Miracle-dz/UniFAR-FTUs huggingface dataset:
ATM resource allocation algorithms: a comparison

Several resource allocation approaches have been proposed in the literature. In this paper we compare various bandwidth allocation schemes and specifically examine the effectiveness (operational region) of these schemes for different traffic types. We also introduce the concept of a traffic space to represent the attributes of the traffic (burstiness, burst size, etc.) and the ATM switch/multiplexer (speed, buffer size, etc.) on a single three dimensional space. This traffic space then helps us in identifying the operational region of a particular resource algorithm in a generic sense.
Identifying robust SIFT features for improved image alignment

Several modern feature detection algorithms use Gau ssi n scale spaces in order to locate scale-invariant and rotationally invariant feature points in an image, including the Scale-Invariant Feature Transform (SIFT) algorithm. These SIFT feat ures are used to enable a wide range of applications, including object recognition, motion tracking, and image stitching. One problem with SIFT is the fact that the number of features d tected in an image can become very large, especially if the input image is big or has a lot o f detail. This slows down feature matching and reduces the performance of these applications. In this thesis, we will study different ways to imp rove feature matching by increasing the quality and reducing the number of SIFT features. W e created an algorithm to identify robust SIFT features by evaluating how invariant individua l feature points are to changes in scale. This allows us to exclude poor SIFT feature points from the matching process and obtain better matching results in reduced time. We also develope d techniques consider scale ratios and changes in object orientation when performing featu re matching. This allows us to exclude false-positive feature matches and obtain better im age alignment results. This thesis is approved for recommendation to the Graduate Council.
A Wearable Bioinformation Recording System

A wearable bioinformation recording system has been developed for monitoring health conditions, daily living activities and heart function of elderly person. A tri-axis accelerometer attached to the elderly person can simultaneously measure dynamic and static acceleration forces. The heart rate, respiration rate, activity, posture and behavior are detected from the measured acceleration forces. These data are automatically transmitted to the host computer every hour, via a Personal Handy Phone (PHS). The host computer makes a graphic chart from these data. The elderly person's immediate family, caregiver or doctor can download the graphic chart to an internet mobile phone. When a heart discomfort is felt, the elderly person pushes the transmission switch on a wearable sensor, which sends the phonocardiogram (PCG) waveforms derived from the dynamic acceleration force of the prior two minutes and the waveforms for two minutes after the switch is pushed, directly to the host computer. The PCG is stored to the host computer. The doctor can download the PCG to the smart phone and monitor graphically.The developed system is not only applicable to at-home solitary elderly people, but could also be useful for monitoring hospital patients.
COHESIVE DEVICES IN JOURNALISTIC ARTICLES AND CHILDREN STORY

ABSTRACT This study attempts to describe the characteristic of cohesive devices used in journalistic texts and children stories. In language learning, it will be beneficial for students to be able to relate the characteristics of the language in use and the function it performs. The quantitative and qualitative analyses were applied in analysing the sample texts; two travel articles taken from magazine and two fables. The finding suggests that personal references tend to be more varied and more dominant in children stories as they are applied to trace characters throughout the story. Demonstrative pronouns are used more frequently in travel articles to refer to places and events. The use of lexical cohesion shows that repetition of the characters’ name occurs significantly in fables; meanwhile the travel articles use more synonymy and meronymy. Collocation plays important role to build discourse unity in both genres. However, it is more topic related rather than genre related. Keywords: cohesive devices, travel article, children story
A Study Of Brain Computer Interface System

Advances in cognitive neuroscience and brain imaging technologies have started to provide us with the ability to interface directly with human brain. Brain Computer Interface (BCI) is a system that acquires and analyzes neural signals with the aim of creating a communication channel directly between the brain and the external device or computer. The major goal of BCI research is to develop a system that allows people severely affected by motor disorders to communicate with other persons and helps to interact with the external environment. Achievement of greater speed and accuracy of the BCI system depends on improvements in signal processing, translation algorithms, and user training. These improvements depend on increased interdisciplinary cooperation between neuroscientists, engineers, computer programmers, psychologists, and rehabilitation specialists. The objective of this paper is to provide insight into the various aspects of BCI which will help the beginner in this field to understand the basics of BCI.
Query and Analysis of Data on Electric Consumption Based on Hadoop

Traditional data management is usually based on relational databases, which are capable of managing small amounts of data. But relational databases have some difficulty in inquiry, management, and analysis of large amounts of data and magnanimity data. The method of effective management of magnanimity data is a problem deserving of study. In this paper, traditional relational databases are moved to Hadoop, in order to implement query and analysis on Hadoop. This paper changes the amount of data record and number of nodes in clusters, and records the query time in different conditions. Advantages and disadvantages of query on Hadoop can be analyzed by comparing the statistics with the query time on relational database Oracle. The factors affecting the time of query on Hadoop can be found by analysis. Furthermore, the result is also a reference material of future research and data managements on cloud platforms.
SPARC64: a 64-b 64-active-instruction out-of-order-execution MCM processor

We report the first implementation of the new SPARC V9 64-b instruction set architecture. The HaL processor called SPARC64 is a ceramic Multi-Chip Module (MCM) that contains one CPU chip, one Memory Management Unit (MMU) chip, and four 64 KB Cache chips. Together, they implement a unique three-level address translation scheme that efficiently supports using virtual addresses spread anywhere in the full 64-b address range. The processor assigns a serial number to each issued instruction to track up to 64 in-progress instructions and can speculatively issue through up to 16 branches. It issues up to 4 instructions per cycle and utilizes superscalar instruction issue, register renaming, and dataflow (potentially out-of-order) execution to fully exploit instruction-level parallelism. The processor maintains a precise-state execution model, and commits in-order, up to 9 instructions in a cycle. In a HaL R1 system, a production SPARC64 running at 143 MHz has a performance of 230 SPECint92 and 300 SPECfp92 and dissipates 50 W from a 3.3 V supply.
Signal preprocessing techniques for an electronic tongue

Electronic tongues are systems composed by an array of sensors plus a pattern recognition for the evaluation of liquids. In our case, voltametric sensors are used due to their selectivity and advantages. However, as is explained in this paper, this kind of sensors presents several problems that can be partially solved by adequate signal processing techniques. The system is completed with a neural network as pattern recognition system plus a scheme for taking account all the information obtained from the sensors.
Investigating Peer Instruction: How the Initial Voting Session Affects Students' Experiences of Group Discussion

Peer Instruction is a popular method of implementation when using Student Response Systems (SRS) in classroom teaching. The students engage in peer discussion to solve conceptual multiple choice problems. Before discussion, students are given time to think and give individual responses with a voting device. In this paper, we investigate how this initial voting session affects students’ experiences of the following discussion. The data is based on student interviews which were analyzed using analytical tools from grounded theory. The students emphasize the individual thinking period as crucial for constructing explanations, argumentation, and participation during discussions, and hence for facilitating learning. However, displaying the results from the initial vote can be devastating for the quality of the discussions, especially when there is a clear majority for a specific alternative. These findings are discussed in light of recent quantitative studies on Peer Instruction.
Analysis, Optimization, and Sensitivity Study of Differential PCM Systems Operating on Noisy Communication Channels

A closed-form analytical expression is obtained for the output signal-to-noise ratio (SNR 0 ) of differential PCM systems operating on noisy digital channels. A procedure is then proposed for maximizing SNR 0 by joint optimization of the quantizer, predictor, and sampling rate. Several examples are considered, including one- and two-sample feedback systems excited by speech and video (Gaussian) signals. The predictor used in the DPCM system is linear and time invariant, but otherwise arbitrary. As with PCM, contributions to output signal distortion can be expressed as a sum of three separate terms resulting, respectively, from quantization errors, channel transmission errors, and mutual errors arising from interaction between quantization and channel errors. When a conventional optimum linear predictor is used, transmission errors are shown to be no more serious for DPCM than for PCM. The results show that SNR 0 for a well-designed DPCM system is considerably higher than for a well-designed PCM system operating on the same digital channel, even if the channel is noisy. In considering examples, particular attention is devoted to determining maximum values for SNR 0 and to examining the dependence of SNR 0 on predictor coefficient values, number of quantization levels, sampling rate, message statistics, and channel error probability. Implications of this dependence on system design are noted.
Network architecture and functionalities in UMTS

The paper analyzes some of the major network topics arising in the UMTS design process. This is done by invoking functional and architectural issues with relation to both the B-ISDN/IN context and the radio access features. The integration of UMTS with the "core" network is discussed by showing functional and network architecture as as well as protocol aspects. A comparison with the solutions adopted for the actual cellular systems, highlights the improving elements characterizing UMTS. Specific UMTS functional schemes are analyzed for call handling and location management procedures. Functional and design issues are also discussed for the radio access part of UMTS. The handover procedure, heavily affecting the architectural choices to be performed, for the UMTS base station is described, and its use in the design process is presented. Basic performance evaluation topics, tied to the achievement of "optimal" solutions for the functions allocation to the network entities are discussed. The paper is based on the work performed within the RACE Project 2066, named MONET.
Generalized translinear circuit principle

It is shown that a generalized interpretation of the translinear (TL) principle leads quite naturally to an extension to MOS circuits. It is shown that two distinct classes of TL circuits exist, one suitable for bipolar and the other for MOS implementation. The MOS-translinear (MTL) circuit principle is derived and an initial classification of simple MTL circuits is proposed. Some examples are given of MTL circuits synthesizing nonlinear functions. >
Resolution of SU(3) Outer Multiplicity Problem and the $SU(3)\otimes SU(3)$ Invariant Group $SO(4,2)$

We resolve the SU(3) outer multiplicity problem by defining all possible $SU(3)\otimes SU(3)$ invariant operators in terms of SU(3) Schwinger bosons. We show that the elementary invariant operators relevant to the outer multiplicity problem form SO(4,2) algebra. Further, they enable us to construct a family of operators any one of which can be used to distinguish repeating representations present in the reduction of the direct product of two SU(3) irreducible representations.
A Convolutional Approach to Melody Line Identification in Symbolic Scores

In many musical traditions, the melody line is of primary significance in a piece. Human listeners can readily distinguish melodies from accompaniment; however, making this distinction given only the written score -- i.e. without listening to the music performed -- can be a difficult task. Solving this task is of great importance for both Music Information Retrieval and musicological applications. In this paper, we propose an automated approach to identifying the most salient melody line in a symbolic score. The backbone of the method consists of a convolutional neural network (CNN) estimating the probability that each note in the score (more precisely: each pixel in a piano roll encoding of the score) belongs to the melody line. We train and evaluate the method on various datasets, using manual annotations where available and solo instrument parts where not. We also propose a method to inspect the CNN and to analyze the influence exerted by notes on the prediction of other notes; this method can be applied whenever the output of a neural network has the same size as the input.
Polarimetric properties of boreal forest in L- and C-band SAR images

In this study the usability of L- and C-band SAR polarimetry in boreal forest remote sensing is examined and discussed. The influence of snow cover, weather conditions, forest type and several other aspects to forest backscattering in L- and C-bands is investigated by using multitemporal polarimetric images.
Unified no-scale attractors

We have presented previously a general treatment of Starobinsky-like inflation in no-scale supergravity where the tensor-to-scalar ratio r = 3(1 − ns)2, and ns is the tilt of the scalar perturbations. In particular, we have shown how this scenario can be unified with modulus fixing, supersymmetry breaking and a small cosmological constant. In this paper we extend these constructions to inflationary models based on generalized no-scale structures. In particular, we consider alternative values of the curvature parameter, α < 1, as may occur if not all the complex Kähler moduli contribute to driving inflation, as well as α > 1, as may occur if complex structure moduli also contribute to driving inflation. In all cases, we combine these α-Starobinsky inflation models with supersymmetry breaking and a present-day cosmological constant, allowing for additional contributions to the vacuum energy from stages of gauge symmetry breaking.
Cyber attacks with bounded sensor reading edits for partially-observed discrete event systems

The problem of cyber attacks with bounded sensor reading edits for partially-observed discrete event systems is considered. An operator observes a plant through an observation mask that does not allow him to detect the occurrence of certain events (silent events). The observation is corrupted by an attacker who can insert and erase some sensor readings. The operator observes the system evolution in order to validate if a state in a given set of unsafe states is reached. The attacker corrupts the observation with the aim of preventing the operator to verify when an interesting state has been reached. Furthermore, the attacker wants to remain stealthy, namely he wants the operator does not realize that someone is corrupting his observation. An automaton, called attack structure is proposed, which supports the attacker in defining an effective attack. In more detail, first, the unbounded attack structure is obtained by doing the concurrent composition of two state observers, the attacker observer and the operator observer. Then, the n-bounded attack structure, for a given integer value of n, is obtained by doing the concurrent composition of the unbounded attack structure and an n-bounded attack automaton. Finally, the n-bounded attack structure can be made supremal and stealthy by appropriately trimming the previous attack structure. A stealthy attacker can elaborate his strategy looking at the supremal stealthy attack substructure and may result in different degrees of effectiveness: strong, weak or vain. The proposed approach can be dually used to verify if such an attack could be effective for the given system, thus to establish if the system is safe under attack.
Saliency-driven Word Alignment Interpretation for Neural Machine Translation

Despite their original goal to jointly learn to align and translate, Neural Machine Translation (NMT) models, especially Transformer, are often perceived as not learning interpretable word alignments. In this paper, we show that NMT models do learn interpretable word alignments, which could only be revealed with proper interpretation methods. We propose a series of such methods that are model-agnostic, are able to be applied either offline or online, and do not require parameter update or architectural change. We show that under the force decoding setup, the alignments induced by our interpretation method are of better quality than fast-align for some systems, and when performing free decoding, they agree well with the alignments induced by automatic alignment tools.
Measurement system for a preliminary characterisation of flash memory cells for multilevel applications

In this work a low-cost measurement system suitable for analog characterisation of standard FLASH memory cells is presented. Our aim, with this system, is to investigate about the possibility of using standard cells for multilevel storage, to increase the bit density of conventional memory devices. Preliminary investigation was carried out by using a measurement system based on standalone instrumentation linked to a controller via IEEE 488 bus. The preliminary characterisation results of the Texas Instruments TMS29FO40 4 Mbit flash Memory show that it is feasible to store and retrieve information with 4 level of injection charge in a single cell. Currently, a first multilevel test-chip is under development. At the same time a new measurement system, specifically suited to debug and test this special device, is under implementation.
From non-paying to premium: predicting user conversion in video games with ensemble learning

Retaining premium players is key to the success of free-to-play games, but most of them do not start purchasing right after joining the game. By exploiting the exceptionally rich datasets recorded by modern video games---which provide information on the individual behavior of each and every player---survival analysis techniques can be used to predict what players are more likely to become paying (or even premium) users and when, both in terms of time and game level, the conversion will take place. Here we show that a traditional semi-parametric model (Cox regression), a random survival forest (RSF) technique and a method based on conditional inference survival ensembles all yield very promising results. However, the last approach has the advantage of being able to correct the inherent bias in RSF models by dividing the procedure into two steps: first selecting the best predictor to perform the splitting and then the best split point for that covariate. The proposed conditional inference survival ensembles method could be readily used in operational environments for early identification of premium players and the parts of the game that may prompt them to become paying users. Such knowledge would allow developers to induce their conversion and, more generally, to better understand the needs of their players and provide them with a personalized experience, thereby increasing their engagement and paving the way to higher monetization.
Brezis-Nirenberg type result for Kohn Laplacian with critical Choquard Nonlinearity

In this article, we are study the following Dirichlet problem with Choquard type non linearity \[ -\Delta_{\mathbb{H}} u = a u+ \left(\int_{\Omega}\frac{|u(\eta)|^{Q^*_\lambda}}{|\eta^{-1}\xi|^{\lambda}}d\eta\right)|u|^{Q^*_\lambda-2}u \; \text{in}\; \Omega,\quad u = 0 \; \text{ on } \partial \Omega , \] where $\Omega$ is a smooth bounded subset of the Heisenberg group $\mathbb{H}^N, N\in \mathbb N$ with $C^2$ boundary and $\Delta_{\mathbb{H}}$ is the Kohn Laplacian on the Heisenberg group $\mathbb{H}^N$. Here, $Q^*_\lambda=\frac{2Q-\lambda}{Q-2},\; Q= 2N+2$ and $a$ is a positive real parameter. We derive the Brezis-Nirenberg type result for the above problem. Moreover, we also prove the regularity of solutions and nonexistence of solutions depending on the range of $a$.
Automatic control of blood oxygen saturation in premature infants

This paper describes research into the development of a controller that regulates blood oxygen saturation (SaO/sub 2/) in premature infants. The patient's SaO/sub 2/ is measured by a pulse oximeter and fed into the controller which adjusts the neonate's inspired air-oxygen (FiO/sub 2/) mixture by actuating a motorized gas blender. This oxygen therapy is used to prevent incidents of hypoxemia and hyperoxemia. A simplified physiological model is described. The designers use a unique control algorithm based on the sign of the error magnitude, velocity and acceleration as inputs. The algorithm applies these inputs to a state machine that determines the trend of the error. This trend defines the next state and an associated FiO/sub 2/ adjustment and time delay. The controller was verified on eight neonates, each over a six hour study period. During automatic oxygen therapy the controller significantly increased the duration of time the patient spent at normal SaO/sub 2/ levels as compared to manual therapy. The numbers of manual interventions were also greatly reduced when the neonates were under automatic oxygen therapy. <<ETX>>
Laser-induced dissociative recombination of carbon dioxide

We experimentally investigate laser-induced dissociative recombination of CO$_2$ in linearly polarized strong laser fields with coincidence measurements. Our results show laser-induced dissociation processes originate from an electron recombination process after laser-induced double ionization. After double ionization of CO$_2$, one electron is recaptured by the CO$_2^{2+}$ and localized to O$^+$ or CO$^+$ in the following dissociation process. We found that the probability of electron localization to O$^{+}$ is much higher than that to CO$^+$. Further, our measurements reveal that the recombination probability of the first ionized electron is three times as high as that of the second ionized electron. Our work may trigger further experimental and theoretical studies on involved nuclear and electron dynamics in laser-induced dissociative recombination of molecules and their applications in controlling molecular dissociation with ultrashort laser pulses.