nils-herrmann/clean_scirepeval huggingface dataset:
LabelMe video: Building a video database with human annotations
Venue: 2009 IEEE 12th International Conference on Computer Vision
Year: 2009

Currently, video analysis algorithms suffer from lack of information regarding the objects present, their interactions, as well as from missing comprehensive annotated video databases for benchmarking. We designed an online and openly accessible video annotation system that allows anyone with a browser and internet access to efficiently annotate object category, shape, motion, and activity information in real world videos. The annotations are also complemented with knowledge from static image databases to infer occlusion and depth information. Using this system, we have built a scalable video database composed of diverse video samples and paired with human guided annotations. We complement this paper demonstrating potential uses of this database by studying motion statistics as well as cause effect motion relationships between objects.
An Evaluation of the Performance Diagnostic Checklist Human Services (PDC HS) Across Domains
Venue: Behavior analysis in practice
Year: 2018

The Performance Diagnostic Checklist Human Services (PDC HS) is an informant based tool designed to assess the environmental variables that contribute to poor employee performance in human service settings. Although the PDC HS has been shown to effectively identify variables contributing to problematic performance, interventions based on only two of the four PDC HS domains have been evaluated to date. In addition, the extent to which PDC HS indicated interventions are more effective than nonindicated interventions for two domains remains unclear. In the current study, we administered the PDC HS to supervisors to assess the variables contributing to infrequent teaching of verbal operants and use of a timer by therapists at a center based autism treatment program. Each of the four PDC HS domains was identified as contributing to poor performance for at least one therapist. We then evaluated PDC HS indicated interventions for each domain. In addition, to assess the predictive validity of the tool, we evaluated various nonindicated interventions prior to implementing a PDC HS indicated intervention for two of the four domains. Results suggest that the PDC HS indicated interventions were effective across all four domains and were more effective than the nonindicated interventions for the two domains for which they were evaluated. Results are discussed in terms of the utility of the PDC HS to identify appropriate interventions to manage therapist performance in human service settings.
Translational medical mycology guides clinical and laboratory practice on fungal diseases
Year: 2014

Patients with fungal infection having skin lesions may consult a dermatologist, which is a diagnostic and therapeutic challenge. Dermatologists take samples from the lesion to check the fungal elements under a microscope by KOH preparation and then treat the patient. This model has advanced from bedside to bench and from bench to bedside (B to B to B) which is defined as Translational Medical Mycology. Dermatologists have an advantageous position in finding, isolating and identifying the pathogenic fungi and treating the patient with antifungal drugs. Samples should be cultured in different media with or without chloramphenicol and cycloheximide and incubated at room temperature or 37 Non culture techniques such as polymerase chain reaction based molecular identification, transmission electron microscopy, scanning electron microscopy, biochemistry tests and histopathology are also necessary to confirm the identification of the species, especially when the routine culture is negative. We start treatment upon obtaining evidence of fungal infection, i.e. positive KOH examination. Antifungal drugs such as itraconazole, fluconazole, terbinafine and amphotericin B can be used alone or in combination based on the fungal species and the location of the lesion. Practice on fungal infection includes screening of the patient, merging all of the laboratory techniques and methods from the microbiologists, pathologists, molecular researchers, identification of the pathogen and determination of the optimum antifungal drug.
Universal Scaling Laws in Schottky Heterostructures Based on Two Dimensional Materials.
Venue: Physical review letters
Year: 2018

We identify a new universality in the carrier transport of two dimensional (2D) material based Schottky heterostructures. We show that the reversed saturation current (J) scales universally with temperature (T) as log(J/T^{b} 1/T, with b=3/2 for lateral Schottky heterostructures and b=1 for vertical Schottky heterostructures, over a wide range of 2D systems including nonrelativistic electron gas, Rashba spintronic systems, single and few layer graphene, transition metal dichalcogenides, and thin films of topological solids. Such universalities originate from the strong coupling between the thermionic process and the in plane carrier dynamics. Our model resolves some of the conflicting results from prior works and is in agreement with recent experiments. The universal scaling laws signal the breakdown of b=2 scaling in the classic diode equation widely used over the past sixty years. Our findings shall provide a simple analytical scaling for the extraction of the Schottky barrier height in 2D material based heterostructures, thus paving the way for both a fundamental understanding of nanoscale interface physics and applied device engineering.
COVID 19: Is herd immunity the only option for fragile Yemen?
Venue: International Journal of Infectious Diseases
Year: 2021

The first case of COVID 19 in Yemen was confirmed on 10 April 2020. Having faced with a six year long conflict that has destroyed half of its healthcare facilities and displaced millions, predictions of infections and mortality in Yemen suggested a looming healthcare catastrophe. Difficulty in implementing coordinated lockdowns and preventive measures due to the daily labor working nature of the majority of the population, provided the perfect breeding ground for the SARS CoV 2 virus. However, official figures of infections and mortality are very low and there have not been confirmed reports of excess mortality. This could indicate that Yemen is silently marching towards forced herd immunity. Seroprevalence studies will provide useful insight into the COVID 19 transmission trajectory in Yemen, which can serve as a guide in planning vaccine distribution strategies and allocating the limited funds wisely.
Effect of Specific Load of Bearing on the Centrifugal Compressor Rotordynamic Stability
Year: 2015

With the ever increasing of the centrifugal compressor capability, such as large scale LNG and CO2 re injection, the stability margin evaluation and instability control is crucial both for the centrifugal compressor OEM and end users. An industrial scale experimental test rig with two 5 pads tilting pad journal bearings and two active magnetic bearings was introduced. Tilting pad bearings were used to support the rotor, and active magnetic bearings were used to exert static load and sub synchronous sine load to excite the rotor. The logarithmic decrement identification method of rotor bearing system was presented. Here, weighted instrument variable and directional frequency response function were combined to improve anti noise performance and separate forward/ backward whirl vibration. Thermoelastohydrodynamic bearing model was used to investigate the effect of hot clearance on the stability prediction of centrifugal compressor. Also, the contribution of bearing specific load on the stability was studied numerically. Also, experimental work was carried out to investigate the damping ratio of rotor under different rotating speed and bearing specific loads. The numerical results correlate with the test results very well. The results of the investigation indicate that: (i) Hot clearance is very important for centrifugal compressor rotordynamic instability prediction; (ii) The effect of pad mechanical deformation are smaller than that of thermal deformation; (iii) With the increase of bearing specific load, the logarithmic decrement is decreasing.
Pervasive device and service discovery protocol in XBee sensor network
Venue: 2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS)
Year: 2016

Internet of Things is a novel paradigm that combined microcomputer and wireless communication technology. IoT device will be considered as a pervasive and ubiquitous device that able to interact with it user and environment autonomously with minimum human intervention. At present, wireless technology already has pervasive features in the link and the network layer. They able to do the dynamic addressing, finding a neighbor and do the routing task such as in Xbee technology. In the future, pervasive sensing will support adaptive context aware services that are not provided by the wireless sensor network protocol in the link and the network layer. Our research proposed pervasive device and service discovery protocol at the application level by creating a protocol in the smart sensor device and the smart sensor gateway. By implementing our protocol, the sensor network gateway is able to find each of the sensor network device and service descriptions and request the on demand service to the smart sensor device. The protocol is implemented in two Arduino Uno integrated with XBee transceiver as the smart sensor device and the raspberry pi as the smart sensor gateway. Result shows, the gateway was able to find both device and service description in the smart sensor network with 4.13 seconds average time. The average round trip time for request and response data from the gateway is 0.201 seconds.
Translating and Assessing Indonesian Folktales to Students from Japan, China, South Korea and Translating Brochure and Website Contents in the Union Institute of Language in Brisbane, Australia
Year: 2019

This final report is written based on the internship program at Union Institute of Language in Brisbane, Australia. It started from August 26 to September 18, 2018. The objective of this final report is to describe the activities during the internship at Union Institute of Language in Brisbane, Australia. The writer did two kinds of internship activities, those were main activities and secondary activities. The main activities were translating and assessing Indonesian folktales and presenting them to students from Japan, China, and South Korea as well as translating procedural documents such as the official brochure and website contents of Union Institute of Language from English to Bahasa Indonesia. The secondary activities were classes provided by UIL about how to do a presentation, write a resume, curriculum vitae and report, and prepare for a job interview. The writer also visited a variety of Australian business and education providers. There were some problems the writer faced during the process of this internship including bad internet connections, difficulties in managing assignments due to deadlines, the lack of photo editing ability, and finding equivalent words in translating documents from English to Indonesian. The strategies the writer applied to solve those difficulties were buying an Australian SIM card in order to have my own hotspot, continuing the task at home or on weekends, operating the easiest photo editing software, using online and offline dictionaries, searching explanations on journals or specific websites, and discussing the translation with internship partners and supervisor.
Survival Rate of Calves and Assessment Reproductive Performance of Heifers and Cows in Dida Tuyura Ranch, Borana Zone, Southern Ethiopia
Venue: Veterinary Medicine Open Journal
Year: 2019

which allows to copy, redistribute, remix, transform, and reproduce in any medium or format, even commercially, provided the original work is properly cited. 1 Retrospective Study Volume 4 Issue 1| cc  The study was conducted at Dida Tuyura Cattle Breeding and Improvement Ranch in Borana zone, southern Ethiopia, with the aims of determining the mortality rate of Ethiopian Boran calves and assessment of the reproductive performance of heifers and cows.  The study was based on the retrospective record of calves, heifers, and cows. The data was taken from 1994 2010 on the calf survival rate and 1994 2005 on reproductive performance of the breed in the ranch were used for this study. The retrospective data collected over the years were used to identify factors associated with calf survival or death.  The mortality rate of calves before weaning and after weaning was 13.3% and 11.2% respectively. Age, sex and birth weight of calf had a significant effect on survival rate. The overall mean values age at first service, age at first calving, calving interval, days open and gestation length were 42.52, 51.67, 20.67, 11.30 and 9.30 months, respectively. Parity had a significant effect on both the calving interval and days open. Gestation length was not significantly affected by parity, sex, and birth weight of calf.  From the present study, it can be concluded that the obtained calf survival rate and reproductive performance are not sufficient to achieve the established objective of the ranch.
An embedded deep learning system for augmented reality in firefighting applications
Venue: 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA)
Year: 2020

Firefighting is a dynamic activity, in which numerous operations occur simultaneously. Maintaining situational awareness (i.e. knowledge of current conditions and activities at the scene) is critical to the accurate decision making necessary for the safe and successful navigation of a fire environment by firefighters. Conversely, the disorientation caused by hazards such as smoke and extreme heat can lead to injury or even fatality. This research implements recent advancements in technology such as deep learning, point cloud and thermal imaging, and augmented reality platforms to improve a firefighter's situational awareness and scene navigation through improved interpretation of that scene. We have designed and built a prototype embedded system that can leverage data streamed from cameras built into a firefighter's personal protective equipment (PPE) to capture thermal, RGB color, and depth imagery and then deploy already developed deep learning models to analyze the input data in real time. The embedded system analyzes and returns the processed images via wireless streaming, where they can be viewed remotely and relayed back to the firefighter using an augmented reality platform that visualizes the results of the analyzed inputs and draws the firefighter's attention to objects of interest, such as doors and windows otherwise invisible through smoke and flames.
Feng Shui principles and the Malaysian housing market: what matters in property selection and pricing?
Year: 2020

This study aims to investigate Feng Shui elements that can influence housing selection and property pricing in the Malaysian housing market.,A structured questionnaire encompassing 26 Feng Shui elements, which were shortlisted based on relevant previous studies, was distributed to prospective homebuyers in the Klang Valley region. The elements were inferred and ranked according to frequency, significance and importance scores. Kruskal Wallis ANOVA tests were used to assess the ratings provided by the different respondent groups, while Spearman's rank correlation tests were utilised to measure the degree of agreement or disagreement among each pair of the ethnic group.,The results obtained indicate the following as the five most influential elements: orientation, main entrance, street location, house number and living room. Despite a multiethnic and multicultural society in Malaysia, Spearman's rank correlation tests showed that there are no differences in the prioritisation of Feng Shui elements between three distinct ethnic groups (Malay, Chinese and Indian) However, the distribution scores are statistically different between the groups. Comparing income level with Feng Shui inclinations, the three most frequently considered elements across the three income groups consistently include orientation, main entrance and street location.,The findings of this study are expected to provide guidance to property stakeholders (developers, real estate agencies, architects, local authorities) in their future development projects. For homebuyers, this study serves as a property Feng Shui checklist for home selection and investment.,This study explored the association of Feng Shui principles to housing selection and property pricing based on cultural and income factors. These findings provide useful insights for designing and positioning of residential properties in both primary and secondary housing markets in Malaysia and beyond.
Developing Gamified Instructional Materials in Genetics for Grade 12 STEM
Year: 2019

As technology advances, the demand for innovative instructional materials also increases. As a result, the Department of Education urges teachers to develop instructional materials. This study was conducted at Bulusan National High School, Bulusan, Sorsogon, Philippines SY 2018 2019 which was aimed to develop gamified instructional materials in genetics that would aid in teaching and learning process of grade 12 STEM students. The developed gamified materials were collectively called the GIM in Genetics which is comprised of two parts; namely, Student's Portfolio and Gamified Lesson Plans. The GIM was anchored on the Teacher's Guide provided by DepEd. Further, it utilized different game elements, to wit: game mechanics, badges, power cards, scoring system, levels, and leaderboards to deliver innovative teaching strategy and quality education. This paper suggests the development of various innovative teaching strategies and instructional materials as well as its utilization across different fields and subject areas.
Multi target human gait classification using LSTM recurrent neural networks applied to micro Doppler
Venue: 2017 European Radar Conference (EURAD)
Year: 2017

A Recurrent Neural Network (RNN) with a Long Short Term Memory (LSTM) implementation can be effectively utilized to classiiy the radar signature of zero to three human gaits, based on their micro Doppler return. The LSTM RNN outperforms the current state of the art with an accuracy of 89.1% The use of a sequence to sequence classification method like RNN additionally brings the benefit of being able to classify measurements with a variable observation time which, on average, is notably less than the state of the art. Another advantage of the LSTM RNN is that it can also be used with measurements that include transitions between classes over time.
Robust time varying Kalman predictor for descriptor system with random one step measurement delays
Venue: 2020 IEEE 16th International Conference on Control Automation (ICCA)
Year: 2020

For the linear stochastic descriptor system with random one step measurement delays and uncertain noise variances, the robust time varying Kalman prediction problem is addressed. The singular value decomposition (SVD) method, the randomization approach and the augmented state approach are presented, which are applied to transform the descriptor system with random one step measurement delay and uncertain noise variances to the standard non descriptor system only with fictitious uncertain variance white noises. For this standard non descriptor system, the minimax robust time varying Kalman predictor is presented based on the minimax robust estimation principle in the sense that its actual prediction error variance is guaranteed to have the corresponding minimal upper bound for all admissible uncertainties. Their robustness is proved by the Lyapunov equation approach. A simulation example about circuits system verifies the correctness of the proposed results.
Classification of Cotton Leaf Spot Disease Using Support Vector Machine
Year: 2014

In order to obtain more value added products, a product quality control is essentially required Many studies show that quality of agriculture products may be reduced from many causes. One of the most important factors of such quality plant diseases. Consequently, minimizing plant diseases allows substantially improving quality of the product Suitable diagnosis of crop disease in the field is very critical for the increased production. Foliar is the major important fungal disease of cotton and occurs in all growing Indian cotton regions. In this paper I express Technological Strategies uses mobile captured symptoms of Cotton Leaf Spot images and categorize the diseases using support vector machine. The classifier is being trained to achieve intelligent farming, including early detection of disease in the groves, selective fungicide application, etc. This proposed work is based on Segmentation techniques in which, the captured images are processed for enrichment first. Then texture and color Feature extraction techniques are used to extract features such as boundary, shape, color and texture for the disease spots to recognize diseases.
A Deep Neural Network for Chinese Zero Pronoun Resolution
Venue: IJCAI
Year: 2017

Existing approaches for Chinese zero pronoun resolution overlook semantic information. This is because zero pronouns have no descriptive information, which results in difficulty in explicitly capturing their semantic similarities with antecedents. Moreover, when dealing with candidate antecedents, traditional systems simply take advantage of the local information of a single candidate antecedent while failing to consider the underlying information provided by the other candidates from a global perspective. To address these weaknesses, we propose a novel zero pronoun specific neural network, which is capable of representing zero pronouns by utilizing the contextual information at the semantic level. In addition, when dealing with candidate antecedents, a two level candidate encoder is employed to explicitly capture both the local and global information of candidate antecedents. We conduct experiments on the Chinese portion of the OntoNotes 5.0 corpus. Experimental results show that our approach substantially outperforms the state of the art method in various experimental settings.