nils-herrmann/clean_scirepeval huggingface dataset:
Simulating Reservoir Operation Using a Recurrent Neural Network Algorithm
Venue: Water
Year: 2019

The reservoir is an important hydraulic engineering measure for human utilization and management of water resources. Additionally, a reasonable and effective reservoir operating plan is essential for realizing reservoir function. To explore the application of a deep learning algorithm on the field of reservoir operations, a recurrent neural network (RNN) long short term memory (LSTM) and gated recurrent unit (GRU) are employed to predict outflows for the Xiluodu (XLD) reservoir. Meanwhile, this paper summarized the law of the effect of parameter setting on model performance compared to the simulation performance of three models, and analyzed the main factors that affect reservoir operation to provide the reference for future model of application research. Results show (1) the number of iterations and hidden nodes mainly influence the model precision, and the former has more effect than the latter, and the batch size mainly affects the calculated speed; (2) all three models can predict the reservoir outflow accurately and efficiently; (3) the operating decision generated by three models can implement the flood control and power generation goal of the reservoir and meet the operating regulation; and (4) under different hydrological periods, the influence factors of reservoir operation and their importance are different.
Brownian Motion and Stochastic Calculus
Year: 2008

1 Preliminaries of Measure Theory Denition 1 F P is said to be an algebra if (1) 2 F (2) A;B 2 F implies A S B 2 F (3) A 2 F implies AC 2 F F is said to be a semialgebra or semi ring is (1) 2 F (2) A;B 2 F implies AB 2 F (3) A;B 2 F implies AnB Pn k=1Ak for some Ak 2 F Denition 2 Class: If A;B 2 implies AB 2 Denition 3 Class: if (1) 2 (2) A;B 2 with A B implies A B 2 (3) An 2 An " A implies A 2 Denition 4 Let L R be such that 2 L implies 1 2 L. L class: (1)1 2 L (2) L is linearly closed (3) n 2 L; 0 n " bounded or 2 L implies 2 L Proposition 5 (i)M being Class Class impliesM is algebra (ii) If Class contains the Class then
Qualitative characterization of olive biomass resources and aptitude at valorization of energy in the delegation of Kalaa Kebira (TUNISIA)
Year: 2017

The production of olive oil generates liquid waste (Olive Mill Wastewater) and solid waste (Pomace exhausted) whose anarchic rejection can threaten the environment. Under these conditions, the search for the performance technology for the treatment of the organic fraction of these residues is becomes an urgent necessity. In this perspective, an investigation was conducted on qualitative characterization (physicochemical parameters and indicators of pollution) of olive residues in order to assess their suitability for energy recovery in the delegation of Kalaa Kebira (Sousse, Tunisia) The samples of Olive Mill Wastewater (OMW) (including acidic pH, EC too high, a ratio COD/BOD 5 indicating ease of biodegradation and strong wealth MOX) and exhausted pomace (particularly dry, rich in carbon and in crude fiber and poor in nitrogen) ensure that the implementation of anaerobic digestion process (or Biomethanation) of olive biomass is feasible. In this respect, the methanogenic potential may be considered variable between 253810 and 1045100 m 3 of biogas (Case of OMW) and valued at 129.4 10 6 MJ (Case of pomace) In addition, the pomace has properties ensuring energy recovery primarily by combustion (heat capacity estimated at 20593 MJ)
Depression, Anxiety and Quality of Life among Chronic Low Back leg Pain Patients with or without Neuropathic Pain
Year: 2016

To investigate depression, anxiety and quality of life among chronic low back leg pain patients with or without neuropathic pain. Place and Duration of Study: Ankara Numune Education and Research Hospital Department of Physical Medicine and Rehabilitation Polyclinic, between October 2012 and June 2013.  One hundred and one patients with chronic low back and leg pain were enrolled in the study. This study is a cross sectional study. The severity of low back and leg pain was evaluated by visual analogue scale (VAS) The DN4 (Douleur Neuropathique en 4 Questions) and LANSS (Leeds Assessment of Neuropathic Symptoms and Signs) scales were used in order to evaluate the neuropathic pain. Existence of depression was evaluated by the Hamilton Depression Rating Scale (HAM D) and anxiety was assessed by Hamilton Anxiety Rating Scale (HAM A) The quality of life was questioned by Short Form 36 (SF 36)  Neuropathic pain was detected in 65.3% by DN4 and 40.6% by LANSS among all patients. According to HAM D results, 22.7% of the patients had depression and according to HAM A results, 8.9% of the patients had anxiety. While frequency of depression was statistically Original Research Article Uzun et al. BJPR, 13(5) 1 8, 2016; Article no.BJPR.28762 2 significantly higher in patients with neuropathic pain according to LANSS (p<0,05) the frequency of anxiety was similar between groups. Although depression and anxiety was more common among patients with neuropathic pain according to DN4, there was no statistically significant difference between chronic low back leg pain patients with or without neuropathic pain. The median SF 36 mental score was significantly lower in patients with NP according to LANSS (p<0.05) Although the median SF 36 scores (mental, physical) were higher in patients with NP according to DN4, there was no significant difference between groups (respectively p>0.05, )  Patients with chronic low back and leg pain should also be questioned in terms of neuropathic symtoms and the conservative treatment should be arranged in this direction. Thus concomitant depression and anxiety would decrease, and the quality of life would increase.
Fall 2020 COVID 19 Needs Assessment among New Jersey Secondary School Educational Professionals
Venue: International journal of environmental research and public health
Year: 2021

Secondary or high school (HS) educational professionals expressed concerns about dealing with environmental and occupational health and safety protocols due to COVID 19. Concerns related to fall 2020 school re opening and getting back into in person teaching whether full time, part time or some other approved hybrid model plus ongoing uncertainty with how the state and federal government will be handling matters about mandates for virtual learning, rapid testing, vaccine distribution, etc. These concerns were related to both their experience as educational professionals and genuine interest in personal and student well being. This study was a cross sectional online survey in early fall from mid September early October 2020. Of a possible maximum participation of 740 New Jersey (NJ) supervisory level HS teachers and administrators (e.g. department chairs, district and school principals) 100 confirmed unique respondents (13.5% consented and completed the survey. Of 100 experienced (mean 18 years teaching) participants, 70% responded to the gender identity question (overall, 61% female, 39% male; by NJ region, gender ratios were similar) There were statistically significant differences (using Fischer's exact test) between NJ regions regarding provision of online counseling and support services for teachers (p 0.001) for resources and equipment for teachers to mediate online learning (p 0.02) for assistive video technology tools (p 0.03) and accessibility to structured online learning and professional development (p 0.002) concerning learning aids to engage students in online instruction, online counseling, and support services for students and their families (p 0.006) appropriate protocol is clean and disinfect areas used by a person with COVID 19 (p 0.002) and, immediately separate staff and students who screen positive for COVID 19 (p 0.03) There were few statistical differences by gender. This study reported what participants wanted regarding the development of future policies then implemented as reopening practices. Data can inform recommendations in NJ and elsewhere at federal, state, and local levels. Data provide new insights and valuable information to inform the consideration of acceptability of various policy measures among HS education professionals.
Small scale displacement measurement with passive harmonic RF tag using Doppler radar
Venue: 2013 IEEE International Wireless Symposium (IWS)
Year: 2013

Measurement accuracy of the displacement from human cardiopulmonary activities has potential in predicting physiological information for the purpose of biomedical remote sensing and non contact monitoring. In this paper, an RF frequency doubling tag was used for detecting small displacement with high accuracy. A heterodyne and a homodyne quadrature radar receiving systems were used to detect small scale tag motion and non tagged motion from a distance, respectively. Arctangent demodulation algorithm and imbalance compensation technique were applied to the raw radar data for displacement estimation. Simulation and experimental results were compared, indicating that by using the frequency doubling tag, a better accuracy can be achieved for small displacement estimation with Doppler radar.
Theoretical study on the light emitting mechanism of circularly polarized luminescence molecules with both thermally activated delayed fluorescence and aggregation induced emission.
Venue: Physical chemistry chemical physics PCCP
Year: 2019

Circularly polarized luminescence molecules with both thermally activated delayed fluorescence (TADF) and aggregation induced emission (AIE) have been reported recently and are thought as potential candidates for circular polarized organic light emitting diodes. Since the study of these kinds of systems is quite limited, it is of great importance to reveal the relationship between the geometry and the light emitting mechanism. In this paper, the TADF and AIE mechanisms were studied based on the study of a series of binaphthalene containing luminogenic enantiomers in both toluene and solid phases. It was found that there was no influence on the light emitting properties of enantiomers except for the electronic circular dichroism (ECD) The radiative rates for both molecules were enhanced in the solid phase, while the non radiative rates were significantly suppressed. Both factors can induce the AIE phenomenon. Based on the calculation of the decay rates and adiabatic excitation energy of the excited states, we found that the TADF mechanisms of the two molecules were different. One is realized by the up conversion process between S1 and T1, while a two step process is involved for the other. Our theoretical research successfully elucidates the experimental measurement and illustrates the AIE and TADF mechanism, which could provide valuable insights for the design of highly efficient CPL emitters.
Key considerations when developing a risk management framework for tailings facilities
Year: 2019

Risk management is a key component of any effective corporate tailings governance framework. Uncertainty is inherent to a mining company's business activities and may present both risk and opportunity. An integrated risk based approach assists management in identifying, evaluating, prioritising and managing key risks to the achievement of the mining company's strategic objectives, as well as opportunities to enhance performance and value. Corporate risk management frameworks are typically designed to manage risks at the enterprise or operational level with specific definitions for consequence and likelihood. Challenges can develop in accurately ranking tailings related risks when utilising an operational level corporate risk management framework. This paper highlights various corporate risk management approaches and discusses some key considerations when developing a tailings risk management framework and governance model.
Loda: Lightweight on line detector of anomalies
Venue: Machine Learning
Year: 2015

In supervised learning it has been shown that a collection of weak classifiers can result in a strong classifier with error rates similar to those of more sophisticated methods. In unsupervised learning, namely in anomaly detection such a paradigm has not yet been demonstrated despite the fact that many methods have been devised as counterparts to supervised binary classifiers. This work partially fills the gap by showing that an ensemble of very weak detectors can lead to a strong anomaly detector with a performance equal to or better than state of the art methods. The simplicity of the proposed ensemble system (to be called Loda) is particularly useful in domains where a large number of samples need to be processed in real time or in domains where the data stream is subject to concept drift and the detector needs to be updated on line. Besides being fast and accurate, Loda is also able to operate and update itself on data with missing variables. Loda is thus practical in domains with sensor outages. Moreover, Loda can identify features in which the scrutinized sample deviates from the majority. This capability is useful when the goal is to find out what has caused the anomaly. It should be noted that none of these favorable properties increase Loda's low time and space complexity. We compare Loda to several state of the art anomaly detectors in two settings: batch training and on line training on data streams. The results on 36 datasets from UCI repository illustrate the strengths of the proposed system, but also provide more insight into the more general questions regarding batch vs on line anomaly detection.
An efficient face recognition system based on hybrid optimized KELM
Venue: Multimedia Tools and Applications
Year: 2019

Face recognition (FR) from video offers a challenging issue in the area of image exploration along with computer visualization, furthermore, as such recognized heaps of deem over the previous years on account of its numerous applications in the scope of domains. The chief challenges in the video centered FR are the restraint of the camera hardware, the random poses captured by means of the camera as the subject is noncooperative, and changes in the resolutions owing to disparate lighting conditions, noise along with blurriness. Numerous FR algorithms were generated in the previous decennium, although these approaches are much better, the image's accuracy is less only. To trounce such difficulties, an efficient FR system centered on hybrid optimized Kernel ELM is proposed. The proposed work encompasses five phases, explicitly (i) preprocessing, (ii) Face detection, (iii) Feature Extraction, (iv) Feature Reduction, and (v) Classification. In the preliminary phase, the data base video clips are converted in to the frames in which pre processing are performed utilizing a Modified wiener filter to eliminate the noise. The succeeding phase is employed for detecting the pre processed image via the viola jones (V J) With this technique, the face is identified. After that, the features are extorted. The extracted ones then will be provided as the input to the Modified PCA approach. Then, perform classification operation using hybrid (PSO GA) optimized Kernel ELM approach. The similar process is replicated for query images (QI) At last, the recognized image is found. Experimental results contrasted with the previous ANFIS classifier and existing methods concerning precision, accuracy, recall, F measure, sensitivity along with specificity. The proposed FR system indicates better accuracy when compared with the prevailing methods.
Macroprudential Regulation and Policy
Year: 2011

The Bank for International Settlements (BIS) and the Bank of Korea (BoK) jointly organized a conference on macroprudential regulation and policy in Seoul, Korea, on 16 18 January 2011. The conference aimed to bring academics together with researchers at central banks and other public institutions to present and discuss ongoing theoretical and empirical work in the field. In response to their call for papers, the organizers received more than 75 submissions from central banks, public agencies, supranational organizations and academic institutions. From these, a selection committee from the BIS and the BoK chose 12 papers organized around the following four themes: systemic risk; financial system procyclicality; macroeconomic impact studies and early warning indicators; and (iv) effective implementation of macroprudential policy. In all, 35 participants took part, including central bank economists from Asia and the Pacific, Europe, Latin America and the United States, as well as academics from Europe, Korea and North America. Governor Choongsoo Kim of the BoK gave the welcome address, and Governor Stefan Ingves of Sveriges Riksbank and Professor Hyun Song Shin from Princeton University gave keynote speeches. The conference concluded with a policy panel focusing on macroprudential policy frameworks. This volume is a collection of the welcome address, keynote speeches, revised versions of all papers presented during the conference and the panel discussions.
An inverse optimization of convection heat transfer in rectangle channels with ribbed surface based on the extremum principle of entransy dissipation
Venue: International Journal of Heat and Mass Transfer
Year: 2019

The ribbed surface is a widely used convection heat transfer enhancement technology. The geometric parameters of the ribbed surface have great influences on its heat transfer performance. It is crucial to determine the optimum geometric parameters. In the present work, the optimal arrangement of ribs mounted in a rectangular channel is provided by solving the inverse optimization problem with the entransy dissipation as the objective function. The parameter analysis based on the direct solution is firstly carried out to get an approximate range near the optimal pitch ratio which can provide the initial value for the inverse optimization problem; afterwards, the inverse optimization problem is solved by a modified simplified conjugate gradient method, and the accurate optimal pitch ratio is obtained; finally the optimization results are discussed in detail. The results indicate that, (1) the inverse optimization analysis presented in this paper can provide an accurate optimal value of the pitch ratio; (2) taking the entransy dissipation as the objective function could lead to a faster converge process and give a more stable result than taking the temperature data as the objective function; (3) the optimal value under the fixed heat flux boundary condition is slightly larger than that under the fixed temperature boundary condition.
Label Propagation Adaptive Resonance Theory for Semi Supervised Continuous Learning
Venue: ICASSP 2020 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2020

Semi supervised learning and continuous learning are fundamental paradigms for human level intelligence. To deal with real world problems where labels are rarely given and the opportunity to access the same data is limited, it is necessary to apply these two paradigms in a joined fashion. In this paper, we propose Label Propagation Adaptive Resonance Theory (LPART) for semi supervised continuous learning. LPART uses an online label propagation mechanism to perform classification and gradually improves its accuracy as the observed data accumulates. We evaluated the proposed model on visual (MNIST, SVHN, CIFAR 10) and audio (NSynth) datasets by adjusting the ratio of the labeled and unlabeled data. The accuracies are much higher when both labeled and unlabeled data are used, demonstrating the significant advantage of LPART in environments where the data labels are scarce.
COVID 19 Pandemic and Mental Health Status of Saudi Citizens Living Abroad
Venue: International journal of environmental research and public health
Year: 2021

The COVID 19 pandemic is a global health crisis associated with unprecedented levels of morbidity and mortality worldwide. The COVID 19 pandemic has been suggested to contribute to a great burden on global mental health. We assumed that individuals in quarantine outside their home country would be more vulnerable to developing mental health disorders during the current pandemic and might face difficulties in accessing mental health services.  To explore the degree of association between the COVID 19 pandemic and mental health status of Saudi citizens living abroad.  (1) To measure the prevalence and risk factors of mental health problems among Saudi citizens studying and living abroad during the COVID 19 pandemic; (2) to assess the correlation between the COVID 19 pandemic and mental health status of Saudi citizens living abroad; and (3) to explore the level of anxiety/depression during the COVID 19 pandemic.  A cross sectional survey was conducted from August 2020 to September 2020 using a self administrated questionnaire composed of sociodemographic, (GAD 7) and (PHQ 9) scales.  A total of 64% of participants experienced psychiatric symptoms during the pandemic, and 34% and 30% met the diagnostic criteria for symptoms of depression and anxiety, respectively. The risk of psychological symptoms was more likely experienced by females, young, single, or divorced, or those who were living alone. In addition, those who lived in the UK and Ireland were more likely to develop depressive and anxiety symptoms. More than 80% appreciated the response of the Saudi government and embassy to meet the MH needs of students undergoing quarantine abroad and in Saudi Arabia.  The COVID 19 pandemic represents an unprecedented threat to global mental health. Two thirds of study participants who were in foreign countries during the COVID 19 pandemic reported anxiety or depressive symptoms. Living away from family and friends was significantly associated with increased loneliness and psychological distress. These and other findings highlight the need to remove barriers preventing easily accessible online mental health services, social and family support, and timely provision of resources.
A clinical process redesign project to improve outcomes and reduce care variance for people with Parkinson's disease.
Venue: Australasian emergency care
Year: 2019

Redesigning clinical processes is an iterative process that seeks to reduce care variance and improve quality, safety and satisfaction for patients. The aim of this project was to optimise multidisciplinary collaboration, management and integration of clinical processes for people with Parkinson's Disease (PD) in one Emergency Department (ED) METHODS The retrospective evaluation study design explored the outcomes of a clinical process redesign project. The project included: a pre post medical record audit, a nurse survey and patient and carer telephone interviews.  The pre post ED medical record audit revealed in favour of the post group a median reduction of 175 minutes (IQR 0:40 19:40) in length of stay, a 21% improvement in timely PD medication administration and 13% improvement in correctly prescribed PD medications. Patients and carers (n=47) were satisfied with their ED experience, clinicians' knowledge and management and healthcare decision engagement. Nurses (n=30) reported improved knowledge, confidence and management in caring for PD patients.  This project led to enhanced multidisciplinary engagement and positive patient, clinician and service outcomes. Redesign principles can provide a pragmatic approach to improve the integration of care, change clinician behaviour, and reduce adverse outcomes within any clinical setting.