nils-herrmann/clean_scirepeval huggingface dataset:
Sensor fusion and deep neural networks for autonomous UAV navigation within orchards
Venue: 2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)
Year: 2020

With the increase of population in the world, the demand for quality food is increasing too. In recent years, increasing demand and environmental factors have heavily influenced the agricultural production. Automation and robotics for fruit and vegetable production/monitoring have become the new standard. This paper discusses an autonomous Unmanned Aerial Vehicle (UAV) able to navigate through rows orchard rows. The UAV is comprised of a flight controller (AP stack) a microcontroller for analog reading of different sensors, and an On Board Computer (OBC) Pictures are taken through a camera and streamed through WiFi to a Ground Control Computer (GCC) running a convolution neural network model. Based on prior training, the model outputs three directions: RIGHT, LEFT and STRAIGHT. A moving average of multiple frames per second is extracted and sent to a build in Proportional IntegralDerivative (PID) controller on the UAV. After error correction from this feedback, controller sends the direction to the flight controller using MAVLink protocol's radio channel overrides, thus performing autonomous navigation.
Enviable roles of manufacturing processes in sustainable fourth industrial revolution A case study of mechatronics
Year: 2021

Industrial productivity in terms of manufacturing processes has witnessed dramatic increments through advances in technology, right with the ascendance of steam power as the driving force in the manufacturing industry heralding the first in Britain in the early 1800s to the introduction of mass production made possible through electrification of factories to replace all other sources of energy previously used and the use of the assembly line in the early 1900s to the automation of manufacturing processes in the 1970s by introducing electronics and information technology. Currently, we are in a time when new digital technology (the Internet of things and cyber physical systems) is on the rise and this is going to be the next revolution in industrial processes commonly called the fourth industrial revolution. This research thereby reviews the enviable roles of manufacturing processes in a sustainable fourth industrial revolution having a deep overview in mechatronics applications.
Scalable reader writer locks
Venue: SPAA '09
Year: 2009

We present three new reader writer lock algorithms that scale under high read only contention. Many previous reader writer locks suffer significant degradation when many readers attempt to acquire the lock concurrently, even though they are all allowed to hold the lock at the same time. In contrast, our locks scale almost perfectly when there is only read contention on a 4 chip system with a total of 256 hardware threads. Two of the algorithms extend the MCS queue mutex to provide reader writer synchronization with low overhead, and can be used when busy waiting synchronization is appropriate. The third algorithm is an improvement on a production quality reader writer lock used in the SolarisTM kernel, which provides robust priority and flexible fairness guarantees. A key tool we developed to implement our reader writer locks is the closable scalable nonzero indicator (C SNZI) a variation on the SNZI object. C SNZI objects allow us to significantly reduce the contention among reads when many readers try to acquire the lock concurrently, but keeps the acquisition overhead small in the absence of read contention. We present an algorithm for C SNZI that achieves this goal, and show how it can be used by each of our lock algorithms to provide scalable reader writer locks with different fairness guarantees.
Rock burst criterion based on clay mineral content
Venue: Arabian Journal of Geosciences
Year: 2020

This study aims to establish a criterion for rock burst based on clay mineral content (CMC) A classification system for rock burst intensity is proposed based on the results of 124 laboratory tests. A CMC based criterion for the probability and intensity of a rock burst is subsequently developed through a statistical analysis of the experimental results. Rock burst in laboratory tests can be classified as not occurring, weak, moderate, or strong according to sound, associated phenomena, fragment shape, and failure modes. When the CMC 10% the probability of a rock burst is high, and the rock burst intensity is from moderate to strong. If 10% CMC 30% the probability becomes moderate and the dominant intensity is from weak to moderate. If CMC 30% the probability of a rock burst is low. This rock burst criterion is used to evaluate the probability of rock burst at the Yaoqiao and Kongzhuang coal mines, China to demonstrate the feasibility of this criterion.
Precise and realistic grasping and manipulation in Virtual Reality without force feedback
Venue: 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)
Year: 2020

This paper introduces a physically based approach of grasping and manipulation regarding virtual objects that would enable fine and stable grasping without haptic force feedback. The main contribution is to enhance an existing method which couples a virtual kinematic hand with a visual hand tracking system. The mismatches between the tracked and virtual hands often yield unstable grasps, especially for small objects. This is overcome by the implementation of grasping assistance based on virtual springs between the tracked and virtual hands. The assistance is triggered based on an analysis of usual grasping criteria, to determine whether a grasp is feasible or not. The proposed method has been validated in a supervised experiment which showed that our assistance improves speed and accuracy for a "pick and place" task involving an exhaustive object set, sized for precision grasp. Moreover, users' feedback shows a clear preference for the present approach in terms of naturalness and efficiency.
Senyawa Bioaktif Daun Kumis Kucing (Orthosiphon stamineus)
Venue: Jurnal Kimia Riset
Year: 2019

AbstrakDaun kumis kucing (Orthosiphon stamineus) umumnya digunakan sebagai tanaman obat keluarga, hal ini diduga karena senyawa bioaktif yang terkandung didalamnya. Tujuan penelitian ini untuk mengetahui senyawa bioaktif ekstrak n heksana daun kumis kucing (Orthosiphon stamineus) menggunakan GCMS. Hasil senyawa bioaktif yang teridentifikasi ekstrak n heksana daun kumis kucing mengandung 1,1 Dicyclopentylethane; Bicyclo[3.2.0]hept 2,6 diene 1,2,3,4,4,5,6 d(7) n Butyl palmitate; 1 oxo03.alpa. (4 methyl 3 pentenyl) 6.alpa. methyl 6a.alpa. carbomethoxy 1,3,3a.alpa.,6a tetrahydrocyclopenta[c]furan; 1,1,3,3,5,5,7,7,9,9,11,11,13,13 tetradecamethylheptasiloxane; 1,4 bis(trimethylsilyl) benzene dan Silicone grease, Siliconfett. Senyawa senyawa bioaktif ekstrak n heksana daun kumis kucing tersebut kemudian dianalisis aktivitas biologi dan farmakologisnya.  Orthosiphon stamineus, senyawa bioaktif, GCMS AbstractThe leaves of cat whiskers (Orthosiphon stamineus) are generally used as family medicinal plants, this is thought to be due to the bioactive compounds contained therein. The purpose of this study was to find out the bioactive compounds of n hexane extract of cat whiskers (Orthosiphon stamineus) using GCMS. The results of bioactive compounds identified with n hexane extract of cat whiskers containing 1,1 Dicyclopentylethane; Bicyclo[3.2.0]hept 2,6 diene 1,2,3,4,4,5,6 d(7) n Butyl palmitate; 1 oxo03.alpa. (4 methyl 3 pentenyl) 6.alpa. methyl 6a.alpa. carbomethoxy 1,3,3a.alpa.,6a tetrahydrocyclopenta[c]furan; 1,1,3,3,5,5,7,7,9,9,11,11,13,13 tetradecamethylheptasiloxane; 1,4 bis(trimethylsilyl) benzene and Silicone grease, Siliconfett. The bioactive compounds of the n hexane extract of the cat's whiskers leaves were then analyzed for their biological and pharmacological activities.  Orthosiphon stamineus, bioactive compound, GCMS
Rock ring detection accuracy improvement in infrared satellite image with sub pixel edge detection
Venue: IET Image Process.
Year: 2019

The projection of space circle can be used for relative pose measurement of satellite targets. The accuracy of elliptical parameters plays an important role in the accuracy of pose recovery. However, the quality of space visible and infrared image is poor. The traditional ellipse detection method is mainly based on the edge of pixel accuracy wise and the ellipse accuracy is low, resulting in pose measurement errors. In this study, a sub pixel accuracy wise edge based ellipse fitting method is proposed to improve the ellipse accuracy. To realise this goal, we improved the arc based ellipse detection method and designed sub pixel edge based ellipse detection method. Experimental results show that the ellipse accuracy fitted by sub pixel edge coordinates is at least 50% higher than that by pixel edge coordinates, especially when the ellipse is incomplete. The author's method is the first one to propose and verify the sub pixel edge coordinate which contributes to enhancing ellipse accuracy.
A new WSN deployment algorithm for water pollution monitoring in Amazon rainforest rivers
Venue: 2013 IEEE Global Communications Conference (GLOBECOM)
Year: 2013

In this paper, we study the wireless sensor network deployment for water pollution monitoring in the Amazon rainforest rivers. Our objective consists in minimising the number of deployed geographical field installations along the river, while ensuring the detection of the substance spilled in the given river regardless of the position of its source. A geographical field installation is formed by a set of barrier coverage underwater sensors which detect the pollutant if its molarity in the water is greater than a predefined threshold. Indeed, the substance molarity is inversely proportional to the moving distance. To generate the best topology, we propose a sub optimal novel geographic Installation Field Deployment Algorithm based on the Backtracking heuristic named BT FIDA. Since the river has a several forks, in order to reduce the number of installation fields, BT FIDA minimises the rate of at least 2 covered river segments. The simulation results obtained show that our proposal minimises the number of field installations (i.e. deployment cost) while minimising the rate of areas which are miss covered and over covered.
Research on reactive compensation and grid connected photovoltaic control strategy of a nRYHO type energy storage Quasi z source inverter
Venue: 2019 Chinese Automation Congress (CAC)
Year: 2019

A combined control strategy of photovoltaic grid connection, reactive power compensation and energy storage was proposed for a novel energy storage quasi z source inverter. According to the different state of the battery, the system applies different control schemes. Based on the control strategy of the battery under normal conditions, this paper analyzes and discusses the unit power facto grid connected while ensuring the maximum utilization of photovoltaic cell energy efficiency and enhancing the stability of grid connected power, and compensates the load with reactive power. Finally, simulation and experiment verify the effectiveness and correctness of the proposed strategy.
Role of big data and social media analytics for business to business sustainability: A participatory web context
Year: 2020

The digital transformation is an accumulation of various digital advancements, such as the transformation of the web phenomenon. The participatory web that allows for active user engagement and gather intelligence has been widely recognised as a value add tool by organisations of all shapes and sizes to improve business productivity and efficiency. However, its ability to facilitate sustainable business to business (B2B) activities has lacked focus in the business and management literature to date. This qualitative research is exploratory in nature and fills this gap through findings arising from interviews of managers and by developing taxonomies that highlight the capability of participatory web over passive web to enable different firms to engage in business operations. For this purpose, two important interrelated functions of business i.e. operations and marketing have been mapped against three dimensions of sustainability. Consequently, this research demonstrates the ability of big data and social media analytics within a participatory web environment to enable B2B organisations to become profitable and remain sustainable through strategic operations and marketing related business activities. The research findings will be useful for both academics and managers who are interested in understanding and further developing the business use of participatory web tools to achieve business sustainability. Hence, this may be considered as a distinct way of attaining sustainability.
Simple Graph Convolutional Networks
Venue: ArXiv
Year: 2021

Many neural networks for graphs are based on the graph convolution operator, proposed more than a decade ago. Since then, many alternative definitions have been proposed, that tend to add complexity (and non linearity) to the model. In this paper, we follow the opposite direction by proposing simple graph convolution operators, that can be implemented in single layer graph convolutional networks. We show that our convolution operators are more theoretically grounded than many proposals in literature, and exhibit state of the art predictive performance on the considered benchmark datasets.
Extrusion and Extruded Products: Changes in Quality Attributes as Affected by Extrusion Process Parameters: A Review
Venue: Critical reviews in food science and nutrition
Year: 2016

Extrusion of foods is an emerging technology for the food industries to process and market a large number of products of varying size, shape, texture, and taste. Extrusion cooking technology has led to production of wide variety of products like pasta, breakfast cereals, bread crumbs, biscuits, crackers, croutons, baby foods, snack foods, confectionery items, chewing gum, texturized vegetable protein (TVP) modified starch, pet foods, dried soups, dry beverage mixes etc. The functional properties of extruded foods plays an important role for their acceptability which include water absorption, water solubility, oil absorption indexes, expansion index, bulk density and viscosity of the dough. The aim of this review is to give the detailed outlines about the potential of extrusion technology in development of different types of products and the role of extrusion operating conditions and their effect on product development resulting in quality changes i.e physical, chemical, and nutritional, experienced during the extrusion process.
Mimicking martingales
Year: 2015

Given the univariate marginals of a real valued, continuous time martingale, (respectively, a family of measures parameterised by t [0, T which is increasing in convex order, or a double continuum of call prices) we construct a family of pure jump martingales which mimic that martingale (respectively, are consistent with the family of measures, or call prices) As an example, we construct a fake Brownian motion. Then, under a further 'dispersion' assumption, we construct the martingale which (within the family of martingales which are consistent with a given set of measures) has the smallest expected total variation. We also give a path wise inequality, which in the mathematical finance context yields a modelindependent sub hedge for an exotic security with payoff equal to the total variation along a realisation of the price process. 1 The problem In this article we are concerned with the following problem: given a martingale M (Mt)0<=t<=T on a stochastic basis (O ,FM ,F ,P construct a fake version of M (or equivalently a process which mimics M) i.e. construct (potentially on a new filtered probability space (O,F ,F,P) a stochastic process X (Xt)0<=t<=T such that X is a F martingale and the univariate marginals of X are the same as those of M but such that the joint marginals are different. The problem can be reformulated in two further ways. First, instead of beginning with a martingale M we can begin with a family of laws (mt)0<=t<=T which are increasing in convex order. Then the aim is to construct a filtered probability space (O,F ,F,P) and a F martingale X (Xt)0<=t<=T on that space such that P(Xt x) mt( x] for all t and all x. Then we say that X is consistent with the measures (mt)0<=t<=T Second, but closely related, instead of beginning with a process or a set of measures we can work in the setting of mathematical finance and start with a double continuum of European call prices {C(t, k) 0 t T, 0 k which satisfy no arbitrage conditions. (We assume that we are working with discounted prices, and then the no arbitrage conditions are that: for each t, C(t, k) is a decreasing convex function with C'(t, 0+ 1 and limk| C(t, k) 0; C(t, 0) is a positive constant, independent of t; and C(t, k) is non decreasing in t, for all k. Then the aim is to find a model which is consistent with the given
Self Imitation Learning for Robot Tasks with Sparse and Delayed Rewards
Venue: 2021 IEEE International Conference on Mechatronics and Automation (ICMA)
Year: 2021

The application of reinforcement learning (RL) in robotic control is still limited in the environments with sparse and delayed rewards. In this paper, we propose a practical self imitation learning method named Self Imitation Learning with Constant Reward (SILCR) Instead of requiring hand defined immediate rewards from environments, our method assigns the immediate rewards at each timestep with constant values according to their final episodic rewards. In this way, even if the dense rewards from environments are unavailable, every action taken by the agents would be guided properly. We demonstrate the effectiveness of our method in some challenging continuous robotics control tasks in MuJoCo simulation and the results show that our method significantly outperforms the alternative methods in tasks with sparse and delayed rewards. Even compared with alternatives with dense rewards available, our method achieves competitive performance. The ablation experiments also show the stability and reproducibility of our method.
Dated language phylogenies shed light on the ancestry of Sino Tibetan
Venue: Proceedings of the National Academy of Sciences
Year: 2019

Given its size and geographical extension, Sino Tibetan is of the highest importance for understanding the prehistory of East Asia, and of neighboring language families. Based on a dataset of 50 Sino Tibetan languages, we infer phylogenies that date the origin of the language family to around 7200 B.P. linking the origin of the language family with the late Cishan and the early Yangshao cultures. The Sino Tibetan language family is one of the world's largest and most prominent families, spoken by nearly 1.4 billion people. Despite the importance of the Sino Tibetan languages, their prehistory remains controversial, with ongoing debate about when and where they originated. To shed light on this debate we develop a database of comparative linguistic data, and apply the linguistic comparative method to identify sound correspondences and establish cognates. We then use phylogenetic methods to infer the relationships among these languages and estimate the age of their origin and homeland. Our findings point to Sino Tibetan originating with north Chinese millet farmers around 7200 B.P. and suggest a link to the late Cishan and the early Yangshao cultures.
Revisiting the Performance of PCA Versus FDA Versus Simple Projection for Image Recognition
Year: 2019

By the advancement of technology, people are using internet for interchanging millions of photos every day from one to another part of the world, where data reductions are used to send file long distance with in minimum period of time. In the medical science physicians are detecting body organs, tumor cells and complex physical phenomena by optical fibers and where image processing is quite useful. One of another important sector of image processing is meteorology where it processes satellite sending images to do daily weather forecasting or finding climate change. There are many other sectors such as military surveillances, underwater search, satellite navigation etc. Suppose there are millions of images in the database of NSA, but they do not have clear image of the suspect (or suspects) Their main aim is to find the image (or multiple images) of particular scene and identify object of interest in the image (or images) In this study, we will set a very well known paradigm of analysis using PCA, FDA and simple projection to recognize people from their facial images. We will consider that we have some images of known people that can be used to compare and recognize new images (of the same set of face images) Moreover we will show graphical and tabular representation for average performance of correct recognition as well as analyze the effectiveness of three projections.  SVD, orthogonal matrix, orthogonal linear transformation, orthogonal projection, PCA, FDA Methodology As images are very high dimensional, it is not easy to analyze them directly. Some common approaches are to reduce their diminution using principal component analysis (PCA) Fisher's discriminant analysis (FDA) and other similar methods. Both PCA and LDA are linear transformation methods. PCA yields the directions (principal components) that maximize the variance of the data, whereas LDA also aims to find the directions that maximize the separation
Recidivism Patterns Among Two Types of Juvenile Homicide Offenders: A 30 Year Follow Up Study
Venue: International journal of offender therapy and comparative criminology
Year: 2018

Although juvenile homicide has been a matter of concern in the United States since the 1980s, prior research has not addressed long term recidivism patterns for convicted juvenile murderers. Furthermore, a prominent juvenile homicide typology had not previously been tested with U.S. offenders. The present study examined whether juvenile offenders who killed or attempted to kill during the commission of a crime differed from those who killed due to some type of conflict on pre incarceration, incarceration, and post incarceration variables. These offenders were sentenced to adult prison in the early 1980s. Follow up data spanned 30 years. The results indicated that approximately 88% of released offenders have been rearrested. Analyses of pre incarceration variables revealed that crime oriented offenders were significantly more likely to commit the homicide offense using accomplices than conflict oriented offenders, and the latter were significantly more likely to use a firearm during the homicide incident. The circumstances of the homicide, however, were not significantly related to any other pre incarceration variables, release from prison, number of post release arrests, and number of post release violent offenses. The implications of the findings, their comparability to previous follow up research on this typology, and avenues for future research are discussed.
$L$ functions for families of generalized Kloosterman sums and $p$ adic differential equations
Year: 2020

In this paper, we focus on a family of generalized Kloosterman sums over the torus. With a few changes to Haessig and Sperber's construction, we derive some relative $p$ adic cohomologies corresponding to the $L$ functions. We present explicit forms of bases of top dimensional cohomology spaces, so to obtain a concrete method to compute lower bounds of Newton polygons of the $L$ functions. Using the theory of GKZ system, we derive the Dwork's deformation equation for our family. Furthermore, with the help of Dwork's dual theory and deformation theory, the strong Frobenius structure of this equation is established. Our work adds some new evidences for Dwork's conjecture.