nils-herrmann/clean_scirepeval huggingface dataset:
TH A 213AB 06: Investigation and Evaluation of Two Point Step Size Gradient Methods for IMRT/VMAT Treatment Plan Optimization
Year: 2012

To investigate and evaluate fast two point step size gradient methods for IMRT/VMAT treatment plan optimization with nonlinear convex models. Commonly applied optimizationmodels for IMRT/VMAT planning are nonlinear and convex, including many quadratic physical models and general nonlinear biological models. The solutions are typically found through gradient based algorithms. Existing methods, however, suffer from the low efficiency of the line search process. In this work, we investigate the use of two point step size gradient methods for solving general nonlinear convex models in IMRT/VMAT planning. With such algorithms, the line search step can be avoided or highly reduced, and significant speedup can be obtained. As a specified form of nonlinear convex models, the quadratic models are particularly investigated and the best form of the gradient method without line search is found.  Five clinical prostate and five clinical head and neck cancer cases were tested for both IMRT and VMAT planning. For general nonlinear convex models, the Modified Two Point Step Size Gradient Method was found to have the best efficiency: for all test cases, approximately 5 times speedup was obtained with similar convergence properties compared to the traditional line search method. For quadratic models, the original Barzilai Borwein method offered the best performance: for all test cases, approximately 10 times speedup was obtained with better convergence properties (i.e. better treatment quality) For instance, for typical prostate cancer cases with a penalty based quadratic model, it takes ~4 seconds to generate optimized 9 beam fluence maps compared to ~40 seconds using traditional line search method on a PC.  This work provides a guideline to speedup IMRT/VMAT treatment plan optimization for general nonlinear convex models without loss of treatment quality. The current experiments were all run on CPU. Based on our previous experience, additional 10 30 times speedup can be expected with GPU based implementation.
Forensic and Anomaly Detection Using Generalized Audit Software
Year: 2020

Detection of fraud is the responsibility of the auditor. In the industrial revolution 4.0, fraud no longer involves manual or physical activities, but auditors must improve their skills by understanding fraud in the form of data anomalies. In conjunction with the audit process, this company information system will be the source of data in the audit process. Technology based company operations make operational data no longer be paper, but are stored in electronic form. Auditors need to understand the importance of understanding and using technology in this audit process because data is available in electronic form (database) so manual procedures for obtaining and analyzing data are no longer effective for use.  Audit Tools and Techniques (CAATs) is a term intended for the use of technology in assisting auditors in carrying out the audit process. Our research is qualitative descriptive, we used primary data from observation, and inquiry or interview. Our interviewees are auditor in accounting firm who already used computer assisted audit techniques in daily work for data extraction and analysis. Our research result shows that auditors can implement CAATs in GAS (Generalized Audit Software) which is software created specifically for audit purposes. GAS has features that can easily test management assertions. GAS able to help auditor in more effective and efficient data extraction and analysis in order to detect symptom of fraud such anomaly in data, but even GAS has a lot of advantage and benefit, still GAS have weakness and disadvantages
The mediating role of identity incompatibility in the relationship between perceived discrimination and acculturation preferences in two generations of the ethnic Russian minority in the North Caucasus
Year: 2018

The present study tested a model in which the perceived incompatibility of ethnic Russian and regional North Caucasian identities mediates the relationship between perceived discrimination and acculturation strategies in two generations of ethnic Russian minority members living in the Kabardino Balkar Republic, North Caucasus, Russian Federation. Two identities might be perceived incompatible when they represent conflicting sets of norms and values and the two communities may place competing demands on individual commitment and loyalty. We sampled 105 dyads from ethnic Russian families (youth: M 18 years, SD 2.35, 48.6% female; parents: M 43 years, SD 6.97, 68.6% female) The questionnaire included measures of perceived discrimination, perceived identity incompatibility, and acculturation strategies. The results of multigroup path analysis showed that the perceived identity incompatibility mediated the relationship between perceived discrimination and two strategies, aimed at culture maintenance (integration and separation) in both generations. Identity incompatibility is regarded as a psychological mechanism that explains the impact of perceived discrimination on minority acculturation preferences in a multicultural region.
Selecting Six Sigma project: a comparative study of DEA and LDA techniques
Year: 2018

Nowadays, most of the organizations have focused through the world on Six Sigma to reduce the costs, improve the productivity and enhance concerned individuals' satisfaction, especially customers' satisfaction. Annually, these organizations define and execute thousands of Six Sigma projects which involve a great deal of investments. But are all of these projects successful and do the organizations benefit from the above advantages? The purpose of this study is to proposing a methodology to to answer this question that: How can we reduce the risk of failure in Six Sigma projects? The first step to reduce the risk of failure in Six Sigma projects is selecting optimal ones which have the most profits and the least expected risks.  First, the effective criteria are recognized and defined in selecting Six Sigma projects. Then, a new data envelopment analysis (DEA) model is proposed for project selection process. A real example is resolved by the presented model. Finally, the authors use linear discriminate analysis (LDA) to examine the validity of obtained results from the proposed model.  The results show that the proposed model is a suitable tool for selecting Six Sigma Projects. The findings demonstrate that the selected projects by suggested integrated DEA model are those confirmed by LDA.  The paper, using a real case study, provides a mathematical model to enhance decision quality in Six Sigma project selection. Applying the specific DEA model is remarkable itself, which joined to a pioneering procedure to use LDA to validity evaluation of the results.
Distributed Representations of Words and Phrases and their Compositionality
Venue: NIPS
Year: 2013

The recently introduced continuous Skip gram model is an efficient method for learning high quality distributed vector representations that capture a large number of precise syntactic and semantic word relationships. In this paper we present several extensions that improve both the quality of the vectors and the training speed. By subsampling of the frequent words we obtain significant speedup and also learn more regular word representations. We also describe a simple alternative to the hierarchical softmax called negative sampling. An inherent limitation of word representations is their indifference to word order and their inability to represent idiomatic phrases. For example, the meanings of "Canada" and "Air" cannot be easily combined to obtain "Air Canada" Motivated by this example, we present a simple method for finding phrases in text, and show that learning good vector representations for millions of phrases is possible.
Ji Yu PPRHe SVMMo Xing Yan Jiu Dong Ting Hu Jing Liu Yu Shu Sha Liang Bian Hua Study on Runoff and Sediment Variation of the Dongting Lake Based on PPR and SVM Model
Year: 2012

Dong Ting Hu Shi Chang Jiang Zhong You Dian Xing De Tun Tu Xing Diao Xu Hu Bo Shou Zi Ran He Ren Wei Yin Su Ying Xiang ,Qi Shu Ru He Shu Chu De Jing Liu Yu Shu Sha Liang Guan Xi Xian Hou Fa Sheng Liao Duo Ci Da De Diao Zheng Guo Cheng Wei Liao Tan Ming Dong Ting Hu Shui Sha Chu Ru Hu Liang Bian Hua He Xiang Hu Guan Xi ,Ben Wen Li Yong Xian You Shui Wen Ni Sha Deng Guan Ce Shi Yan Zi Liao ,Ji Yu Tou Ying Xun Zong Hui Gui (PPR)He Zhi Chi Xiang Liang Ji Mo Xing (SVM)Dui Dong Ting Hu Jing Liu Yu Shu Sha Liang Bian Hua Te Zheng Jin Xing Liao Mo Ni He Yan Zheng ,Bing Dui Mo Ni Wu Chai Jin Xing Liao Dui Bi Jie Guo Biao Ming ,Liang Chong Mo Xing Jun Ke Yi Yong Yu Mo Ni Dong Ting Hu Shui Wang Jing Liu Yu Shu Sha Liang Guan Xi ,Dan Zhi Chi Xiang Liang Ji Mo Xing (SVM)Jing Que Du Jiao Gao ,Gua Yong Xing Jiao Hao ,Ke Wei Dong Ting Hu De Zong He Zheng Zhi Ti Gong Li Lun Zhi Cheng He Ke Xue Yi Ju The Dongting Lake is very important for flood storage and water sources in the midstream of the Yangtze River. Due to the dual effects of nature and human activities, several major changes have been taken place on the runoff and sediment conditions and the relationships between rivers and lakes successively. In order to explore the relationships of runoff and sediment in and out the lake, the existing hydrologic and sediment and other observation data of the Dongting Lake area are fully used, and two non linear simulation models, Projection Pursuit Regression (PPR) and Support Vector Machine (SVM) are established. The simulation errors are also compared. The results show that the Support Vector Machine (SVM) has better validity and credibility, which could be used as an effective tool to simulate the complicated river system. This finding provides theoretical support and scientific basis for comprehensive improvement and ecological restoration of the Dongting Lake.
Globalization and the Labor Share in National Income
Year: 2017

Contradicting the conventional wisdom of constant factor shares, the portion of national income accruing to labor has been trending downward in the last three decades. This decline must have contributed to rising inequality as labor income is more evenly distributed than capital income. This study contributes to the literature on income inequality by exploring the role of globalization in driving the labor share. In particular, we focus on the impacts of trade openness and foreign direct investments (FDI) on the labor share. Using country level panel data for 1980 2010, the study finds that trade is a significant and robust determinant of labor share. Generally speaking, export depresses while import increases the labor share. The impact of FDI, however, is insignificant. These results are similar for both developed and developing countries.
Potential Processing Routes for Recovery of Platinum Group Metals from Southern African Oxidized PGM Ores: A Review
Venue: Journal of Sustainable Metallurgy
Year: 2017

The beneficiation of platinum group metals (PGMs) from pristine (unweathered) sulfide ores has conventionally been conducted through froth flotation, which typically achieves platinum recoveries of over 85% The achieved successes of PGM concentration by flotation from the pristine sulfide ores are largely due to the occurrence of PGMs in close association with base metal sulfide minerals like chalcopyrite, pentlantite, and pyrrhotite which are easily floatable. However, the fast depletion of sulfide PGM bearing minerals has triggered interest in exploring the recovery of the PGMs from near surface oxidized PGM ores which have proven to be more difficult to process by conventional means as an alternative source to sustain production of PGMs. Earlier attempts to process the oxidized PGM ores by conventional flotation methods achieved poor recoveries (typically less than 50% The resource estimates of oxidized PGM ores which are either unmined, mined, and stockpiled or discarded as overburden waste in South Africa and Zimbabwe are over 500 million tonnes. The economic benefits that could be realized in the event of an alternative and effective processing technique being developed would be immense. This paper reviews and discusses different research efforts that have been made to improve PGM recoveries from oxidized ores, and their merits and demerits.
If I were a grown up: Children's response to the rubber hand illusion with different hand sizes.
Venue: Journal of experimental child psychology
Year: 2019

During childhood, children's bodies undergo rapid physical growth, which may affect their ability to accurately perceive their own bodies as well as the external environment. Concurrently, multisensory processes underlying bodily self consciousness gradually develop. However, little is known of the relation between changes in body size and corresponding update in bodily self consciousness. In this study, 6 to 8 year old children experienced the "rubber hand illusion" while watching a regular (child like) or larger (adult like) rubber hand being touched either synchronously or asynchronously with their own real hand. We measured proprioceptive drift and subjective ownership as well as changes in weight estimation of objects. Synchronous versus asynchronous visuotactile stroking with both the regular and larger hands caused a change in subjective body ownership but did not make a difference in perceived hand location and weight estimation of objects having the same size but different weight. Intriguingly, simply viewing the regular hand led to greater proprioceptive drift and to overestimation of the objects' weight relative to the larger hand. In addition, weight estimation was also influenced by hand size after visuotactile stroking. These results demonstrate that visuotactile information modulates the intrinsic properties of body representation in terms of size in children and further corroborate previous findings suggesting late developing optimal calibration of visual and proprioceptive signals.
Of Fighting Flies, Mice, and Men: Are Some of the Molecular and Neuronal Mechanisms of Aggression Universal in the Animal Kingdom?
Venue: PLoS genetics
Year: 2015

Aggressive behavior is widespread in the animal kingdom, but the degree of molecular conservation between distantly related species is still unclear. Recent reports suggest that at least some of the molecular mechanisms underlying this complex behavior in flies show remarkable similarities with such mechanisms in mice and even humans. Surprisingly, some aspects of neuronal control of aggression also show remarkable similarity between these distantly related species. We will review these recent findings, address the evolutionary implications, and discuss the potential impact for our understanding of human diseases characterized by excessive aggression.
Neonatal Sepsis
Venue: Current Emergency and Hospital Medicine Reports
Year: 2019

made in infants less than 28 days of life and consists of a clinical syndrome that may include systemic signs of infection, circulatory shock, and multisystem organ failure.Recent FindingsCommonly involved bacteria include Staphylococcus aureus and Escherichia coli. Risk factors include central venous catheter use and prolonged hospitalization. Neonates are at significant risk of delayed recognition of sepsis until more ominous clinical findings and vital sign abnormalities develop. Blood culture remains the gold standard for diagnosis.SummaryNeonatal sepsis remains an important diagnosis requiring a high index of suspicion. Immediate treatment with antibiotics is imperative.
Towards AoI aware Smart IoT Systems
Venue: 2020 International Conference on Computing, Networking and Communications (ICNC)
Year: 2020

Age of Information (AoI) has gained importance as a Key Performance Indicator (KPI) for characterizing the freshness of information in information update systems and time critical applications. Recent theoretical research on the topic has generated significant understanding of how various algorithms perform in terms of this metric on various system models and networking scenarios. In this paper, we study AoI behavior on experimental implementations of packet flows among IoT nodes and over the Internet. AoI measurements are taken for several transport protocols such as TCP, UDP and web socket, on wired and wireless links. Practical issues such as synchronization and selection of hardware along with transport protocol, and their effects on AoI are discussed. The results provide insight toward application and transport layer mechanisms for optimizing AoI in real life networks.
The Influence of Supply Chain Finance on Inventory Management Under Supply Uncertainty
Venue: 2018 15th International Conference on Service Systems and Service Management (ICSSSM)
Year: 2018

It's well known that small and medium sized enterprises(SMEs) occupy a significant position in Chinese economy. However, in credit practices, SMEs are often considered as high risk lenders who often need to pay higher capital costs to obtain funds. This paper explores (1) debt financing can distort a retailer's inventory decision when the retailer with limited funds and selling multiple products with different price, cost, revenue, and yield uncertainty parameters; (2) we also explore the role of each parameter in this distortion. Because of the limited liability, a debt financed retailer prefers items with high selling price, high penalty factor(late delivery) and low salvage value. Furthermore, based on the fact that the capital cost of suppliers has always been higher than that of banks, we discuss that this distortion can be mitigated when the financing is provided by the supplier who can observe the actual order quantities before determining the credit terms. Besides, borrowing goods instead of borrowing cash limits the retailer's ability to deviate from the first best inventory decision. On the other hand, based on the fact that the capital cost of suppliers has always been higher than that of banks, we studied the combination of bank and supplier financing to enable retailers to achieve the best way of financing.
NEURAL NETWORK BASED LEAF DISEASE DETECTION AND REMEDY RECOMMENDATION SYSTEM
Year: 2020

1 Student Department of computer Science Dhaanish Ahmed Institute of Technology, Tamil Nadu, India 2 Student, Department of computer Science Dhaanish Ahmed Institute of Technology, Tamil Nadu, India 3 Professor, Department of computer Science Dhaanish Ahmed Institute of Technology, Tamil Nadu, India 4 Professor, Department of computer Science Dhaanish Ahmed Institute of Technology, Tamil Nadu, India Abstract Agriculture is one field which has a high impact on life and economic status of human beings. Loss in agricultural products occur due to improper management. Lack of knowledge about disease by farmers and hence less production happens. Kisan call centers are available but do not offer service 24*7 and sometimes communication too fail. Farmers are unable to explain disease properly on call need to analysis the image of affected area of disease. Though, images and videos of crops provide better view and agro scientists can provide a better solution to resolve the issues related to healthy crop yet it not been informed to farmers. It is required to note that if the productivity of the crop is not healthy, it has high risk of providing good and healthy nutrition. Due to the improvement and development in technology where devices are smart enough to recognize and detect plant diseases. Recognizing illness can prompt faster treatment in order to lessen the negative impacts on harvest. This paper therefore focus upon plant disease detection using image processing approach This work utilizes an open dataset of 5000 pictures of unhealthy and solid plants, where convolution system and semi supervised techniques are used to characterize crop species and detect the sickness status of 4 distinct classes.
Linear morphea induced atrophy treated with hyaluronic acid filler injections.
Venue: Dermatologic surgery official publication for American Society for Dermatologic Surgery [et al.
Year: 2011

Linear morphea in an en coup de sabre pattern is a variant of localized scleroderma that develops on the frontal or frontoparietal scalp. Approximately two thirds of cases occur before the age of 18. The etiology is unknown, but the disease is thought to be most likely autoimmune in nature. Between 50% and 75% of these patients have been found to have a positive serum antinuclear antibody (ANA) although ANA positivity has not been noted to correlate with disease activity. In en coup de sabre morphea, trauma has also been cited as a possible trigger. Although lesions may be limited to the skin, en coup de sabre morphea is notorious for extracutaneous involvement, and lesions may extend deep into underlying tissues and may be associated with neurologic, ophthalmologic, and oral abnormalities.
Deep neural networks employing Multi Task Learning and stacked bottleneck features for speech synthesis
Venue: 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2015

Deep neural networks (DNNs) use a cascade of hidden representations to enable the learning of complex mappings from input to output features. They are able to learn the complex mapping from text based linguistic features to speech acoustic features, and so perform text to speech synthesis. Recent results suggest that DNNs can produce more natural synthetic speech than conventional HMM based statistical parametric systems. In this paper, we show that the hidden representation used within a DNN can be improved through the use of Multi Task Learning, and that stacking multiple frames of hidden layer activations (stacked bottleneck features) also leads to improvements. Experimental results confirmed the effectiveness of the proposed methods, and in listening tests we find that stacked bottleneck features in particular offer a significant improvement over both a baseline DNN and a benchmark HMM system.
Opportunities of Integrating CO 2 Utilization with RES E a Power to Methanol Business Model with Wind Power Generation
Year: 2018

Under the need to reduce CO2 emissions, renewable energy sources for electricity (RES E) and more efficient processes are needed to decrease GHG emission rates. Carbon dioxide utilization (CDU) for the production of fuels, chemicals and materials is becoming complementary to captured CO2 and a promising source of competitive advantage for the European industry. CDU processes are at conceptual design, up to small demonstration readiness level. Since the CDU process has to compete with wellestablished conventional synthesis processes, they may not be profitable at current market conditions. Moreover, to have lower carbon footprint than the benchmark process, it has been demonstrated that they need electricity from renewable sources when CO2 is combined with H2 as raw material  This work aims at evaluating the connection of a methanol CDU plant with a wind power portfolio, to elucidate under which conditions this relationship is advantageous for both: (i) the CDU plant as a source of low cost and zero emission energy, and (ii) the wind producer for the maximization of its profit. The business model proposed here lies in the methodology developed by  aiming at reducing the wind power forecasting uncertainty, between the closure of the day ahead market and the first intraday bidding session in the Spanish power market. We have implemented an ad hoc linear programming optimization based in GAMS that maximizes the revenue from the wind producer's perspective. The model considers the options of a wind producer of selling its RES E to the day ahead power market or of using its RES E to synthesize and sell methanol. The intraday market is used as balancing market for the deviations of the wind power forecasting.