Miracle-dz/UniFAR-FTUs huggingface dataset:
The lattice of nil-Hecke algebras over real and complex reflection groups

Associated to every complex reﬂection group, we construct a lattice of quotients of its braid monoid-algebra, which we term nil-Hecke algebras, and which are obtained by killing all braid words that are “suﬃciently long”, as well as some integer power of each generator. These include usual nil-Coxeter algebras, nil-Temperley–Lieb algebras, and their variants, and lead to symmetric semigroup module categories which necessarily cannot be monoidal.Motivated by classical work of Coxeter (1957) and the Brou´e–Malle–Rouquier freeness conjecture [ J. reine Angew. Math. 1998], and continuing beyond work of the second author [ Trans. Amer. Math. Soc. 2018], we obtain a complete classiﬁcation of the ﬁnite-dimensional nil-Hecke algebras for all complex reﬂection groups W . These comprise the usual nil-Coxeter algebras for W of ﬁnite type, their “fully commutative” analogues for W of FC-ﬁnite type, three exceptional algebras (of types F 4 , H 3 , H 4 ), and three exceptional series (of types B n and A n , two of them novel). In particular, we ﬁnd the ﬁrst – and only two – ﬁnite-dimensional nil-Hecke algebras over discrete complex reﬂection groups; this breaks from the nil-Coxeter case (where no braid words are further killed, and) where Marin [ J. Pure Appl. Alg. 2014] and Khare [ Trans. Amer. Math. Soc. 2018] showed that such algebras do not exist. In addition to these algebras, and also algebraic connections (to PBW deformations and non-monoidal tensor categories), we further uncover combinatorial bases of algebras, both known (fully commutative elements) and novel (12-avoiding signed permutations). Our classiﬁcation draws from and brings together results of Popov [ Comm. Math. Inst. 1982], Stembridge [ J. Alg. Combin. 1996, 1998], Malle Transform. Groups 1996], Postnikov via Gowravaram–Khovanova (2015), [ J. Group Th. and Khare
A Multi-View Framework to Detect Redundant Activity Labels for More Representative Event Logs in Process Mining

Process mining aims to gain knowledge of business processes via the discovery of process models from event logs generated by information systems. The insights revealed from process mining heavily rely on the quality of the event logs. Activities extracted from different data sources or the free-text nature within the same system may lead to inconsistent labels. Such inconsistency would then lead to redundancy in activity labels, which refer to labels that have different syntax but share the same behaviours. Redundant activity labels can introduce unnecessary complexities to the event logs. The identification of these labels from data-driven process discovery are difficult and rely heavily on human intervention. Neither existing process discovery algorithms nor event data preprocessing techniques can solve such redundancy efficiently. In this paper, we propose a multi-view approach to automatically detect redundant activity labels by using not only context-aware features such as control–flow relations and attribute values but also semantic features from the event logs. Our evaluation of several publicly available datasets and a real-life case study demonstrate that our approach can efficiently detect redundant activity labels even with low-occurrence frequencies. The proposed approach can add value to the preprocessing step to generate more representative event logs.
Laminar and Transitional Flow disturbances in Diseased and Stented Arteries

Cardiovascular diseases (CVD) are the number one causes of death in the world. According to the world Health Organization (WHO) 17.5 million people died from cardiovascular disease in 2005, representing 30 % of all global deaths . Of these deaths, 7.6 million were due to heart attacks and 5.7 million due to stroke. If current trends are allowed to continue, by 2015 an estimated 20 million people will die annually from cardiovascular disease. The trends are similar in the United States where on an average 1 person dies every 37 seconds due to CVD. In 2008 an estimated 770,000 Americans will experience a new heart attack (coronary stenosis) and 600,000 will experience a first stroke. Although the exact causes of cardiovascular disease are not well understood, hemodynamics has been long thought to play a primary role in the progression of cardiovascular disease and stroke. There is strong evidence linking the fluid mechanical forces to the transduction mechanisms that trigger biochemical response leading to atherosclerosis or plaque formation. It is hypothesized that the emergence of abnormal fluid mechanical stresses which dictate the cell mechanotransduction mechanisms and lead to disease progression is dependent on the geometry and compliance of arteries, and pulsatility of blood flow. Understanding of such hemodynamic regulation in relation to atherosclerosis is of significant clinical importance in the prediction and progression of heart disease as well as design of prosthetic devices such as stents. The current work will systematically study the effects of compliance and complex geometry and the resulting fluid mechanical forces. The objective of this work is to understand the relationship of fluid mechanics and disease conditions using both experimental and computational methods where (a) Compliance effects are studied in idealized stenosed coronary and peripheral arteries using Digital Particle Image Velocimetry (DPIV), (b) Complex geometric effects of stented arteries with emphasis on its design parameters is investigated using CFD, Also (c) a novel method to improve the accuracy of velocity gradient estimation in the presence of noisy flow fields such as in DPIV where noise is inherently present is introduced with the objective to improve accuracy in the estimation of WSS, which are of paramount hemodynamic importance. The broad impact of the current work extends to the understanding of fundamental physics associated with arterial disease progression which can lead to better design of prosthetic devices, and also to better disease diagnostics.
Modelling operation parameters of UAV on spray effects at different growth stages of corns

Abstract: Currently, unmanned aerial vehicles (UAVs) were widely applied to spray for pest and disease control. However, spray effect can be further improved by setting operation parameters more reasonably and scientifically. Therefore, this study attempts to derive the relationship between operation parameters and spray effect. Different growth stages were distinguished by various corn heights. A six-rotor UAV was operated at different heights and velocities to test pesticides spray effects for corns at different growth stages. Different plant canopy coverage rate and penetrating coefficients were obtained, according to which, the effects on droplet deposition rate caused by different UAVs’ operation parameters were analyzed. Droplet penetrating coefficients were applied as indexes to evaluate and select UAVs operation parameters for corns at different growth stages respectively. Mathematical models of droplet penetrating coefficients with UAVs operation parameters were established for corns at all growth stages. The determination coefficients (R2) of all models were greater than 0.90 and average relative errors were within 20%, which asserted high forecasting accuracy of droplet penetrating rate. With the help of the models, parameters like operating height away from the bottom of corns and UAVs velocities were further analyzed, which guided the optimization of parameter settings and selection of spray methods for corns at different growth stages. Keywords: multi-rotor unmanned aerial vehicle, spraying, parameter model, growth stage, corn DOI: 10.3965/j.ijabe. 20171003.2578 Citation: Zheng Y J, Yang S H, Zhao C J, Chen L P, Lan Y B, Tan Y. Modelling operation parameters of UAV on spray effects at different growth stages of corns. Int J Agric & Biol Eng, 2017; 10(3): 57–66.
Teamwork Exercises and Technological Problem Solving with First-Year Engineering Students: An Experimental Study

An experiment was conducted investigating the utility of teamwork exercises and problem structure for promoting technological problem solving in a student team context. The teamwork exercises were designed for participants to experience a high level of psychomotor coordination and cooperation with their teammates. The problem structure treatment was designed based on small group research findings on brainstorming, information processing, and problem formulation. First-year college engineering students (N = 294) were randomly assigned to three levels of team size (2, 3, or 4 members) and two treatment conditions: teamwork exercises and problem structure (N = 99 teams). In addition, the study included three nonmanipulated, independent variables: team gender, team temperament, and team teamwork orientation. Teams were measured on technological problem solving through two conceptually related technological tasks or engineering design activities: a computer bridge task and a truss model task. The computer bridge score and the number of computer bridge design iterations, both within subjects factors (time), were recorded in pairs over four 30-minute intervals. For the last two intervals with the computer bridge, teams started construction of the truss model task, which created low and high task load conditions for the computer bridge: another within subjects factor. A repeated measures ANOVA was used to analyze time (computer bridge) by factor interactions. No significant time by teamwork exercises or time by problem structure interactions on computer bridge scores were found [F(2.31, 198.46) = 0.10, p = . 928; F(2.31, 198.46) = 0.03, p = . 984]. There was a significant interaction between the factors of time and team size [F(4.62, 198.46) = 2.75, p = . 023]. An ANOVA was conducted with the between subject factors on the truss model task. A significant main effect was found for teamwork exercises [F(1, 86) = 2.84, p = . 048, one-tailed], but not for problem structure or team size. Post hoc analyses were conducted for team size on computer bridge and iteration scores over time, as well as teamwork exercises effects for each team size. Findings and their implications were reported, along with suggestions for future research on technological problem solving in a team context. iv Teamwork and Technological Problem Solving
Come as You Are: Examining Autistic Identity Development and the Neurodiversity Movement through an Intersectional Lens

Singer intended for neurodiversity to be a new category of intersectionality. However, intersectionality has been neglected in autism research and practice. This paper aims to inform an intersectional approach to autism by exploring autistic identity development in relation to other marginalized identities. We reviewed literature about neurodiversity, intersectionality, discrimination, and the identity development of autistic people, racial/ethnic minorities, and gender and sexual minorities. We discuss minority stress and evidence that cultural traditions alleviate it. Autistic culture can reframe personal difficulties as a politicized struggle. While the stereotype of autism is one of withdrawal, the history of autistic people coming together for justice defies this notion. Intersectionality teaches us that we must understand differences within the autistic community if we wish to help all autistic people experience the dignity they deserve. Using an intersectional lens, we can become more flexible in our understanding of positive autistic identity development and strategies to promote it.
A Comparison of Dynamical Perceptual-Motor Primitives and Deep Reinforcement Learning for Human-Artificial Agent Training Systems

Effective team performance often requires that individuals engage in team training exercises. However, organizing team-training scenarios presents economic and logistical challenges and can be prone to trainer bias and fatigue. Accordingly, a growing body of research is investigating the effectiveness of employing artificial agents (AAs) as synthetic teammates in team training simulations, and, relatedly, how to best develop AAs capable of robust, human-like behavioral interaction. Motivated by these challenges, the current study examined whether task dynamical models of expert human herding behavior could be embedded in the control architecture of AAs to train novice actors to perform a complex multiagent herding task. Training outcomes were compared to human-expert trainers, novice baseline performance, and AAs developed using deep reinforcement learning (DRL). Participants’ subjective preferences for the AAs developed using DRL or dynamical models of human performance were also investigated. The results revealed that AAs controlled by dynamical models of human expert performance could train novice actors at levels equivalent to expert human trainers and were also preferred over AAs developed using DRL. The implications for the development of AAs for robust human-AA interaction and training are discussed, including the potential benefits of employing hybrid Dynamical-DRL techniques for AA development.
Optimal Design of Process Parameters During Laser Direct Metal Deposition of Multi-Material Parts

ii DEDICATION . iv ACKNOWLEDGEMENTS . v LIST OF TABLES . x LIST OF FIGURES . xi CHAPTER ONE INTRODUCTION . 1 1.1 MOTIVATION AND BACKGROUND . 1 1.2 METAL BASED MANUFACTURING OF HETEROGENEOUS MATERIALS . 3 1.3 DMD PROCESS. 5 1.4 RESEARCH OBJECTIVES . 9 CHAPTER TWO CURRENT RESEARCH STATE AND LITERATURE REVIEW 13 2.1 PROCESS MODELING OVERVIEW . 13 2.1.1 Powder Flow . 13 2.1.2 Laser Powder Interaction . 20 2.1.3 Laser Heating of Substrate . 23 2.1.4 Free Surface Evolution . 26 2.2 DESIGN OF INJECTION NOZZLE . 32 2.3 FGM PARTS FABRICATION BY DMD . 37 2.3. 1 Deposition Materials . 37 2.3. 2 Challenges in Quality of Parts . 39 2.3. 3 Modeling the DMD of Multi-Material . 41 2.4 SCOPE OF THE PRESENT STUDY . 43
Pengaruh Kompetensi Terhadap Kinerja Pegawai Di Badan Perpustakaan, Arsip dan Dokumentasi Kota Denpasar

ABSTRACT Competence of employees is very important in the organization. These competencies will create a superior employee performance and effective in carrying out the work. Technological change rapid w ill lead human resources to understand technological development , so the employee needed is competence of employee sufficient and able to use the technology. The problem underlying this study is the average employees only graduated of senior high school (SMA) graduated which is its haven’t achieve the minimal standard level of archieve proffesion and not all employee can operate the information technology such as computers. The method that was used is associative method quantitative approach which purpose seeking influence between competence (variable X) toward employee performance (Y). Primary data in this study were obtained through questionnaires as much as the number of samples is 72 Employees of Library institution, Archives and the documentation of Denpasar . Samples in this study using sampling techniques saturated. The results of the analysis of this study indicate that the variable competence affect positive and significant with the employee performance with regression equation Y = 19.188 + 0.377 X. The result R2 of 31.1%, and the remaining 68.9% is affected by other factors. From test of significance test obtained t (5.622) is bigger than t table (1.666) and showing competencies affect significant positive on employee performance in Badan Perpustakaan, Arsip dan Dokumentasi Kota Denpasar Keywords: Competence, Employees Performance, Library, Archives and The Documentation of Denpasar
Wake transitions and steady $z$-instability of an Ahmed body in varying flow conditions

Abstract The paper investigates experimentally the flow past a flat-back, taller than wide Ahmed body having rectangular base aspect ratio $H/W=1.11$ in the context of ground vehicle aerodynamics. Parametric studies at Reynolds number $2.1\times 10^5$ explore the sensitivity of the aerodynamic force and body pressure distribution with respect to varying flow conditions defined from variable ground clearance $C$ (taken at mid-distance from the front and rear axles of the body), pitch angle $\alpha$, and yaw angle $\beta$ (equivalent to a crosswind). Two-dimensional parametric maps in the parametric spaces $(\beta,C)$ and $(\beta,\alpha )$ are obtained for parameter ranges covering real road vehicle driving conditions. The study of the base pressure gradient reveals non-trivial and sharp transitions identified as significant changes of near wake orientation in both parametric spaces. All unsteady transitions correspond to fluctuation crises of the vertical gradient component only. These transitions are summarized in phase diagram representations. Both phase diagrams in $(\beta,C)$ and $(\beta,\alpha )$ parametric spaces can be unified at large yaw in the $(\beta,C_r)$ space, where the rear clearance $C_r$ separating the lower edge of the base from the ground is a simple function of the pitch $\alpha$ and the clearance $C$. The impacts of the wake transitions are clearly identified in the base drag, drag, lift and side force coefficients. The contribution of the steady near wake $z$-instability (Grandemange et al., Phys. Fluids, vol. 25, 2013a, pp. 95–103) is assessed by repeating the sensitivity analysis with a rear cavity. As reported previously, the rear cavity suppresses the steady instability by symmetrizing the wake. A domain for the existence of the instability is finally proposed in the attitudes map $(\beta,\alpha )$ defined from regions where the mean lateral force coefficients are significantly decreased by the presence of the rear cavity. In addition, it is found that the steady instability forces the wake to be less unsteady for all attitudes that do not correspond to unsteady transitions.
Multiphase large-eddy simulations of human cough jet development and expiratory droplet dispersion

Abstract Violent respiratory events play critical roles in the transmission of respiratory diseases, such as coughing and sneezing, between infectious and susceptible individuals. In this work, large-scale multiphase flow large-eddy simulations have been performed to simulate the coughing jet from a human's mouth carrying pathogenic or virus-laden droplets by using a weakly compressible smoothed particle hydrodynamics method. We explicitly model the cough jet ejected from a human mouth in the form of a mixture of two-phase fluids based on the cough velocity profile of the exhalation flow obtained from experimental data and the statistics of the droplets’ sizes. The coupling and interaction between the two expiratory phases and ambient surrounding air are examined based on the interaction between the gas particles and droplet particles. First, the results reveal that the turbulence of the cough jet determines the dispersion of the virus-laden droplets, i.e. whether they fly up evolving into aerosols or fall down to the ground. Second, the droplet particles have significant effects on the evolution of the cough jet turbulence; for example, they increase the complexity and butterfly effect introduced by the turbulence disturbance. Our results show that the prediction of the spreading distance of droplet particles often goes beyond the social distancing rules recommended by the World Health Organization, which reminds us of the risks of exposure if we do not take any protecting protocol.
Delegated Replies: Alleviating Network Clogging in Heterogeneous Architectures

Heterogeneous architectures with latency-sensitive CPU cores and bandwidth-intensive accelerators are attractive as they deliver high performance at favorable cost. These architectures typically have significantly more compute cores than memory nodes. The many bandwidth-intensive accelerators hence overwhelm the few memory nodes, resulting in suboptimal accelerator performance — as their bandwidth needs are not met — and poor CPU performance — because memory node blocking creates high latencies. We call this phenomenon network clogging. Since network clogging is a widespread issue in heterogeneous architectures, we first investigate if existing state-of-the-art approaches can address it. We find that the most effective prior approach, called Realistic Probing (RP), is suboptimal because it searches the local caches of other cores for missing data.We propose Delegated Replies which lets memory nodes speculatively delegate the responsibility of replying to last-level cache hits to the private cache that last accessed the requested cache block, hence avoiding the search that fundamentally limits RP. Moreover, Delegated Replies uses the (typically) under-utilized request network for delegation; it is the reply network links of the memory nodes that commonly clog because replies include complete cache blocks in addition to metadata. We evaluate Delegated Replies in the context of heterogeneous architectures with latency-sensitive CPU cores and bandwidth-intensive GPU cores and find that it improves GPU (CPU) performance by 14.2% (5.2%) and 25.7% (8.8%) on average compared to RP and our baseline, respectively.
Opportunities for Pumped Hydro Energy Storage in Australia

Pumped hydroelectricity energy storage (PHES) is by far the most significant form of large-­‐scale energy storage in use around the world today with approximately 130 GW of generation capacity installed. PHES facility construction is resurging globally as evolving electricity supply systems place greater value on stored energy. Australia has approximately 1.5 GW of PHES capacity; however, no large-­‐scale facilities have been installed in the last 30 years. This paper examines opportunities for the construction of additional large-­‐scale PHES facilities in Australia.
Propeller Cavitation Breakdown Analysis

A Reynolds-Averaged Navier-Stokes computational model of homogeneous multiphase flow is presented. Cavitation driven thrust and torque breakdown over a wide range of advance ratios is modeled for an open propeller. Computational results are presented as a form of validation against water tunnel measured thrust and torque breakdown for the propeller. Successful validation of the computational model is achieved. Additional observations are made with regards to cavity size and shape as well as cavitation breakdown behavior. © 2003 ASME
Galvatron: Monitoring and Controlling of Generator Systems Through Androids

The electric power generators prove to be handy when, it comes to power shortages. They are reliable but expect somebody to keep up them an opportunity to time. Electric power generators require continuous conservation to give a high performance. The manual monitoring and maintenance of the generators is a complex task. In the era of automation, the facility of generators can also be automated to minimize the human involvement and increase the life of the power generators. In this paper, we have introduced a system that is created to keep track of generators without requiring someone to manually monitor them on a regular basis. The concept is to design an app that uses the popular Android operating system to remotely monitor energy generators. The proposed system automatically monitors devices, update status and provide alarms. Simple banners are transmitted by the sensors, which offer reliable data on the generator's status. The model portrays the advancement of Generator parameter checking framework. The checking parameters of generator like fuel level, oil level, temperature, flow, voltage controls are educated to the approved faculty through by means of Internet of Things (IoT) application. Consequently, the Arduino smaller scale controller generates the results in its propelled condition and then converts the yield into a following banner. The banner is subsequently communicated to the Android phone via a switch, changes and updates these data. As a result, the generator's state may be monitored in real time.