nils-herrmann/clean_scirepeval huggingface dataset:
Survey of Image Complexity Metrics for Infrared Target Recognition
Year: 2013

Metrics of infrared image complexity were not only used to characterize the variation of complex scenario for target recognition,but also are applied widely in infrared imaging system performance prediction and evaluation,performance comparison of target recognition algorithms,constructing and improving target acquisition model,and other fields.The definition of image complexity for infrared target recognition is presented,and some recently presented and some classical image complexity metrics in this field are summarized and analyzed comparatively.The basis for choosing metrics is proposed,and the shortcomings and deficiencies of existing metrics are pointed out.Image complexity metrics for infrared target recognition will develop towards fusing many features or integrating many metrics in the future.
Relationship between regional food and hypertension in the East of Turkey
Venue: International Journal Of Community Medicine And Public Health
Year: 2019

It is important to focus on behavioral risk factors, such as harmful habits, unhealthy diet, for hypertension. In the study the aim is to examine the hypertension frequency of adults in Bitlis city center, factors affecting this and other related factors. The target population of the cross sectional research consists of people aged 30 and higher in Bitlis city center. Face to face interviews were performed with people incorporated to the sample between February 15th and April 15th 2015 time interval in order to collect data from the field. Hypertension frequency was found to be 35.5% 59.3% of the people with hypertension are aware of the situation. The blood pressure of 26.3% of the people who are aware of their situation is under control. Significant difference was determined between hypertension and consumption frequency of regional foods such as fried fish, local cheese, fish Basma and Kurut. In logistic regression analysis significant relation was determined between hypertension and old age, women, obesity>=30 and Kurut frequent consumption. In the research the hypertension frequency was found to be 35.5% Significant relation was detected between hypertension and frequent consumption of Kurut which is a regional food.
Effect of an organic acid blend and phytase added to a rapeseed cake containing diet on performance, intestinal morphology, caecal microflora activity and thyroid status of broiler chickens.
Venue: Journal of animal physiology and animal nutrition
Year: 2010

The experiment was carried out on 96 female broilers, allocated to eight groups of 12 birds kept in individual cages. Two basal wheat and soyabean meal based diets containing 150 g/kg of rapeseed expeller cake were formulated, differing in the level of P: 7.1 g/kg in diet H or 5.9 g/kg in diet L. Rapeseed cake supplied 3.15 micromol alkenyl glucosinolates per gram of diet. The eight treatments were: basal diets only, basal diets phytase (1000 U/kg) basal diets organic acid blend (OA, 6 g/kg) or basal diets both additives. Diets were fed from day 8 to 28 of life. The results showed that the lower dietary P content and OA supplementation did not significantly affect feed intake or BWG, while both increased (p 0.001) after phytase supplementation. Tibia ash content as well as tibia ultimate strength were lower (p 0.001) in birds fed diets L compared with diets H, and increased (p 0.01) with phytase supplementation of diet L, while OA had no influence on either parameter. Dietary P levels and OA supplementation had no influence on the pH of gut digesta, but the pH of jejunal digesta increased following phytase supplementation (p 0.01) Morphological measurements of the small intestinal mucosa of chicks indicated that OA added to diet L depressed villi height (p 0.001) and crypt depth (p 0.001) both parameters increased after phytase supplementation (p 0.01) The lower total SCFA as well as acetic, propionic and butyric acid concentrations in caecal digesta indicated lower activity of caecal microflora in birds fed diets L compared with H. OA supplementation had no influence, while phytase supplementation increased the concentration of acetic acid in caecal digesta. Supplementation of diets with either phytase or OA increased thyroid weight by 16% (p 0.01) and 11% (p 0.05) respectively. The increase in thyroid weight because of phytase supplementation was greater at the lower dietary P level, and the greatest when both phytase and OA were added to the diet.
What Does Time Tell? Tracing the Forgetting Curve Using Deep Knowledge Tracing
Venue: AIED
Year: 2019

Recurrent Neural Network (RNN) based Deep Knowledge Tracing (DKT) can extract a complex representation of student knowledge just using the historical time series of correct incorrect responses given as input and can predict the student's performance on the next problem. funtoot is a personalized and adaptive learning system used by students to practice problems in school and at home. Our analysis of students' interaction with funtoot showed a time gap as high as 1 h, 1 day and also 1 week between two problems attempted by a student in a task. In this work, along with the time series of previous correct incorrect responses, we also encode the time gap as a feature to investigate its effect on predictions. We call this variant of DKT as DKT t. We test these models on our dataset and two major publicly available datasets from Assistments and Carnegie Learning's Cognitive Tutor and analyze the predicted student knowledge by both the models and report our findings. We also show that DKT t can help us trace the forgetting curve given various response sequences and their knowledge states.
Convolution Neural Networks: A Comparative Study for Image Classification
Venue: 2020 IEEE 15th International Conference on Industrial and Information Systems (ICIIS)
Year: 2020

Wide range of convolution neural network architectures are available for image classification, segmentation and object detection. Most of the architecture focus on accuracy as primary factor for implementation. However, when it comes to real time application deployment, there are other primary factors like memory and performance which is equally important. Also, each CNN architecture showcases its advantages and limitations but comparison over their peers are not equally considered. The goal of this paper is to provide a comparative study of various CNN architecture for image classification and serve as a guide for selection based on applications requirement and hardware capabilities. In this paper, we discuss about 18 different CNN state of art architectures that are widely used. In order to access model suitability for a given problem, CIFAR 10 image dataset is trained on different architectures with a specified set of hyper parameters to measure the accuracy, performance and memory consumption. The experiment findings are presented to suggest suitable CNN architecture based on application/hardware attributes.
How do trade and investment flows affect environmental sustainability? Evidence from panel data
Year: 2013

The inter linkage between trade and investment flows and environmental sustainability is a widely researched area. It has been noted that FDI is increasingly being directed to the LDCs and developing countries in recent period, whose export basket is generally more intensive in primary and manufacturing products. In this background, the current study contributes to the existing pool of research by conducting a panel data empirical analysis over 2000 10 for 114 countries to understand the relationship between trade and investment flows and environmental performance index (EPI) for countries at various income levels. The regression results indicate that while environmental sustainability of countries is negatively related with merchandise export orientation and FDI inward movements, it is positively influenced by service exports and FDI outward movements. The findings also confirm a positive relationship between several politico economic factors (e.g. liberal democratic setup and lesser corruption) and environmental performance of countries. Interestingly, the EPI variable displays a negative coefficient for lower income countries, while a positive relationship is noted for their higher income counterparts. The empirical findings lend proof to the contention that trade and investment flows significantly influences environmental sustainability of countries. It also raise serious concerns over the interface between environmental sustainability and economic and trade policy choice of developing countries and LDCs.
Automated design of add/drop equipment and effective wavelength assignment in complex DWDM networks
Venue: OPTO
Year: 2018

Recent growth of optical networks requires the installation of new and upgrade of existing components to support increased capacity demands. The task of designing optical transport systems and selecting equipment requires taking into account installed equipment as well as transceivers and (R)OADMs available at a moment. Often real OADMs, MDXs and transceivers operate at particular wavelengths, i.e. equipment is wavelength specific. Eventually, when designing a network, an engineer should take into account topology constraints such as optical channel path budget and equipment operating parameters such as transceiver reach and sensitivity. As WDM optical communication systems evolve from simple point to point links to complex network architectures, the optimized design of add/drop equipment and effective wavelength utilization becomes a challenging task when considering equipment constraints. We demonstrate an algorithmic approach, that offers an efficient method for the wavelength assignment and add/drop equipment allocation problem. This approach, which could be part of a comprehensive planning environment, allows optical network engineers to design cost effective add/drop equipment configurations with the most compact wavelength plan, resulting in the effective utilization of the DWDM grid. Our approach accounts for future channel loading, optical channel path parameters, e.g. its length, traffic demand parameters such as signal rate, equipment parameters such as add/drop port capability, operating wavelengths, transceiver bandwidth, etc. We will demonstrate how this approach will provide an easy way to design an optical network from scratch or upgrade the configuration of the existing ones. Different node architectures, including WSS based configurations or cascaded OADMs can be accommodated.
Repeated Sprint Ability Part I
Venue: Sports medicine
Year: 2011

Short duration sprints <10 seconds) interspersed with brief recoveries <60 seconds) are common during most team and racket sports. Therefore, the ability to recover and to reproduce performance in subsequent sprints is probably an important fitness requirement of athletes engaged in these disciplines, and has been termed repeated sprint ability (RSA) This review (Part I) examines how fatigue manifests during repeated sprint exercise (RSE) and discusses the potential underpinning muscular and neural mechanisms. A subsequent companion review to this article will explain a better understanding of the training interventions that could eventually improve RSA.Using laboratory and field based protocols, performance analyses have consistently shown that fatigue during RSE typically manifests as a decline in maximal/mean sprint speed (i.e. running) or a decrease in peak power or total work (i.e. cycling) over sprint repetitions. A consistent result among these studies is that performance decrements (i.e. fatigue) during successive bouts are inversely correlated to initial sprint performance. To date, there is no doubt that the details of the task (e.g. changes in the nature of the work/recovery bouts) alter the time course/magnitude of fatigue development during RSE (i.e. task dependency) and potentially the contribution of the underlying mechanisms.At the muscle level, limitations in energy supply, which include energy available from phosphocreatine hydrolysis, anaerobic glycolysis and oxidative metabolism, and the intramuscular accumulation of metabolic by products, such as hydrogen ions, emerge as key factors responsible for fatigue. Although not as extensively studied, the use of surface electromyography techniques has revealed that failure to fully activate the contracting musculature and/or changes in inter muscle recruitment strategies (i.e. neural factors) are also associated with fatigue outcomes. Pending confirmatory research, other factors such as stiffness regulation, hypoglycaemia, muscle damage and hostile environments (e.g. heat, hypoxia) are also likely to compromise fatigue resistance during repeated sprint protocols.
Writer Self Efficacy and Student Self Identity in Developmental Writing Classes: A Case Study
Year: 2017

The purpose of this qualitative case study was to explore how instructional approaches to teaching developmental writing at a large urban community college foster the development of college students' self efficacy regarding academic writing and selfidentity as college students. The case study examined the perspectives of four instructors and six students. The research considered: 1) how students experience the development of self efficacy related to their academic writing; 2) how students experience their selfidentity as college students; 3) how writing instructors foster students' development of self efficacy as writers; and 4) how writing instructors foster students' self identities as college students. The findings of this study provided a description of some of the specific ways students enrolled in developmental writing courses experienced the development of self efficacy and self identity. The study illuminated some of the practices that instructors use to facilitate both self efficacy and self identity in their approaches to teaching. With regard to students, what emerged in the analysis of this data was a sense that they felt both more empowered toward writing in an academic context and more self identified as college students. The significance of the study demonstrated that fostering relationships among students and with the institution itself, along with scaffolding and contextualizing assignments, builds effective pathways to student success.
FELIX: Fast and Energy Efficient Logic in Memory
Venue: 2018 IEEE/ACM International Conference on Computer Aided Design (ICCAD)
Year: 2018

The Internet of Things (IoT) has led to the emergence of big data. Processing this amount of data poses a challenge for current computing systems. PIM enables in place computation which reduces data movement, a major latency bottleneck in conventional systems. In this paper, we propose an in memory implementation of fast and energy efficient logic (FELIX) which combines the functionality of PIM with memories. To the best of authors' knowledge, FELIX is the first PIM logic to enable the single cycle NOR, NOT, NAND, minority, and OR directly in crossbar memory. We exploit the voltage threshold based memristors to enable single cycle operations. It is a purely in memory execution which neither reads out data nor changes sense amplifiers, while preserving data in memory. We extend these single cycle operations to implement more complex functions like XOR and addition in memory with 2x lower latency than the fastest published PIM technique. We also increase the amount of in memory parallelism in our design by segmenting bitlines using switches. To evaluate the efficiency of our design at the system level, we design a FELIX based HyperDimensional (HD) computing accelerator. Our evaluation shows that for all applications tested using HD, FELIX provides on average 128.8x speedup and 5,589.3x lower energy consumption as compared to AMD GPU. FELIX HD also achieves on average 2.21x higher energy efficiency, 1.86x speedup, and 1.68x less memory as compared to the fastest PIM technique.
Visual Odometric Localization and Mapping for Ground Vehicles Using SE(2) XYZ Constraints
Venue: 2019 International Conference on Robotics and Automation (ICRA)
Year: 2019

This paper focuses on the localization and mapping problem on ground vehicles using odometric and monocular visual sensors. To improve the accuracy of vision based estimation on ground vehicles, researchers have exploited the constraint of approximately planar motion, and usually implemented it as a stochastic constraint on an SE(3) pose. In this paper, we propose a simpler algorithm that directly parameterizes the ground vehicle poses on SE(2) The out of SE(2) motion perturbations are not neglected, but incorporated into an integrated noise term of a novel SE(2) XYZ constraint, which associates an SE(2) pose and a 3D landmark via the image feature measurement. For odometric measurement processing, we also propose an efficient preintegration algorithm on SE(2) Utilizing these constraints, a complete visual odometric localization and mapping system is developed, in a commonly used graph optimization structure. Its superior performance in accuracy and robustness is validated by real world experiments in industrial indoor environments.
What makes a rhythm complex? The influence of musical training and accent type on beat perception
Venue: PloS one
Year: 2018

Perception of a regular beat in music is inferred from different types of accents. For example, increases in loudness cause intensity accents, and the grouping of time intervals in a rhythm creates temporal accents. Accents are expected to occur on the beat: when accents are "missing" on the beat, the beat is more difficult to find. However, it is unclear whether accents occurring off the beat alter beat perception similarly to missing accents on the beat. Moreover, no one has examined whether intensity accents influence beat perception more or less strongly than temporal accents, nor how musical expertise affects sensitivity to each type of accent. In two experiments, we obtained ratings of difficulty in finding the beat in rhythms with either temporal or intensity accents, and which varied in the number of accents on the beat as well as the number of accents off the beat. In both experiments, the occurrence of accents on the beat facilitated beat detection more in musical experts than in musical novices. In addition, the number of accents on the beat affected beat finding more in rhythms with temporal accents than in rhythms with intensity accents. The effect of accents off the beat was much weaker than the effect of accents on the beat and appeared to depend on musical expertise, as well as on the number of accents on the beat: when many accents on the beat are missing, beat perception is quite difficult, and adding accents off the beat may not reduce beat perception further. Overall, the different types of accents were processed qualitatively differently, depending on musical expertise. Therefore, these findings indicate the importance of designing ecologically valid stimuli when testing beat perception in musical novices, who may need different types of accent information than musical experts to be able to find a beat. Furthermore, our findings stress the importance of carefully designing rhythms for social and clinical applications of beat perception, as not all listeners treat all rhythms alike.
Potential Role of Curcumin and Its Nanoformulations to Treat Various Types of Cancers
Venue: Biomolecules
Year: 2021

Cancer is a major burden of disease globally. Each year, tens of millions of people are diagnosed with cancer worldwide, and more than half of the patients eventually die from it. Significant advances have been noticed in cancer treatment, but the mortality and incidence rates of cancers are still high. Thus, there is a growing research interest in developing more effective and less toxic cancer treatment approaches. Curcumin (CUR) the major active component of turmeric (Curcuma longa L. has gained great research interest as an antioxidant, anticancer, and anti inflammatory agent. This natural compound shows its anticancer effect through several pathways including interfering with multiple cellular mechanisms and inhibiting/inducing the generation of multiple cytokines, enzymes, or growth factors including IkB kinase b (IkKb) tumor necrosis factor alpha (TNF a) signal transducer, and activator of transcription 3 (STAT3) cyclooxygenase II (COX 2) protein kinase D1 (PKD1) nuclear factor kappa B (NF kB) epidermal growth factor, and mitogen activated protein kinase (MAPK) Interestingly, the anticancer activity of CUR has been limited primarily due to its poor water solubility, which can lead to low chemical stability, low oral bioavailability, and low cellular uptake. Delivering drugs at a controlled rate, slow delivery, and targeted delivery are other very attractive methods and have been pursued vigorously. Multiple CUR nanoformulations have also been developed so far to ameliorate solubility and bioavailability of CUR and to provide protection to CUR against hydrolysis inactivation. In this review, we have summarized the anticancer activity of CUR against several cancers, for example, gastrointestinal, head and neck, brain, pancreatic, colorectal, breast, and prostate cancers. In addition, we have also focused on the findings obtained from multiple experimental and clinical studies regarding the anticancer effect of CUR in animal models, human subjects, and cancer cell lines.
Instagram Engagement for University
Venue: 2020 International Conference on Information Management and Technology (ICIMTech)
Year: 2020

Social media is used as an online communication today. In addition, institutions, schools, and companies make social media as a part of media marketing to introduce their brands. Instagram will be discussed in this study because the majority I Generation in Indonesia used Instagram. Universities use Instagram for marketing media by posting photos and videos with captions. Besides posting, the engagement between users and university social media accounts is very important for marketing purpose. In this research, we will learn about how much user engagement to university social media in Indonesia. The purpose of this research is to identify user's opinion about university Instagram official accounts and to analyze the engagement of five top universities official Instagram account in Indonesia with Analisa.io tool and questionnaire survey for one university as a case study. The result of this study can be used as advice or input about social media engagement for university official Instagram account.
From Visual Place Recognition to Navigation: Learning Sample Efficient Control Policies across Diverse Real World Environments
Venue: ArXiv
Year: 2019

Visual navigation tasks in real world environments often require both self motion and place recognition feedback. While deep reinforcement learning has shown success in solving these perception and decision making problems in an end to end manner, these algorithms require large amounts of experience to learn navigation policies from high dimensional inputs, which is generally impractical for real robots due to sample complexity. In this paper, we address these problems with two main contributions. We first leverage place recognition and deep learning techniques combined with goal destination feedback to generate compact, bimodal images representations that can then be used to effectively learn control policies at kilometer scale from a small amount of experience. Second, we present an interactive and realistic framework, called CityLearn, that enables for the first time the training of navigation algorithms across city sized, real world environments with extreme environmental changes. CityLearn features over 10 benchmark real world datasets often used in place recognition research with more than 100 recorded traversals and across 60 cities around the world. We evaluate our approach in two CityLearn environments where our navigation policy is trained using a single traversal. Results show our method can be over 2 orders of magnitude faster than when using raw images and can also generalize across extreme visual changes including day to night and summer to winter transitions.