nils-herrmann/clean_scirepeval huggingface dataset:
Performance assessment of photovoltaic modules based on daily energy generation estimation
Year: 2018

Performance assessment can improve photovoltaic (PV) plant economics by identifying the need for timely corrective actions. Performance assessment of PV plants is usually based on the comparison between measured and modeled outputs of PV plants, i.e. an alarm occurs for abnormal operation when a significant difference is detected. For such methods, it is critical to estimate the potential electricity generation of PV plants in normal operation. However, unpredictable conditions affecting solar modules pose challenges to develop reliable PV models. In this paper, a practical approach to improve estimating daily energy generation of PV plants for performance assessment is proposed, which includes two main components: (i) a data preprocessing method; (ii) sub models in different weather conditions. The proposed data preprocessing method detects outliers by comparing normalized outputs of adjacent inverters instantaneously. It is robust against erroneous measurements in normal operation. Sub models in different weather conditions are developed using a Principal Component Analysis and Support Vector Machine method for better representation of PV plant outputs. Results show that the proposed method can detect deviations between the estimated and the measured daily energy generation of 10% Moreover, false alarms, i.e. an abnormal point identified while the system is operating normally, are significantly reduced.
Subjective life expectancy and associated factors among cancer survivors over 45 years old: evidence from the CHARLS
Venue: Quality of Life Research
Year: 2021

Associations between subjective life expectancy (SLE) and a variety of factors are well documented, but the relationship regarding cancer is limited. The purpose of this study was to disclose this potential relationship and identify the covariates that might influence this relationship. Data were extracted from the China Health and Retirement Longitudinal Study (CHARLS) and a sample of 448 cancer survivors and 43,795 individuals without cancer were analyzed. Multilevel mixed effects logistic regression was performed to examine the SLE associated with cancer survivors and participants without cancer after controlling for demographic, socioeconomic, health related, and psychosocial factors. The findings revealed that cancer survivors had a 39% reduction in longer life expectancy compared to respondents without cancer. Disparities in SLE existed based on diverse individual characteristics. The rate of high SLE in urban citizens was 75% higher compared to that of rural residents, while the rate of high SLE in participants with disability fell by 55% The rate of high SLE decreased by 22% and 35% in respondents with high blood pressure and diabetes, respectively. The proportion of respondents with high SLE was reduced by 70% when depression was present. Furthermore, the out of pocket expenditures of participants with and without cancer showed a significant difference, but discrepancies with respect to SLE among different cancer treatment options were not found. The more challenging one's socioeconomic status is and the unhealthier one's physical and mental conditions are, the lower one's prospect of subjective life expectancy is. Further work is warranted to confirm the causal association between subjective life expectancy and certain characteristics in cancer survivors.
Observation of reactor electron antineutrinos disappearance in the RENO experiment.
Venue: Physical review letters
Year: 2012

The RENO experiment has observed the disappearance of reactor electron antineutrinos, consistent with neutrino oscillations, with a significance of 4.9 standard deviations. Antineutrinos from six 2.8 GW(th) reactors at the Yonggwang Nuclear Power Plant in Korea, are detected by two identical detectors located at 294 and 1383 m, respectively, from the reactor array center. In the 229 d data taking period between 11 August 2011 and 26 March 2012, the far (near) detector observed 17102 (154088) electron antineutrino candidate events with a background fraction of 5.5% (2.7% The ratio of observed to expected numbers of antineutrinos in the far detector is 0.920+ 0.009(stat) 0.014(syst) From this deficit, we determine sin(2)2th(13)=0.113+ 0.013(stat) 0.019(syst) based on a rate only analysis.
DAWLANCE (Private) Limited: The Air Fryer Microwave Oven Launch
Venue: Asian Journal of Management Cases
Year: 2019

On September 17th, 2015, Mr Hasan Jameel, Head of Marketing at Dawlance' needs to firm up marketing mix details for the planned launch of their first microwave oven with air fryer technology. The original plan was to launch the air fryer as a five in one microwave oven which would allow consumers to heat, cook, bake, grill, and air fry food items using the same oven. Some managers at Dawlance; however, are concerned that offering so many options in one oven would increase the complexity and costs leading to high prices and reduced sales. They think that air fryer technology should be offered as a stand alone unit, similar to those of competitors. Pricing is also a concern. Various price points from PKR 18,000 to PKR 30,000 are possible. Finally, the advertising and distribution spend is under consideration. Mr Jameel needs to finalise his recommendations for the upcoming presentation to the MD.
A unified model for coupling mesoscopic dynamics of keyhole, metal vapor, arc plasma, and weld pool in laser arc hybrid welding
Venue: Journal of Manufacturing Processes
Year: 2019

Although building a model of laser arc hybrid welding has attracted substantial attention in recent decades, many problems remain. In particular, existing models failed to reproduce the highly transient (down to several tens of nanoseconds) physical interactions between solid, liquid, vapor plume and plasma occurring in the welding process. These interactions control the key physical processes of laser arc hybrid welding and play dominant roles in process defect formation and final joint quality. Development of a unified model for laser arc hybrid welding capable of modeling the multiphase physical interactions is faced with three major challenges. The first is how to decouple the highly correlated and mesoscopic interactions between the solid, liquid, vapor plume and plasma phases. The second and third are respectively the numerical treatments of the nonlinear discontinuous sheath layer between the arc plasma and the weld pool and the Knudsen layer between the vapor plume and the weld pool. In this study, we have developed a three dimensional unified mathematical model that couples the mesoscopic dynamics of the arc plasma, keyhole, metal vapor, and weld pool in the laser TIG hybrid welding process. To decouple the highly correlated gas, liquid, solid and plasma interactions, we proposed a novel approach in which the electromagnetic field in the workpiece (including solid and liquid phases) and outside the workpiece (gaseous phase and plasma) were continuously modeled globally, but in which the heat transfer and fluid flow are modeled separately within and outside of the workpiece and then coupled through boundary conditions. To treat the nonlinear interface between the arc plasma and weld pool outside the keyhole as well as between the vapor plume/plasma and the weld pool inside the keyhole, we proposed a novel ghost fluid based multiple timescale stepping algorithm. The results indicate that our model can be used to predict the time dependent mesoscopic dynamics of vapor plume, plasma, keyhole and weld pool in a coupled manner. Good agreement was obtained between the numerical predictions and experimental results and literature data.
Predicting antibiotic resistance in hospitalized patients by applying machine learning to electronic medical records.
Venue: Clinical infectious diseases an official publication of the Infectious Diseases Society of America
Year: 2020

Computerized decision support systems are becoming increasingly prevalent with advances in data collection and machine learning algorithms. However, they are scarcely used for empiric antibiotic therapy. Here we accurately predict the antibiotic resistance profiles of bacterial infections of hospitalized patients using machine learning algorithms applied to patients' electronic medical records (EMR) METHODS The data included antibiotic resistance results of bacterial cultures from hospitalized patients, alongside their electronic medical records. Five antibiotics were examined: Ceftazidime (n=2942) Gentamicin (n=4360) Imipenem (n=2235) Ofloxacin (n=3117) and Sulfamethoxazole Trimethoprim (n=3544) We applied lasso logistic regression, neural networks, gradient boosted trees, and an ensemble combining all three algorithms, to predict antibiotic resistance. Variable influence was gauged by permutation tests and Shapely Additive Explanations analysis.  The ensemble model outperformed the separate models and produced accurate predictions on a test set data. When no knowledge regarding the infecting bacterial species was assumed, the ensemble model yielded area under the receiver operating characteristic (auROC) scores of 0.73 0.79, for different antibiotics. Including information regarding the bacterial species improved the auROCs to 0.8 0.88. The effects of different variables on the predictions were assessed and found consistent with previously identified risk factors for antibiotic resistance.  Our study demonstrates the potential of machine learning models to accurately predict antibiotic resistance of bacterial infections of hospitalized patients. Moreover, we show that rapid information regarding the infecting bacterial species can improve predictions substantially. The implementation of such systems should be seriously considered by clinicians to aid correct empiric therapy and to potentially reduce antibiotic misuse.
Trilinear fuzzy seepage model of shale gas reservoirs with multiple fuzzy parameters
Venue: J. Intell. Fuzzy Syst.
Year: 2021

This paper focuses on establishing the trilinear fuzzy seepage model with multiple fuzzy parameters for shale gas reservoirs. Different from the conventional seepage models of shale gas reservoirs, the multiple fuzzy parameters seepage model uses fuzzy numbers to describe some parameters with uncertainty. Firstly, the multiple fuzzy parameters seepage model is constructed based on fuzzy concepts. The fuzzy structure element method and the centroid method are used to solve the fuzzy seepage model and defuzzifier, respectively. Secondly, the advantages of the development fuzzy model over the conventional seepage model are discussed and illustrated through numerical examples and simulations. Finally, to further study the seepage laws inside shale gas reservoirs, this paper explores the sensitivity of relevant main control parameters to gas production based on the development model.
Breast cancer and synchronous multiple myeloma as a diagnostic challenge: Case report and review of literature.
Venue: Current problems in cancer
Year: 2018

Multiple myeloma is a hematological malignancy, which sometimes creates difficulties in diagnosis, based on the presence of monoclonal protein in serum/urine and plasmocyte infiltration in the bone marrow, and on the other hand, synchronous cancers are also a diagnostic challenge. We present a case report of a patient with concurrent breast cancer and multiple myeloma. A 68 year old woman was admitted to the hospital with diagnosis of left breast cancer in first stage of the disease. In the past, she had had several episodes of thrombocytopenia, leucocytosis, and mild anaemia, which were followed by hematologist in outpatient setting. She was operated and started adjuvant chemotherapy. During treatment, episodes of hematological abnormalities were observed. After completion of the chemotherapy for breast cancer, the patient was observed and short time after that multiple myeloma was diagnosed as a synchronous cancer. Patient was first treated for breast cancer, then subsequently for multiple myeloma (2 lines therapy: CTD and VMP) We describe diagnostic problems with multiple myeloma; however, they could be caused by curation of breast cancer, which might have supressed the proliferation of plasmocytes and could delay the diagnosis. All symptoms of multiple myeloma were interpreted as a secondary effect of chemotherapy. Review of the literature shows the clinical approaches in such situations.
Rekayasa Pembuatan Kampas Rem Berbahan Dasar Serbuk Tempurung Kelapa Bermatriks Phenolic Resin Terhadap Performa Gesek Pengereman
Year: 2020

Penelitian ini bertujuan untuk menganalisa sifat mekanik material komposit berpenguat tempurung kelapa sebagai bahan dasar campuran kampas rem. Untuk menggantikan kampas rem berbahan asbes yang berbahaya bagi kesehatan dan lingkungan. Metode yang digunakan mencampurkan komposisi bahan kampas rem yang diteliti bermatriks phenolic resin penguat serbuk tempurung kelapa dengan limbah serbuk logam (aluminium, kuningan, barium sulfat, kalsium karbonat, grafit) dan fiberglass. Beban penekanan 10 ton serta waktu pengepresan campuran material yaitu 5 menit pada temperatur 150degC, 8 menit pada temperature 130degC dan 10 menit pada temperatur 120degC. Pengujian gesek dalam kondisi kering dan basah dengan pembebanan 15 kg serta pengujian kekerasan dengan durometer. Hasil penelitian yang didapatkan yaitu nilai keausan dan kekasaran kampas rem sangat dipengaruhi oleh komposisi material penyusun serta waktu dan temperatur penekanan.
Use of a systematic risk analysis method (FMECA) to improve quality in a clinical laboratory procedure.
Venue: Annali di igiene medicina preventiva e di comunita
Year: 2016

Risk management is a set of actions to recognize or identify risks, errors and their consequences and to take the steps to counter it. The aim of our study was to apply FMECA (Failure Mode, Effects and Criticality Analysis) to the Activated Protein C resistance (APCR) test in order to detect and avoid mistakes in this process.  We created a team and the process was divided in phases and sub phases. For each phase we calculated the probability of occurrence (O) of an error, the detectability score (D) and the severity (S) The product of these three indexes yields the RPN (Risk Priority Number) Phases with a higher RPN need corrective actions with a higher priority.  The calculation of RPN showed that more than 20 activities have a score higher than 150 and need important preventive actions; 8 have a score between 100 and 150. Only 23 actions obtained an acceptable score lower than 100.  This was one of the first experience of application of FMECA analysis to a laboratory process, and the first one which applies this technique to the identification of the factor V Leiden, and our results confirm that FMECA could be a simple, powerful and useful tool in risk management and helps to identify quickly the criticality in a laboratory process.
Concurrent test case generation from UML activity diagram based on dynamic programming
Venue: ICSCA '17
Year: 2017

Concurrency is a challenging and difficult task for software testing. Many researchers try to solve this problem and propose a solution, i.e. control flow graph, breadth first search (BFS) combined activity diagram and I/O explicit activity diagram. This paper proposes the method to generate concurrent test cases from UML activity diagrams. This method first builds a concurrent activity diagram from an ordinary UML activity diagram. It then transforms a UML activity diagram to an activity graph. Using dynamic programming techniques to find the number of total paths and of total condition paths in concurrent test cases. Test coverage measures the amount of tests performed by a set of tests which can also assure the quality of tests.
Savremeni platni sistemi: razvoj i integracija
Year: 2017

Intenzivan proces globalizacije svetske ekonomije tokom poslednjih trideset godina uslovio je medunarodnu integraciju platnih sistema. Ujedinjenje zemalja u EU obelodanilo je probleme koji se mogu javiti na tom planu. Evropska komisija i Evropska centralna banka ulazu znacajne napore da kreiraju integralni platni sistem za zemlje Evrozone, kao i harmonizovana pravila placanja u okviru EU. Tema unifikacije platnih sistema, na ovim prostorima, postala je vrlo aktuelna poslednjih godina, kao posledica teznje Republike Srbije da se integrise sa EU. Republika Srbija, u procesu pridruzivanja EU, vec izvesno vreme intenzivno sprovodi neophodne mere koje ce joj obezbediti ekonomsku integraciju. U kontekstu integracije finansijskih trzista, ona nastoji da unapredi i nacionalni platni sistem, kao jedan od kljucnih elemenata infrastrukturalne integracije. Osnovni razlog lezi u cinjenici da bi kasnjenje u razvoju nacionalnog platnog sistema i njegovih institucija produzilo vreme i povecalo troskove integracije sa EU. Prema tome, predmet ove naucne monografije je analiza stepena razvijenosti nacionalnog platnog sistema Republike Srbije i procesa njegovog prilagodavanja standardima koje je EU postavila u tom domenu. Cilj monografije je da se obrani hipoteza da Republika Srbija ima dovoljno razvijenu i organizaciono dobro postavljen nacionalni platni sistem, sto ce joj omoguciti da se bez velikih promena i ulaganja ukljuci u integralni platni sistem i sistem za kliring i saldiranje hartija od vrednosti EU.
Automatic Floor Cleaning Robot using Encoder
Year: 2019

Copyright (c) 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal.   This research work is based on design and construction of a floor cleaning robot with two modes automatic and manual mode. It supports automatic mode in this paper. IR sensor is used to avoid the obstacles and change left direction after right direction and it is mounted at the front side of the robot. It is applied to meet the U turn movement for complete coverage navigation by using optocoupler based encoder feedback. In this system, two motors (555 dc gear motor) are used with L298 for robot movement, and other (12V dc) motor is used with MOSFET driver to control the speed of the cleaner. The wireless connection between remote control and robot is established by using RF module. In U paths, the robot moves forward direction and turn left if it is detected wall and turn left again and move forward direction. Battery percentage, cleaner speed, movement of the robot and selected mode are displayed on the LCD. ATmega328P microcontrollerbased Arduino UNO board are applied as the heart of the system. Simulation test and experimental test are utilized for stable response in domestic application.
General Analysis of Resolution Enhancement on Time Synchronized Sampling and its Multi Resolution Solution in 20GSPS Acquisition System
Venue: IEEE Access
Year: 2019

Multiple resolutions have become a new feature required in ultra fast data acquisition systems (UF DASs) for various high end applications, especially for large scale physical experiments and radar equipment. However, plenty of repetitive efforts are paid to build various UF DASs with different resolutions for many similar purposes. In this paper, a system level sampling solution featuring multi resolution is explored for UF DASs to make the trade off between accuracy and speed. Firstly, a resolution enhancement mechanism based on a time synchronized sampling technique is studied more generally with probabilistic and statistical theory, and its applicable premise is discussed quantificationally at the same time. Then, a hardware based reconfigurable structure for the purpose of multi resolution high speed sampling is discussed with the combination of time interleaved and time synchronized sampling methods. Furthermore, to verify the proposed theory, a prototype with a maximal 20GSPS sampling rate and different resolutions of 8,9,10 bit is established. The experimental results show that three vertical resolutions of 8, 9 and 10 bit are achieved in the same prototype, and the effective number of bit (ENOB) in the two higher resolution modes has been improved remarkably from a single low resolution analog to digital converter (ADC) Therefore, the proposed theory and multi resolution sampling solution are important guides to the resolution trade off requirement in ultra fast acquisition systems.
Stock price prediction using LSTM, RNN and CNN sliding window model
Venue: 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
Year: 2017

Stock market or equity market have a profound impact in today's economy. A rise or fall in the share price has an important role in determining the investor's gain. The existing forecasting methods make use of both linear (AR, MA, ARIMA) and non linear algorithms (ARCH, GARCH, Neural Networks) but they focus on predicting the stock index movement or price forecasting for a single company using the daily closing price. The proposed method is a model independent approach. Here we are not fitting the data to a specific model, rather we are identifying the latent dynamics existing in the data using deep learning architectures. In this work we use three different deep learning architectures for the price prediction of NSE listed companies and compares their performance. We are applying a sliding window approach for predicting future values on a short term basis. The performance of the models were quantified using percentage error.
THE CONCEPT, EVOLUTION AND CHALLENGES OF DIGITAL LIBRARY DEVELOPMENT IN NIGERIA
Year: 2015

The adoption of information and communication technologies in information environment has made a radical change in information management. One of such revolutions has exhibited in the form of digital libraries. The evolution of digital libraries has ensured the emergence of global networked environment that has dramatically changed the status of libraries, their processes, service delivery as well as storage and retrieval systems. This paper examines the development of digital libraries, the concept, characteristics, funding, infrastructure, and ICT policy in Nigeria. The paper enumerates a number of challenges hindering the development of digital libraries in Nigeria and proffers some recommendations.
Strengthening Couples from a Single Parent Household Using Relational Cultural Therapy
Venue: Journal of Creativity in Mental Health
Year: 2019

Individuals initially learn about intimate relationships from observing others, such as their parents or caregivers' relationship, which may positively or negatively affect their own romantic relationship. This article focuses on the application of Relational Cultural Therapy (RCT) concepts to establish resilience among couples with at least one partner from a single parent household. Some individuals from single parent households may not have witnessed romantic relationships to confidently engage in adult romantic relationships. Additionally, clinicians may not consider family background as a source of contention for a couple's presenting concerns. Thus, this article provides creative interventions and implications to assist counselors in working with couples.