nils-herrmann/clean_scirepeval huggingface dataset:
A Study on the Election of Suitable Leader Vehicle in Vehicle Platooning Using the Raft Algorithm
Venue: 2019 Eleventh International Conference on Ubiquitous and Future Networks (ICUFN)
Year: 2019

Existing vehicle platooning creates platooning of vehicles with the same destination, and the leader vehicle manages the platooning. Since there is no way to elect a leader vehicle for platooning management, and the leader vehicle has not changed since its initial election, it is difficult to cope with the traffic situation in real time. To complement this, it is proposed that the Raft algorithm is applied to automatically elect the appropriate leader vehicle. To verify this, the proposed platooning was analyzed by comparing them according to the platooning scenarios to confirm that flexible platooning is possible.
Binary neural network based real time emotion detection on an edge computing device to detect passenger anomaly
Venue: 2021 34th International Conference on VLSI Design and 2021 20th International Conference on Embedded Systems (VLSID)
Year: 2021

Passenger safety in public transportation especially while riding in the form of shared cabs, and taxis are often ignored, and not much preventive protocols are devised. In the connected mobility world, emotion recognition from facial expressions is a possibility, however a faster processing and edge computing device to derive anomaly state inferences will be apt for further notifying about the safety of the passenger. FPGA implementation is a viable approach to not only implement in the embedded system automotive electronics, but also accelerate the inference results, hence making it as an ideal real time candidate for passenger anomaly state identification. For the same, a real time emotion detection system using facial features was implemented on FPGA. A Binary Neural Network (BNN) feeded by Local Binary Pattern (LBP) output was designed towards the development of an improved and faster emotion recognition system. LBP is configured as a preprocessing step to extract facial features that is passed on to the BNN layer for successful inference. The preprocessing method utilizes Viola Jones (VJ) algorithm to extract facial data while removing other background information from the image. The LBP BNN network is modelled using Facial Expression 2013 (FER 2013) data set for training. The custom hardware accelerator or the overlay is synthesized and the designed IP is implemented on FPGA for the inference. Inference is done using the trained model on FPGA to enable faster classified results. Emotion detection using facial expressions is classified to six states namely: angry, disgust, fear, happy, sad, and surprise. The LBP BNN network is implemented in FPGA, to realize a real time facial emotion recognition by capturing the image of a person from a web camera interfaced to the FPGA acting as edge computing inference device, with acceptable accuracy. The image processing based emotion detection design is highly suitable for other applications including tracking of emotions for movement disorder patients in hospitals.
A hybrid switch based soft switching inverter for ultrahigh efficiency traction motor drives
Venue: 2012 IEEE Energy Conversion Congress and Exposition (ECCE)
Year: 2012

This paper presents a hybrid switch that parallels a power MOSFET and an IGBT as the main switch of a zero voltage switching inverter. The combination features the MOSFET conducting in the low current region and the IGBT conducting in the high current region, and the soft switching avoids the reverse recovery problem during the device turn on. A custom hybrid switch module has been developed for a variable timing controlled coupled magnetic type ZVS inverter with a nominal input voltage of 325 V and the continuous output power of 30 kW for a traction motor drive. Experimental results of the hybrid switch based inverter with the total loss projected by temperature indicate that the inverter achieves 99% efficiency at the nominal condition and demonstrate ultrahigh efficiency operation over a wide load range. At 375 V input, the maximum measured efficiency through temperature projection and loss separation analysis is 99.3%
The Sonic Hedgehog signaling pathway regulates inferior alveolar nerve regeneration
Venue: Neuroscience Letters
Year: 2018

Activation of Shh signaling is known to be observed following injury of the peripheral nerves such as the sciatic nerve. However, the precise role of Shh signaling during peripheral nerve regeneration is not fully understood. The inferior alveolar nerve (IAN) is most commonly injured during oral surgery. Unlike the sciatic nerve, the IAN is isolated from other craniofacial tissues, as it resides in a long bony canal within the mandible. The IAN is thus an excellent experimental model for investigating peripheral nerve regeneration. In this study, the role of Shh signaling in peripheral nerve regeneration was investigated using the mouse IAN transection model. During regeneration, Shh signaling was activated within the entire distal region of the IAN and proximal stumps. Inhibition of Shh signaling by cyclopamine application at the transection site led to abnormal axon growth in random directions, a reduced number of macrophages, and an increase in myelin debris within the distal region. Shh signaling is thus involved in peripheral nerve regeneration via the regulation of myelin degradation.
Clustering large attributed information networks: an efficient incremental computing approach
Venue: Data Mining and Knowledge Discovery
Year: 2012

In recent years, many information networks have become available for analysis, including social networks, road networks, sensor networks, biological networks, etc. Graph clustering has shown its effectiveness in analyzing and visualizing large networks. The goal of graph clustering is to partition vertices in a large graph into clusters based on various criteria such as vertex connectivity or neighborhood similarity. Many existing graph clustering methods mainly focus on the topological structures, but largely ignore the vertex properties which are often heterogeneous. Recently, a new graph clustering algorithm, SA cluster, has been proposed which combines structural and attribute similarities through a unified distance measure. SA Cluster performs matrix multiplication to calculate the random walk distances between graph vertices. As part of the clustering refinement, the graph edge weights are iteratively adjusted to balance the relative importance between structural and attribute similarities. As a consequence, matrix multiplication is repeated in each iteration of the clustering process to recalculate the random walk distances which are affected by the edge weight update. In order to improve the efficiency and scalability of SA cluster, in this paper, we propose an efficient algorithm In Cluster to incrementally update the random walk distances given the edge weight increments. Complexity analysis is provided to estimate how much runtime cost Inc Cluster can save. We further design parallel matrix computation techniques on a multicore architecture. Experimental results demonstrate that Inc Cluster achieves significant speedup over SA Cluster on large graphs, while achieving exactly the same clustering quality in terms of intra cluster structural cohesiveness and attribute value homogeneity.
Optimisation of a prestressed fibre reinforced polymer shell for composite bridge deck
Year: 2019

This paper proposes a prestressed fibre reinforced polymer (FRP) shell for composite bridge deck with FRP and concrete. Geometric parameters including cross section shape, arch radius and number of arches were first optimised by the finite element (FE) method. A self balancing prestressed basalt FRP (BFRP) shell system was proposed to resist the deformation under construction load and to enhance the integrated mechanical behaviour. The mechanical behaviour of the proposed FRP shell were examined under a simulated construction load. The stresses and deformations of the FRP shell were analysed during both prestress tensioning and construction loading. A static test was further conducted on the BFRP shell concrete composited bridge deck to verify prestressing effect. The results show a corrugated cross section with two arches on its lower flange further enhances the stiffness of FRP shell for a composite bridge deck. The prestressed FRP shell offsets the deformation under construction by the camber and exhibits more linear structural behaviour when compared to the non prestressed BFRP shell. The stress monitored during loading indicates a superior integrated behaviour of the FRP shell and prestressing FRP laminates. Furthermore, the load displacement relationship of prestressed composite bridge deck demonstrates a high loading capacity and small deflection at serviceability limit state.
Identifying the bone breaker at the Navalmaillo Rock Shelter (Pinilla del Valle, Madrid) using machine learning algorithms
Year: 2020

In recent years, reports on bone breakage at archaeological sites have become more common in the taphonomic literature. The present work tests a recently published method, based on the use of machine learning algorithms for analysing the processes involved in bone breakage, to identify the agent that broke the bones of medium sized animals at the Mousterian Navalmaillo Rock Shelter (Pinilla del Valle, Madrid) This is the first time this method has been used in an archaeological setting. The results show that these bones were mostly broken by anthropic action, while some were slightly ravaged by carnivores, probably hyaenas. These findings agree very well with published interpretations of the site, and show the method used to be useful in taphonomic studies of archaeological materials with poorly preserved cortical surfaces.
Combined photoelectrocatalytic microbial fuel cell (PEC MFC) degradation of refractory organic pollutants and in situ electricity utilization.
Venue: Chemosphere
Year: 2019

A new photoelectrocatalytic (PEC) and microbial fuel cell (MFC) process was developed and applied to simultaneously remove refractory organic pollutants (i.e. phenol and aniline) from wastewater while recovering energy for in situ utilization. The current generated by the MFC process was applied to drive the PEC reaction. Compared with single PEC or MFC processes, the PEC MFC combined process showed higher pollutant and chemical oxygen demand (COD) removal capacities and electricity production. Over 95% of the phenol or aniline was removed by these process, even at high initial concentrations. The COD removal efficiencies for phenol and aniline were ca. 96% (from 700 to 29 mg L 1) and 70% (from 165 to 49 mg L 1) respectively. Although the PEC process showed a limited contribution to phenol and aniline removals (16.5% and 43% respectively) the utilization of PEC treated phenol or aniline streams resulted in a MFC with higher voltage output, higher coulombic efficiency, maximal volumetric power density, and lower internal resistance as compared to untreated water. High performance liquid chromatography coupled with mass spectrometry measurements revealed quinones/hydroquinones and low molecular weight organic acids to be produced as intermediates after the PEC process, which could improve the production of electricity in the MFC.
Identifying functionally similar code in complex codebases
Venue: 2016 IEEE 24th International Conference on Program Comprehension (ICPC)
Year: 2016

Identifying similar code in software systems can assist many software engineering tasks such as program understanding and software refactoring. While most approaches focus on identifying code that looks alike, some techniques aim at detecting code that functions alike. Detecting these functional clones code that functions alike in object oriented languages remains an open question because of the difficulty in exposing and comparing programs' functionality effectively. We propose a novel technique, In Vivo Clone Detection, that detects functional clones in arbitrary programs by identifying and mining their inputs and outputs. The key insight is to use existing workloads to execute programs and then measure functional similarities between programs based on their inputs and outputs, which mitigates the problems in object oriented languages reported by prior work. We implement such technique in our system, HitoshiIO, which is open source and freely available. Our experimental results show that HitoshiIO detects more than 800 functional clones across a corpus of 118 projects. In a random sample of the detected clones, HitoshiIO achieves 68+ true positive rate with only 15% false positive rate.
Urban Storm Water Modeling and Analysis Based on SWMM LID Modules
Year: 2018

The urban green garden department and its surrounding areas in Jinniu District, Chengdu city were selected as the study area. The SWMM (Storm Water Management Model) was used to simulate the discharge hydrographs at the outlets of the drainage system when the study area encountered design storm with different return periods under current situation and LID (Low Impact Development) applied situation. The results were then analyzed to estimate the reduction effects of sponge city with LID measures on urban storm flood. The results show that LID measures can effectively reduce urban storm flood, and the reduction effects are more obvious when the return period of design storm is smaller, which will provide reference for the application of LID measures in the urban storm floodcontrol.
Optimised approach based on hybrid MAC protocol for M2M networks
Venue: IET Networks
Year: 2018

In machine to machine (M2M) networks, the ability to access the radio channel requires a rigid design of a medium access control (MAC) protocol. Here, an optimised hybrid MAC protocol will be proposed which is composed of two main processes, the contending process and the transmission process. During contention process, the devices randomly contend the transmission opportunities with equal probabilities by using the conventional based slotted ALOHA (S ALOHA) mechanism. Only successful devices can assign a transmission slot during the transmission process by using the reservation based time division multiple access mechanism. Additionally, an optimisation problem will be formulated to obtain the maximum aggregated throughput. Moreover, the optimum relation between the contention and transmission periods under different number of devices is calculated. The optimisation problem is solved with the aid of mathematical analysis which is carried out through Monte Carlo simulation. Furthermore, extensive MATLAB programs are executed to study the system performance in terms of: the system throughput, the average packet delay, the success access ratio, and the reservation ratio. The simulation results show that the proposed hybrid technique outperforms other related hybrid when compared.
Current and Recent Advanced Strategies for Combating Biofilms
Year: 2015

Biofilms are matrix enclosed microbial aggregates that adhere to a biological or nonbiological surface. Biofilm formation is a significant problem in the medical, food, and marine industries and can lead to substantial economic and health problems. The complex microbial community of a biofilm is highly resistant to antibiotics and sanitizers and confers persistent survival that is a challenge to overcome. There are several conventional approaches to combating biofilms, physical and/or mechanical removal, chemical removal, and the use of antimicrobials, sanitizers, or disinfectants to kill biofilm organisms. However, biofilms are highly resistant to these approaches as opposed to planktonic cells. Thus, novel approaches other than the conventional methods are urgently needed. In this review, we discuss current and new advanced antibiofilm strategies that are superior to the conventional method in terms of addressing the biofilm problem for the improvement of healthcare, food safety, and in industrial processes.
Tapping a vital resource: increasing the yield of family care conferences.
Venue: Critical care medicine
Year: 2014

450 www.ccmjournal.org February 2014 Volume 42 Number 2 3. Mercat A, Richard J, Vielle B, et al: Positive end expiratory pressure setting in adults with acute lung injury and acute respiratory distress syndrome: A randomized controlled trial. JAMA 2008; 299:646 655 4. Meade MO, Cook DJ, Guyatt GH, et al: Ventilation strategy using low tidal volumes, recruitment maneuvers, and high positive end expiratory pressure for acute lung injury and acute respiratory distress syndrome: A randomized controlled trial. JAMA 2008;  A, et al: Higher vs lower positive end expiratory pressure in patients with acute lung injury and acute respiratory distress syndrome: Systematic review and meta analysis.  Positive end expiratory pressure in adult respiratory failure.  1982; 307:1381 1384 7. Suter PM, Suter PM, Fairley HB, et al: Optimum end expiratory airway pressure in patients with acute pulmonary failure.   New goals for positive end expiratory pressure in acute respiratory distress syndrome: A paradigm shift or the end of an area of uncertainty? Am J Respir Crit Care Med 2010;  9. Gattinoni L, Caironi P, Cressoni M, et al: Lung recruitment in patients with the acute respiratory distress syndrome.  2006; 354:1775 1786 10. Villar J, Perez Mendez L, Lopez J, et al: An early PEEP/FIO2 trial identifies different degrees of lung injury in patients with acute respiratory distress syndrome. Am J Respir Crit Care Med 2007; 176:795 804 11. Chiumello D, Cressoni M, Carlesso E, et al: Bedside Selection of Positive End Expiratory Pressure in Mild, Moderate, and Severe Acute Respiratory Distress Syndrome. Crit Care Med 2014;  Mechanical ventilation learning objectives for residents in the ICU: Results of an expert panel consensus process. Am J Resp Crit Care Med 2011;  Pressure time curve predicts minimally injurious ventilatory strategy in an isolated rat lung model. Anesthesiology 2000;  1328 14. Talmor D, Sarge T, Malhotra A, et al: Mechanical ventilation guided by esophageal pressure in acute lung injury.  2008; 359:2095 2104 15. ARDS Definition Task Force, Ranieri VM, Rubenfeld GD, Thompson BT, et al: Acute respiratory distress syndrome: The Berlin definition. JAMA 2012; 307:2526 2533 16. Tsuchida S, Engelberts D, Peltekova V, et al: Atelectasis causes alveolar injury in nonatelectatic lung regions. Am J Respir Crit Care Med 2006;  Effects of recruiting maneuvers in patients with acute respiratory distress syndrome ventilated with protective ventilatory strategy. Anesthesiology 2002; 96:795 802 18.  Best compliance during a decremental, but not incremental, positive end expiratory pressure trial is related to open lung positive end expiratory pressure: A mathematical model of acute respiratory distress syndrome lungs. Am J Respir Crit Care Med 2001; 163:69 78 19. Costa ELV, Borges JB, Melo A, et al: Bedside estimation of recruitable alveolar collapse and hyperdistension by electrical impedance tomography. Intensive Care Med 2009; 35:1132 1137
TrafficPredict: Trajectory Prediction for Heterogeneous Traffic Agents
Venue: AAAI
Year: 2019

To safely and efficiently navigate in complex urban traffic, autonomous vehicles must make responsible predictions in relation to surrounding traffic agents (vehicles, bicycles, pedestrians, etc. A challenging and critical task is to explore the movement patterns of different traffic agents and predict their future trajectories accurately to help the autonomous vehicle make reasonable navigation decision. To solve this problem, we propose a long short term memory based (LSTM based) realtime traffic prediction algorithm, TrafficPredict. Our approach uses an instance layer to learn instances' movements and interactions and has a category layer to learn the similarities of instances belonging to the same type to refine the prediction. In order to evaluate its performance, we collected trajectory datasets in a large city consisting of varying conditions and traffic densities. The dataset includes many challenging scenarios where vehicles, bicycles, and pedestrians move among one another. We evaluate the performance of TrafficPredict on our new dataset and highlight its higher accuracy for trajectory prediction by comparing with prior prediction methods.
A new fuzzy sliding mode controller design for delta operator time delay nonlinear systems
Venue: Int. J. Syst. Sci.
Year: 2019

This paper investigates the sliding mode control (SMC) problem for a class of delta operator uncertain time delay nonlinear systems through Takagi Sugeno fuzzy models. Some new sufficient conditions for asymptotic stability analysis of the sliding motion are obtained in terms of linear matrix inequalities with some convexification techniques. Then two new dynamic SMC design methods are synthesised to force the resulting closed loop system states onto the sliding surface in finite time. Two simulation examples are finally given to illustrate the effectiveness of the proposed approaches.
Visual Question Answer System Based on Bidirectional Recurrent Networks
Year: 2018

Visual Question Answer (VQA) system is the task of automatically answering natural language questions based on the content of reference image. A commonly approach for VQA is to extract image feature and question feature by convolution neural network (CNN) and long short term memory network (LSTM) respectively, and then combine them to infer the answer through attention mechanism such as the stacked attention networks (SAN) However, the CNN ignores the information between adjacent image regions and the LSTM just memorizes the past contextual information of the question. In this paper, we propose a model based on two bidirectional recurrent networks (BiSRU and BiLSTM) to improve the accuracy of feature extraction. The BiSRU is used to allow the adjacent local region vectors of the image to maintain information each other. The BiLSTM is used to encode the question feature, which obtains past and future contextual information meanwhile when the question is very complex. The feature of image and question obtained by bidirectional recurrent networks is used to predict the answer precisely. Experiment result shows that our model get better performance on four datasets.
Design LED innovation: Shifting from smart follower to digital strategy leader in the Australian airport sector
Venue: 2013 IEEE Tsinghua International Design Management Symposium
Year: 2013

This paper presents and discusses organisational barriers and opportunities arising from the dissemination of design led innovation within a leading Australian airport corporation. This research is part of a greater action research program which aims to integrate design as a strategic capability through design led innovation within Australian businesses. Findings reveal that there is an opportunity to employ the theoretical framework and tools of design led innovation in practice to build collaborative idea generation by involving customers and stakeholders within the proposal of new to world propositions. The iterative gathering of deep customer insights also provided an opportunity to leverage a greater understanding of stakeholders and customers in strengthening continuing business partnerships through co design. Challenges to the design led approach include resistance to the exploratory nature of gathering deep customer insights, the testing of long held assumptions and market data, and the disruption of an organisational mindset geared toward risk aversion instilled within the aviation industry. The implication from these findings is that design led innovation can provide the critical platform to allow for a business to grow and sustain internal design capabilities necessary to challenge prevailing assumptions about how its business model operates to deliver value to customers and stakeholders alike. The platform of design led innovation also provides an avenue to support a cultural transformation towards anticipating future needs necessary for establishing a position of leadership within the broader economic environment.