nils-herrmann/clean_scirepeval huggingface dataset:
Data Mining: Review, Drifts and Issues
Year: 2013

This paper gives a good overview of Data and Information or Knowledge has a significant role on human activities. Data mining is the knowledge discovery process by analyzing the large volumes of data from various perspectives and summarizing it into useful information. Due to the importance of extracting knowledge/information from the large data repositories, data mining has become an essential component in various fields of human life. Advancements in Statistics, Machine Learning, Artificial Intelligence, Pattern Recognition and Computation capabilities have evolved the present day's data mining applications and these applications have enriched the various fields of human life including business, education, medical, scientific etc. Hence, this paper discusses the various improvements in the field of data mining from past to the present and explores the future trends
Unit Ball Model for Embedding Hierarchical Structures in the Complex Hyperbolic Space
Year: 2021

Learning the representation of data with hierarchical structures in the hyperbolic space attracts increasing attention in recent years. Due to the constant negative curvature, the hyperbolic space resembles tree metrics and captures the tree like properties naturally, which enables the hyperbolic embeddings to improve over traditional Euclidean models. However, many real world hierarchically structured data such as taxonomies and multitree networks have varying local structures and they are not trees, thus they do not ubiquitously match the constant curvature property of the hyperbolic space. To address this limitation of hyperbolic embeddings, we explore the complex hyperbolic space, which has the variable negative curvature, for representation learning. Specifically, we propose to learn the embeddings of hierarchically structured data in the unit ball model of the complex hyperbolic space. The unit ball model based embeddings have a more powerful representation capacity to capture a variety of hierarchical structures. Through experiments on synthetic and real world data, we show that our approach improves over the hyperbolic embedding models significantly.
Modified shave surgery combined with nail window technique for the treatment of longitudinal melanonychia: evaluation of the method on a series of 67 cases.
Venue: Journal of the American Academy of Dermatology
Year: 2019

Nail matrix histopathological examination is still the gold standard to diagnose longitudinal melanonychia (LM)  To introduce modified shave surgery combined with nail window technique for managing LM, and evaluate the postoperative outcome of the procedure.  We retrospectively reviewed the medical records of 67 cases with LM who underwent shave surgery combined with longitudinal strip nail window technique at our institution from March 2015 to June 2018.  Pathological diagnosis was accessible in all cases and 60 cases were assessable for the postoperative outcomes. Forty five (75.0% cases had no postoperative nail dystrophy and the recurrence of nail pigmentation was only found in 8 (13.3% cases.  This was a retrospective study.  Modified shave surgery combined with nail window technique is a preferable management for LM cases, with limited postoperative nail dystrophy and pigmentation recurrence.
RUSE: Regressor Using Sentence Embeddings for Automatic Machine Translation Evaluation
Venue: WMT
Year: 2018

We introduce the RUSE metric for the WMT18 metrics shared task. Sentence embeddings can capture global information that cannot be captured by local features based on character or word N grams. Although training sentence embeddings using small scale translation datasets with manual evaluation is difficult, sentence embeddings trained from large scale data in other tasks can improve the automatic evaluation of machine translation. We use a multi layer perceptron regressor based on three types of sentence embeddings. The experimental results of the WMT16 and WMT17 datasets show that the RUSE metric achieves a state of the art performance in both segment and system level metrics tasks with embedding features only.
Subcubic Equivalences Between Graph Centrality Measures and Complementary Problems
Venue: ArXiv
Year: 2019

Despite persistent efforts, there is no known technique for obtaining unconditional super linear lower bounds for the computational complexity of the problems in P. Vassilevska Williams and Williams introduce a fruitful approach to advance a better understanding of the computational complexity of the problems in P. In particular, they consider All Pairs Shortest Paths (APSP) and other fundamental problems such as checking whether a matrix defines a metric, verifying the correctness of a matrix product, and detecting a negative triangle in a graph. Abboud, Grandoni, and Vassilevska Williams study well known graph centrality problems such as Radius, Median, etc. and make a connection between their computational complexity to that of two fundamental problems, namely APSP and Diameter. They show any algorithm with subcubic running time for these centrality problems, implies a subcubic algorithm for either APSP or Diameter. In this paper, we define vertex versions for these centrality problems and based on that we introduce new complementary problems. The main open problem of Abboud et al. is whether or not APSP and Diameter are equivalent under subcubic reduction. One of the results of this paper is APSP and CoDiameter, which is the complementary version of Diameter, are equivalent. Moreover, for some of the problems in this set, we show that they are equivalent to their complementary versions. Considering the slight difference between a problem and its complementary version, these equivalences give us the impression that every problem has such a property, and thus APSP and Diameter are equivalent. This paper is a step forward in showing a subcubic equivalence between APSP and Diameter, and we hope that the approach introduced in our paper can be helpful to make this breakthrough happen.
Ontological and Fuzzy Set Similarity between Perception Based Words
Venue: 2019 IEEE International Conference on Fuzzy Systems (FUZZ IEEE)
Year: 2019

Fuzzy short text semantic similarity measures allow the inclusion of human perception based words to be within the similarity measurement which results in better correlation on the meaning of the short text with human understanding. Existing measures such as FUSE and FAST rely on the creation of fuzzy ontological structures from the modelling of perception words using type 1 or type 2 fuzzy sets. Due to the complex methodology of creating these ontologies, fuzzy word representation cannot be guaranteed due to language evolution. This paper presents a comparative study of simpler fuzzy set similarity measures. The results surprisingly indicate that a very simple fuzzy set similarity measure created from the center of gravity (COG) distance between type 2 fuzzy sets has a very high correlation with the FUSE semantic similarity measure.
Competencias laborales para la gestion publica y productividad de las unidades organicas de un municipio provincial.
Year: 2020

The objective of this research is to explain how labor competencies for public management affect the productivity of the organic units of the Jorge Basadre Provincial Municipality, in 2018. It is a basic type research quantitative, not experimental, explanatory. In the present investigation, information has been taken from 108 workers, of the total population; A work skills test and a documentary record form were used as an instrument to record productivity data. The content validation was by expert opinion, the test of reliability of the test was performed using the Cronbach's Alpha method, having obtained an alpha indicator of 0.866 points. The results of the labor competencies, report an average of 44.54, according to the scale is in the regular level, the measurement of the indicators reports that 63.9% of those evaluated have a regular level of knowledge, 59.3% with regular skills and 67.6% with indifferent attitudes. The productivity results indicate a score of 49.14 which means a level of progress in progress, the analysis of the activities of each organic unit reports that the Project Liquidation Sub Division has the lowest average with 26.67% and the Sub Management Accounting has the highest average with 70.0% The hypothesis test with Pearson's correlation coefficient r gives us the sig. Bilateral 0.029 <0.05, therefore, the null hypothesis is rejected and the alternate hypothesis is accepted. In conclusion, if there is a significant effect of labor competencies on the productivity of the organic units of the Provincial Municipality of Jorge Basadre, in this way, confirming that there is a high positive correlation between labor competencies and productivity in the Provincial Municipality Jorge Basadre.
The Attributes of Customer Needs Tenun Ikat SME for Competitive Market in Indonesia
Year: 2020

The development of economy in Indonesia will not be separated from the role of small and medium enterprises. Tenun Ikat industrial centers is one of a collection of tenun ikat artisans in Kediri that less can compete with other similar products. On the basis of problems that often occur in Small Medium Enterprise, related the fulfillment of customer satisfaction. This research provide the solution method of the selection criteriabased product development strategy of competitive advantage such as quality, cost, delivery, service, and morale. Method of collecting data with a detailed questionnaire on the Tenun Ikat customers and analysed by using Importance Performance Analysis based on the criteria of customer needs for competitive advantage. The results of this study indicate that the plot from the value of each attribute in a Cartesian diagram that influence customer satisfaction and support in winning market competition.
Farm level feeding and production response of pacific white shrimp (Penaeus vannamei) in periphyton based farming system
Year: 2017

Study on feeding and production response of Penaeus vannamei in periphyton based farming system was done at two farm levels, one at Certitude Shrimp Farm, Vetaikaranirrupu Nagapattinam and second at TST Aqua farm, Karuvelankadai, Nagapattinam in Tamil Nadu state of India. Growth and feed consumption pattern of trial and the control ponds were recorded every week from 37 days of culture (DOC) to 108 DOC. Trial pond was harvested at 108 DOC with an average body weight (ABW) of 33 g, with a total production of 4, 700 kg. In control pond, the total production was 3, 750 kg with an ABW of 26.8 g. During the first week immersion period in the pond, the substrates (split bamboos of 1.5 inch thickness and 3 feet height, tied together at 1 meter interval, to a length of 20 meter and erected continuously with 1.5 meter gap in 0.5 ha trial pond) were observed with formation of slimy biofilm over the substrate and after two weeks the growth of periphyton was observed over the substrate colonized by diatoms, green algae, blue green algae and copepods. The weekly feed consumption pattern was also less by 15 to 20 percent in trial pond during the culture period compared with the control pond. The trial pond (1: 1.22) has proven a better food conversion ratio (FCR) compared to control pond (1: 1.35) This farm level study has illustrated that the periphyton developed in Penaeus vannamei culture pond serve as natural food. Hence, periphyton growth on substrate serve as natural food source, thus reduces the intake of supplementary feed, also maintains good water quality, favors fast growth in Penaeus vannamei with good FCR and maintains good health condition.
Computational Model for Understanding Emotions in Sarcasm: A Survey
Year: 2020

Sarcasm is generally associated with a negative emotion. The question is which negative emotionanger, sadness, disgust, any other? This paper presents a methodology of detecting the exact emotion(s) in a sarcastic sentence. Sarcasm arises from contextual incongruity in a sentence and bears a surface sentiment which is different from the intended sentiment. While the surface sentiment may be positive, the intended sentiment is negative. Thus the underlying emotion recognition task becomes one of the most difficult parts of the conundrum. Previous works have extensively studied sentiment and emotion in language, while the relationship between sarcasm and emotion has been largely unaddressed. In this paper, we investigate various challenges and techniques for Sarcasm Detection, Emotion Analysis and relationship between them.
Strategic Audit Expertise Orientation and Audit Success: Evidence from Cooperative Auditor in Thailand
Year: 2016

Audit environment changes rapidly due to accounting regulations. It is a complex factor that leads auditors to consider strategic orientation. This study aims to provide a better understanding on how strategic audit expertise orientation can lead to audit success. A conceptual framework is developed to investigate the relationship between strategic audit expertise orientation and audit success. This study proposes five dimensions of strategic audit expertise orientation which include dynamic audit learning, excellent audit knowledge, modern audit skills, continuous audit environment education, and valuable audit experience. Strategic audit expertise orientation may positively influence consequence variables audit planning proficiency, audit review quality, audit monitoring effectiveness, best audit practice, audit information utilization and audit report efficiency. Subsequently, these variables may lead to audit success.
DiSCO: Differentiable Scan Context With Orientation
Venue: IEEE Robotics and Automation Letters
Year: 2021

Global localization is essential for robot navigation, of which the first step is to retrieve a query from the map database. This problem is called place recognition. In recent years, LiDAR scan based place recognition has drawn attention as it is robust against the appearance change. In this letter, we propose a LiDAR based place recognition method, named Differentiable Scan Context with Orientation (DiSCO) which simultaneously finds the scan at a similar place and estimates their relative orientation. The orientation can further be used as the initial value for the down stream local optimal metric pose estimation, improving the pose estimation especially when a large orientation between the current scan and retrieved scan exists. Our key idea is to transform the feature into the frequency domain. We utilize the magnitude of the spectrum as the place descriptor, which is theoretically rotation invariant. In addition, based on the differentiable phase correlation, we can efficiently estimate the global optimal relative orientation using the spectrum. With such structural constraints, the network can be learned in an end to end manner, and the backbone is fully shared by the two tasks, achieving better interpretability and lightweight. Finally, DiSCO is validated on three datasets with long term outdoor conditions, showing better performance than the compared methods. Codes are released at https:/github.com/MaverickPeter/DiSCO pytorch.
Towards a full integration of optimization and validation phases: An analytical quality by design approach.
Venue: Journal of chromatography. A
Year: 2015

When using an analytical method, defining an analytical target profile (ATP) focused on quantitative performance represents a key input, and this will drive the method development process. In this context, two case studies were selected in order to demonstrate the potential of a quality by design (QbD) strategy when applied to two specific phases of the method lifecycle: the pre validation study and the validation step. The first case study focused on the improvement of a liquid chromatography (LC) coupled to mass spectrometry (MS) stability indicating method by the means of the QbD concept. The design of experiments (DoE) conducted during the optimization step (i.e. determination of the qualitative design space (DS) was performed a posteriori. Additional experiments were performed in order to simultaneously conduct the pre validation study to assist in defining the DoE to be conducted during the formal validation step. This predicted protocol was compared to the one used during the formal validation. A second case study based on the LC/MS MS determination of glucosamine and galactosamine in human plasma was considered in order to illustrate an innovative strategy allowing the QbD methodology to be incorporated during the validation phase. An operational space, defined by the qualitative DS, was considered during the validation process rather than a specific set of working conditions as conventionally performed. Results of all the validation parameters conventionally studied were compared to those obtained with this innovative approach for glucosamine and galactosamine. Using this strategy, qualitative and quantitative information were obtained. Consequently, an analyst using this approach would be able to select with great confidence several working conditions within the operational space rather than a given condition for the routine use of the method. This innovative strategy combines both a learning process and a thorough assessment of the risk involved.
Reseni sporu o dite a uloha organu socialne pravni ochrany deti
Year: 2011

Family is a key institution for a child and for an adult. One of the most important family functions is a child upbringing and its preparation for independent life. Parental role brings a big responsibility, pleasure and happiness to both parents. On the other hand it brings also conflicts, especially in case of parents (and family) separation or divorce. It is difficult for a child to understand parental disagreements. Submitted bachelor thesis is devoted to law relations between parents and children. It indicates possibilities of juridical solutions of situations such as parents don?t cooperate, parents can not reach agreements, parents try to restrict rights of one to the other. The author devotes her thesis also to children's rights, children's position in juridic proceedings, socio legal protection of children.
Combined application of biochar and sulfur regulated growth, physiological, antioxidant responses and Cr removal capacity of maize (Zea mays L. in tannery polluted soils.
Venue: Journal of environmental management
Year: 2020

Soil contamination due to heavy metals is a serious problem worldwide. Leather industry is one of the leading sectors in this regard in Pakistan, discharging heavy metal chromium (Cr) through untreated wastewater. In this study, effect of biochar and elemental sulfur (ES) were evaluated on maize growth, physiology, redox homeostasis and Cr dynamics in tannery polluted soils. Biochar was produced through pyrolysis of sugarcane bagasse at 350 degC and was applied at a rate of 3% (w/w) along with different rates of ES (3 and 6 g kg 1 soil) Results revealed that Cr toxicity in tannery polluted soils negatively affected plant growth, physiological and biochemical attributes. Reduction in plant growth and accumulation of Cr(III) and Cr(VI) in roots and shoots were higher in Sialkot (S) soil compared to Kasur (K) soil. Application of biochar and ES (6 g kg 1) resulted in maximum increase in plant height, biomass, chlorophyll content, photosynthesis, relative water, starch and protein content, as compared to control. While electrolyte leakage, soluble sugars, proline content, lipid peroxidation and antioxidant enzymes (APX, CAT, GSH, GR, GPX, GST and SOD) were decreased by addition of biochar and ES in tannery polluted soils. Similarly, combined application of biochar and ES decreased Cr concentrations in soil, and reduced uptake of Cr(VI) and Cr(III) concentration in roots and shoots of plants in S soil compared with K soil. In conclusion, application of biochar in combination with ES could be considered an interesting environmentally sound option for remediation of tannery polluted soils.
Automated Muscle Segmentation from Clinical CT Using Bayesian U Net for Personalized Musculoskeletal Modeling
Venue: IEEE Transactions on Medical Imaging
Year: 2020

We propose a method for automatic segmentation of individual muscles from a clinical CT. The method uses Bayesian convolutional neural networks with the U Net architecture, using Monte Carlo dropout that infers an uncertainty metric in addition to the segmentation label. We evaluated the performance of the proposed method using two data sets: 20 fully annotated CTs of the hip and thigh regions and 18 partially annotated CTs that are publicly available from The Cancer Imaging Archive (TCIA) database. The experiments showed a Dice coefficient (DC) of 0.891+ 0.016 (mean+ std) and an average symmetric surface distance (ASD) of 0.994+ 0.230 mm over 19 muscles in the set of 20 CTs. These results were statistically significant improvements compared to the state of the art hierarchical multi atlas method which resulted in 0.845 0.031 DC and 1.556 0.444 mm ASD. We evaluated validity of the uncertainty metric in the multi class organ segmentation problem and demonstrated a correlation between the pixels with high uncertainty and the segmentation failure. One application of the uncertainty metric in active learning is demonstrated, and the proposed query pixel selection method considerably reduced the manual annotation cost for expanding the training data set. The proposed method allows an accurate patient specific analysis of individual muscle shapes in a clinical routine. This would open up various applications including personalization of biomechanical simulation and quantitative evaluation of muscle atrophy.
A survey for the quadratic assignment problem
Venue: Eur. J. Oper. Res.
Year: 2007

The quadratic assignment problem (QAP) one of the most difficult problems in the NP hard class, models many real life problems in several areas such as facilities location, parallel and distributed computing, and combinatorial data analysis. Combinatorial optimization problems, such as the traveling salesman problem, maximal clique and graph partitioning can be formulated as a QAP. In this paper, we present some of the most important QAP formulations and classify them according to their mathematical sources. We also present a discussion on the theoretical resources used to define lower bounds for exact and heuristic algorithms. We then give a detailed discussion of the progress made in both exact and heuristic solution methods, including those formulated according to metaheuristic strategies. Finally, we analyze the contributions brought about by the study of different approaches.
The mechanics and physics of high speed dislocations: a critical review
Year: 2020

High speed dislocations have long been identified as the dominant feature governing the plastic response of crystalline materials subjected to high strain rates, controlling deformation and failure in industrial processes such as machining, laser shock peening, punching, drilling, crashworthiness, foreign object damage, etc. Despite decades of study, the role high speed dislocations have on the materials response remains elusive. This article reviews both experimental and theoretical efforts made to address this issue in a systematic way. The lack of experimental evidence and direct observation of high speed dislocations means that most work on the matter is rooted on theory and simulations. This article offers a critical review of the competing theoretical accounts of high speed mechanisms, their underlying hypothesis, insights, and shortcomings, with particular focus on elastic continuum and atomistic levels. The article closes with an overview of the current state of the art and suggestions for key developments in future research.