Miracle-dz/UniFAR-FTUs huggingface dataset:
Flexible Intentions in the Posterior 1 Parietal Cortex : An Active Inference 2 Theory

We present a normative computational theory of how neural circuitry in the Dorsal 8 Visual Stream (DVS) and the Posterior Parietal Cortex (PPC) support visually guided goal-directed 9 actions in a dynamical environment through flexible goal-encoding intentions. It builds on Active 10 Inference, in which perception and motor control signals are inferred through dynamic 11 minimization of generalized prediction error. The PPC is proposed to maintain expectations, or 12 beliefs over environment and body state, and by manipulating them it is involved along with 13 visual, frontal, and motor areas in dynamically generating goal-directed actions. Specifically, the 14 PPC is viewed as a dynamic system computing flexible motor intentions and directing belief over 15 the latent body state towards the dynamic future goals, while the DVS and proprioceptive 16 pathways implement generative models translating belief into sensory-level predictions in order 17 to infer targets, posture, and motor commands. A proof-of-concept agent embodying an actuated 18 upper limb, visual and proprioceptive sensors and controlled by Active Inference extended with 19 flexible intentions was tested on target reaching tasks. The agent behaved correctly under 20 various conditions, including static and dynamic targets, different sensory feedbacks, sensory 21 precisions, intention gains, and movement policies; limit conditions were individuated, too. Active 22 Inference driven by flexible intentions can thus support goal-directed behavior in dynamically 23 changing environments and the PPC can host its core intention mechanism. More broadly, the 24 study provides normative basis for research on goal-directed behavior in end-to-end settings and 25 further advances Artificial Intelligence methods for sensorimotor control. 26
wenda_gpu: fast domain adaptation for genomic data

Motivation Domain adaptation allows for development of predictive models even in cases with limited sample data. Weighted elastic net domain adaptation specifically leverages features of genomic data to maximize transferability but the method is too computationally demanding to apply to many genome-sized datasets. Results We developed wenda_gpu, which uses GPyTorch to train models on genomic data within hours on a single GPU-enabled machine. We show that wenda_gpu returns comparable results to the original wenda implementation, and that it can be used for improved prediction of cancer mutation status on small sample sizes than regular elastic net. Availability wenda_gpu is available on GitHub at https://github.com/greenelab/wenda_gpu/. Contact casey.s. greene@cuanschutz.edu Supplementary information Supplementary data are available at Bioinformatics online.
Deterministic, near-linear 𝜀-approximation algorithm for geometric bipartite matching

Given two point sets A and B in ℝd of size n each, for some constant dimension d≥ 1, and a parameter ε>0, we present a deterministic algorithm that computes, in n·(ε−1 logn)O(d) time, a perfect matching between A and B whose cost is within a (1+ε) factor of the optimal matching under any ℓp-norm. Although a Monte-Carlo algorithm with a similar running time is proposed by Raghvendra and Agarwal [J. ACM 2020], the best-known deterministic ε-approximation algorithm takes Ω(n3/2) time. Our algorithm constructs a (refinement of a) tree cover of ℝd, and we develop several new tools to apply a tree-cover based approach to compute an ε-approximate perfect matching.
Enhancing Writing Quality in Engineering Capstone Project Documents

Quality of technical writing in capstone reports is an important attribute to express and communicate the ideas, methodology and results of the technical content of a project. Technical writing expertise for engineering students in general, and for international (non-English) in particular, need improvements in this area. Capstone instructors end up spending significant amount of time in helping student teams in correcting the project documentation for style, grammar, organization and format. This research introduces the concept of bringing in a Technical Writing Assistant (TWA) in to the class room for capstone projects to work with student teams. TWAs conducted sessions with student teams (Onsite and Online) to help with the writing quality of capstone documentations. TWA staff were in addition to the course instructor. This research team used university’s writing center expertise to staff TWAs, and they helped in developing a set of metrics/rubrics to evaluate the capstone documents for their technical writing quality. In order to assess the impact of TWAs, this paper analyses and compares capstone project reports done with and without TWAs using the metrics/rubrics. The findings of this evaluation and analysis can lay the foundation for changes, recommendations, and deployment of TWAs in engineering curriculums.
Simple Power Transformer Fiber Bragg Grating Temperature Sensor

This study has designed, developed, and tested a high temperature sensor based on Fiber Bragg grating. The new introduced interrogation system makes the sensor suitable for installation inside the power transformer. Unlike the existing fiber Bragg grating based temperature sensors, the interrogation system of the sensor is based on amplitude modulation (AM). The distinctive characteristics of the designed temperature sensor, in addition to inherent advantages of FBG is, its real-time monitoring, small size, and low cost. The sensor is tested in harsh environment at temperature starting from -27 oC to 400 oC. The long-term stability and reliability of the designed sensors of one sensor head is tested in furnace at 400 oC for 338 hours. Furthermore, the sensor head was under test in 600 oC for about 18 hours. The sensor head which is used in this experiment is fiber Bragg grating Corning SMF-28, Ge-doped optical fibers with 4% Ge content in its core. It was loaded with hydrogen prior to writing with 248 nm excimer laser. The Bragg wavelength of the two prepared sensors head for this work is around 1530 nm and 1550 nm. In this study, we used Amplified spontaneous emission (ASE) light source as an input light for the sensor head. ASE light source makes it possible to have linear input light in two different ranges with 4 nm span. The sensors head Bragg wavelength is designed in the range in which the ASE light source spectrum is linear. The sensor has the Photodiode (PD) to convert the Bragg reflected spectrum power into its equivalent current.
What’s happening in Australian mathematics professional learning?

The project, Towards Educating Mathematics Professionals Encompassing Science and Technology (TEMPEST), examines the extent and quality of professional learning (PL) opportunities for teachers of mathematics. Teaching of Science, Technology, Engineering and Mathematics (STEM) has become a focus of the Australian Government as these subjects are seen as essential to the future Australian economy. It is a professional requirement that teachers undergo PL. Many teachers of mathematics are not mathematics specialists and therefore it is essential that PL is of high quality. One aim of the TEMPEST project is to provide a quality framework to ensure the standard of any PL offered. Before developing this framework, 65 experts who deliver, design or facilitate mathematics PL for teachers were surveyed to determine the current state of mathematics PL in Australia. This paper summarises and analyses their responses. It describes current PL including year level focus, format (one-day workshop, weekly sessions for example) and type of teacher targeted. The paper reports gaps in PL currently offered throughout the country. Some gaps were identified by the expert respondents, while others emerged from analysis of the survey data. Gaps are reported in terms of target teacher audience, year level focus, location and PL format.
Spectral bounds of the ε-entropy of kernel classes

We develop new upper and lower bounds on the 𝜀 -entropy of a unit ball in a reproducing kernel Hilbert space induced by some Mercer kernel 𝐾 . Our bounds are based on the behaviour of eigenvalues of a corresponding integral operator. In our approach we exploit an ellipsoidal structure of a unit ball in RKHS and a previous work on covering numbers of an ellipsoid in the euclidean space obtained by Dumer, Pinsker and Prelov. We present a number of applications of our main bound, such as its tightness for a practically important case of the Gaussian kernel. Further, we develop a series of lower bounds on the 𝜀 -entropy that can be established from a connection between covering numbers of a ball in RKHS and a quantization of a Gaussian Random Field that corresponds to the kernel 𝐾 by the Kosambi-Karhunen-Loève transform.
Automatic source code summarization with graph attention networks

Source code summarization aims to generate concise descriptions for code snippets in a natural language, thereby facilitates program comprehension and software maintenance. In this paper, we propose a novel approach– GSCS –to automatically generate summaries for Java methods, which leverages both semantic and structural information of the code snippets. To this end, GSCS utilizes Graph Attention Networks to process the tokenized abstract syntax tree of the program, which employ a multi-head attention mechanism to learn node features in diverse representation sub-spaces, and aggregate features by assigning different weights to its neighbor nodes. GSCS further harnesses an additional RNN-based sequence model to obtain the semantic features and optimizes the structure by combining its output with a transformed embedding layer. We evaluate our approach on two widely-adopted Java datasets; the experiment results confirm that GSCS outperforms the state-of-the-art baselines.
High-speed visualization of thermal plasma characteristics

Thermal plasmas are expected to be utilized for a number of industrial applications, such as nanomaterial synthesis and waste treatment. The thermal plasma generation and its characteristics remain to be explored for more attractive processing. In particular, the electrode dynamics are one of the most considerable issues for the practical use of industrial applications, because it determines the electrode lifetime and the performance of materials in thermal plasmas. High-speed imaging provides a powerful tool to reveal the plasma dynamics. High-speed video camera with bandpass filter system was used to measure the electrode temperature as well as the arc fluctuation. Electrode temperature was evaluated from the radiation intensities at 785 nm and 880 nm from the electrode thermal emission. This system can be also applied to observe the dynamic behavior of vapor generation from the electrode on the millisecond time scale. Emissions from tungsten vapor were observed at the wavelength of 393 nm. The tungsten electrode started to evaporate just after the peak top of the arc current in the anodic period. The tungsten vapor became the main species in the anodic arc when the electrode started to evaporate. In contrast, a small amount of tungsten evaporation was observed during the cathodic period. These experimental studies enable us to understand the electrode erosion mechanism of the multiphase AC arc. Fundamental researches for electrode phenomena determining thermal plasma characteristics lead to the development of innovative industrial applications of material processing and waste treatment.
Rancang Bangun Shaking Water Bath Berbasis Mikrokontroler ATmega16

Shaking water bath berbasis mikrokontroler ATmega16 telah dirancang-bangun. Shaking water bath terdiri dari alat shaking dan water bath . Water bath digunakan untuk memanaskan sampel dalam air pada suatu temperatur konstan. Air dipanaskan oleh elemen pemanas dan temperaturnya diindera oleh sensor temperatur LM35. Temperatur air dipertahankan sesuai dengan rentang yang diinginkan. Elemen pemanas dikendalikan dalam modus on-off dengan menghidup-matikan relai. Alat shaking water bath menggunakan motor mesin cuci 220 V untuk menguncang-guncang ( shaking ). Laju motor diatur secara manual dengan sebuah potensiometer pada rangkaian pengendali. Nilai temperatur air dan lama waktu pemanasan yang diinginkan dimasukan melalui keypad dan ditampilkan pada LCD. Uji akhir alat memperlihatkan bahwa alat ini mampu mengendalikan temperatur air yang diinginkan dalam lebarrentang ( span ) optimal sebesar 10 C. Alat mampu beroperasi paling lama sekitar 30 menit sebelum motor mengalami kelebihan panas yang menyebabkan putarannya melambat. Kata kunci: shaking water bath , modus on-off , LM35, mikrokontroler
Surface reconstruction for thin aero engine blade from disorganized contact measured points

Blade surface reconstruction is one of the necessary steps in blade adaptive machining system. The majority of the current reconstruction methods are based on point-cloud, which is obtained using noncontact measurements. Correspondingly, these methods are invalid when the points are obtained using contact measurements. In this paper, we studied the method of surface reconstruction for thin features based on measured contact points. Owing to the random order of the measured points, and the fact that when the distance between two measured points is larger than the wall thickness of the blade will lead to interpolation errors, a quad tree-based region division method, and a points sorting algorithm, are proposed for correctly ordering the points. On this basis, inverse interpolation of cross-sectional curves using a cubic NURBS curve is used to fit them and reconstruct surfaces. Surface reconstruction examples are presented herein, and a comparison between the reconstructed and designed surfaces is used to verify the validity of our method.
ERICA: an energy resolving photon counting readout ASIC for X-ray in-line cameras

We present ERICA (Energy Resolving Inline X-ray Camera) a photon-counting readout ASIC, with 6 energy bins. The ASIC is composed of a matrix of 8 × 20 pixels controlled by a global digital controller and biased with 7 independent digital to analog converters (DACs) and a band-gap current reference. The pixel analog front-end includes a charge sensitive amplifier with 16 mV/ke− gain and dynamic range of 45 ke−. ERICA has programmable pulse width, an adjustable constant current feedback resistor, a linear test pulse generator, and six discriminators with 6-bit local threshold adjustment. The pixel digital back-end includes the digital controller, 8 counters of 8-bit depth, half-full buffer flag for any of the 8 counters, a 74-bit shadow/shift register, a 74-bit configuration latch, and charge sharing compensation processing to perform the energy classification and counting operations of every detected photon in 1 μ s. The pixel size is 330 μm × 330 μm and its average consumption is 150 μW. Implemented in TSMC 0.25 μm CMOS process, the ASIC pixel's equivalent noise charge (ENC) is 90 e− RMS connected to a 1 mm thickness matching CdTe detector biased at −300 V with a total leakage current of 20 nA.
Combined Forecasting Mode of Subgrade Settlement Based on Support Vector Machine and Real-coded quantum Evolutionary Algorithm

Due to the normal forecasting methods for subgrade settlement using observation data have different applicability and disadvantages, The Combined forecasting model is put forward based on support vector machine (SVM) and real-coded quantum evolutionary algorithm (RQEA) in this paper. Its core is that, according to the basic settlement law of subgrade and characteristics of settlement curve, the growth curve which has S-type characteristic are chosen as single forecasting model, then support vector machine is used to combine the predicting results of each single forecasting model, at the same time, RQEA is adopted to optimize support vector machine parameter to improve the SVM’s performance. The analytical result of engineering practice indicates that the proposed combined forecasting model of subgrade settlement base on SVM and RQEA can not only improve the predicting accuracy, but also reduce the predicting risk, and can meet engineering demand.
SILS: A Smart Indoors Localisation Scheme Based on on-the-go Cooperative Smartphones Networks Using Onboard Bluetooth, WiFi and GNSS

Seamless outdoors-indoors localization based on Smartphones sensors is essential to realize the full potential of Location Based Services. This paper proposes a Smart Indoors Localization Scheme (SILS) whereby participating Smartphones (SPs) in the same outdoors and indoors vicinity, form a Bluetooth network to locate the indoors SPs. To achieve this, SILS will perform 3 functions: (1) synchronize & locate all reachable WiFi Access Points (WAPs) with live GNSS time available on the outdoors SPs; 2) exchange a database of all SPs location and time-offsets; 3) calculate approximate location of indoor-SPs based on hybridization of GNSS, Bluetooth and WiFi measurements. These measurements includes a) Bluetooth to Bluetooth relative pseudo ranges of all participating SPs based on hop-synchronization and Master-Slave role switching to minimize the pseudo-ranges error, b) GNSS measured location of outdoors-SPs with good geometric reference points, and c) WAPs-SPs Trilateration estimates for deep indoors localization. Results, obtained from OPNET simulation and live trials of SILS built for various SPs network size and indoors/outdoors combinations scenarios, show that we can locate under 1 meter in near-indoors while accuracy of around 2-meters can be achieved when locating SPs at deep indoors situations. Better accuracy can be achieved when large numbers of SPs (up to 7) are available in the network/vicinity at any one time and when at least 4 of them have a good sky view outdoors.
Human-Robot Interactions for Single Robots and Multi-Robot Teams

Human-Robot Interaction (HRI) research has mainly concentrated on developing efficient ways for humans to control and supervise robot behavior. Recently, research has also focussed on developing social robots that can sense human communication cues for more natural interactions. This allows humans to interact with robots without prior training. For robots to successfully take part in bi-directional social interactions with people, they must be capable of recognizing and responding to human affect. Such robots would promote more effective and engaging interactions with users that would lead to better acceptance of these robots by their intended user. In addition, socially assistive robots can be used as an effective technology for the elderly to provide social interaction and cognitive assistance with activities of daily living. A combination of inputs from different modes could lead to better affect recognition. Only a handful of multimodal affect recognition systems have been used in HRI, and they have focussed primarily on modes of facial and vocal expressions. Body language plays an important role in conveying changes in human emotions during social interactions, and has yet to be incorporated into these affect recognition systems. In this thesis, a multimodal bi-directional affect architecture is proposed that determines user affect using a unique combination of user body language and vocal intonation. HRI experiments are conducted to investigate a robot’s ability to detect affect using the proposed architecture. In addition to one-on-one HRI, multi-robot teams can provide valuable assistance in Urban Search and Rescue (USAR) missions by exploring cluttered and dangerous environments, while searching for potential victims. One of the main challenges an operator may face in controlling a multi-robot team is the simultaneous control of multiple robots while juggling between tasks and keeping situational awareness of all robots. Past controllers have used automation to relieve workload and stress from the operator. However, they have been limited in their capabilities to avoid obstacles and identify victims automatically. This thesis also proposes a multi-robot collaboration architecture using a learning-based semiautonomous controller that provides the ability to effectively allocate sub-tasks to robots to complete the overall USAR mission. Experiments were conducted to investigate the influence of the operator-to-robot ratio on the performance of the architecture used to aid an operator in a multirobot team USAR.
IRIS AND FINGERPRINT BASED ENGINE CONTROL SYSTEM

This paper proposes an affordable vision-based system to precisely identify Eyes Off target (EOR). The unit has three primary components: 1) robust facial feature monitoring 2) mind pose and gaze estimation and three) 3-D geometric reasoning to know EOR. Inside the video stream inside you put onto the controls column, our physiques tracks facial expression inside the driver’s face. When using the supervised landmarks along with a 3-D face model, the unit computes mind pose and gaze direction. Distracted driving may be the primary reasons for vehicle collisions inside the u . s . states . States. Passively monitoring a driver’s activities comprises the muse inside the automobile safety system that may potentially reduce the amount of accidents by estimating the driver’s focus of attention. The mind pose estimation formula is robust to no rigid face deformations because of alterations in expressions. Finally, obtaining a 3-D geometric analysis, the unit reliably detects EOR. The suggested system doesn't need any driver-dependent calibration or manual initialization and works instantly (25 FPS), throughout the day and night. Our physiques accomplished above 90% EOR precision for people examined situations. To validate the performance within the system within the real vehicle atmosphere, we transported out an extensive experimental evaluation under all kinds illumination conditions, facial expressions, and people.
Precision of evaluation methods in white light interferometry. Correlogram correlation method

Abstract In this letter we suggest a method for the evaluation of a surface’s topography which we call the correlogram correlation method. Employing a theoretical analysis as well as numerical simulations the method is proven to be the most accurate among available evaluation algorithms in the common case of uncorrelated noise. We obtain variance estimations for conventional methods and compare them to simulations. Experimental examples illustrate the superiority of the correlogram correlation method over the common envelope and phase methods.
The Scope and Range of General Systems Transdisciplinarity

The pioneers of the general systems movement envisioned the development of a new scientific ‘meta-discipline’ grounded in a “General Systems Theory” (GST), a theory that encompasses universal principles underlying the systemic behaviours of all kinds of “real-world” systems. In contemporary terms we can identify this as a vision for a “transdiscipline” and we discuss its relationship to other conceptions of transdisciplinarity. In line with arguments presented elsewhere we identify this transdiscipline as “General Systemology”, and the application of it “General Systems Transdisciplinarity” (GSTD). The founders of the general systems movement argued that GSTD would be important for assisting the transfer knowledge between disciplines, facilitating interdisciplinary communication, supporting the development of exact models in areas where they are lacking, and promoting the “unity” of knowledge. In this paper we defend this view, and infer that the scope and range of GSTD is wider than hitherto recognized, and argue that GSTD would potentially be the most powerful of the transdisciplines.