nils-herrmann/clean_scirepeval huggingface dataset:
IoT enabled Smart Fog Computing for Vehicular Traffic Control
Year: 2019

Internet was initially designed to connect web sites and portals with data packets flowing over the networks for communications at corporate levels. Over time, live video streaming, real time data and voice is being offered over hosted Clouds for business entertainment. Enterprise applications like Office 365, banking and e commerce are available over smartphones. With the advent of Fog Computing and Internet of Things, corporate enterprises and non IT industries see potential in this technology. Billions of Internet enabled devices, globally distributed nodes, embedded sensor gateways transmit real time generated over the internet to the cloud data centres. Cloud environments are not designed to handle this level of data that is being generated and Computing limits are being severely tested. Fog Computing has the potential to be the go to option for Cloud service delivery.  This paper reviewed existing research works and presents unique Smart Fog Computing based taxonomy. The authors also implemented experimental setup for Smart Cities using Smart Fog Computing for controlling Vehicular traffic.  Smart Vehicular Management is viable use case for Fog and IoT technology. The authors designed and implemented two experimental setups. The first setup involves standard Cloud implementation and the second setup employs Fog Computing implemented using IoT Sensor nodes to compare the performance of the Vehicle Management Fog application regarding the Response time and Bandwidth Consumed. The architecture and implementation involved deploying 50 IoT sensors nodes across the university areas and routes.  The main results obtained in this paper are the following. As compared to Cloud computing, on deploying Fog Computing and IoT devices: End to End Processing time dropped from 29.44 to 6.7 seconds almost 77% less Number of hops traversed reduced from 56 to 4 hops almost 92% less Bandwidth usage dropped from 247 to 8 kbps almost 96.7% less  From the experimental setups as compared to Cloud computing, the Fog and IoT processes the traffic data locally on the edge devices, which reduces the end to end time.
Tinjauan hukum ekonomi Syariah terhadap penentuan harga di Restoran Sezuqa All You Can Eat Bandung
Year: 2019

Pelaksanaan jual beli makanan dengan dua konsep yaitu makanan per porsi dan makanan bayar satu harga dapat makan sepuasnya. Dua konsep yang berbeda ini menimbulkan perbedaan pelayanan dan perbedaan harga diantara keduanya. Penetapan harga restoran dalam dua konsep berbeda. Penelitian ini berdasarkan pada pemikiran bahwa penentuan suatu harga seharusnya memenuhi unsur keadilan dan berlaku secara umum. Adanya dua konsep pada Restoran Sezuqa "All You Can Eat" adalah sebuah ketidakadilan bagi pembeli. Pada Restoran Sezuqa "All You Can Eat" Bandung terdapat perbedaan pelayanan yaitu sistem ambil sendiri dan dilayani dan terdapat selisih harga yang cukup jauh apabila seluruh jenis makanan di pesan dengan jumlah yang sama namun dengan konsep yang berbeda. Jika ditotalkan harga makanan per porsi Rp. 205.000,00 dan harga makanan sepuasnya Rp. 42.500,00 terjadi selisih harga. Penentuan harga seharusnya didasari dengan cara dan tujuan yang benar sesuai syariat islam yang berlaku. Penelitian ini bertujuan untuk mengetahui: 1. Konsep Restoran Sezuqa "All You Can Eat" Bandung, 2. penentuan harga jual makanan per porsi dan makanan sepuasnya di Restoran Sezuqa "All You Can Eat" Bandung. 3. Tinjauan hukum ekonomi syariah terhadap penentuan hargadi Restoran Sezuqa "All You Can Eat" Bandung. Metode yang digunakan dalam penelitian ini adalah metode studi kasus, dengan metode ini diharap dapat mendeskripsikan analisis secara utuh sebagai satu kesatuan yang terintegrasi dalam penelitian mengenai perekonomian khususnya dalam jual beli yang terjadi di masyarakat. Adapun teknik pengumpulan datanya adalah wawancara, observasi dan studi kepustakaan. Setelah data terkumpul data kemudian dianalisis dengan menggunakan metode deskriptif. Berdasarkan data yang ditemukan di lapangan bahwa penetapan harga yang berbeda di Restoran Sezuqa "All You Can Eat" Bandung, dalam tinjauan Hukum Ekonomi Syariah telah sesuai dengan konsep harga dalam Islam dan standar pelayanan yang baik. Berdasarkan kaidah urf tijari "Sesuatu yang dikenal diantara masyarakat itu seperti menjadi syarat dikalangan mereka"Sesuatu yang telah dikenal karena 'urf seperti yang disyaratkan dengan suatu syarat yakni Sesuatu yang telah dikenal antara pedagang berlaku sebagai syarat diantara mereka.
Numerical study on wave phenomena produced by the super high speed evacuated tube maglev train
Venue: Journal of Wind Engineering and Industrial Aerodynamics
Year: 2019

With the increasing demand of faster, safer, and more comfortable rail travel, the evacuated tube maglev train (ETMT) has gradually attracted hot concerns in recent years. According to Kantrowitz limit theory, ETMT may encounter chocked flows, leading to more complex generation and development of a series of waves as ETMT moves rapidly in the tube. To study the wave phenomena produced by ETMT running at the super high speed, the computational domain geometry model was simplified and then 2 D axisymmetric compressible N S equation was established in the paper. Dynamic mesh method and dynamic adaptive mesh method were used to simulate the real motion of ETMT and improve the capture accuracy of the waves respectively. Results show that the wave structure is mainly composed of expansion waves, reflected shock waves and normal shock waves as ETMT moves for enough time at the speed of 1250 km/h. The intensity of the normal shock wave in front of the head car experiences four states consisting of rapid increase, initial stability, sudden drop and final stability. In the wake, the flow velocity attenuates in a fluctuating way along the opposite motion direction of ETMT due to the complicated interaction between shock waves and expansion waves.
The Effects of Sport Education and Fine Arts Education on Social Appearance Anxiety
Venue: Journal of Education and Training Studies
Year: 2019

The purpose of this study is to compare the social appearance anxiety levels of university students studying in different fields. Social appearance anxiety scales which were filled in by 481 students were assessed in the study. T test and one way ANOVA were used for statistical analysis, while LSD tests were used to find out differences.Social appearance anxiety scale scores were found to be higher in male students when compared with female students. No statistically significant difference was found between social appearance anxiety scale scores in terms of genders (p>0.05) In terms of field of education, social appearance anxiety scale scores of students receiving sport education were found to be lower than the scores of students receiving art and music education and the highest social appearance anxiety scale scores were found in students in the department of educational sciences. Statistically significant difference was found between social appearance anxiety scale scores in terms of field of education (p<0.001).As a conclusion, it was found that sport education caused a higher decrease in social appearance anxiety when compared with fine arts education, while fine arts education caused a decrease in social appearance anxiety when compared with students who received neither sport nor fine arts education. In terms of social appearance contribution, it is thought that art and music education have similar effects to those of sport. Giving sport education to students who are not receiving sport education or making them do sport and giving those interested in sport a chance to be interested in art can be a factor in decreasing social appearance anxiety.
Performance optimization of MapReduce based Apriori algorithm on Hadoop cluster
Venue: Comput. Electr. Eng.
Year: 2018

Many techniques have been proposed to implement the Apriori algorithm on MapReduce framework but only a few have focused on performance improvement. FPC (Fixed Passes Combined counting) and DPC (Dynamic Passes Combined counting) algorithms combine multiple passes of Apriori in a single MapReduce phase to reduce the execution time. In this paper, we propose improved MapReduce based Apriori algorithms VFPC (Variable Size based Fixed Passes Combined counting) and ETDPC (Elapsed Time based Dynamic Passes Combined counting) over FPC and DPC. Further, we optimize the multi pass phases of these algorithms by skipping pruning step in some passes, and propose Optimized VFPC and Optimized ETDPC algorithms. Quantitative analysis reveals that counting cost of additional un pruned candidates produced due to skipped pruning is less significant than reduction in computation cost due to the same. Experimental results show that VFPC and ETDPC are more robust and flexible than FPC and DPC whereas their optimized versions are more efficient in terms of execution time.
How Limiting Fast Food Consumption Effects Food Waste
Year: 2019

By Alexus Wimbish, Environmental Studies Advisor: Amy Townsend Small Presentation ID: PM_ATRIUM13 Abstract: Food packaging proves to be one of the leading wastes found in landfills. The Green Cincinnati Plan of Action has a goal to decrease residential tonnage to landfills by 20% and an overall goal of producing zero waste by 2035. I plan to investigate the effectiveness of limiting or removing fast and packaged foods from peoples diets in an attempt to reduce waste. I plan to do this by challenging City of Cincinnati employees to spend a month preparing lunch and snacks at home in a sustainable fashion, rather than going to fast food restaurants or the vending machines at work. I hope to find that reducing the use of fast food and snacks proves to be a much healthier and sustainable lifestyle in a very short amount of time.
Capillary Refill Time
Year: 2020

Capillary refill time (CRT) is a useful and rapid metric in determining the intravascular volume status of ill patients, particularly those with conditions that arise or result from hypovolemia. Examples of these pathologic states include but are not limited to: hypo and hyperthermia, all forms of shock, hemorrhage, loss of plasma volume in burns, gastrointestinal losses through diarrhea or vomiting, over diuresis, and anaphylactic reactions Information obtained from CRT assessment can then be used to guide fluid resuscitation strategies, reassess an implemented therapy, and define the endpoint of treatment. Volume status can also be assessed via an assortment of other clinical exams and objective measurements. Briefly, markers of reduced perfusion include abnormal vital signs (hypotension, tachycardia, increased pulse pressure variation) deranged physical exam findings (delayed CRT, dry mucous membranes, poor skin turgor, absence of diaphoresis, altered mental status) More objective indicators of hypovolemia include laboratory abnormalities (increased BUN, increased creatinine, increasing lactate, fluctuating hemoglobin levels, increased urine specific gravity, presence of oliguria/anuria) and radiographic derangements (increased collapsibility of the IVC on ultrasound, reduced cardiac chamber diameters on ultrasound or CT, changes in transpulmonary thermodilution) While accurate assessment of intravascular volume status is best accomplished through a combination of these methods, this article will focus specifically on the measurement of capillary refill time and it's growing application in guiding medical diagnosis and subsequent management.
The impact of an in vehicle display on glance distribution in partially automated driving in an on road experiment
Year: 2018

One of the major challenges of designing an HMI for partially automated vehicles is the trade off between a sufficient level of system information and avoidance of distracting the driver. This study aimed to investigate drivers' glance behavior as an indicator of distraction when vehicle guidance is partially automated. Therefore, an on road experiment was conducted comparing two versions of an in vehicle display (during partially automated driving) and no display (during manual driving) on a heavy congested highway segment. The distribution of drivers' total glance durations on the HMI showed that visual attention was shifted away from monitoring the central road scene towards looking at the in vehicle display to a considerable extent. However, an analysis of the distribution of single glance durations supports the view that using partial automation and a respective HMI does not lead to a critical increase in distraction. Driving with a simplified version of the HMI had the potential to reduce glance duration on and thus potential distraction of the in vehicle display.
A Koopman based Deep Convolutional Network for Modeling Latent Dynamics from Pixels
Year: 2021

With the development of end to end control based on deep learning, it is important to study new system modeling techniques to realize dynamics modeling with high dimensional inputs. In this paper, a novel Koopman based deep convolutional network, called CKNet, is proposed to identify latent dynamics from raw pixels. CKNet learns an encoder and decoder to play the role of the Koopman eigenfunctions and modes, respectively. The Koopman eigenvalues can be approximated by eigenvalues of the learned state transition matrix. The deterministic convolutional Koopman network (DCKNet) and the variational convolutional Koopman network (VCKNet) are proposed to span some subspace for approximating the Koopman operator respectively. Because CKNet is trained under the constraints of the Koopman theory, the identified latent dynamics is in a linear form and has good interpretability. Besides, the state transition and control matrices are trained as trainable tensors so that the identified dynamics is also time invariant. We also design an auxiliary weight term for reducing multi step linearity and prediction losses. Experiments were conducted on two offline trained and four online trained nonlinear forced dynamical systems with continuous action spaces in Gym and Mujoco environment respectively, and the results show that identified dynamics are adequate for approximating the latent dynamics and generating clear images. Especially for offline trained cases, this work confirms CKNet from a novel perspective that we visualize the evolutionary processes of the latent states and the Koopman eigenfunctions with DCKNet and VCKNet separately to each task based on the same episode and results demonstrate that different approaches learn similar features in shapes.
Rancang Bangun Alat Penjejak Sinar Matahari dan Monitoring Delphi Berbasis Mikrokontroler pada Panel Surya
Year: 2020

Pembangkit Listrik Tenaga Surya (PLTS) merupakan salah satu inovasi penerapan teknologi energi baru terbarukan yang ramah lingkungan dan memiliki potensi ketersediaan energi yang tidak terbatas. Pemasangan panel surya yang saat ini kebanyakan dalam keadaan statis atau diam sehingga kurang optimal dalam proses penyerapan sinar matahari. Untuk penyerapan sinar matahari yang optimal diperlukan adanya sistem yang dapat menggerakkan panel surya selalu tegak lurus dengan arah pantulan sinar matahari. Alat ini bergerak secara vertikal dan horizontal dengan dua buah motor DC dan sensor Light Dependent Resistor (LDR) berbasis mikrokontroler. Alat ini juga dapat dikontrol dan dimonitor pada aplikasi visual Dephi 7. Untuk pengujian alat, dilakukan pengujian panel surya 50Wp pada keadaan tanpa beban dan berbeban dengan dua kondisi yaitu outdoor dan indoor Pengujian outdoor tanpa penggerak diperoleh total energi sebesar 85.76 Wh sedangkan bergerak sebesar 125.99 Wh selama 6 jam mulai pukul 9:00 s/d 15:00 dengan 19 kali data pengujian setiap 20 menit. Pengujian indoor menggunakan lampu dilengkapi dengan stand sudut. Hasil pengujian pada keadaan alat diam diperoleh Tegangan Hubung Buka (Voc) sebesar 4.02 V dan Arus Hubung Singkat (Isc) sebesar 6.88 mA sedangkan pada keadaan alat bergerak Tegangan Voc sebesar 4.28 V dan Arus Isc sebesar 7.96 mA.
Rapid Synthesis of a Long Double Stranded Oligonucleotide from a Single Stranded Nucleotide Using Magnetic Beads and an Oligo Library
Venue: PloS one
Year: 2016

Chemical synthesis of oligonucleotides is a widely used tool in the field of biochemistry. Several methods for gene synthesis have been introduced in the growing area of genomics. In this paper, a novel method of constructing dsDNA is proposed. Short (28 mer) oligo fragments from a library were assembled through successive annealing and ligation processes, followed by PCR. First, two oligo fragments annealed to form a dsDNA molecule. The double stranded oligo was immobilized onto magnetic beads (solid support) via streptavidin biotin binding. Next, single stranded oligo fragments were added successively through ligation to form the complete DNA molecule. The synthesized DNA was amplified through PCR and gel electrophoresis was used to characterize the product. Sanger sequencing showed that more than 97% of the nucleotides matched the expected sequence. Extending the length of the DNA molecule by adding single stranded oligonucleotides from a basis set (library) via ligation enables a more convenient and rapid mechanism for the design and synthesis of oligonucleotides on the go. Coupled with an automated dispensing system and libraries of short oligo fragments, this novel DNA synthesis method would offer an efficient and cost effective method for producing dsDNA.
Blockchain Enabled Trustless API Marketplace
Venue: 2020 International Conference on COMmunication Systems NETworkS (COMSNETS)
Year: 2020

There has been an unprecedented surge in the number of service providers offering a wide range of machine learning prediction APIs for tasks such as image classification, language translation, etc. thereby monetizing the underlying data and trained models. Typically, a data owner (API provider) develops a model, often over proprietary data, and leverages the infrastructure services of a cloud vendor for hosting and serving API requests. Clearly, this model assumes complete trust between the API Provider and cloud vendor. On the other hand, a malicious/buggy cloud vendor may copy the APIs and offer an identical service, under report model usage metrics, or unfairly discriminate between different API providers by offering them a nominal share of the revenue. In this work, we present the design of a blockchain based decentralized trustless API marketplace that enables all the stakeholders in the API ecosystem to audit the behavior of the parties without having to trust a single centralized entity. In particular, our system divides an AI model into multiple pieces and deploys them among multiple cloud vendors who then collaboratively execute the APIs. Our design ensures that cloud vendors cannot collude with each other to steal the combined model, while individual cloud vendors and clients cannot repudiate their input or model executions.
Impact of shape of container on natural convection and melting inside enclosures used for passive cooling of electronic devices
Year: 2011

The present paper numerically analyzes a passive cooling system using enclosures with different geometries filled with thermal conductivity enhanced phase change material (PCM) A numerical code is developed using an unstructured finite volume method and an enthalpy porosity technique to solve for natural convection coupled to a solid liquid phase change. Five geometries containing the same volume of PCM are compared while cooling the same surface. The unsteady evolution of the melting front and the velocity and temperature fields is detailed. Other indicators of cooling efficiency are monitored, including the maximum temperature reached at the cooled surface. The computational results show the high impact of varying geometry: a maximum temperature difference as high as 40 degC is observed between two of the enclosures. The best efficiency is obtained for an enclosure shifted vertically relative to the cooled surface. Other findings and recommendations are made for the design of PCM filled enclosures.
Do Green Products Make Us Better People?
Venue: Psychological science
Year: 2010

Consumer choices reflect not only price and quality preferences but also social and moral values, as witnessed in the remarkable growth of the global market for organic and environmentally friendly products. Building on recent research on behavioral priming and moral regulation, we found that mere exposure to green products and the purchase of such products lead to markedly different behavioral consequences. In line with the halo associated with green consumerism, results showed that people act more altruistically after mere exposure to green products than after mere exposure to conventional products. However, people act less altruistically and are more likely to cheat and steal after purchasing green products than after purchasing conventional products. Together, our studies show that consumption is connected to social and ethical behaviors more broadly across domains than previously thought.
Power Ups in Digital Games: The Rewarding Effect of Phantom Game Elements on Player Experience
Venue: CHI PLAY
Year: 2019

Power ups are a type of game reward that allow the player to customise their experience by altering gameplay for a short period of time. Despite the wide use of power ups in video games, little is known about their effect on gaming experiences. To explore this, we conducted an experimental study that compares the experiences of players depending on their exposure to power ups in a recreational video game. The results show that players who collected power ups felt significantly more immersed in the game, experienced more autonomy, but did not feel more competent or challenged than those who played the game without these collectables. Interestingly, a similar effect was observed for those players who picked up 'placebo' power ups, despite the items having no effect on the gameplay. We provide a discussion of these results and their implications both for games user researchers and game designers.
Exploring the Progression of Early Programmers in a Set of Computational Thinking Challenges via Clickstream Analysis
Venue: IEEE Transactions on Emerging Topics in Computing
Year: 2020

In recent years, many initiatives have aimed to develop basic computational thinking skills. Despite the popularity of online platforms for early programmers, we still lack detailed information to analyze how these skills are acquired. In the present study we analyzed clickstream data from 3,355 participants enrolled in several Computational Thinking workshops using Kodetu, an online platform with fine grained logging features. Participants used Kodetu's coding blocks to solve challenges of increasing difficulty while we gathered their clickstream in the platform. Here, we present our findings after evaluating these data in regards of participants' characteristics (age, sex, previous knowledge) similarity with previously submitted solutions, and degree of discrepancy from the optimal solution. To facilitate collaboration with other researchers in this area, we released our dataset under an open license. To the best of our knowledge, this is the largest Computational Thinking related datasets publicly available.