nils-herrmann/clean_scirepeval huggingface dataset:
PENGARUH PENAMBAHAN SERBUK HIDROKSIAPATIT CANGKANG KERANG DARAH PADA RESIN AKRILIK BAHAN PEMBUAT GIGI TERHADAP SIFAT MEKANIK UNTUK APLIKASI GIGI TIRUAN
Year: 2017

Pada saat ini resin akrilik merupakan bahan utama untuk pembuatan gigi tiruan. Namun, bahan resin akrilik untuk gigi buatan ini sulit di peroleh dan harus diimpor dengan harga yang mahal. Untuk itu diperlukan usaha mencari alternatif bahan pengganti yang mempunyai biokompatibitas baik terhadap tubuh manusia salah satunya bahan dari hidroxsiapatit (HA) HA adalah kalsium fosfat dengan formula kimia Ca10(PO4)6(OH)2 banyak digunakan dalam bidang kedokteran dan kedokteran gigi sebagai tulang buatan dan akar gigi tiruan. HA bisa didapatkan dari tulang, gigi binatang, cangkang telur, kerang dan sebagainya. Bahan tersebut tersedia melimpah di Indonesia, namum belum termanfaatkan dengan baik. Salah satu yang cukup berpotensi adalah cangkang kerang. Serbuk HA yang diperoleh dari cangkang kerang akan digunakan sebagai pencampur bahan gigi tiruan impor (sintetis) Dengan substitusi bahan impor dengan serbuk HA dari cangkang kerang, diharapkan ketergantungan bahan impor bisa dikurangi. Material dari kerang darah yang dikoleksi dari Kuala tungkal Jambi dicuci kemudian dikeringkan, setelah itu dihaluskan dengan ditumbuk, dihaluskan dengan pulvarizer, kemudian dilanjutkan dengan ball mill hingga diperoleh serbuk dengan kehalusan hingga 62 um. Serbuk kerang darah dikalsinasi di dalam furnace pada temperatur 200, 400, 600 dan 800 oC dengan waktu pemanasan 30 menit dan waktu istirahat 10 menit, selanjutnya serbuk HA yang diperoleh dari proses pemanasan ini, siap digunakan sebagai kalsium sumber sintetis. Serbuk Hidroksiapati cangkang kerang darah (HACK) kemudian dicampur dengan Tepung akrilik resin bahan pembuat gigi (TRA) dan Cairan Akrilik Resin (CRA) dengan persentase berat campuran masing masing divariasikan. Campuran ketiga bahan ini selanjutnya dicetak menurut ukuran (dia. 10x10mm) kemudian dikeringkan di dalam alat pengering (magic com) Sampel yang telah jadi dikarakterisasi untuk mengetahui sifat sifat mekaniknya. Hasil Penelitian menunjukkan bahwa campuran serbuk HA dari cangkang kerang darah (HACK) dengan tepung resin akrilik (TRA) menghasilkan kekuatan tekan hingga 176 MPa dan kekerasan hingga 0,26 GPa. Dari kekuatan tekan sudah memenuhi persyaratan sebagai material penambah dalam pembuatan gigi tiruan sedangkan kekerasan belum memenuhi persyaratan. Oleh sebab itu perlu diteliti lebih lanjut untuk meningkatkan pengaruh kekerasan HACK terhadap TRA sehingga dapat memenuhi syarat sebagai bahan penambah material gigi tiruan.  Hidroksiapatit HACK, TRA, sifat mekanik.
Recognition of Side scan Sonar Shipwreck Image Using Convolutional Neural Network
Venue: 2020 2nd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI)
Year: 2020

In order to enable the AUV to quickly and automatically identify the image of the side scan sonar shipwreck, improve the speed of search and rescue of wrecked ships and the accuracy of the verification of shipwreck targets in submarine obstacles. Aiming at the limitation that AUV side scan sonar image data cannot be transmitted in real time, a method for recognizing shipwreck image of side scan sonar image based on convolutional neural network is proposed. Sample data is expanded through standardization and normalization processing, data augmentation, etc. according to the characteristics of the side scan sonar image sample data set, referring to the classic convolutional neural network VGG 16 model, a simplified convolutional neural network model is constructed; by adding Dropout, the joint adaptability between neuron nodes of the model is weakened, overfitting is reduced, and generalization ability is improved. The experimental results show that the accuracy of the model to the side scan sonar shipwreck image recognition can reach 90.58%
BAGAIMANA CONSUMER PERCEPTION DAN CONSUMER ATTITUDE MEMPENGARUHI MOTIVASI PEMBELIAN GREEN PRODUCT (KAJIAN PERILAKU KONSUMEN DARI BERBAGAI BUDAYA DAN NEGARA)
Venue: Competence Journal of Management Studies
Year: 2019

ABSTRA CT Currently, the environmental damage occurs almost throughout the earth. Many people try to find the way to save the environment. It causes the companies to make green products in the contribution of protecting the environtment. But not everyone can accept the green product. This study case choose svarious countr ies, such as Niger, China, United State s India, Lesotho, Italia, Sweden, South Korea, and Hong Kong. Not all countries have good perception and good attitude toward s green product s but most of them have good perception toward s green product s and they have good attitude if the green product s can give them a benefit. Marketers can give more education about green product to countries which have negative perception and negative attitude towards green product. Marketers also have a big opportunity to market their green product to countries which have a positive perception and positive attitude toward green product s
An Automated Robot Car Control System with Hand Gestures and Mobile Application Using Arduino
Year: 2019

Gesture recognition has always been a technique to decrease the distance between the physical and the digital world. In this work, we introduce an Arduino based vehicle system which no longer require manual controlling of the cars. The proposed work is achieved by utilizing the Arduino microcontroller, accelerometer, RF sender/receiver, and Bluetooth. Two main contributions are presented in this work. Firstly, we show that the car can be controlled with hand gestures according to the movement and position of the hand. Secondly, the proposed car system is further extended to be controlled by an android based mobile application having different modes (e.g. touch buttons mode, voice recognition mode) In addition, an automatic obstacle detection system is introduced to improve the safety measurements to avoid any hazards. The proposed systems are designed at lab scale prototype to experimentally validate the efficiency, accuracy, and affordability of the systems. We remark that the proposed systems can be implemented under real conditions at large scale in the future that will be useful in automobiles and robotics applications.
Tourism development, rights consciousness and the empowerment of Chinese historical village communities1
Year: 2014

In recent years, China's tourism researchers have started to pay attention to the empowerment of rural communities. Current theoretical research and social practices reflect that tourism needs to seek localized empowerment with respect to different types of tourism destinations. This paper, taking Furong Historical Village in Zhejiang Province as a case study, examines a special kind of Chinese historical village community in which the villagers' consciousness of their rights is weak and tourism development is only in its initial stages. Based on the field surveys, this paper points out four roots of such a community's disempowerment: (1) the failure of political institutions to ensure the community's public interest; (2) accusations of historical villages 'damaging protection' (3) information asymmetry in the relationship between rural leaders and villagers; and (4) a sense of powerlessness in the daily lives of rural residents. Based on these findings, this paper suggests several empowerment paths: (1) placing the enhancement of psychological power as the core of community empowerment; (2) addressing villager empowerment needs according to different types, rather than generalizing a community as a whole; and (3) including a diversity of subjects in the process of empowerment. These empowerment paths would be a moderate extension toward increasing community empowerment, based on this empirical study.
Face Expression Recognition: A Review
Year: 2020

Recognition of outward appearances assumes a significant job in many mechanized framework applications like mechanical technology, instruction, man made brainpower, and security. Perceiving outward appearances precisely is testing. Approaches for explaining FER (Facial Expression Recognition) issue can be ordered into 1) Static single pictures and 2) Image successions. Customarily, various procedures like Multi layer Perceptron Model, k Nearest Neighbors, Support Vector Machines were utilized by scientists for fathoming FER. These techniques removed highlights like Local Binary Patterns, Eigenfaces, Facemilestone highlights, and Texture highlights. Among every one of these techniques, Neural Networks have increased especially ubiquity and they are broadly utilized for FER. As of late, CNNs (Convolutional Neural Networks) have picked up notoriety in field of profound learning in view of their easygoing engineering and capacity to give great outcomes without prerequisite of manual component extraction from crude picture information. This paper centers around review of different face demeanor acknowledgment methods dependent on CNN. It incorporates cutting edge techniques proposed by various scientists. The paper additionally shows steps required for utilization of CNN for FER. This paper additionally incorporates examination of CNN based methodologies and issues requiring consideration while picking CNN for unraveling FER.  Classification, Survey, FER, Face Expression Recognition, Deep Learning, CNN.
Efficient 3D scene abstraction using line segments
Venue: Comput. Vis. Image Underst.
Year: 2017

A robust and efficient line based Multi v iew Stereo algorithm is introduced.It uses geometric line matching, which makes it invariant to illumination changes.3D lines are reconstructed via an efficient graph clustering of 2D line segments.The algorithm can process large scale datasets within less than a sec./image.The source code is publicly available for download under the GPL license. Extracting 3D information from a moving camera is traditionally based on interest point detection and matching. This is especially challenging in urban indoor and outdoor environments, where the number of distinctive interest points is naturally limited. While common Structure from Motion (SfM) approaches usually manage to obtain the correct camera poses, the number of accurate 3D points is very small due to the low number of matchable features. Subsequent Multi view Stereo approaches may help to overcome this problem, but suffer from a high computational complexity. We propose a novel approach for the task of 3D scene abstraction, which uses straight line segments as underlying features. We use purely geometric constraints to match 2D line segments from different images, and formulate the reconstruction procedure as a graph clustering problem. We show that our method generates accurate 3D models with low computational costs, which makes it especially useful for large scale urban datasets.
A Survey on Agriculture Analysis for Crop Yield Prediction Using Data Mining Techniques
Year: 2018

Now a day's agriculture is one of the most important field in the emerging real world and it is the main occupation and backbone of our country. Agriculture is in poor condition since before comparing previous years. The main reasons for this is without a well formed pattern about farming and proper guidance to the farmers. Due to these problems, farming affects the yield of crop and unawareness about the crop cultivation methodologies. And also season to cultivate the crop and choosing which soil is the best to cultivate the particular crop based on the weather condition and also when to harvest the crop for the best yield. If the farmer is aware about the crop cultivation methodologies and harvesting it will more helpful for the people in the real world and also to maximize the crop productivity. Data mining is the process of finding new template from large data sets, this technology which is employed in inferring useful knowledge that can be put to use from a vast amount of data, various data mining techniques such as classification, prediction, clustering and outlier analysis can be used for the purpose. Climate is one of the meteorological data that is rich by important knowledge. This paper presents a brief comparative study of various papers that deal with various techniques used to figure out the crop yield. Different data mining techniques that are in use for the crop yield estimation are K Means, K Nearest neighbor (KNN) Artificial Neural Networks(ANN) Recently data processing techniques in agriculture required decide, storage, monitored and retrieval the resources used. This survey aims to search out appropriate data processing models to realize high accuracy and prediction capabilities.
Topic Modelling Twitter Data with Latent Dirichlet Allocation Method
Venue: 2019 International Conference on Electrical Engineering and Computer Science (ICECOS)
Year: 2019

Twitter is a popular social media for every user to issue thoughts and emotional forms which are tweets, tweets that only have 140 characters with limitations to write in text. Twitter is one of the social media places to get information that is always up to date, tweets are categorized into big data because tweets are information that can be used as a source of data for research. Latent Dirichlet Allocation (LDA) as an algorithm that can process large text data (big data) In this study using the LDA method as an algorithm to produce topic modeling, each topic similarity, and visualization of topic clusters from the tweet data generated as many as 4 topics (Economic, Military, Sports, Technology) in Indonesian, where each topic has a number different tweets. The LDA method used in the processing of tweet data is successfully carried out and works optimally, in each topic extraction, topic modeling, generating index words that are in each topic cluster and computer visualization in the topic.LDA output shows optimal performance in the process of word indexing in Sport topics with 1260 tweets with an accuracy of 98% better than the LSI method in Topic Modeling.
From yeast to humans roles of the Kennedy pathway for phosphatidylcholine synthesis
Venue: FEBS letters
Year: 2018

The major phospholipid present in most eukaryotic membranes is phosphatidylcholine (PC) comprising 50% of phospholipid content. PC metabolic pathways are highly conserved from yeast to humans. The main pathway for the synthesis of PC is the Kennedy (CDP choline) pathway. In this pathway, choline is converted to phosphocholine by choline kinase, phosphocholine is metabolized to CDP choline by the rate determining enzyme for this pathway, CTP:phosphocholine cytidylyltransferase, and cholinephosphotransferase condenses CDP choline with diacylglycerol to produce PC. This Review discusses how PC synthesis via the Kennedy pathway is regulated, its role in cellular and biological processes, as well as diseases known to be associated with defects in PC synthesis. Finally, we present the first model for the making of a membrane via PC synthesis.
Hydrodynamic Characterization of USV Vessels with Innovative SWATH Configuration for Coastal Monitoring and Low Environmental Impact
Year: 2016

The high costs associated with the use of research oceanographic vessels and the maturity of the unmanned surface vehicles (USV) makes now possible to develop systems for monitoring coastal areas based on networks of independent USVs. This type of vessels is a valid alternative to conventional vessels, which have a limited mission profile due to their high environmental impact (conventional propulsion systems based on polluting fossil fuels) inhibiting their access to protected coastal regions. Moreover, conventional vessels have high hydrodynamic resistance (limiting the autonomy) producing high levels of noise that can dramatically influence the monitoring equipment shipped: beside the environmental impact reduction, there is also the necessity of low resistance/low noise hydrodynamic specification. Consequently, the coastal monitoring (of also protected regions) needs unconventional vessels able to address both the issues related to the environmental impact and the hydrodynamic performance. In this framework, this work aims to characterize the hydrodynamic performance of a system based on USV units able to launch and recover autonomous vehicles of different nature (gliders, autonomous underwater vehicle (AUVs) motor gliders, wire guided Underwater Exploration Robots (ROVs) and able to acquire environmental data (in the column water from free surface to the sea floor) in order to meet the requirements of civil and military applications. The cutting edge aspects that characterize the USV studied are the hull SWATH type (Small Waterplane Area Twin Hulls) non conventional, optimized so as to ensure a unique seakeeping and a reduced resistance, along with the propulsion system with propellers in mantle, developed to combine propulsive efficiency and low noise. In the present paper, a SWATH shaped USV designed for monitoring of protected coastal regions is numerically studied solving the Navier Stokes equations on the fully appended vessels with several environmental conditions. An accurate hydrodynamic characterization will presented in order to investigate its performances and eventual maneuverability issues.
Developing Remote Training Consultants as Leaders Dialogic/Network Application of Path Goal Leadership Theory in Leadership Development
Year: 2017

Although considered experts in software implementation, software training consultants are often in leadership roles but have little to no leadership training. Using the dialogic networked development techniques, five key leadership capacities could be developed in remote training consultant teams utilizing path goal theory leadership styles (House Mitchell, 1974) The leadership capacities include customer service, creativity and innovation, listening and communication, coaching and mentoring, and conflict management (Turner, Chih Hung, Schroeder, Johnson, 2016)
Relationship Between Rewards and Nurses' Work Motivation in Addis Ababa Hospitals
Venue: Ethiopian journal of health sciences
Year: 2012

Nurses constitute the largest human resource element and have a great impact on quality of care and patient outcomes in health care organizations. The objective of this study was to examine the relationship between rewards and nurse motivation on public hospitals administrated by Addis Ababa health bureau.  A cross sectional survey was conducted from June to December 2010 in 5 public hospitals in Addis Ababa. Among 794 nurses, 259 were selected as sample. Data was collected using self administered questionnaire. After the data was collected, it was analysed using SPSS version 16.0 statistical software. The results were analysed in terms of descriptive statistics followed by inferential statistics on the variables.  A total of 230 questionnaires were returned from 259 questionnaires distributed to respondents. Results of the study revealed that nurses are not motivated and there is a statistical significant relationship between rewards and the nurse work motivation and a payment is the most important and more influential variable. Furthermore, there is significant difference in nurse work motivation based on age, educational qualification and work experience while there is no significant difference in nurse work motivation based on gender.  The study shows that nurses are less motivated by rewards they received while rewards have significant and positive contribution for nurse motivation. Therefore, both hospital administrators' and Addis Ababa health bureau should revise the existing nurse motivation strategy.
Skill learning and task outcome prediction for manipulation
Venue: 2011 IEEE International Conference on Robotics and Automation
Year: 2011

Learning complex motor skills for real world tasks is a hard problem in robotic manipulation that often requires painstaking manual tuning and design by a human expert. In this work, we present a Reinforcement Learning based approach to acquiring new motor skills from demonstration. Our approach allows the robot to learn fine manipulation skills and significantly improve its success rate and skill level starting from a possibly coarse demonstration. Our approach aims to incorporate task domain knowledge, where appropriate, by working in a space consistent with the constraints of a specific task. In addition, we also present an approach to using sensor feedback to learn a predictive model of the task outcome. This allows our system to learn the proprioceptive sensor feedback needed to monitor subsequent executions of the task online and abort execution in the event of predicted failure. We illustrate our approach using two example tasks executed with the PR2 dual arm robot: a straight and accurate pool stroke and a box flipping task using two chopsticks as tools.
Detection of aflatoxin B1 with a new label free fluorescent aptasensor based on exonuclease I and SYBR Gold.
Venue: Analytical methods advancing methods and applications
Year: 2020

This paper describes a new label free fluorescent aptasensor for the detection of aflatoxin B1 (AFB1) based upon exonuclease I (Exo I) and SYBR Gold, in which SYBR Gold, aptamer, AFB1, and Exo I were used. Specific combinations of aptamer and AFB1 occurred in the presence of AFB1 and consequently altered the spatial structure of the aptamer, thereby preventing its digestion by Exo I. When SYBR Gold was added, intense fluorescence was observed. Additionally, a good linear relationship was observed under optimized conditions between the fluorescence intensities and the AFB1 concentrations (R2 0.993) The established aptamer sensor was highly sensitive and exhibited a low limit of detection of 1.82 ng mL 1, with superior specificity for AFB1. It was also used in the quantification of AFB1 levels in soybean sauce samples and demonstrated satisfactory recoveries in the scope of 94.8 108.9% The proposed sensor is highly sensitive, low cost, and capable of rapid detection and can thus be used to determine mycotoxin levels in a wide range of feeds and food products in a high throughput and quantitative means.
Path loss dataset for modeling radio wave propagation in smart campus environment
Venue: Data in brief
Year: 2018

Path loss models are often used by radio network engineers to predict signal coverage, optimize limited network resources, and perform interference feasibility studies. However, the propagation mechanisms of electromagnetic waves depend on the physical characteristics of the wireless channel. Therefore, efficient radio network planning and optimization requires detailed information about the specific propagation environment. In this data article, the path loss data and the corresponding information that are needed for modeling radio wave propagation in smart campus environment are presented and analyzed. Extensive drive test measurements are performed along three different routes (X, Y, and Z) within Covenant University, Ota, Ogun State, Nigeria (Latitude 6deg40'30.3''N, Longitude 3deg09'46.3''E) to record path loss data as the mobile receiver moves away from each of the three 1800 MHz base station transmitters involved. Also, the longitude, latitude, elevation, altitude, clutter height, and the distance information, which describes the smart campus environment, are obtained from Digital Terrain Map (DTM) in ATOLL radio network planning tool. Results of the first order descriptive statistics and the frequency distributions of all the seven parameters are presented in tables and graphs respectively. In addition, correlation analyses are performed to understand the relationships between the network parameters and the terrain information. For ease of reuse, the comprehensive data are prepared in Microsoft Excel spreadsheet and attached to this data article. In essence, the availability of these data will facilitate the development of path loss models for efficient radio network planning and optimization in smart campus environment.