nils-herrmann/clean_scirepeval huggingface dataset:
Total Anomalous Pulmonary Venous Connection: From Embryology to a Prenatal Ultrasound Diagnostic Update

.08.002 C and the Chinese Taipei Society o mons.org/licenses/by-nc-nd/4.0/ also as a part of complex heart diseases or genetic syndromes. Among cyanotic heart diseases, total anomalous pulmonary venous connection (TAPVC) is the only condition involving a venous system malformation  and is easily misdiagnosed. The key characteristic of this uncommon congenital heart disease (CHD) is that all four pulmonary veins (PVs) fail to form a direct connection to the left atrium (LA); instead, they drain into the right heart through different routes of systemic venous return. The incidence of this condition is approximately 7e9 per 100,000 live births [2,3], and it accounts for 0.7e1.5% of all CHDs . Patients with CHD who were born from 2000 to 2006 in Taiwan also exhibited a similar prevalence of TAPVC (0.11/ 1000) .
Block Chain based Searchable Symmetric Encryption

The mechanism for traditional Searchable Symmetric Encryption is pay-then-use. That is to say, if a user wants to search some documents that contain special keywords, he needs to pay to the server firstly, then he can enjoy search service. Under this situation, these kinds of things will happen: After the user paying the service fees, the server may either disappear because of the poor management or returning nothing. As a result, the money that the user paid cannot be brought back quickly. Another case is that the server may return incorrect document sets to the user in order to save his own cost. Once such events happen, it needs the arbitration institution to mediate which will cost a long time. Besides, to settle the disputes the user has to pay to the arbitration institution. Ideally, we deeply hope that when the user realizes the server has a tendency to cheat in the task of searching, he can immediately and automatically withdraw his money to safeguard his right. However, the existing SSE protocols cannot satisfy this demand. To solve this dilemma, we find a compromised method by introducing the block chain into SSE. Our scheme achieves three goals stated below. Firstly, when the server does not return any thing to user after he gets the search token, the user can get some compensation from the server, because the server can infer some important information from the Index and this token. Besides, the user also doesn’t pay the service charge. Secondly, if the documents that the server returns are false, the server cannot receive service fees, meanwhile, he will be punished. Lastly, when the user receives some bitcoin from server at the beginning, he may terminate the protocol. Under this situation, the server is a victim. In order to prevent such thing from happening, the server will broadcast a transaction to redeem his pledge after an appointed time. ∗Corresponding author Email addresses: tianhb@mail.sysu.edu.cn (Haibo Tian), isszhfg@mail.sysu.edu.cn (Fangguo Zhang )  2017
Cost Efficient Design of Fault Tolerant Geo-Distributed Data Centers

Many critical e-commerce and financial services are deployed on geo-distributed data centers for scalability and availability. Recent market surveys show that failure of a data center is inevitable resulting in a huge financial loss. Fault-tolerance in distributed data centers is typically handled by provisioning spare capacity to mask failure at a site. We argue that the operating cost and data replication cost (for data availability) must be considered in spare capacity provisioning along with minimizing the number of servers. Since the operating cost and client demand vary across space and time, we propose cost-aware capacity provisioning to minimize the total cost of ownership (TCO) for fault-tolerant data centers. We formulate the problem of spare capacity provisioning in fault-tolerant distributed data centers using mixed integer linear programming (MILP), with an objective of minimizing the TCO. The model accounts for heterogeneous client demand, data replication strategies (single and multiple site), variation in electricity price and carbon tax, and delay constraints while computing the spare capacity. Solving the MILP using real-world data, we observed a saving in the TCO to the tune of 35% compared to a model that minimizes the total number of servers and 43% compared to the model that minimizes the average response time. We demonstrate that our model is beneficial when the cost of electricity, carbon tax, and bandwidth vary significantly across the locations, which seems to be the problem for most of the operators.
Enhancing the Data Storage Capacity in QR Code Using Compression Algorithm and Achieving Security and Further Data Storage Capacity Improvement Using Multiplexing

This paper focuses on increasing the data storage capacity with less storage space of QR code by applying compression techniques. Further data capacity can be increased by applying multiplexing techniques i.e. Grouping of bits into codeword and providing security by replacing the codeword by special type of character. As there are varieties of medium for information sharing over distances. Thus QR code can be used as information sharing medium. QR code is 2 Dimension Barcode and comes under the category of data hiding techniques as it store data in hidden form. It stores data in matrix form using unique pattern. Data from QR code can be retrieved by using phone Camera of 2 Mega pixels or more. As QR has many advantage over 1D so it has been used in many diverse field for research areas such as techniques for data hiding like scanning of barcode, watermarking, steganography, Histogram based techniques, techniques for better recognition and also for security purpose it can be used in more application.
Accurate modeling, wave mechanisms, and design considerations of a substrate integrated waveguide

A new method of analysis is presented in this paper for the determination of complex propagation constants in substrate integrated waveguides (SIWs). This method makes use of the concept of surface impedance to model the rows of conducting cylinders, and the proposed model is then solved by combining a method of moments and a transverse resonance procedure. The proposed method is further applied to extract results in terms of parametric curves and graphs which demonstrate fundamental and interesting wave guidance and leakage properties of this type of periodic waveguide. Useful design rules are extracted from this analysis, suggesting that appropriate design parameters and regions should be carefully selected for practical applications. In addition, comprehensive review and comparisons with published results are also presented to show the performance and accuracy of the proposed modeling technique. Practical measurements of fabricated samples with different levels of loss have confirmed the accuracy of this new method and validity of design rules
Augmented Reality in education

The paper presents Augmented Reality (AR) as a step b etween reality and virtual reality for the benifit of education. After some in troductory example of where AR heads, the technology itself is explained. Then, we descri be the modules of the AR portal that we have developed and how it can be used. We give exam ples of its use in university courses and activities. Furthermore we describe an experime nt that we set up at a secondary school to help in popularizing chemistry and raising grade s of students, besides making then enjoy involvement with the topic. Our results are very po sitive, so we consider our efforts to be a starting point for further developments.
Dynamic Wi-Fi Reconfigurable FPGA Based Platform for Intelligent Traffic Systems

This chapter proposes a software and hardware platform based on a FPGA board to which a Wi-Fi communication device has been added in order to make remote wireless reconfiguration possible. This feature introduces a high level of flexibility allowing the development of applications which can quickly adapt to changes in environmental conditions and which can react to unexpected events with high speed. The capabilities introduced by wireless technology and reconfigurable systems are important in road traffic control systems, which are characterized by continuous parameter variation and unexpected event and incident occurrence. Intelligent Transportation System (ITS) is the term commonly used to describe the employment of electronic devices for the management of road traffic and other types of transportation networks for improving decision making by operators and users. There are many new available technologies which can be used for increasing the efficiency of road systems and many cities are introducing ITS models as pilot schemes to test their effectiveness. Reconfigurable hardware offers many benefits and this led to its use in the ITS field also. Traffic light systems implemented on FPGAs were developed and examples can be found in the literature (El-Medany & Hussain, 2007; Zhenggang et al., 2009). This research led to the conclusion that FPGA based devices can be a good solution for this type of systems conferring them scalability, adaptability and stability, and increasing their efficiency (Zhenggang et al., 2009). FPGAs had also been used in vehicle-to-vehicle communication (V2V), the authors of (Sander et al., 2009) presenting a V2V communication system based on this technology and special mechanisms that exploit its benefits. The result consists of a modular and flexible framework for software routines which in the same time supports critical tasks with special hardware accelerators. The modularity achieved with the help of FPGA technology allows the system to react to changes in the environmental conditions or in the user demands.
Epileptic seizure detection for multi-channel EEG with deep convolutional neural network

A new epileptic seizure detection method based on deep convolutional network is proposed. The proposed network is designed for multi-channel EEG signals and considers spatio-temporal correlation, a feature in epileptic seizure detection, using 1D and 2D convolutional layers. 1D convolutional layer considers temporal evolution of the EEG signal of each channel and 2D convolutional layers considers spatial relationships between EEG channels. We make datasets for training and test by extracting the EEG segments from CHB-MIT EEG Scalp database and SNUH-HYU EEG database: the recordings of long-term EEG monitoring at Seoul National University Hospital and Children's Hospital Boston. Our model is trained and tested using the EEG segments with varying durations. We also investigate the effect of artifact elimination on epileptic seizure detection by applying a low-pass filter to the EEG signals. Our model achieves 90.5% prediction accuracy with SNUH-HYU EEG dataset.
Ontology Generator from Relational Database Based on Jena

There are a lot of difficulties in the ontology generation from relational database such as unclear generation approaches, un-unified ontology languages and so on. So in order to provide unified ontology and improve the quality of ontology generation, approach proposed in this paper firstly extracts database metadata information from relational database using reverse engineering technique, and then analyzes the correspondent relationship between relational database and OWL ontology, and presents an ontology generation from relational database. Finally, a prototype tool of the generator, implemented based on Jena in Java development platform, and case study demonstrates the feasibility and effectiveness of the approach.
Amorphous silicon thin film transistor circuit integration for organic LED displays on glass and plastic

This paper presents design considerations along with measurement results pertinent to hydrogenated amorphous silicon (a-Si:H) thin film transistor (TFT) drive circuits for active matrix organic light emitting diode (AMOLED) displays. We describe both pixel architectures and TFT circuit topologies that are amenable for vertically integrated, high aperture ratio pixels. Here, the OLED layer is integrated directly above the TFT circuit layer, to provide an active pixel area that is at least 90% of the total pixel area with an aperture ratio that remains virtually independent of scaling. Both voltage-programmed and current-programmed drive circuits are considered. The latter provides compensation for shifts in device characteristics due to metastable shifts in the threshold voltage of the TFT. Various drive circuits on glass and plastic were fabricated and tested. Integration of on-panel gate drivers is also discussed where we present the architecture of an a-Si:H based gate de-multiplexer that is threshold voltage shift invariant. In addition, a programmable current mirror with good linearity and stability is presented. Programmable current sources are an essential requirement in the design of source driver output stages.
Stochastic Geometric Analysis of User Mobility in Heterogeneous Wireless Networks

Horizontal and vertical handoffs are important ramifications of user mobility in multitier heterogeneous wireless networks. They directly impact the signaling overhead and quality of calls. However, they are difficult to analyze due to the irregularly shaped network topologies introduced by multiple tiers of cells. In this paper, a stochastic geometric analysis framework on user mobility is proposed, to capture the spatial randomness and various scales of cell sizes in different tiers. We derive theoretical expressions for the rates of all handoff types experienced by an active user with arbitrary movement trajectory. Furthermore, noting that the data rate of a user depends on the set of cell tiers that it is willing to use, we provide guidelines for optimal tier selection under various user velocities, taking both the handoff rates and the data rate into consideration. Empirical studies using user mobility trace data and extensive simulation are conducted, demonstrating the correctness and usefulness of our analysis.
Open IE as an Intermediate Structure for Semantic Tasks

Semantic applications typically extract information from intermediate structures derived from sentences, such as dependency parse or semantic role labeling. In this paper, we study Open Information Extraction’s (Open IE) output as an additional intermediate structure and find that for tasks such as text comprehension, word similarity and word analogy it can be very effective. Specifically, for word analogy, Open IE-based embeddings surpass the state of the art. We suggest that semantic applications will likely benefit from adding Open IE format to their set of potential sentencelevel structures.
User experience: challenges and opportunities

User expectations, motivations and feelings when using a product or encountering a system have urged the need to investigate beyond the traditional functionality and usability concerns by assessing and designing for the user experience. Having this realized, we can ensure positive user experience as well as desirable products. This paper aims at providing an overview of the main concepts and principles related to user experience. The topics discussed in this paper cover both theories from the academia as well as empirical studies from the industry. Due to misconception of user experience, it was found that industry depends on and uses the traditional usability methods in the product development as user experience practices. As a result, this paper discusses and elaborates the relationship between conventional usability and user experience in addition to the variety of methods which can be used for user experience evaluation during different time spans. Furthermore, user experience extends over different areas such as human computer interaction, and product design and development. Knowledge and concepts related to user experience are scattered due to the dynamic concepts of user experience. In other words, authors tend to discuss the user experience from their own perspective and interest. Hence, this paper is trying to provide and establish a holistic understanding of the user experience by covering different topics related to user experience. The output of this paper may provide and assist researchers and practitioners to establish a base to aid in proper understanding of user experience, its concepts and principles.
Automated Heart Wall Motion Abnormality Detection from Ultrasound Images Using Bayesian Networks

Coronary Heart Disease can be diagnosed by measuring and scoring regional motion of the heart wall in ultrasound images of the left ventricle (LV) of the heart. We describe a completely automated and robust technique that detects diseased hearts based on detection and automatic tracking of the endocardium and epicardium of the LV. The local wall regions and the entire heart are then classified as normal or abnormal based on the regional and global LV wall motion. In order to leverage structural information about the heart we applied Bayesian Networks to this problem, and learned the relations among the wall regions off of the data using a structure learning algorithm. We checked the validity of the obtained structure using anatomical knowledge of the heart and medical rules as described by doctors. The resultant Bayesian Network classifier depends only on a small subset of numerical features extracted from dual-contours tracked through time and selected using a filterbased approach. Our numerical results confirm that our system is robust and accurate on echocardiograms collected in routine clinical practice at one hospital; our system is built to be used in real-time.
Gracker: A Graph-Based Planar Object Tracker

Matching-based algorithms have been commonly used in planar object tracking. They often model a planar object as a set of keypoints, and then find correspondences between keypoint sets via descriptor matching. In previous work, unary constraints on appearances or locations are usually used to guide the matching. However, these approaches rarely utilize structure information of the object, and are thus suffering from various perturbation factors. In this paper, we proposed a graph-based tracker, named Gracker, which is able to fully explore the structure information of the object to enhance tracking performance. We model a planar object as a graph, instead of a simple collection of keypoints, to represent its structure. Then, we reformulate tracking as a sequential graph matching process, which establishes keypoint correspondence in a geometric graph matching manner. For evaluation, we compare the proposed Gracker with state-of-the-art planar object trackers on three benchmark datasets: two public ones and a newly collected one. Experimental results show that Gracker achieves robust tracking results against various environmental variations, and outperforms other algorithms in general on the datasets.
Gamification Solutions to Enhance Software User Engagement - A Systematic Review

Gamification is the use of video-game mechanics and elements in nongame contexts to enhance user engagement and performance. The purpose of this study is to conduct a systematic review to have an in-depth investigation into the existing gamification solutions targeted at solving user engagement problems in different categories of software. We carried out this systematic review by proposing a framework of gamifying process, which is the basis for comparison of existing gamification solutions. In order to report the review, the primary studies are categorized according to the following: a) gamified software and their platforms, b) elements of the gamifying process, c) gamification solutions in each software type, d) gamification solutions for software user engagement problems, e) gamification solutions in general, and f) effects of gamification on software user engagement and performance. Based on the search procedure and criteria, a total of 78 primary studies were extracted. Most of the studies focused on educational and social software, which were developed for web or mobile platforms. We concluded that the number of studies on motivating users to use software content, solving problems in learning software, and using real identity is very limited. Furthermore, few studies have been carried out on gamifying the following software categories: productivity software, cloud storage, utility software, entertainment software, search engine software, tool software, fitness software, software engineering, information worker software, and health-care software. In addition, a large number of gamification solutions are relatively simple and require improvement. Thus, for future studies, researchers can work on the items discovered in this review; they can improve the quality of the current gamified systems by using a wide variety of game mechanics and interface elements, utilizing a combination of contextual types of rewards and giving users the ability to use received rewards “in-game” and “out-game”.
Phased array systems and technologies in SELEX-Sistemi Integrati: State of art and new challenges

This paper is a follow-on of  and , presented at 1996 and 2003  After a brief recall of 3D Long Range phased array concepts, already presented in , the focus is on the G-band multifunction radar systems and on the technological capabilities that SELEX-Sistemi Integrati is developing by taking advantage of its Research and Development facilities. At the end, future trends about new challenging applications and technological issues are presented and discussed.
Energy-Brushes: Interactive Tools for Illustrating Stylized Elemental Dynamics

Dynamic effects such as waves, splashes, fire, smoke, and explosions are an integral part of stylized animations. However, such dynamics are challenging to produce, as manually sketching key-frames requires significant effort and artistic expertise while physical simulation tools lack sufficient expressiveness and user control. We present an interactive interface for designing these elemental dynamics for animated illustrations. Users draw with coarse-scale energy brushes which serve as control gestures to drive detailed flow particles which represent local velocity fields. These fields can convey both realistic and artistic effects based on user specification. This painting metaphor for creating elemental dynamics simplifies the process, providing artistic control, and preserves the fluidity of sketching. Our system is fast, stable, and intuitive. An initial user evaluation shows that even novice users with no prior animation experience can create intriguing dynamics using our system.
Factorization machines with follow-the-regularized-leader for CTR prediction in display advertising

Predicting ad click-through rates is the core problem in display advertising, which has received much attention from the machine learning community in recent years. In this paper, we present an online learning algorithm for click-though rate prediction, namely Follow-The-Regularized-Factorized-Leader (FTRFL), which incorporates the Follow-The-Regularized-Leader (FTRL-Proximal) algorithm with per-coordinate learning rates into Factorization machines. Experiments on a real-world advertising dataset show that the FTRFL method outperforms the baseline with stochastic gradient descent, and has a faster rate of convergence.