nils-herrmann/clean_scirepeval huggingface dataset:
PENGEMBANGAN APLIKASI ALAT BANTU PENGENAL NOMINAL MATA UANG RUPIAH BAGI PENYANDANG TUNANETRA MENGGUNAKAN MODEL MOBILENET
Year: 2018

Saat ini transaksi ekonomi sudah menjadi hal yang biasa dilakukan sehari hari. Orang orang setiap harinya selalu bertransaksi dengan menggunakan alat pembayaran berupa uang melalui proses jual beli. Uang menjadi peran yang sangat penting dalam bertransaksi. Akan tetapi, terdapat permasalahan dalam bertransaksi bagi penyandang tunanetra seperti kesulitan mengenali nominal uang, terutama uang kertas. Metode pengolahan citra yang dapat digunakan untuk mengklasifikasi uang rupiah adalah Convolutional Neural Network (CNN) Metode CNN ini memiliki banyak jenis berdasarkan arsitektur yang dibangunnya, salah satunya adalah arsitektur Mobilenet. Arsitektur Mobilenet berfokus pada penggunaan sumber daya yang kecil dan cepat. Pendekatan yang dilakukan pada penelitian ini adalah menggunakan Transfer Learning, agar proses training dapat dilakukan lebih cepat. Pada penelitian ini digunakan 7 kelas citra uang rupiah yang masing masing terdiri dari 200 citra. Tingkat akurasi model yang dibangun dengan arstitektur Mobilenet adalah sebesar 82% Hasil kuesioner menunjukkan aplikasi ini cukup membantu bagi responden. At this time economic transactions have become commonplace. People always transact using money in the form of payment through the buying and selling process. Money is a very important role in transactions. However, there are problems in transactions for people with visual impairments such as difficulty recognizing money, especially banknote. Image processing methods that can be used to classify rupiah banknote are Convolutional Neural Networks (CNN) The CNN method has many types based on the architecture that is built, one of them is Mobilenet architecture. Mobilenet architecture focuses on small and fast resource usage. In this study we used Transfer Learning in training process. Therefore the process becomes faster. 7 classes of rupiah banknote were used, each class consists of 200 images. The accuracy of the model built with the Mobilenet architecture is 82% The results of the questionnaire indicate that this application is quite helpful for the respondents.
Knowledge as a Service Framework for Disaster Data Management
Venue: 2013 Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises
Year: 2013

Each year, a number of natural disasters strike across the globe, killing hundreds and causing billions of dollars in property and infrastructure damage. Minimizing the impact of disasters is imperative in today's society. As the capabilities of software and hardware evolve, so does the role of information and communication technology in disaster mitigation, preparation, response, and recovery. A large quantity of disaster related data is available, including response plans, records of previous incidents, simulation data, social media data, and Web sites. However, current data management solutions offer few or no integration capabilities. Moreover, recent advances in cloud computing, big data, and NoSQL open the door for new solutions in disaster data management. In this paper, a Knowledge as a Service (KaaS) framework is proposed for disaster cloud data management (Disaster CDM) with the objectives of 1) storing large amounts of disaster related data from diverse sources, 2) facilitating search, and 3) supporting their interoperability and integration. Data are stored in a cloud environment using a combination of relational and NoSQL databases. The case study presented in this paper illustrates the use of Disaster CDM on an example of simulation models.
Halogen bonding and other s hole interactions: a perspective.
Venue: Physical chemistry chemical physics PCCP
Year: 2013

A s hole bond is a noncovalent interaction between a covalently bonded atom of Groups IV VII and a negative site, e.g. a lone pair of a Lewis base or an anion. It involves a region of positive electrostatic potential, labeled a s hole, on the extension of one of the covalent bonds to the atom. The s hole is due to the anisotropy of the atom's charge distribution. Halogen bonding is a subset of s hole interactions. Their features and properties can be fully explained in terms of electrostatics and polarization plus dispersion. The strengths of the interactions generally correlate well with the magnitudes of the positive and negative electrostatic potentials of the s hole and the negative site. In certain instances, however, polarizabilities must be taken into account explicitly, as the polarization of the negative site reaches a level that can be viewed as a degree of dative sharing (coordinate covalence) In the gas phase, s hole interactions with neutral bases are often thermodynamically unfavorable due to the relatively large entropy loss upon complex formation.
Deep Garment Image Matting for a Virtual Try on System
Venue: 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
Year: 2019

To improve online shopping experience, many fashion retailers try to provide high quality garment images, capturing fine details as well as various opacities. A skilled operator can deliver a satisfactory result using manual segmentation tools, but it is challenging to scale up this process to address seasonal demands. To balance the quality and the processing cost, we investigate the use of a deep learning based matting technique that can produce a high quality alpha map from an approximate garment segmentation. The proposed model adopts the deep image matting model, but we replace the refinement network with a sequence of recursive convolutional network (RCN) units. Our main motivation for this modification is that the fine garment details created by different materials are represented better with the mixture of the image features from different scales. Therefore, we need to construct deeper convolutional layers for better scale analysis but we also need to maintain the number of unknowns low as producing training data is expensive. The proposed RCN based refinement network can address these conflicting restrictions well and our experiments demonstrate that it can achieve a lower training loss and produce better prediction results than the baseline refinement model under the same training condition.
Robust Granular Neural Networks, Fuzzy Granules and Classification
Venue: RSKT
Year: 2010

We introduce a robust granular neural network (RGNN) model based on the multilayer perceptron using back propagation algorithm for fuzzy classification of patterns. We provide a development strategy of the network mainly based upon the input vector, linguistic connection weights and target vector. While the input vector is described in terms of fuzzy granules, the target vector is defined in terms of class membership values and zeros. The connection weights among nodes of RGNN are in terms of linguistic variables, whose values are updated by adding two linguistic hedges. The updated linguistic variables are called generalized linguistic variables. The node functions of RGNN are defined in terms of linguistic arithmetic operations. We present the experimental results on several real life data sets. Our results show that the classification performance of RGNN is superior to other similar type of networks.
An Adaptive Sliding Mode Control of Interior Permanent Magnet Synchronous Motor Based on Maximum Torque Per Ampere
Venue: 2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS)
Year: 2018

The paper presents an adaptive sliding mode controller (ASMC) based on the maximum torque per ampere(MTPA) control, which is proposed for the speed tracking control of Interior Permanent Magnet Synchronous Motor (IPMSM) servo system with external disturbance torque. In order to solve the problem, Newton Lawson iteration method is adopted to achieve the distribution of d q axis stator current under MTPA control. In addition, an adaptive sliding mode controller is designed for reducing the chatter and improving the stability of the servo system. The comparison of simulation results show that the proposed method effectively improves not only the dynamic and steady state performance but also the anti disturbance capability of the system.
CASSANDRA A DISTRIBUTED NOSQL DATABASE FOR HOTEL MANAGEMENT SYSTEM
Year: 2016

Apache Cassandra is a distributed storage system for managing very large amounts of structured data. Cassandra provides highly available service with no single point of failure. Cassandra aims to run on top of an infrastructure of hundreds of nodes possibly spread across different data centers with small and large components fail continuously. Cassandra manages the persistent state in the face of the failures which drives the reliability and scalability of the software systems. Cassandra does not support a full relational data model because it resembles a database and shares many design and implementation strategies. In this paper, discuss an implementation of Cassandra as Hotel Management System application. Cassandra system was designed to run on cheap commodity hardware. Cassandra provides high write throughput and read efficiency.
Preparation and characterization of a wetting agglomeration based hybrid coal dust suppressant
Year: 2018

Driven by the advancement of science and technology, the number of safety incidents in coal mines has been steadily declining. Nonetheless, a small scale killer, i.e. coal dust, has become a dominating factor threatening the safe production in coal mines. Therefore, the control of coal dust has become the key to the safe and efficient production of coal mines. The present paper discusses the preparation of a type of hybrid dust suppressant by cross linking sodium ligninsulfonate and acrylamide, which generates a type of macromolecular product. Subsequently, Fourier infrared spectroscopy, X ray diffraction spectroscopy and scanning electron microscopy experiments are conducted to analyze the structure of the product. Moreover, the TG DSC experiments are carried out to analyze the thermal stability of the product. It is found through a single factor experiment that the optimal synthesis condition is: the mass ratio of lignin to acrylamide is 2:7; the mass ratio of cross linking agent to acrylamide is 3% the optimal reaction temperature is 65 degC; an examination of the product through a high power microscope with ultra depth of field reveals that the prepared macromolecular product can cause the coal dust particles to undergo an agglomeration process; however, the prepared product cannot sufficiently wet the coal dust; to enhance the wettability of the production, 0.15% (by mass fraction) of dodecyl dimethyl betaine (DDB) is added to the system. An experiment concerning the interaction between coal dust and the prepared product indicates that the present suppressant can effectively suppress the dispersion of coal dust through a combination of wetting and agglomeration effects.
Growth of Tourism and Hospitality Industry: Impact on Environment and Demographic Trend of Chittagong Hill Tracts
Venue: Asian Journal of Economics, Business and Accounting
Year: 2019

This paper tries to focus on environmental impact and the demographic phenomenon of tourism. Bangladesh is now on the highway to achieve the Sustainable development goals by 2030 after fulfilling significant achievement of Millennium Development Goals. The government has made some ambitious targets to achieve Sustainable Development Goals. It is important to note that sustainable development comprises several criteria. There is a significant need for environmental protection which is one of the three pillars of sustainable development. The other two are economic growth and social progress. Tourism and hospitality sector is seen to have emerged as a new area of sustainable development in recent time to contribute to social development. The scope of the positive contribution of tourism and hospitality is ample and relates to several dimensions such as earning of foreign exchange, employment generation, increasing productivity, hotel accommodation and transportation etc. However, the recent studies reveal that tourism has dramatically affected social, cultural, economic and environmental aspects of hospitality. Especially in Chittagong Hill Tract area; which is a great tourist attraction of the country; experiencing the impacts of unfair practice of tourism. The lack of proper policy and lack of awareness about sustainable growth of tourism activities is profoundly effecting the environment and life of the local ethnic groups of that area. Nevertheless, with proper planning and implementation of rules regulations, the scenario can be shifted to the positive side. The paper attempts to analyze the contribution of tourism and hospitality as a weapon of sustainable development agenda and to assess how it effects on the environment and demographic pattern or local communities of Chittagong Hill Tracts.
Real brands in imaginary worlds: investigating players' experiences of brand placement in digital games
Year: 2006

This paper explores the development of brand placement in digital games using focus groups with game players. Growth in in game brand placement is explained by game developers' financial and creative priorities and experimentation in marketerss' use of media. The external context of game play is then examined based on explanations of the non material aspects of consumer behaviour. Internal game processes are also reviewed, including psychological processes that are likely to be of interest to marketers. The reported experiences of players are then considered in terms of these processes. Findings seem to support the use of brand placement in games. Players easily recall encounters with brands during game play and are generally positive about these experiences, suggesting that brands increase realism because it allows individuals to create and explore consumption based daydreams. However, some players reject brand placement, preferring in game fantasies that are independent of mundane commodities. The findings also raise issues related to the ways in which individuals may use digital games to reflect on our consumer society and this raises a question of the degree to which digital games may support or oppose existing consumer cultures. Other problems for managers wishing to use this technique were revealed by the repetitive nature of games which may cause message wear out, and by playerss' frustration with aspects of a game which may lead to negative evaluations of in game brands
A Fast Map Matching Algorithm Based on Topological Relation of Road Network
Venue: 2019 International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI)
Year: 2019

A fast map matching algorithm based on improved topological relation of road network is proposed on the problem that trajectory data cannot satisfy both accuracy and time efficiency in map matching. The topological relation of road network is combined with Hidden Markov Model by introducing the road network district index, and the A* algorithm based on the topological relation of road network is used to calculate the shortest path between nodes in the transition probability, which greatly improve the time efficiency of map matching on the premise of ensuring the matching accuracy, and the validity of the algorithm is verified by Changchun experimental data.
Electrochemical Properties and XPS Analysis of Ni B/SiC Nanocomposite Coatings
Year: 2018

Few studies have reported the electrochemical properties and XPS analysis of Ni B/SiC nanocomposite coatings with high wear resistance prepared by electro co deposition. In this study, NiB/SiC nanocomposite coating was prepared by electrodeposition using trimethylamine borane as boron source in a Ni B electrolyte containing dispersed SiC nanoparticles. The corrosion resistance and antiwear properties of the Ni B/SiC composite coating were examined. XPS was employed to analyze the element electronic state of the coating surface. The results show that the corrosion resistance of the NiB/SiC composite coating was enhanced which may be related to the dense structure, barrier effect and the reduction in the active surface area of Ni B matrix by the presence of inert SiC particles. The XPS analysis indicated that the as deposited coating contains metallic nickel, oxide or hydroxide nickel, and the SiC particles. Ni B/SiC nanocomposite coating with dense structure shows superior anti corrosion and wear resistance than Ni B and Ni/SiC coatings.
Utilization of biochar from unwashed peanut shell in cementitious building materials Effect on early age properties and environmental benefits
Venue: Fuel Processing Technology
Year: 2021

Early stage and fresh properties of cementitious materials are critical to ease of placement and durability. This study investigated the potential of biochar, prepared by pyrolysis of locally generated waste peanut shells, to improve workability, hydration, early age strength and shrinkage of cement mortar and cement fly ash mortar. Experimental observations suggest that addition of biochar slightly reduced workability, reflected in the increase in yield stress and reduction in flow. The biochar used in this study enhanced the degree of hydration by 13 23% and accelerated rate of final setting by 1 1.5 h depending on mix composition. The presence of contaminants including salt and phosphorus in the biochar influences hydration kinetics and setting of cement pastes. The fine particle size of the biochar improved the compactness of cementitious matrix which contributed to increase in early age strength (up to 7 days) of normal and fly ash mortar by 18% and 22% respectively. The results show that biochar addition can accelerate strength development in fly ash cement, which is promising for the development of high early strength concrete with reduced cement demand. However, shrinkage of mortar increased with the dosage of biochar, due to the presence of salts in unwashed peanut shells. Using biochar to replace 3% of cement, can reduce CO2 equivalent emission, attributed to the net sequestration of carbon in the biochar.
Contexto para decisiones de inversion en el mercado de divisas y forwards
Year: 2018

El presente documento de trabajo titulado "CONTEXTO PARA DECISIONES DE INVERSION EN EL MERCADO DE DIVISAS Y FORWARDS" pretende informar acerca del comportamiento que se tiene conforme a la utilizacion de los derivados financieros, especificamente el Forward, como funcionan los mismos, sus posiciones y metodos de entrega, su evolucion a traves del tiempo y la acogida e incremento que se ha tenido desde 1997; asi mismo, se pretende demostrar de manera estadistica el comportamiento de la TRM y del contrato Forward en Colombia, a traves de un analisis comparativo y asi poder brindar una resolucion a los usuarios de estos contratos y proponer una perspectiva optima para que los inversionistas tengan una base historica y puedan proyectar una toma de decisiones al momento de tranzar divisas.
Augmentation for small object detection
Venue: ArXiv
Year: 2019

In recent years, object detection has experienced impressive progress. Despite these improvements, there is still a significant gap in the performance between the detection of small and large objects. We analyze the current state of the art model, Mask RCNN, on a challenging dataset, MS COCO. We show that the overlap between small ground truth objects and the predicted anchors is much lower than the expected IoU threshold. We conjecture this is due to two factors; (1) only a few images are containing small objects, and (2) small objects do not appear enough even within each image containing them. We thus propose to oversample those images with small objects and augment each of those images by copy pasting small objects many times. It allows us to trade off the quality of the detector on large objects with that on small objects. We evaluate different pasting augmentation strategies, and ultimately, we achieve 9.7\ relative improvement on the instance segmentation and 7.1\ on the object detection of small objects, compared to the current state of the art method on MS COCO.
Software Engineering for Smart Cyber Physical Systems: Challenges and Promising Solutions
Venue: SOEN
Year: 2017

Smart Cyber Physical Systems (sCPS) are modern CPS systems that are engineered to seamlessly integrate a large number of computation and physical components; they need to control entities in their environment in a smart and collective way to achieve a high degree of effectiveness and efficiency. At the same time, these systems are supposed to be safe and secure, deal with environment dynamicity and uncertainty, cope with external threats, and optimize their behavior to achieve the best possible outcome. This "smartness" typically stems from highly cooperative behavior, self awareness, self adaptation, and selfoptimization. Most of the "smartness" is implemented in software, which makes the software one of the most complex and most critical constituents of sCPS. As the specifics of sCPS render traditional software engineering approaches not directly applicable, new and innovative approaches to software engineering of sCPS need to be sought. This paper reports on the results of the Second International Workshop on Software Engineering for Smart Cyber Physical Systems (SEsCPS 2016) which specifically focuses on challenges and promising solutions in the area of software engineering for sCPS.
Modelling and field testing of a breakwater integrated U OWC wave energy converter with dielectric elastomer generator
Year: 2020

This paper introduces a theoretical and experimental study of a wave energy converter (WEC) that combines the two innovative concepts of U oscillating water column (U OWC) and dielectric elastomer generator (DEG) power take off (PTO) The U OWC is a type of oscillating water column that features a U shaped duct that is introduced to tune its dynamics to a certain wave period without active means of phase control. The DEG is a compliant polymeric generator that makes it possible to convert mechanical energy into electrical energy by exploiting the large deformations of elastomeric membranes. A lumped parameter mathematical model of the proposed WEC has been set up and a small scale model/prototype has been preliminary tested in a benign real sea environment. During experiments, relevant experimental data have been collected and used for assessing the reliability of the modelling approach. Beside the model validation, specific experiments have been conducted to test a simple but yet effective load shedding system based on the progressive opening of an air valve. Finally, a preliminary design of a full scale U OWC equipped with DEG PTO has been studied through wave to wire analysis. The obtained numerical results show an overall performance that is comparable with that of more conventional, expensive and complex PTO technologies.