nils-herrmann/clean_scirepeval huggingface dataset:
Stochastic Process Underlying Emergent Recognition of Visual Objects Hidden in Degraded Images
Venue: PloS one
Year: 2014

When a degraded two tone image such as a "Mooney" image is seen for the first time, it is unrecognizable in the initial seconds. The recognition of such an image is facilitated by giving prior information on the object, which is known as top down facilitation and has been intensively studied. Even in the absence of any prior information, however, we experience sudden perception of the emergence of a salient object after continued observation of the image, whose processes remain poorly understood. This emergent recognition is characterized by a comparatively long reaction time ranging from seconds to tens of seconds. In this study, to explore this time consuming process of emergent recognition, we investigated the properties of the reaction times for recognition of degraded images of various objects. The results show that the time consuming component of the reaction times follows a specific exponential function related to levels of image degradation and subject's capability. Because generally an exponential time is required for multiple stochastic events to co occur, we constructed a descriptive mathematical model inspired by the neurophysiological idea of combination coding of visual objects. Our model assumed that the coincidence of stochastic events complement the information loss of a degraded image leading to the recognition of its hidden object, which could successfully explain the experimental results. Furthermore, to see whether the present results are specific to the task of emergent recognition, we also conducted a comparison experiment with the task of perceptual decision making of degraded images, which is well known to be modeled by the stochastic diffusion process. The results indicate that the exponential dependence on the level of image degradation is specific to emergent recognition. The present study suggests that emergent recognition is caused by the underlying stochastic process which is based on the coincidence of multiple stochastic events.
GAMBARAN BEBERAPA FAKTOR TERKAIT PEMANFAATAN BED OCCUPANCY RATE (BOR) DI RUMAH SAKIT UMUM DAERAH dr. R. KOESMA KABUPATEN TUBAN
Year: 2017

BOR indicators is an important indicator to determine the level of hospital services that are used by hospital management. The purpose of this study is to describe the factors related to the utilization of bed occupancy rate (BOR) in RPH of sr.  This research is explanatory research with quantitative qualitative method. The population of this research are all heads of the wards in dr.  The sample of this research is total population of 12 persons chief of inpatient room, 1 person chief of nursing hospitalization, and 1 deputy director of field services. The results of the univariate study shows the percentage of knowledge (78.6% the percentage of completeness data collection (70.93% the percentage of utilization of the data (37.5% Planning for energy needs, infrastructure, mapping hospitalization, and finance are obtained from Regional Revenue and Expenditure Budget, State Revenue and Expenditure Budget, fund hospital. Human resources are still lacking for some of the wards and no reward in the utilization BOR. Suggestion from the researcher to chief the nursing hospitalization are to provide education and training related to the daily inpatient room census filling, prepare standard operating procedures on the utilization of BOR for chief of the ward, and give rewards to the ward.
Sozialstatus, Sportpartizipation und sportmotorische Leistungsfahigkeit Social status, sports participation, and motor performance
Year: 2011

Zusammenfassung Der Einfluss von sozialer Ungleichheit (Geschlecht, Sozialstatus) auf Sportverhalten und motorische Leistung wird in der Literatur kontrovers diskutiert und dargestellt. Gerade die Effekte bei Kindern und Jugendlichen, deren Sozialstatus von den Eltern abgeleitet ist, werden in diesem Kontext nur unzureichend thematisiert. Anhand einer Stichprobe von Schulern im Saarland (1. 4. 7. und 10. Klasse) soll der Frage nachgegangen werden, inwieweit das Geschlecht sowie der von den Eltern abgeleitete Sozialstatus sowohl Sportverhalten als auch motorische Leistungen determinieren.  The influence of social inequality (gender, social status) on sports behavior and motor performance has been debated extensively in literature. Yet the effects of social inequality on children and young people whose social status is inherited, in a sense, from their parents has not been adequately addressed. Using a sample of students in Saarland (first, fourth, seventh, and tenth grade) we addressed the question of whether gender and social status (derived from the parents) have an impact on sports behavior and motor performance. The parents of 1,286 students were asked about their social status and aspects of their children's involvement in sports activities. 887 of these students were tested for motor performance using the DMT 6 18 (Deutscher Motorik Test) We found that athletic engagement in sports clubs and participation in competitions depends significandy on gender (the majority of sport participants are boys) However, general sports participation is independent of gender (regardless of the organizational form) Both sports engagement and motor performance depend on the social status of the parents.
The effects of different temperature on the antioxidant (GSH) levels of the kidney tissue of Oreochromis niloticus
Year: 2017

It is known that increasing seasonal environment temperature affects negatively on the physico chemical structure of the living. In this study, changes in antioxidant levels were examined in renal tissues of Oreochromis niloticus at different temperatures (15 and 25degC) The antioxidant levels of glutathione (GSH) were analyzed by analysis with spectrophotometric methods at 24 th 48 th and 72 nd hours. GSH levels firstly decrease compared with control fish and then increased. This reduction was about 33% at 24 hours and then it was observed that GSH levels increased at the level to the control fish at the end of 72 hours. This study showed that GSH levels were sensitive and affected depending on the temperature in the kidney tissue of O. niloticus species.
Learning Based Outdoor Localization Exploiting Crowd Labeled WiFi Hotspots
Venue: IEEE Transactions on Mobile Computing
Year: 2019

The ever expanding scale of WiFi deployments in metropolitan areas has made accurate GPS free outdoor localization possible by relying solely on the WiFi infrastructure. Nevertheless, neither academic researches nor existing industrial practices seem to provide a satisfactory solution or implementation. In this paper, we propose WOLoc (WiFi only Outdoor Localization) as a learning based outdoor localization solution using only WiFi hotspots labeled by crowdsensing. On one hand, we do not take these labels as fingerprints as it is almost impossible to extend indoor localization mechanisms by fingerprinting metropolitan areas. On the other hand, we avoid the over simplified local synthesis methods (e.g. centroid) that significantly lose the information contained in the labels. Instead, WOLoc adopts a semi supervised manifold learning approach that accommodates all the labeled and unlabeled data for a given area, and the output concerning the unlabeled part will become the estimated locations for both unknown users and unknown WiFi hotspots. Moreover, WOLoc applies text mining techniques to analyze the SSIDs of hotspots, so as to derive more accurate input to its manifold learning. We conduct extensive experiments in several outdoor areas, and the results have strongly indicated the efficacy of our solution in achieving a meter level localization accuracy.
AX Semantics' Submission to the SIGMORPHON 2019 Shared Task
Year: 2019

This paper describes the AX Semantics' submission to the SIGMORPHON 2019 shared task on morphological reinflection. We implemented two systems, both tackling the task for all languages in one codebase, without any underlying language specific features. The first one is an encoder decoder model using AllenNLP; the second system uses the same model modified by a custom trainer that trains only with the target language resources after a specific threshold. We especially focused on building an implementation using AllenNLP with out of the box methods to facilitate easy operation and reuse.
Systematic literature review of machine learning based software development effort estimation models
Venue: Inf. Softw. Technol.
Year: 2012

Software development effort estimation (SDEE) is the process of predicting the effort required to develop a software system. In order to improve estimation accuracy, many researchers have proposed machine learning (ML) based SDEE models (ML models) since 1990s. However, there has been no attempt to analyze the empirical evidence on ML models in a systematic way.  This research aims to systematically analyze ML models from four aspects: type of ML technique, estimation accuracy, model comparison, and estimation context.  We performed a systematic literature review of empirical studies on ML model published in the last two decades (1991 2010)  We have identified 84 primary studies relevant to the objective of this research. After investigating these studies, we found that eight types of ML techniques have been employed in SDEE models. Overall speaking, the estimation accuracy of these ML models is close to the acceptable level and is better than that of non ML models. Furthermore, different ML models have different strengths and weaknesses and thus favor different estimation contexts.  ML models are promising in the field of SDEE. However, the application of ML models in industry is still limited, so that more effort and incentives are needed to facilitate the application of ML models. To this end, based on the findings of this review, we provide recommendations for researchers as well as guidelines for practitioners.
Development and Application of the Leadership Archetype Questionnaire
Year: 2009

The Leadership Assessment Questionnaire (LAQ) is a 360 degree survey instrument designed to help organizational leaders identify their own style of leadership and formulate appropriate development objectives. It is designed to provide a means for developing an executive team in which multiple leadership archetypes are represented. The LAQ is based on eight leadership archetypes Strategist, Change catalyst, Transactor, Builder, Innovator, Processor, Coach, and Communicator. These archetypes are representations of ways of leading in a complex organizational environment. In this article we discuss the development, design, and psychometric analysis of the LAQ. We detail the conceptual foundations of the questionnaire and the psychometric methods used to confirm the validity and reliability of the instrument. We conclude with avenues for future research.
Similarity of Business Process Models A State of the Art Analysis
Venue: ACM Comput. Surv.
Year: 2017

Business process models play an important role in today's enterprises, hence, model repositories may contain hundreds of models. These models are, for example, reused during process modeling activities or utilized to check the conformance of processes with legal regulations. With respect to the amount of models, such applications benefit from or even require detailed insights into the correspondences between process models or between process models' nodes. Therefore, various process similarity and matching measures have been proposed during the past few years. This article provides an overview of the state of the art regarding business process model similarity measures and aims at analyzing which similarity measures exist, how they are characterized, and what kind of calculations are typically applied to determine similarity values. Finally, the analysis of 123 similarity measures results in the suggestions to conduct further comparative analyses of similarity measures, to investigate the integration of human input into similarity measurement, and to further analyze the requirements of similarity measurement usage scenarios as future research opportunities.
Fast Warehouse Management System (WMS) using RFID based goods locator system
Venue: 2017 IEEE 6th Global Conference on Consumer Electronics (GCCE)
Year: 2017

In rapidly growing e commerce businesses, searching purchased items in the warehouse and delivering them within a very short time becomes a crucial problem. In order to solve this problem, we propose a complete RFID based goods locator system which consists of specially designed RFID reader and an integrated cloud based Warehouse Management System (WMS) The RFID reader is able to detect and sense the distance to the location of the purchased item which is attached with a RFID tag based on its RSSI information. The RFID reader is connected with the WMS application installed in a smartphone, through a Bluetooth connection. To update the inventory item information in real time, the Android based WMS application is connected to cloud based logistic and commerce database. Hence, by using this system, the time needed to search the purchased item and track the item delivery status can be shortened. As the result, it increases the efficiency of WMS system.
Reinforcement Learning Based Relay Mobility and Power Allocation for Underwater Sensor Networks Against Jamming
Venue: IEEE Journal of Oceanic Engineering
Year: 2020

Underwater sensor networks (UWSNs) are vulnerable to jamming attacks due to the narrow frequency bandwidth and the fast fading channels. In this paper, we propose a reinforcement learning (RL) based antijamming relay scheme for UWSNs that enables an underwater relay to decide whether to leave the heavily jammed location and choose the relay power based on the state that consists of the bit error rate of the previous transmission, the previous relay power, the current transmit power of the sensor, and the jamming power measured by the relay node. We also propose a deep RL based relay scheme to further improve the relay performance for the node that supports deep learning computation. We discuss the computational complexity of the deep RL based relay scheme and provide the relay performance bound regarding the bit error rate, energy consumption, and utility of the relay node. Experiments taken in a nonanechoic pool with underwater transducers against smart jamming attacks verify the analysis results. According to the experimental results, the proposed relay scheme can improve the relay performance compared with the benchmark underwater relay schemes.
PENGARUH PENGETAHUAN TENTANG BANK SYARIAH DAN LITERASI KEUANGAN TERHADAP MINAT MENABUNG SISWA PADA BANK SYARIAH DI KELAS XI IPS MAN 2 KOTA MALANG
Venue: JURNAL EKONOMI PENDIDIKAN DAN KEWIRAUSAHAAN
Year: 2020

Penelitian ini bertujuan untuk menganalisis pengaruh pengetahuan tentang bank syariah dan literasi keuangan terhadap minat menabung siswa pada bank syariah di kelas XI IPS MAN 2 Kota Malang.Pendekatan yang digunakan dalam penelitian ini adalah penelitian kuantitatif.Teknik pengambilan sampel yang digunakan adalah teknik sampling jenuh, dimana seluruh populasi digunakan sebagai sampel, yaitu sebanyak 62 orang siswa.Dalam penelitian ini analisis yang digunakan untuk mengetahui pengaruh pengetahuan tentang bank syariah dan literasi keuangan terhadap minat menabung di bank syariah dengan menggunakan regresi linier berganda.Berdasarkan hasil analisis data, dapat disimpulkan bahwa pengetahuan tentang bank syariah berpengaruh terhadap minat menabung siswa pada bank syariah di kelas XI IPS MAN 2 Kota Malang.
Effects of Examination Oriented Teaching on Academic Aspiration among Secondary School Students in Imenti South District, Kenya
Year: 2014

This study sought to examine the effects of examination oriented teaching on academic aspiration among secondary school students in Imenti South District of Kenya. The study adopted a descriptive survey research design on a target population of 14,847 respondents, comprising of teachers, students and Assistant Education Officers in Imenti South District. Stratified random sampling and purposive sampling techniques were employed to obtain the desired sample. Data was collected using three sets of questionnaires whose reliability was estimated by use of CronbachaEUR(tm)s Alpha Coefficient using SPSS version 17.0. The study findings indicated that examination oriented teaching negatively affects studentsaEUR(tm) academic aspiration in secondary school. Therefore, it is anticipated that the findings and recommendations of this study will provide valuable reference for curriculum planning, development, administration, implementation and evaluation with a view of providing a holistic educational experience among secondary schools students in Imenti South District, Kenya.
Inclusiones pseudo bastones de Auer en celulas plasmaticas de un mieloma multiple IgG kappa
Year: 2020

Las inclusiones pseudo bastones de Auer en el citoplasma de celulas plasmaticas son un hallazgo morfologico muy poco frecuente. Se observan mayormente en mieloma multiple de tipo IgG kappa, como en el presente caso. Su significado pronostico aun no ha sido determinado.
Pose Based Two Stream Relational Networks for Action Recognition in Videos
Venue: ArXiv
Year: 2018

Recently, pose based action recognition has gained more and more attention due to the better performance compared with traditional appearance based methods. However, there still exist two problems to be further solved. First, existing pose based methods generally recognize human actions with captured 3D human poses which are very difficult to obtain in real scenarios. Second, few pose based methods model the action related objects in recognizing human object interaction actions in which objects play an important role. To solve the problems above, we propose a pose based two stream relational network (PSRN) for action recognition. In PSRN, one stream models the temporal dynamics of the targeted 2D human pose sequences which are directly extracted from raw videos, and the other stream models the action related objects from a randomly sampled video frame. Most importantly, instead of fusing two streams in the class score layer as before, we propose a pose object relational network to model the relationship between human poses and action related objects. We evaluate the proposed PSRN on two challenging benchmarks, i.e. Sub JHMDB and PennAction. Experimental results show that our PSRN obtains the state the of art performance on Sub JHMDB (80.2% and PennAction (98.1% Our work opens a new door to action recognition by combining 2D human pose extracted from raw video and image appearance.
The sublethal effects of pesticides on beneficial arthropods.
Venue: Annual review of entomology
Year: 2007

Traditionally, measurement of the acute toxicity of pesticides to beneficial arthropods has relied largely on the determination of an acute median lethal dose or concentration. However, the estimated lethal dose during acute toxicity tests may only be a partial measure of the deleterious effects. In addition to direct mortality induced by pesticides, their sublethal effects on arthropod physiology and behavior must be considered for a complete analysis of their impact. An increasing number of studies and methods related to the identification and characterization of these effects have been published in the past 15 years. Review of sublethal effects reported in published literature, taking into account recent data, has revealed new insights into the sublethal effects of pesticides including effects on learning performance, behavior, and neurophysiology. We characterize the different types of sublethal effects on beneficial arthropods, focusing mainly on honey bees and natural enemies, and we describe the methods used in these studies. Finally, we discuss the potential for developing experimental approaches that take into account these sublethal effects in integrated pest management and the possibility of integrating their evaluation in pesticide registration procedures.
Family Interdependence, Spiritual Perspective, Self Transcendence, and Depression Among Korean College Students
Venue: Journal of Religion and Health
Year: 2017

The purpose of this study was to examine the mechanisms that might account for the effects of spirituality and self transcendence on Korean college students' depression among 197 Korean fathers, mothers, and children. A structural equation analysis indicated that spiritual perspective related to lower depression through the mediating pathway of self transcendence for individuals. Mothers' spiritual perspective and self transcendence related to their children's depression through the mediating pathway of their own depression, but the same was not true for fathers. Findings help explicate the intergenerational transmission of depression and important predictors of depression related to spirituality.
Whittle Index for AoI Aware Scheduling
Venue: 2020 International Conference on COMmunication Systems NETworkS (COMSNETS)
Year: 2020

We consider a system consisting of multiple sensors that send updates to a monitoring station via a shared communication channel. The focus is on designing scheduling policies to minimize the time average of the weighted sum of the Age of Information of the sensors. We consider multiple channel models (i.i.d./Markov) and multiple information settings (CSI/delayed CSI/no CSI) and show that the scheduling problem is indexable for all settings considered. In addition, we compute the Whittle index in closed form for some of the settings. Via simulations, we show that Whittle Index based scheduling policies either outperform or match the performance of the best known policy for all the settings studied.
Genetic algorithm and a double chromosome implementation to the traveling salesman problem
Venue: SN Applied Sciences
Year: 2019

The variety of methods used to solve the traveling salesman problem attests to the fact that the problem is still vibrant and of concern to researchers in this area. For problems with a large search space, similar to the traveling salesman problem, evolutionary algorithms such as genetic algorithm are very powerful and can be used to obtain optimized solutions. However, the challenge in applying a genetic algorithm to the traveling salesman problem is the choice of appropriate operators that could produce legal tours. In the literature, additional repair algorithms have been introduced and employed and the offspring produced by these genetic algorithm operators are modified to ensure that the generated chromosomes represent legal tours. Rather than sticking to repair algorithms, a double chromosome approach is proposed in this article. The proposed method can be employed to optimize problems similar to the traveling salesman problem. The double chromosome approach has been tested with a variety of traveling salesman problems, and the results indicated that the proposed method has a high rate of convergence toward the shortest tour.