if $u,v\in S$ implies $d_G(u,v)>b$, where $d_G(u,v)$ is the shortest distance between $u$ and $v$ in $G$. The $b$-independence number $\a_b(G)$ is the size of the largest $b$-independent subset of $G$. When $b=1$ this reduces to the standard definition of independence number. We study this parameter in relation to the random graph $G_{n,p},\,p=d/n$, in particular, when $d$ is a large constant. We show that w.h. p. if $d\geq d_{\epsilon, b}$, $$ \left| \alpha_b(G_{n,p}) - \frac{2bn}{d^b} \biggl(\log{d} - \frac{\log{\log{d}}}{b} - \frac{\log{2b}}{b} + \frac{1}{b}\biggr)\right| \leq \frac{\epsilon n}{d^b}. $$
A reward field model generation in Q-learning by dynamic programming

Many obstacles and paths exist in a real environment, and hence, it is difficult for an agent to learn such an environment. Q-learning is suitable in such cases because it does not define any learning model. By Q-learning, an agent learns to reach a state wherein it can receive a reward for selecting an action. However, no information on how to receive a reward is available. In the initial learning stage, an agent sometimes selects an action that makes it move to a state wherein it cannot receive a reward. Hence, the learning time and learning cost to select an optimal action is increased. In order to assist an agent to learn by Q-learning, if a model is created automatically, both the problems of time and cost can be solved together. In this paper, we propose a method that creates such a model automatically by dynamic programming. This model causes an agent be able to notice when it is close to the state wherein it can receive a reward. An agent is driven by the model to the state wherein it can receive a reward when it enters the field of reward affection. By conducting experiments, we also compared the success rate between conventional Q-learning and the proposed method. Our results showed that the success rate of the proposed method was approximately 187% higher than that of Q-learning.
Probability Interval Partitioning Entropy Codes

A novel approach to entropy coding is described that provides the coding efficiency and simple probability modeling capability of arithmetic coding at the complexity level of Huffman coding. The key element of the proposed approach is given by a partitioning of the unit interval into a small set of disjoint probability intervals for pipelining the coding process along the probability estimates of binary random variables. According to this partitioning, an input sequence of discrete source symbols with arbitrary alphabet sizes is mapped to a sequence of binary symbols and each of the binary symbols is assigned to one particular probability interval. With each of the intervals being represented by a fixed probability, the probability interval partitioning entropy (PIPE) coding process is based on the design and application of simple variable-to-variable length codes. Probability modeling can either be fixed or adaptive while the PIPE code for each probability interval remains fixed and is decoupled from the modeling stage. The excess rate of PIPE coding is shown to be comparable to that of arithmetic coding.
Using High-Frequency Data to Model Volatility Dynamics

he covariance matrix of asset returns is important for a wide range of individuals.1 Academics use estimates of the covariance matrix to test asset-pricing theories. Portfolio managers use the covariance matrix in designing tracking strategies where the return on their portfolio is designed to closely follow the return on a benchmark portfolio. Risk managers use the matrix to construct measures such as “value at risk. ” Corporate managers require accurate measures of covariances for hedging strategies.
CLASH PLACEMENT IN QUANTITY-INSENSITIVE LANGUAGES

This paper investigates the typology of quantity-insensitive languages that tolerate stress clashes. Two descriptive generalisations emerge from this typology: 1) clashes are preferentially realised away from the edge, and 2) clashes with primary stress are avoided. We will compare various theories of clash placement (e.g Kager 2001; Gordon 2002; Alber 2005). I will argue that Kager’s (2001) clash-licensing constraints, given in (1), derive the most restrictive typology.
A Generation X Cohort Analysis of E-shoppers: Satisfaction, Loyalty and Repurchase Intentions in a Developing Country

ABSTRACT Research effort devoted to investigating the influence of e-satisfaction and e-loyalty on repurchase intention in the context of South African online environments have largely been scarce. This study examines the influence of e-satisfaction and e-loyalty on repurchase intentions among a cohort of generation x consumers. The study is located within a quantitative research paradigm in order to test the proposed hypotheses. Data was collected from generation x online consumers in the southern Gauteng region, South Africa. A snowball sampling method was employed and a total of 369 questionnaires were analysed through correlation and regression analysis. The results show that e-satisfaction and e-loyalty have a positive and significant relationship with repurchase intention. E-shopping satisfaction also positively influenced e-shopping loyalty. Limitations, implications and future research directions are suggested.
A Field Study of Digital Forensics of Intrusions in the Electrical Power Grid

The paper describes the findings of a field study that we conducted to practically determine the digital forensics processes, tools, and technical considerations that apply to investigations of computer intrusions into the electrical power grid. Our findings are based on technical interactions with industry and law enforcement, as well as on actual applied research in the lab. In the paper, we discuss the most widespread vulnerabilities of industrial control systems, and thus build on those preliminaries to describe the inner workings of control system forensics in the real world. Several advanced works on control systems forensics abstract from low-level fundamentals, assuming that those are easily doable. The main contribution made by this paper is the focus on those fundamentals, with the goal of laying the foundation for further developments of practical and hence usable digital forensics in the electrical power grid.
Group-Based Trust Management Scheme for Clustered Wireless Sensor Networks

Traditional trust management schemes developed for wired and wireless ad hoc networks are not well suited for sensor networks due to their higher consumption of resources such as memory and power. In this work, we propose a new lightweight group-based trust management scheme (GTMS) for wireless sensor networks, which employs clustering. Our approach reduces the cost of trust evaluation. Also, theoretical as well as simulation results show that our scheme demands less memory, energy, and communication overheads as compared to the current state-of-the-art trust management schemes and it is more suitable for large-scale sensor networks. Furthermore, GTMS also enables us to detect and prevent malicious, selfish, and faulty nodes.
On finding non-intersecting paths in grids and its application in reconfiguring VLSI/WSI arrays

The key result in this paper is an efficient algorithm for solving the following geometrical problem: given a set of points in a 2-dimensional grid; find a set of non-intersecting straight lines such that every line starts at a point and connects it to one of the boundaries of the grid. The algorithm presented here has quadratic (in the number of points) time complexity and is the first known polynomial time algorithm for this problem. Geometrical problems of this nature arise in the study of reconfigurable processor arrays, and the efficient algorithms developed in this paper can be used instead of the algorithms, based on exhaustive searches, that have been proposed in the literature.
The dynamical status of the cluster of galaxies 1E0657-56

We present the results of a new spectroscopic and photometric survey of the hot X-ray cluster 1E0657-56, at z =0 :296. We determine the presence of a low velocity dispersion subcluster, which is oset from the main cluster position by 0.7 Mpc and'600 km s 1 . We determine the virial masses and total luminosities of the cluster and its subcluster, and solve for the two-body dynamical model. With additional constraints from the results of the analysis of the cluster X-ray emission by Markevitch et al. (2001), we nd that the subcluster passed through the cluster centre'0.15 Gyr ago. Taken at face value the mass of the subcluster is typical of a loose group. It is however dicult to establish the pre-merger mass of the colliding system. We provide tentative evidence that the subcluster is in fact the remnant core of a moderately massive cluster, stripped by the collision with 1E0657-56. The main cluster dynamics does not seem to have suered from this collision. On the contrary, the cluster X-ray properties seem to have been signicantly aected. We also discuss the eect of the subcluster collision in relation to starburst events and the cluster radio halo.
Conference on " Monetary Policy-Making under Uncertainty " Frankfurt / Main , December 3 / 4 , 1999

Recently, several central banks have abandoned the usual secrecy in monetary policy and become very transparent. This paper provides an explanation for this puzzling fact, focussing on the disclosure of central bank forecasts. It shows that transparency leads to lower inflation and gives the central bank greater flexibility to respond to shocks in the economy. Furthermore, it makes it easier for a central bank to build reputation. To achieve these benefits of transparency it is generally necessary to publish the conditional central bank forecasts for both inflation and output. ∗I thank Ignazio Angeloni, Brad De Long, Barry Eichengreen, Vítor Gaspar, Philipp Hartmann, Jérôme Henry, Rich Lyons, Klaus Masuch, Maury Obstfeld, Huw Pill, David Romer, Frank Smets, Oreste Tristani, Volker Wieland, Bernhard Winkler and seminar participants at the European Central Bank (ECB) and UC Berkeley for helpful discussion and/or comments. Part of this paper was written while I was at the Directorate General Research of the ECB, which I thank for its hospitality. The views expressed in this paper are mine and do not necessarily reflect those of the ECB and/or the European System of Central Banks (ESCB). Any errors are mine as well. †Department of Economics, University of California, Berkeley, 549 Evans Hall #3880, Berkeley, CA 94720-3880. Email: geraats@econ.berkeley. edu.
Experimental Analysis of Vibration-induced Phase Noise of Crystal Oscillator Circuit

Today, The vibration-induced phase noise has impact on the design of the subassembly of crystal oscillator. In this paper, the vibration-induced phase noise for sinusoidal vibration and random vibration is validated by experimental testing. The important range of vibration frequency is obtained, and it is shown that the resonant frequency increases the phase noise of crystal oscillator circuit and result in carrier frequency excursion
Realistic Modeling of Agents in Crowd Simulations

Simulation of crowd behaviors is a widely discussed topic for over a decade for computer games, architecture and entertainment. The most important thing is that agents should execute the human like behaviors in real life scenarios. This situation becomes very complex with dense crowds. Our proposed Realistic Behavior Agent Simulation (RBAS) model simulates the agents from the knowledge of empirical findings of crowd physical behaviors and crowd psychology. This paper presents a novel technique to design the agents to with following modules 1) Path planning behavior for collision avoidance 2) Situation awareness during herding behavior and turbulent flow in high density crowds. 3) Personal Reaction bubble (PRB) based response and perceptions. The evaluation with real life situations is performed to validate the RBAS model. The RBAS model allows the agents to use cognitive understandings to plan ahead their path using the visual perception information. This model encapsulates the emergent crowd behaviors such as self-organization behavior in herding situation. During turbulent high density flows, most of the existing models fail to predict the behavior of agents, the evaluations show the RBAS model mimics the same behavior of the crowd in different situations.
A rare-earth free SHEV powertrain and its control

A topology of a candidate rare-earth free Series Hybrid Electric Vehicle (SHEV) powertrain and the coordinated control of its components is presented in this paper. The powertrain is fed with a field controlled synchronous generator and a controlled battery bank and drives a 60 kW rare-earth free traction motor. Simulation results are presented for normal operating conditions and two faulted-mode operating scenarios where the power electronic converter in the system is faulted are investigated.
A Novel Sparse Stepped Chaotic Signal and its Compression Based on Compressive Sensing

We propose a novel signal model by combining the sparse stepped frequency signals with chaotic signals, i.e., the sparse stepped chaotic signal (SSCS) model, as well as the corresponding compression algorithm based on compressed sensing. In SSCS, the chaotic signals are modulated to sparse stepped frequencies to compose a transmitting burst. When receiving, the echo signals are demodulated to the baseband and then can be sampled directly at a rate much lower than the Nyquist rate determined by the bandwidth of chaotic signal of each subpulse. Compared with radars using conventional stepped frequency waveforms, the SSCS radar can transmit fewer subpulses in a burst and directly use lower speed ADC next to the receiver. Both simulated and real radar data are processed to demonstrate the effectiveness of the proposed SSCS as well as the compression algorithm by which high resolution range profiles are very well reconstructed.
Cost sharing mechanisms for near-optimal traffic aggregation and network design

A fundamental network design problem is the one of Traffic Aggregation or Network Design. The goal is to design a network which is able to support a unit flow for each commodity, at a time, between its source-sink pair, e.g., to support buffered multicast traffic. When the flows are unsplittable, this corresponds to the Steiner forest problem and to the problem of sharing cost of multicast by different users. As a result of greedy selfish behavior of users in the network design game, the overall quality of the resulting solution is often not as good as the globally optimum solution of the underlying problem. We are therefore interested in the problem of designing distributed cost sharing mechanisms that induce the selfish agents to converge to the near-optimum solutions. In this paper, our main contribution is showing that (1+ε) ratio can be achieved by (non-obvious) unfair cost sharing mechanism, at least for the fractional version of the problem. Our second contribution is showing how to implement our cost sharing mechanism which guarantees fast convergence to a near-optimum equilibrium.
Technologies for Everyday Life Reflection: Illustrating a Design Space

Reflection gives insight, supports action and can improve wellbeing. People might want to reflect more often for these benefits, but find it difficult to do so in everyday life. Research in HCI has shown the potential of systems to support reflection in different contexts. In this paper we present a design space for supporting everyday life reflection. We produced a workbook with a selection of conceptual design proposals, which show how systems can take different roles in the process of reflection: triggering, supporting and capturing. We describe a design space with two dimensions by combining these roles with strategies found in literature. We contribute to the extensive body of work on reflection by outlining how design for everyday life reflection requires a focus on more holistic reflection, design with openness and integration in everyday life.
Building community, benefiting neighbors: “Buying local” by people who do not fit the mold for “ethical consumers”

According to nearly all studies, ethical consumption is a regular practice mainly of people who are well educated and politically active in conventional ways. Buying local has also recently been portrayed as part of an “eco-habitus” associated with ecological thinking, cultural capital, and the desire for more “authentic” things. In this article, I challenge both these notions. Specifically, drawing on Holt’s model of the relationship between cultural capital and consumption, I make two arguments. First, while relatively few people have access to robust local food systems, buying local by supporting businesses in general, and not just food producers, seen as rooted in regional economic and civic life, may be widespread even among people lacking in cultural capital, economic capital, or interest in conventional politics. Second, buying local among people who do not fit the mold of the “typical” ethical consumer is not consciously connected to concern for environmental problems. Rather, the buying local practiced by this understudied group is motivated by the desire to directly benefit community members and secure public goods such as good jobs, and safe streets. The findings of this article matter first for how social scientists understand who engages in buying local, as a form of ethical consumption. But this article also raises the question of what the real-world impacts of buying local might be, when some practitioners are relatively unguided by signals from social movement organizations and other entities that might establish firm criteria for what counts as “local” and what does not.
A QR Code-Based on-Street Parking Fee Payment Mechanism

Quick response (QR) code is a convenient product for mobile phone users. People can use a smartphone camera to capture the code, and then decode it through a dedicated reader application. Specifically, that code stands for concise text, contact information, or a web hyperlink. Its existence assists phone users in keypad typing more easily. This paper proposes an on-street parking fee payment mechanism based on the QR code of an E-bill. People can regard the code as a bill to pay their parking fee, where the parking information is recorded into a remote server by the fee collectors. The main idea of this mechanism is to save on resources such as reducing paper consumption. Simulation results showed that the proposed mobile application provides a new mode for E-bill payment for on-street parking in Taiwan. Furthermore, the said application also serves as an exemplary model for other parking payment methods.