Miracle-dz/UniFAR-FTUs huggingface dataset:
An Acoustic Echo Cancellation System based on Adaptive Algorithms

Adaptive filtering technique is one of the core technologies in digital signal processing and finds numerous application areas in science as well as in industry. Adaptive filtering technique is widely used in many applications, including echo cancellation, adaptive noise cancellation, adaptive beam forming and adaptive equalization. Acoustic echo is a common occurrence in today’s telecommunication systems. The distraction caused by the acoustic echo, reduces the speech quality in the communication. In the communication system acoustic echo cancellers is used works as the far-end signal is delivered to the system, it will be reproduced by the loudspeaker in the room. A microphone in the room picks up the resulting direct path sound and consequent reverberant sound as a near-end signal, The far-end signal is filtered and delayed to resemble the near-end signal, filtered far-end signal is subtracted from the near-end signal. The resultant signal represents sounds present in the room excluding any direct or reverberated sound produced by the loudspeaker. The AEC with adaptive filtering technique will more accurately enhance the speech quality in hands-free and teleconferencing communication systems. The focus is on speech enhancement of speech signal with reverberated signal in handsfree speech communication using AEC with adaptive filtering technique. There are many adaptive algorithms available in the literature for echo cancellation and every algorithm have its own properties, but the aim of algorithms using for echo cancellation is to achieve higher ERLE(amount of echo cancelled) in dB at a higher rate of convergence with low complexity. The adaptive algorithms NLMS, APA and RLS for echo cancellation were successfully implemented in MATLAB. The three algorithms for AEC are tested with simulation in three different echo occurring environments by changing microphone position, source position and room dimensions. The performance evaluation of the NLMS, APA and RLS algorithms are measured with ERLE parameter. The results show that the RLS algorithm have good performance with high rate of convergence speed but the computational complexity is high which makes it impractical in real time applications. The amount of echo cancellation with APA algorithm is higher than NLMS with less computational complexity than RLS and easy to implement in real time. The amount of echo cancellation with NLMS is low when compared to RLS and APA but it is easy to implement in real time with less computational complexity. The detailed view of the comparison results of three algorithms at three different environments are shown in section 6.
SounBe, an innovative sound project tool involving sensory analysis: new possible applications in food consumption

The theme of multisensory product experience appears to be today very up-to-date in the design research, as well as in consumer science. But even if some senses such as sight and touch have been deeply examined, other senses such as hearing still represent a quite unexplored potential in the current scientific research. Nowadays it is acknowledged that product sound design should be integrated in the main design process to enhance the user experience, however this integration requires specific tools and methods. The aim of this research is to find the best response to all these needs, showing the development of SounBe® tool, an innovative patented device and method for the acoustic sensorial analysis of materials. During the research pathway, different qualitative and quantitative investigation methods typical of the sensory analyses have been adopted. The mechanical sound decomposition in three main generating variables (material, shape and gesture) and the use of SounBe® allowed to generate, compare and describe by a trained panel of tasters various possible sounds obtained by the material samples collected in MATto, the material library of Politecnico di Torino, generating a real sound database. The versatility of this approach allows applying it in several design fields starting from the most "traditional" to the most innovative ones. Right the world of food, its packaging and the consumption phase represent an interesting testing ground, starting from the studies that relate food with sound perception. Finally, designers dealing with sounding objects, packaging and, eventually, food have now available a new instrument to create new sounds or to evaluate the existing ones: thanks to SounBe® tool they will be able to gather some useful meta-project advices related to their needs. A new conscious approach to sounding objects will generate new designed soundscapes, avoiding the increasing of noise pollution and poor sounding objects
Jitter, Phase Noise and Spurs in Frequency Multiplying Delay-locked loops: A Simple Model and Analysis

We study the jitter performance of multiplying delay locked loops (MDLLs) and provide an effective approach to derive the phase noise of open loop MDLLs. We demonstrate that the ring oscillator phase noise models from Abidi and Hajimiri are essentially the same. Based on the analysis for MDLL jitter performance, new system models for Edge Combining DLLs and Recirculating DLLs are proposed which are accurate and simple for stability and noise analysis. Moreover, spurs caused by mismatch errors in Edge Combining DLLs are studied based on the new system model.
The evolution of an innovation policy in a local system of production. The case of the Regional Programme for Industrial Research, Innovation and Technology Transfer

Aim of this thesis is to analyse the evolution of a policy within a local system of production. We consider policy as standardised social technologies devoted to the coordination of the physical technologies of production. In this sense we can compare them to institutions: arising spontaneously as organic entities for the development of networks of production and then becoming pragmatic as formally embedded in laws and norms. To investigate this process we will employ as case study some industrial policies developed by Regione Emilia Romagna from the 1970s to the Regional Programme for Industrial Research, Innovation and Technology Transfer (PRRIITT) in 2003.
Comparison of Single-stage and Two-stage Tubular SOFC-GT Hybrid Cycles: Energy and Exergy Viewpoints

In this work, single-stage and two-stage tubular solid oxide fuel cell /gas turbine (SOFC-TG) hybrid cycles are comparatively examined from the energy and exergy viewpoints. For this purpose, mass, energy and exergy balances are applied to all components of the cycles. The behavior of tubular solid oxide fuel cell modeled in this study is validated with the experimental test data of tubular SOFC developed by Siemens Westinghouse. The results of simulation show that two-stage SOFC-GT hybrid cycle not only generate more power, but also it has high efficiency in comparison to single-stage SOFC-GT. The values of first law efficiency and exergetic performance coefficient (EPC) are increased from 60.69% and 1.405 in single-stage SOFC-GT to 63.93% and 1.725 in two-stage SOFCGT, respectively. This means that for equivalent generated power of single and two-stage SOFC-GT hybrid cycles, the amount of exergy destruction for two-stage SOFC-GT cycle is less than single-stage SOFC-GT. Also, exergy destruction of all components of the hybrid cycles is calculated separately and the results are compared. Finally, a parametric study is performed to find out optimal values for solid oxide fuel cell design parameters. Effects of these parameters are evaluated on efficiency, generated power and total exergy destruction of the hybrid cycles.
Power & performance optimized hardware classifiers for efficient on-device malware detection

Dynamic malware detection methods are able to detect the presence of malware at run-time, while malicious payloads are being executed. These methods are valuable tools in detection and protection from ever-increasing malicious threats, in particular, dynamic code loading and execution of previously-encrypted payloads, which are both scenarios where commonly used static analysis cannot provide reliable detection. However, in order to detect the execution of malware in its early stage, these approaches need to be run directly on devices, which are typically battery-powered. In order to improve the battery runtime of these devices, malware detectors (and so the classifiers on which they are based) need to be implemented in a low power fashion. This work presents HLS-generated versions of three classifiers commonly used for dynamic malware detection: Logistic Regression, Naive Bayes and Support Vector Machines. These classifiers are first optimized for power and then optimization directives are added to improve performance. The results show that the hardware classifiers decrease the power consumption up to 33 times with respect to their software counterparts, while providing the same accuracy.
Elastic flow asymmetries in microfluidic flow-focusing devices

Complex Flows of Complex Fluids, Liverpool 2008 a) Dep. de Engenharia Quimica, CEFT, Faculdade de Engenharia da Universidade do Porto, 4200-465 Porto, Portugal. b) CEFT, Faculdade de Engenharia da Universidade do Porto, 4200-465 Porto, Portugal. c) Universidade do Minho, 4704-553 Braga, Portugal. d) Dep. of Engineering, University of Liverpool, Liverpool, L69 3GH, United Kingdom. e) Dep. de Engenharia Electromecânica, Universidade da Beira Interior, 6201-001 Covilha, Portugal Monica S. N. Oliveira a) Fernando T. Pinho b), c) Rob J. Pooled) Paulo J. Oliveira e) Manuel A. Alves a) Elastic flow asymmetries in microfluidic flow-focusing devices
Adaptive Mediation for Data Exchange in IoT Systems

Messaging and communication is a critical aspect of next generation Internet-of-Things (IoT) systems where interactions among devices, software systems/services and end-users is the expected mode of operation. Given the diverse and changing communication needs of entities, the data exchange interactions may assume different protocols (MQTT, CoAP, HTTP) and interaction paradigms (point to point, multicast, unicast). In this paper, we address the issue of supporting adaptive communications in IoT systems through a mediation-based architecture for data exchange. Here, components called mediators support protocol translation to bridge the heterogeneity gap. Aiming to provide a placement of mediators to nodes, we introduce an integer linear programming solution that takes as input: a set of Edge nodes, IoT devices, and networking semantics. Our proposed solution achieves adaptive placement resulting in timely interactions between IoT devices for larger topologies of IoT spaces.
Integrated Circuit Design for High-Speed Frequency Synthesis

Synthesizer Architectures. System Level Overview of PLL-Based Frequency Synthesis. Digital Design Considerations. CMOS Logic and Current Mode Logic. Dividers and Phase-Frequency Detectors. Charge Pumps and Loop Filters. Voltage-Controlled Oscillators. Sigma-Delta Modulation for Fractional-N Synthesis. Direct Digital Synthesis. Direct Modulation in Frequency Synthesizers.
Time is of the essence: Explaining the duration of European Union lawmaking under the co-decision procedure

The article explores factors affecting the duration of the co-decision procedure (currently the ordinary legislative procedure), the main procedure for adopting legislation in the European Union. Drawing from rational choice institutionalism, it expects the speed of co-decision to be determined by three attributes: the impatience of legislators, issue linkage and the characteristics of Council and European Parliament negotiators (relais actors). The hypotheses are tested using survival analysis on a dataset of 599 controversial legislative acts submitted and enacted under co-decision between 1999 and 2009. The results show that co-decision proposals are decided faster when they are urgent, negotiated prior to the European Parliament elections and concluded through single proposal logrolls. By contrast, multi-proposal packages and the ideological distance between relais actors prolong decision-making. Overall, the article contributes to the literature by showing that the impatience of legislators, package deals and the properties of negotiators are relevant drivers of co-decision duration.
Successful Software Projects and Products : A quantitative study

Successful or failed software projects have been discussed in literature for many years. Successful software projects are often defined as meeting business objectives, deliver on time and within budget, and meeting requirements. Different factors that contribute to software project success have been identified in the literature. Some of the most common factors that lead to software project success are: user involvement, management support, realistic requirements, and having good estimations. However, there are different opinions about what a successful software project is. Linberg found in a study that managers had a different perception from software practitioners (developers, testers etc.) about what a successful software project is. Since there are different perceptions of what a successful project is among different roles in software development, there may be differences from other perspectives too. This observation relates to the overall research questions in the thesis: Could there be different perceptions about what success factors are for software projects among different countries and customer-supplier relationships? Do people from different countries have different perceptions about what success factors are for software products? This study investigated if there are any differences and similarities between Swedish and Australian companies. In addition, a comparison between bespoke and market driven and bespoke and in-house customer-supplier relationships was made. The result shows that there are differences of which factors that lead to software project success among the two countries as well as between different types of customer-supplier relationships.
Yarn-Dyed Fabric Defect Detection Based On Autocorrelation Function And GLCM

Abstract In this study, a new detection algorithm for yarn-dyed fabric defect based on autocorrelation function and grey level co-occurrence matrix (GLCM) is put forward. First, autocorrelation function is used to determine the pattern period of yarn-dyed fabric and according to this, the size of detection window can be obtained. Second, GLCMs are calculated with the specified parameters to characterise the original image. Third, Euclidean distances of GLCMs between being detected images and template image, which is selected from the defect-free fabric, are computed and then the threshold value is given to realise the defect detection. Experimental results show that the algorithm proposed in this study can achieve accurate detection of common defects of yarn-dyed fabric, such as the wrong weft, weft crackiness, stretched warp, oil stain and holes.
Providing CCN functionalities over OpenFlow switches

Content-Centric Networking (CCN) and Software-Defined Networking (SDN) are gathering special attention from academia and industry and are perceived as a potential future of networking. Providing CCN functionalities over SDN devices is an important requirement to enable the innovation and optimization of network resources. However, current SDN devices like OpenFlow switches do not support CCN functionalities such as name forwarding and caching. In this paper, we propose an approach to provide CCN functionalities over OpenFlow switches without having to change OpenFlow, by adding an abstraction layer, called the Wrapper, between OpenFlow and CCN. The preliminary results performed with CCNx, the reference CCN implementation, show the feasibility and the low overhead of this approach.
A Hierarchy Transformer Network for Extractive Summaries

Extractive Summarization is a popular research subjects in the field of Nature Language Process. The goal of extractive summarization is to select salient segments, sentences or passages from articles. In this paper, a Hierarchy Transformer Network based sequence model is proposed to solve the problems of inefficient and inaccurate when summarizing electrical documents. Our model has the two significant advantages. One is of being very interpretable. The predictions are truncated by abstract features such as article content, significant and novelty are allowed to visualize. Another advantage of the proposed approaches is that our extractive model can train on generated reference summaries by human, which may help eliminate the requirement of sentence level extractive notations.
Effect of supplementation with Lactobacillus casei of endothelial function and inflammation in subjects with metabolic syndrome — A pilot study

Based on animal studies, intake of probiotic bacteria was suggested to improve insulin sensitivity by reducing endotoxinemia and inflammation. The objective of this study was to determine the effects of supplementation with the probiotic strain Lactobacillus casei Shirota (LcS) over 12 wk on insulin sensitivity, β-cell function, inflammation, and endothelial dysfunction parameters in subjects with metabolic syndrome. In a randomizedcontrolled study, 30 subjects with metabolic syndrome either received Lactobacillus casei Shirota 3 times daily for 12 wk or served as controls with standard medical therapy. Fasting blood samples were taken and a 75-g oral glucose tolerance test was performed to derive indices for insulin sensitivity and β-cell function. In addition, parameters to assess endothelial function and inflammation markers were determined. Even though the insulin sensitivity index significantly improved after 3 mo of probiotic supplementation (0.058 ± 0.021 vs. 0.038 ± 0.025), the change was not significantly different compared with the control group. No improvements were seen in additional indices of insulin sensitivity (quantitative insulin sensitivity check index, insulin sensitivity by oral glucose tolerance test, and homeostasis model assessment for insulin resistance) and β-cell function (first and second phase insulin secretion, and homeostasis model assessment for β-cell function). Probiotic supplementation resulted in a significant reduction in soluble vascular cell adhesion molecule-1 (sVCAM-1) level (1,614 ± 343 vs. 1,418 ± 265 ng/ mL). No significant changes in parameters used to assess low-grade inflammation or endothelial dysfunction were observed. Intake of LcS for 12 wk in subjects with metabolic syndrome did not improve insulin sensitivity, β-cell function, endothelial function, or inflammation markers in this trial.
Construction of a High Density Genetic Map and QTL Mapping of PEG-Induced Drought Tolerance at Seedling Stage in Sesame Using Whole Genome Re-Sequencing

BackgroundImprovement in sesame (Sesamum indicum L.) drought tolerance at seedling stage is important for yield stability. Genetic approaches combing with conventional breeding is the most effective way to develop drought-tolerant cultivars. So far, very few studies have been reported to reveal gene/ quantitative trait loci (QTL) controlling drought tolerance in sesame. To identify the genomic regions associated with drought tolerance, we constructed a high-density genetic map using a recombinant inbred line (RIL) population through whole genome re-sequencing (WGRS) technique. QTLs contributing to three seedling traits were identified under both non-stress and water stress conditions.ResultsThree drought tolerance related traits and their relative values (the ratio of value under stress to value under control condition), including seedling weight (SW), shoot length (SL) and root length (RL), were evaluated under control and PEG-induced osmotic conditions at seedling stage in a RIL population derived from cross of Zhushanbai (ZSB) and Jinhuangma (JHM). Significant variation and high broad sense heritability were observed for all traits except SW under stress condition in the population. With this population, a high-density linkage map with 1354 bin markers was constructed through WGRS strategy. Composite interval mapping analysis was performed for all the traits as well as their relative phenotypic data. A total of 34 QTLs were detected for these three traits under both conditions and their relative values, and 13 stable QTLs associated with seven traits could be revealed in two independent experiments, explaining on average, 4.95-16.26% of phenotypic variation for each QTL. Four of them contributed more than 10% of phenotypic variation. Root length related QTLs were first identified in sesame. One region on chromosome 12 contained two major QTLs related to RL under osmotic condition and relative RL. ConclusionThe current study reports the first QTL mapping of drought tolerance related traits through a RIL population and first QTL detection of root related trait (root length) in sesame. These findings will provide new genetic resources for molecular improvement of drought tolerance and candidate gene identification in sesame.
Virtual Vehicle-Driving cycle application for measuring emission and fuel consumption on HDVS

The suggested method for measuring running/operational properties of all vehicles in particular HDVs originates from the objectives of COST 346.10 To develop an improved methodology for estimating pollutant emissions and fuel consumption from commercial road transport operated with HDVs in Europe. It also builds on the foundation lied by our contribution to COST 319, where we worked on Quasi-static method of engine loading and its application in estimating fuel consumption and emission production [1]. The quasi-static method affords the possibility of using the information technology in effectively taking advantage of the cheap acceleration measuring whilst maintaining the priorities of transient state measuring using a dynamometer. The actual measuring proceeds as follows: At a predetermined constant fuel feed/supply the combustion engine is braked using the vehicle brakes (steady analyzer of emissions) for 10 to 20 seconds. During this period the variable z (CO, CO 2 , HC, NO x ) and variable x (frequency of revolutions) are measured. Then the engine is relieved and accelerated and during this period the variable y (engine torque) is measured. Mathematical computation of these variaBoleslav KADLECEK Ladislav PEJSA Martin PEXA
SeMap: automatic semantic mapping for large-scale indoor spaces

Due to the rapid development of indoor location-based services, semantic mapping becomes a highly promising technique for ubiquitous applications. Semantic mapping is challenging due to semantic diversity and indoor environment variations. This paper presents a novel semantic mapping method (namely SeMap) that uses crowd-sourced images and motion traces. It first constructs a scene graph, which serves as the foundation for the semantics localization stage. It then extracts semantics, estimates the local pose of each image using crowdsourced images, and calculates the global pose of each image using motion traces of users. Furthermore, by combining multiple viewpoints, a semantic localization algorithm is proposed to label semantics of general entities in an indoor map. Extensive experiments are conducted on a real dataset. The experimental results indicate that our method achieves an average location error of 1.05m. It demonstrates the advantage of our proposed method.
THERMAL PROPERTIES OF SOME ASPHALTIC CONCRETE MIXES

To obtain an increased understanding of the energy transfer in asphaltic concrete recycling processes that use surface heat, laboratory tests were carried out on four asphaltic concrete mixes (three having limestone aggregate and one with expanded shale lightweight aggregate) to determine thermal properties. It was found that the thermal conductivity of the three limestone mixes depended on asphalt content and aggregate gradation, but that the conductivity of the lightweight aggregate mixes varied little as the asphalt content was increased from 3.5 to 6.5 percent. The specific heat and diffusivity of the mixes varied with mineralogy and gradation but changed little with asphalt content.