Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Speech Recognition by Combining Short-Term and Long-Term Spectrum Based Position-Dependent CMN with Conventional CMN

In a distant-talking environment, the length of channel impulse response is longer than the short-term spectral analysis window. Conventional short-term spectrum based Cepstral Mean Normalization (CMN) is therefore, not effective under these conditions. In this paper, we propose a robust speech recognition method by combining a short-term spectrum based CMN with a long-term one. We assume that a static speech segment (such as a vowel, for example) affected by reverberation, can be modeled by a long-term cepstral analysis. Thus, the effect of long reverberation on a static speech segment may be compensated by the long-term spectrum based CMN. The cepstral distance of neighboring frames is used to discriminate the static speech segment (long-term spectrum) and the non-static speech segment (short-term spectrum). The cepstra of the static and non-static speech segments are normalized by the corresponding cepstral means. In a previous study, we proposed an environmentally robust speech recognition method based on Position-Dependent CMN (PDCMN) to compensate for channel distortion depending on speaker position, and which is more efficient than conventional CMN. In this paper, the concept of combining short-term and long-term spectrum based CMN is extended to PDCMN. We call this Variable Term spectrum based PDCMN (VT-PDCMN). Since PDCMN/VT-PDCMN cannot normalize speaker variations because a position-dependent cepstral mean contains the average speaker characteristics over all speakers, we also combine PDCMN/VT-PDCMN with conventional CMN in this study. We conducted the experiments based on our proposed method using limited vocabulary (100 words) distant-talking isolated word recognition in a real environment. The proposed method achieved a relative error reduction rate of 60.9% over the conventional short-term spectrum based CMN and 30.6% over the short-term spectrum based PDCMN.
Design of Synchronous Section-Carry Based Carry Lookahead Adders with Improved Figure of Merit

The section-carry based carry lookahead adder (SCBCLA) architecture was proposed as an efficient alternative to the conventional carry lookahead adder (CCLA) architecture for the physical implementation of computer arithmetic. In previous related works, self-timed SCBCLA architectures and synchronous SCBCLA architectures were realized using standard cells and FPGAs. In this work, we deal with improved realizations of synchronous SCBCLA architectures designed in a semi-custom fashion using standard cells. The improvement is quantified in terms of a figure of merit (FOM), where the FOM is defined as the inverse product of power, delay and area. Since power, delay and area of digital designs are desirable to be minimized, the FOM is desirable to be maximized. Starting from an efficient conventional carry lookahead generator, we show how an optimized section-carry based carry lookahead generator is realized. In comparison with our recent work dealing with standard cells based implementation of SCBCLAs to perform 32-bit addition of two binary operands, we show in this work that with improved section-carry based carry lookahead generators, the resulting SCBCLAs exhibit significant improvements in FOM. Compared to the earlier optimized hybrid SCBCLA, the proposed optimized hybrid SCBCLA improves the FOM by 88.3%. Even the optimized hybrid CCLA features improvement in FOM by 77.3% over the earlier optimized hybrid CCLA. However, the proposed optimized hybrid SCBCLA is still the winner and has a better FOM than the currently optimized hybrid CCLA by 15.3%. All the CCLAs and SCBCLAs are implemented to realize 32-bit dual-operand binary addition using a 32/28nm CMOS process.
On the Effective Use of Fault Injection for the Assessment of AUTOSAR Safety Mechanisms

The automotive safety standard ISO 26262 strongly recommends the use of fault injection (FI) for the assessment of safety mechanisms that typically span composite dependability and real-time operations. However, with the standard providing very limited guidance on the actual design, implementation and execution of FI experiments, most AUTOSAR FI approaches use standard fault models (e.g., bit flips and data type based corruptions), and focus on using simulation environments. Unfortunately, the representation of timing faults using standard fault models, and the representation of real-time properties in simulation environments are hard, rendering both inadequate forthe comprehensive assessment of AUTOSAR's safety mechanisms. The actual development of ISO 26262 advocated FI is further hampered by the lack of representative software fault models and the lack of an openly accessible AUTOSAR FI framework. We address these gaps by (a) adapting the open source FI framework GRINDER to AUTOSAR and (b) showing how to effectively apply it for the assessment of AUTOSAR's safety mechanisms.
In Vitro and In Vivo Evaluation of Vancomycin-Loaded PMMA Cement in Combination with Ultrasound and Microbubbles-Mediated Ultrasound

Ultrasound (US) has been used to increase elution of antibiotic from an antibiotic-loaded poly(methyl methacrylate) (PMMA) bone cement (ALBC). We aimed to further investigate whether microbubbles-mediated US (US + MB) facilitate elution of vancomycin (VAN) from cylindrical specimens and enhance the activity of the eluted antibiotic against Staphylococcus aureus (S. aureus) in vitro. The study groups comprised cylindrical bone cement fabricated with VAN (VAN), ALBC using US (VAN + US), and ALBC using MB-mediated US (VAN + US + MB). We also carried out an in vivo study involving the activity of VAN from cylindrical cement implanted in tibiae of New Zealand white rabbits inoculated with S. aureus. We found that (1) in vitro, elution from VAN + US + MB cylinders was significantly higher than from either the VAN or VAN + US specimens; (2) the activity of the eluted VAN from the VAN + US + MB cylinders against planktonic S. aureus was significantly higher than from either the control or VAN or VAN + US specimens; and (3) in the rabbits, the activity of the eluted VAN from the VAN + US + MB cylinders against S. aureus was significantly higher than from either the control or VAN or VAN + US specimens. The present results suggest that VAN-loaded PMMA cement irradiated with MB-mediated US may have a role in controlling prosthetic joint infection.
School Bullying and Cyberbullying Among Boys and Girls: Roles and Overlap

ABSTRACT The purpose of this study was to investigate gender differences in the overlap between school and cyberbullying according to the different types of involvement in such behaviors. The current study involved 2,785 Italian students, ages 11–17 recruited from 7 secondary schools, who anonymously self-reported about school and cyberbullying as victims and/or perpetrators. Based on their responses, students were classified as ‘only-bullies,’ ‘only-victims,’ ‘bully/victims,’ or ‘not involved’ in school and/or online. To explain the relationship between school and online bullying, 2 theoretical frames were tested: role continuity and role inversion. Results showed that, for girls, ‘school only-bullies’ were not overlapping with ‘cyber only-bullies,’ and ‘school only-victims’ were not overlapping with ‘cyber only-victims,’ but these categories were related for boys. ‘School bully/victims’ were significantly overlapping with ‘cyber bully/victims’ for both boys and girls. It was concluded that the role continuity approach is most appropriate to explain these 2 disturbing problems in adolescents especially for boys. Intervention efforts should especially target the bully/victims group.
Sensor scan timing compensation in environment models for automated road vehicles

Environment perception is one of the most important tasks for Advanced Driver Assistance Systems and Automated Driving. Various types of sensors are used concurrently and fused into a consistent representation of the vehicle's surrounding. With more than one device involved, timing behavior becomes a relevant aspect of such systems. Delays due to processing and transferring data need to be considered when fusing sensor data. While some sensors, such as camera devices, perceive the environment as a snapshot, other sensors are based on a scanning technique. The iterative acquisition principle of scanning sensors lead to considerable time differences between single measurements within a scan. In addition to transfer and processing delays, these time differences have to be considered properly for a comprehensive environment representation. This paper focuses on time-related effects resulting from using a scanning sensor. The influence on two commonly utilized environment representations is discussed, grid-based and object-based approaches for stationary and movable elements, respectively. We present a comprehensive approach to incorporate the ego motion into grid-based models. We propose an adaptive prediction horizon for object tracking algorithms, based on sensor scan timing characteristics. Performance gains are evaluated with simulated data and verified within a real-world application. The presented algorithms are computationally feasible and real-time capable on a standard PC.
Phospholipase D2 Is Involved in the Formation of Golgi Tubules and ArfGAP1 Recruitment

Lipids and lipid-modifying enzymes play a key role in the biogenesis, maintenance and fission of transport carriers in the secretory and endocytic pathways. In the present study we demonstrate that phosphatidic acid generated by phospholipase D2 (PLD2) is involved in the formation of Golgi tubules. The main evidence to support this is: 1) inhibitors of phosphatidic acid formation and PLD2 depletion inhibit the formation of tubules containing resident enzymes and regulators of intra-Golgi transport in a low temperature (15°C) model of Golgi tubulation but do not affect brefeldin A-induced tubules, 2) inhibition of PLD2 enzymatic activity and PLD2 depletion in cells cultured under physiological conditions (37°C) induce the formation of tubules specifically containing Golgi matrix proteins, and, 3) over-expression of PLD2 induces the formation of a tubular network. In addition, it was found that the generation of this lipid by the isoenzyme is necessary for ArfGAP1 recruitment to Golgi membranes. These results suggest that both proteins are involved in the molecular mechanisms which drive the formation of different types of Golgi tubules.
Elliptic Curve Discrete Logarithms and Wieferich Primes

Recently, a new method, called by Xedni calculus, to solve ECDLP was proposed by Silverman and Kim et. al. [11, 5]. The Xedni addresses a novel idea, but has two difficulties. One is to find good liftings and the other is to compute the dependence relation among lifted rational points. In this paper, we propose a fast algorithm to compute the dependence relation modulo the order, nP̃ , of P̃ for given two dependent rational points of elliptic curve over Q. Using this, if we could find liftings P, Q and E with rank 1 of P̃ , Q̃, Ẽ, then we can solve the ECDLP very fast. Moreover, by this algorithm, we can easily check whether two lifted points are linearly independent or not. Also we investigate the possibility to get such liftings for elliptic curves with a non-trivial 2-torsion, and generate lots of liftings of rank ≤ 2.
Developing Theory and Ethnographic Applications for Explanations of Emergent Structure and Network Dynamics

Project SUMMARY 1 Project DESCRIPTION 3 I. Objectives 3 II. Rationale 3 III. Conceptual Perspective 3 Modeling Strategies, Patterns and Mathematical Theorems, and Working Hypotheses 4 Heuristics for Theorizing Dynamic Evolution of Coherence among Formal Patterns 7 Dynamics 9 IV Measurement: Detecting Patterns in Networks 9 V. Hypothesis Tests on Social Transformations 10 VI. Modeling and Hypothesis Testing: Research Problems and Questions 11 Problem 1: Cohesive Unity 11 Problem 2: Exchange Balances and Multilevel Graphs 12 Problems 3/4: Bundling and Scaling 13 Problem 5: Distributive Transformation 14 VIII. Developing Methods for the Integration and Extension of Network Results 14 Cohesive Groups, Cohesive Roles, Cohesive Blockmodels 14 VIII. Research Schedules and Deliverables 17 IX. Key Personnel and Training 17
Novel fast switchover on OpenFlow switch

The specifications of OpenFlow switch define the fast failover1 group table, which allows the switch quickly adapt to failure based on its local states. In a failure scenario, the traffic on a faulty path is fast switched to a predetermined path in a so-called active/standby manner. That is likely the standard and only way of achieving fast switchover. In this paper, we introduce a novel method for fast switchover/failover on the OpenFlow switch. The conceptual idea is that the new switchover follows an active/active manner rather than the active/standby one in the standard. Specifically, instead of using the fast failover group table we leverage the another one named select. By doing so, the traffic of an end-to-end connection is striped over multiple active paths on a weighted round robin (WRR) fashion. Whenever a failure happens across the paths, the data flow on a failed path is rapidly switched over to the remaining active paths. We modify an OpenFlow 1.3 switch to include the proposed switchover and evaluate the new switch under failure scenarios. The new OpenFlow switch has a better resource allocation as well as less traffic lost during the recovery process than the standard one.
Commanding Board of Director Attention: Investigating How Organizational Performance and CEO Duality Affect Board Members Attention to Monitoring

Foundational RBV work suggests that firms possess capabilities that represent strengths and others that represent weaknesses. In contrast, contemporary research has examined capability strengths while largely ignoring weaknesses. Addressing this oversight, we examine the direct and integrated effects of sets of capability strengths and capability weaknesses on competitive advantage and its empirical correlate - relative performance. Additionally, we explore how environmental and firm-specific factors influence change in these drivers of competitive advantage over time. Results suggest that weakness sets have a negative effect on relative performance, while strength sets have an increasingly positive effect. The integrative effects of strength and weakness sets affect relative performance in a complex manner. For example, while high strength/low weakness firms perform at high levels, firms integrating high strength with high weakness perform well, but experience considerably more variance in their realized outcomes. Lastly, we find that the strength and weakness sets change significantly over time in markets where competition is more intense, thereby undermining the durability of competitive advantage. Our theory and results indicate that achieving temporary advantage is more difficult than previously thought and that the erosion of advantage occurs routinely as a result of dynamic and interactive rivalry.
VALIDATION OF CARTOSAT-1 DTM GENERATION FOR THE SALON DE PROVENCE TEST SITE

Cartosat-1 is the eleventh satellite of the Indian Space Research Organisation series and is primarily meant for topographic mapping and Digital Terrain Model (DTM) generation. In the framework of the Cartosat-1 Scientific Assessment Programme, the Politecnico di Milano University (Italy) evaluated as Co-Investigator the performances of the Cartosat-1 satellite in the generation of DTMs. This paper describes the outcomes for the Salon de Provence test site (France) with respect to existing standards and products actually used in France and also provides a comparison with the global Shuttle Radar Topography Mission’s DTM supplied by NASA and widely used in the remote sensing community.
Multiple faces tracking based on joint kernel density estimation and robust feature descriptors

In this paper, we present a robust implementation of multi-face tracker using Joint Feature Model, Kalman filter-based Mean-shift and Speeded-Up Robust Features (SURF), which can tolerate interference caused by objects of similar color, partial occlusion, total occlusion, rotation and scale change. The Joint Feature Model for each person combines the non-parametric distribution of colors in the face region and gradient information of face, Mean-shift based on Kalman filter is adopted to update the position and velocity of the object in real-time and predict the locations in the subsequent frame, and SURF solves the object-recovery problem in occlusion. Experimental results demonstrate the efficiency of the tracking algorithm and the recovery capability even in case of total occlusion.
Impact of Chronic Neonicotinoid Exposure on Honeybee Colony Performance and Queen Supersedure

Background Honeybees provide economically and ecologically vital pollination services to crops and wild plants. During the last decade elevated colony losses have been documented in Europe and North America. Despite growing consensus on the involvement of multiple causal factors, the underlying interactions impacting on honeybee health and colony failure are not fully resolved. Parasites and pathogens are among the main candidates, but sublethal exposure to widespread agricultural pesticides may also affect bees. Methodology/Principal Findings To investigate effects of sublethal dietary neonicotinoid exposure on honeybee colony performance, a fully crossed experimental design was implemented using 24 colonies, including sister-queens from two different strains, and experimental in-hive pollen feeding with or without environmentally relevant concentrations of thiamethoxam and clothianidin. Honeybee colonies chronically exposed to both neonicotinoids over two brood cycles exhibited decreased performance in the short-term resulting in declining numbers of adult bees (−28%) and brood (−13%), as well as a reduction in honey production (−29%) and pollen collections (−19%), but colonies recovered in the medium-term and overwintered successfully. However, significantly decelerated growth of neonicotinoid-exposed colonies during the following spring was associated with queen failure, revealing previously undocumented long-term impacts of neonicotinoids: queen supersedure was observed for 60% of the neonicotinoid-exposed colonies within a one year period, but not for control colonies. Linked to this, neonicotinoid exposure was significantly associated with a reduced propensity to swarm during the next spring. Both short-term and long-term effects of neonicotinoids on colony performance were significantly influenced by the honeybees’ genetic background. Conclusions/Significance Sublethal neonicotinoid exposure did not provoke increased winter losses. Yet, significant detrimental short and long-term impacts on colony performance and queen fate suggest that neonicotinoids may contribute to colony weakening in a complex manner. Further, we highlight the importance of the genetic basis of neonicotinoid susceptibility in honeybees which can vary substantially.
Modeling Wnt/β-Catenin Target Gene Expression in APC and Wnt Gradients Under Wild Type and Mutant Conditions

The Wnt/β-catenin pathway is involved in the regulation of a multitude of physiological processes by controlling the differential expression of target genes. In certain tissues such as the adult liver, the Wnt/β-catenin pathway can attain different levels of activity due to gradients of Wnt ligands and/or intracellular pathway components like APC. How graded pathway activity is converted into regionally distinct patterns of Wnt/β-catenin target gene expression is largely unknown. Here, we apply a mathematical modeling approach to investigate the impact of different regulatory mechanisms on target gene expression within Wnt or APC concentration gradients. We develop a minimal model of Wnt/β-catenin signal transduction and combine it with various mechanisms of target gene regulation. In particular, the effects of activation, inhibition, and an incoherent feedforward loop (iFFL) are compared. To specify activation kinetics, we analyze experimental data that quantify the response of β-catenin/TCF reporter constructs to different Wnt concentrations, and demonstrate that the induction of these constructs occurs in a cooperative manner with Hill coefficients between 2 and 5. In summary, our study shows that the combination of specific gene regulatory mechanisms with a time-independent gradient of Wnt or APC is sufficient to generate distinct target gene expression patterns as have been experimentally observed in liver. We find that cooperative gene activation in combination with a TCF feedback can establish sharp borders of target gene expression in Wnt or APC gradients. In contrast, the iFFL renders gene expression independent of gradients of the upstream signaling components. Our subsequent analysis of carcinogenic pathway mutations reveals that their impact on gene expression is determined by the gene regulatory mechanism and the APC concentration of the cell in which the mutation occurs.
Associating Data in System of Systems Using Measures of Information

Many modern day collaborative systems/system of systems rely heavily on the sharing of information in order to improve performance, manage resources, and maximize overall capability. These types of systems are characterized by many decentralized nodes that can either all be identical or partitioned into a finite set of specialized types. When information is shared within any system of systems, the overall performance hinges on its ability to correctly associate the information received. The primary hypothesis evaluated by any system of systems after the receipt of new information is to determine whether this information belongs to a previously observed entity, or not. When this hypothesis is false, the new information belongs to a new entity, which includes both real and false entities. To evaluate this hypothesis, and to determine the optimal assignments to make at each time step, a data association discriminator or scoring function that performs like a distance function between two probability distribut.
Biosignals separation method for medical diagnostic system

In this paper, we will propose method to separate biosignals such as breath, blood, heart signal from mixed signals in body. As a result, we could get only target signal which is breath, blood and heart signals from actual mixture signals of carotid artery sound that extracted from a healthy human subject in a real environment using our algorithms and microphone sensors. Although this method is first trial to separate biosignals from sound in body, we get a significant result.
Robust Color Image Segmentation through Tensor Voting

This paper presents a new method for robust color image segmentation based on tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. First, an adaptation of tensor voting to both image denoising and robust edge detection is applied. Second, pixels in the filtered image are classified into likely-homogeneous and likely-inhomogeneous by means of the edginess maps generated in the first step. Third, the likely-homosgeneous pixels are segmented through an efficient graph-based segmenter. Finally, a modified version of the same graph-based segmenter is applied to the likely-inhomogeneous pixels in order to obtain the final segmentation. Experiments show that the proposed algorithm has a better performance than the state-of-the-art.