Miracle-dz/UniFAR-FTUs huggingface dataset:
Lab, Field, Gallery, and Beyond

Over the last 10 years we have seen a growing number of researchers integrating design experiments in their research inquiries. Initially, this work borrowed heavily from neighboring fields, employing a dual strategy in which design experiments and their evaluation were largely treated as separate processes that were often carried out by different people. More recently, design researchers have developed several approaches that integrate design-specific work methods into research. This paper takes a methodological look at three such established approaches that the authors call Lab, Field, and Gallery. They are described and their similarities and differences analyzed. In conclusion, whether design research today needs foundations based on the standards established for other disciplines is discussed.
Learning to extract geographic information from internet router hostnames

Geolocating Internet routers is a long-standing and notoriously difficult challenge, and current solutions lack the accuracy and adaptability to yield reliable results. We revisit this problem, designing a solution capable of accurately and comprehensively extracting geographic information that network operators embed into router interface hostnames. We train our system using dictionaries that map geographic codes to known locations, and constrain inferences with delay measurements conducted from a distributed set of vantage points. While most operators use known geographic codes, some devise their own mnemonic codes for locations, which our system also extracts and interprets. We evaluate our system on Internet-wide topology datasets, automatically learning regular expressions (regexes) for 1023 different domain suffixes with IPv4 routers, and 241 different domain suffixes with IPv6 routers. We received ground truth from operators of 13 domain suffixes, all of whom confirmed the correctness of our learned regexes, and that our system correctly interpreted 78.6% of the custom geographic codes. For these 13 suffixes, our solution more accurately extracts and interprets geographic information than the previous state-of-the-art, correctly geolocating 94.0% of router hostnames with a geohint compared to DRoP (56.6%) and HLOC (73.1%). This work advances the ability of researchers and network operators to characterize the location of critical Internet infrastructure, a foundational building block of network performance, security, and resilience analysis. We release the source code of our system and our inferred regexes.
AN IMPROVEMENT OF WAVE REFRACTION-DIFFRACTION EFFECT IN SWAN

SWAN, a wind wave model, has been modified to take into account wave refraction-diffraction effects from the extended mild-slope equation when wind waves pass through a extremely uneven sea bottom in the presence of current. In our modified model, the diffraction correction parameter introduced by Holthuijsen et al. [10] has been adjusted to better predict the combined effect of the higher-order bottom effect, wave-bottom interaction and wave-current interaction. After a preliminary analysis, the influence of the correction parameter is discussed, and a comparison is made between the original and the new phase-decoupled versions of SWAN through some typical examples of wave fields around semiinfinite breakwaters, breakwaters with gap, and detached breakwaters on different bathymetries. The results show that the new phase-decoupled model exhibits improvements in both numerical convergence and Prediction results for the case of a steep varying an extremely uneven sea bottom than the original one.
Application of Markov chain on daily rainfall data in Paraíba-Brazil from1995-2015

is study analyzed the behavior of daily rainfall in the State of Paraíba using the data from five meteorological stations distributed across the mesoregions of this state. We used the three-state Markov Chain model, in which states are defined as dry, wet and rainy. We calculated transition probabilities among states, probabilities of equilibrium of states, and expected lengths of the defined states for all stations and seasons to investigate spatial/seasonal variability. Results showed that for the entire region and for all seasons, the probability of dry days is greater than the probability of rainy days; expected values of rainy spells are low, indicating that the rainfall regime in Paraíba is characterized by high rainfall intensity distributed over short rainy periods. e dry-dry transition probability presents the highest values for all seasons and stations, as well as the corresponding expected dry spell length, indicating that this region is subjected to prolonged dry periods. e transition probabilities that lead to dry condition are higher in the interior of the State, while probabilities that lead to rainy condition are higher in the coastal region as well as the probability of rainy days, which is greater in fall, during the rainy season.
CADHERIN mediated AMIS localisation

Individual cells within de novo polarising tubes and cavities must integrate their forming apical domains into a centralised apical membrane initiation site (AMIS). This is necessary to enable organised lumen formation within multi-cellular tissue. Despite the well documented importance of cell division in localising the AMIS, we have found a division-independent mechanism of AMIS localisation that relies instead on CADHERIN-mediated cell-cell adhesion. Our study of de novo polarising mESCs suggest that cell-cell adhesion directs the localisation of apical proteins such as PAR-6 to a centralised AMIS. Unexpectedly, we also found that mESC cell clusters lacking functional E-CADHERIN were still able to form a lumen-like cavity in the absence of AMIS localisation and did so at a later stage of development via a ‘closure’ mechanism, instead of via hollowing. This work suggests that there are two, interrelated mechanisms of apical polarity localisation: cell adhesion and cell division. Alignment of these mechanisms allows for redundancy in the system and ensures the localisation of a coherent epithelial structure within a growing organ.
Fusing Lexing and Parsing

Lexers and parsers are typically defined separately and connected by a token stream. This separate definition is important for modularity, but harmful for performance. We show how to fuse together separately-defined lexers and parsers, drastically improving performance without compromising modularity. Our staged parser combinator library, flap , provides a standard parser combinator interface, but generates specialized token-free code that runs several times faster than ocamlyacc on a range of benchmarks.
Learning to Grasp Objects in Virtual Environments through Imitation

In spite of the huge progress seen in the field of robotics, robot manipulation still stands as a great challenge for the engineering community. We propose using the human manipulation of objects as a basis for robot manipulation, applied through imitation learning. Considering that obtaining the data of the human manipulation from video can add noise due to obstructions or simply due to the complexity of a fully dexterous hand, we present the virtual environment as a better medium to collect data and record the samples to be used for robotic imitation. The virtual environment will be interactable with a glove with position sensors capable of fully capture the human hand movements in all its intricacy, and vibrating plaques on the fingertips to simulate the touch of a virtual object (haptic feedback). For the work we consider two experimental conditions: Presence vs. absence of haptic feedback while executing grasps. With the samples recorded, the subconscious human mannerisms will be applied and tested on a virtual hand using the output of neural networks, in particular, a recurrent neural network responsible for the reaching portion of a task and another responsible for the remainder/manipulation portion of the task, being the output followed switched from the reaching recurrent neural network to the manipulation recurrent neural network when the object to interact is considered grasped. Both recurrent neural networks will be trained with the recorded demonstrations, each with their respective portion, enabling the robot to grasp objects successfully in most attempts. It will also be tested if the use of haptic feedback actually leads to better demonstrations. We also aim to provide freely our dataset, to enable researchers without the hardware needed to record demonstrations to test their own training algorithms.
Approach to fuzzy control of an indirect field-oriented induction motor drives

The field orientation control of an induction motor has been permitted fast transient response by decoupled torque and flux. The conventional PI controller has been widely used in industrial applications due to the simple control algorithm and easy implementation. With help of the Matlab/Simulink, a block model of an induction motor drives can be constructed. This paper presents a novel fuzzy controller of an indirect field oriented induction motor drive for high performance applications. The superiority of the proposed fuzzy controller over a conventional PI controller in handling nonlinear systems such as induction motors has been effectively demonstrated by comparing this speed controller with a conventional PI controller under varying operating conditions like step change in speed reference and torque reference. The results validate the robustness and effectiveness of the proposed fuzzy logic controller for high performance induction motor drive systems.
GRACE-Os: An Energy -Efficient Mobile Multimedia Operating System

Multimedia-enabled mobile devices need to support multimedia quality of service (QoS) requirements under limited battery energy and also provide new opportunities due to the adaptive hardware and software components. Researchers have therefore introduced adaptation into various system layers. Previous adaptation work often adapts only some layers or only at coarse time. We believe that to fully reap the benefits of adaptation, it is necessary to take a cross-layer adaptation approach, in which all system layers adapt cooperatively in response to system changes at different time granularity. This thesis presents a novel operating system, called GRACE-OS, to support such cross-layer adaptation by coordinating the adaptation in different layers and enforcing the coordinated decisions via energy-aware real-time scheduling. This thesis makes four major contributions. First, we propose a hierarchical adaptation framework to coordinate adaptation in different layers. This framework consists of global and internal adaptation. The former coordinates all three layers in response to large system changes, while the latter adapts each individual layer in response to small system changes. Second, we extend traditional real-time scheduling to decide how fast to execute applications in addition to when to execute what applications. Third, we develop a set of algorithms for internal adaptation algorithms to handle small variations in application CPU demand. Finally, we develop a kernel-based profiling technique predict the CPU demand of multimedia applications for both global and internal adaptation. We have implemented GRACE-OS in the Linux kernel and evaluated it with adaptive Athlon processor and adaptive video codec applications. Our experimental results show that GRACE-OS efficiently trades off QoS for energy with acceptable overhead. In particular, compared to previous systems that adapt only some system layers, GRACE-OS achieves the user-desired battery lifetime and saves energy by up to 59% while providing better or the same multimedia quality. Compared to previous systems that adapt only at coarse time granularity, GRACE-OS saves energy by 2% to 8.9% without affecting multimedia quality.
New Applications of Lipid and Polymer-Based Nanoparticles for Nucleic Acids Delivery

Nucleic acids represent a promising lead for engineering the immune system. However, naked DNA, mRNA, siRNA, and other nucleic acids are prone to enzymatic degradation and face challenges crossing the cell membrane. Therefore, increasing research has been recently focused on developing novel delivery systems that are able to overcome these drawbacks. Particular attention has been drawn to designing lipid and polymer-based nanoparticles that protect nucleic acids and ensure their targeted delivery, controlled release, and enhanced cellular uptake. In this respect, this review aims to present the recent advances in the field, highlighting the possibility of using these nanosystems for therapeutic and prophylactic purposes towards combatting a broad range of infectious, chronic, and genetic disorders.
Epigenomics and Lipidomics Integration in Alzheimer Disease: Pathways Involved in Early Stages

Background: Alzheimer Disease (AD) is the most prevalent dementia. However, the physiopathological mechanisms involved in its development are unclear. In this sense, a multi-omics approach could provide some progress. Methods: Epigenomic and lipidomic analysis were carried out in plasma samples from patients with mild cognitive impairment (MCI) due to AD (n = 22), and healthy controls (n = 5). Then, omics integration between microRNAs (miRNAs) and lipids was performed by Sparse Partial Least Squares (s-PLS) regression and target genes for the selected miRNAs were identified. Results: 25 miRNAs and 25 lipids with higher loadings in the sPLS regression were selected. Lipids from phosphatidylethanolamines (PE), lysophosphatidylcholines (LPC), ceramides, phosphatidylcholines (PC), triglycerides (TG) and several long chain fatty acids families were identified as differentially expressed in AD. Among them, several fatty acids showed strong positive correlations with miRNAs studied. In fact, these miRNAs regulated genes implied in fatty acids metabolism, as elongation of very long-chain fatty acids (ELOVL), and fatty acid desaturases (FADs). Conclusions: The lipidomic–epigenomic integration showed that several lipids and miRNAs were differentially expressed in AD, being the fatty acids mechanisms potentially involved in the disease development. However, further work about targeted analysis should be carried out in a larger cohort, in order to validate these preliminary results and study the proposed pathways in detail.
51.2: A. 4.3‐in. VGA (188 ppi) AMOLED Display with a New Driving Method

We developed a 4.3‐inch VGA driver‐integrated AM‐OLED display with the world's highest pixel density of 188ppi by using high performance TFTs, a top emission structure, a technology for improving the precision of mask alignment in OLED deposition by RGB emitter's selective deposition method, and a 4Tr/Cell digital time‐gray‐scale driving method which improves image quality by fixing the gate potential of driving TFT.
Diagnosis of multiple simultaneous fault via hierarchical artificial neural networks

We discuss a new type of macroarchitecture of neural networks called a hierarchical artificial neural network (HANN) and how to train it for fault diagnosis given appropriate data patterns. The HANN divides a large number of patterns into many smaller subsets so the classification can be carried out more efficiently via an artificial neural network. One of its advantages is that multiple faults can be detected in new data even if the network is trained with data representing single faults. The use of a HANN is illustrated in fault diagnosis of a chemical reactor
The Flipped Classroom: Learning Revolution to Improve Students’ English Speaking Skills

The flipped classroom is one of the revolutions in education that utilizes internet technology in learning. Students are required to access and study material online at home before face-to-face learning in the classroom. In class, the teacher focuses on the students to be directly involved in their English speaking skills. This study aims to develop learning media based on the flipped classroom that was feasible and effectively used to improve students’ English speaking skills. The research and development (R&D) was the type of this study. The procedure and design are from the Gall, Gall & Borg, and Dick, Carey & Carey models. Based on the results of expert validation, trial evaluations, and student achievement tests. Thus, the learning media based on the flipped classroom was feasible and effectively used to improve students’ English speaking skills.
A CMOS-compatible fluid density sensor

We report a CMOS-compatible resonant sensor to measure the density of fluids. The device is fabricated using a standard CMOS process followed by simple post-processing consisting of sacrificial aluminium etching and silicon bulk micromachining. The sample volume of liquid probed by the resonating structure is only 11 pl.
Hybrid Feature Based Classifier Performance Evaluation of Monophonic and Polyphonic Indian Classical Instruments Recognition

Instrument recognition in computer music is an important research area that deals with sound modelling. Musical sounds comprises of five prominent constituents which are Pitch, timber, loudness, duration, and spatialization. The tonal sound is function of all these components playing critical role in deciding quality. The first four parameters can be modified, but timbre remains a challenge [6]. Then, inevitably, timbre became the focus of this piece. It is a sound quality that distinguishes one musical instrument from another, regardless of pitch or volume, and it is critical. Monophonic and polyphonic recordings of musical instruments can be identified using this method. To evaluate the proposed approach, three Indian instruments were experimented to generate training data set. Flutes, harmoniums, and sitars are among the instruments used. Indian musical instruments classify sounds using statistical and spectral parameters. The hybrid features from different domains extracting important characteristics from musical sounds are extracted. An Indian Musical Instrument SVM and GMM classifier demonstrate their ability to classify accurately. Using monophonic sounds, SVM and Polyphonic produce an average accuracy of 89.88% and 91.10%, respectively. According to the results of the experiments, GMM outperforms SVM in monophonic recordings by a factor of 96.33 and polyphonic recordings by a factor of 93.33.
Likelihood and Duration of Flow Breakdown

The effect of rain on freeway flow breakdown behavior is investigated. Three aspects of flow breakdown are analyzed for rain versus no rain (clear) weather conditions. First, the probability of breakdown occurrence is examined by analyzing the distribution of prebreakdown flow rates observed immediately before the onset of traffic breakdown by using a survival analysis approach. At all study sections, a reduction with pre-breakdown flow rates is observed under rain conditions compared with distributions under no rain and confirms higher breakdown likelihoods at lower flows. Log likelihood ratio tests confirm the statistical significance of differences in the prebreakdown flow rate distribution parameters under rain compared with clear conditions. Second, breakdown duration is examined by estimating a semiparametric Cox proportional hazard model. With a rain event indicator set as an independent variable, the effect of rain on breakdown duration is observed. Rain during a breakdown episode is found to increase its duration, whereas rain before breakdown does not appear to affect duration. Finally, prebreakdown and postbreakdown flow rates are compared. Overall, while a reduction in prebreakdown flow rates is observed because of rain, the flow drop between prebreakdown and postbreakdown is not much different between rain (3.9% to 12.0%) and no rain (7.8% to 12.7%) conditions.
A Constrained, Information Needs Based Sensor Fusion Resource Management Design Methodology

The role of the resource manager is to analyze the fusion process and refine the information stream in order to achieve a set of mission level goals. For moving platforms such as aircraft where the primary goal is often to maximize situation awareness, it is not obvious how to specify the measure of effectiveness relating to the kinematic and identification state of each object in the environment. A novel method is to approach the problem from the perspective of the fusion consumer. For situation awareness, the mission goals can be defined in terms of pilot decision points which can be decomposed further into the time at which a decision must be made and what information is necessary to make that decision. These information boundaries and associated information needs define a dimensional space that can be used to assess effectiveness. A benefit from this perspective is that the mission goals can be directly related to the sensor capabilities and ultimately used to define the closed loop fusion performance. The construct of information boundaries with threshold information needs leads to the definition of a constrained objective function for efficient sensor resource management. The objective function is constrained in the sense that it incorporates the concept of sufficiency where, once the desired state is achieved, there is no benefit in additional accuracy. This methodology maximizes the number of objects in the environment that achieve the desired information state.
Investigation on the Effect of Dynamic Fracture Toughness to Zirconia Ceramic Grinding Performance with Different Grain Sizes

To reveal the material removal mechanism of zirconia ceramics, an improved prediction models of the critical grinding force and maximum subsurface damage depth models are developed based on the dynamic fracture toughness. The effects of three different grain sizes on the material removal mechanism during brittle- ductile transition process of zirconia ceramics is analyzed through grinding experiments. And the influence of grain size on grinding force, workpiece surface roughness, surface fragmentation rate and subsurface damage depth in grinding are discussed. The results of the experiment results indicated that the value of dynamic fracture toughness tends to decrease with an increase in equivalent grinding thickness, and the ductile removal range of zirconia ceramics expands for the reason that the critical grinding force considering dynamic fracture toughness is higher than the static grinding force considering static fracture toughness, and the maximum subsurface damage depth is closer to actual maximum subsurface damage depth. Besides the smaller the grain size of zirconia ceramics, the higher the surface quality of grinding.
Logistic Model for Rating Urban Bicycle Route Safety

In response to renewed appreciation of the benefits of bicycling to the environment and public health, public officials across the nation are working to establish bicycle routes. During the past two decades a number of methods have been endorsed for the selection of "suitable" bicycle routes. These methods are limited in that they do not explicitly address bicycle safety nor do they reflect urban conditions. The purpose of this research is to develop an objective bicycle route safety rating model based on injury severity. The model development was conducted with a logistic transformation of bicycle crash data from Jersey City, New Jersey, for the period 1997 to 2000. The resulting model meets a 90% confidence level by using various operational and physical factors (traffic volume, lane width, population density, highway classification, and presence of vertical grades, one-way streets, and truck routes) to predict the severity of an injury that would result from a motor vehicle crash that occurred at a specific location. The modeled rating of the bicycle route's relative safety is defined as the expected value of the predicted injury severity. This rating is founded on the premise that safe routes produce less-severe crashes than do unsafe routes. The contribution of this research goes beyond the model's predictive capacity in comparing the safety of alternative routes by providing planners with an understanding, derived from objective data, of the factors that add to the route's safety, factors that reduce safety, and factors that are irrelevant.