nils-herrmann/clean_scirepeval huggingface dataset:
What exactly is viral marketing ?

So what is viral marketing? In 1997, when we first coined the term in a Netscape newsletter (www.dfj.com/viralmarketing), we used several examples to illustrate the phenomenon, defined loosely as “network-enhanced word of mouth.” Its original inspiration came from the adoption pattern of Hotmail, the Webbased email service that launched in 1996. Tim Draper persuaded Hotmail to include a promotional pitch with a clickable URL in every message sent by a Hotmail user. Therein lay one of the critical elements of viral marketing: every customer becomes an involuntary salesperson simply by using the product.
A simple intrusion detection method for controller area network

The Controller Area Network (CAN) is established as the main communication channel inside vehicles. CAN relies on frame broadcast to share data between different microcontrollers managing critical or comfort functions such as cruise control or air conditioning. CAN is distinguished by its simplicity, its real-time application compatibility and its low deployment cost. However, CAN major drawback is its lack of security support. That is, CAN fails to provide protections against attacks such as intrusion, denial of service or impersonation. We propose in this work a simple intrusion detection method for CAN. Our main idea is to make each microcontroller monitor the CAN bus to detect malicious frames.
Optimal Distributed Online Prediction

Online prediction methods are typically studied as serial algorithms running on a single processor. In this paper, we present the distributed mini-batch (DMB) framework, a method of converting a serial gradient-based online algorithm into a distributed algorithm, and prove an asymptotically optimal regret bound for smooth convex loss functions and stochastic examples. Our analysis explicitly takes into account communication latencies between computing nodes in a network. We also present robust variants, which are resilient to failures and node heterogeneity in an asynchronous distributed environment. Our method can also be used for distributed stochastic optimization, attaining an asymptotically linear speedup. Finally, we empirically demonstrate the merits of our approach on large-scale online prediction problems.
Echo State Networks for data-driven downhole pressure estimation in gas-lift oil wells

Process measurements are of vital importance for monitoring and control of industrial plants. When we consider offshore oil production platforms, wells that require gas-lift technology to yield oil production from low pressure oil reservoirs can become unstable under some conditions. This undesirable phenomenon is usually called slugging flow, and can be identified by an oscillatory behavior of the downhole pressure measurement. Given the importance of this measurement and the unreliability of the related sensor, this work aims at designing data-driven soft-sensors for downhole pressure estimation in two contexts: one for speeding up first-principle model simulation of a vertical riser model; and another for estimating the downhole pressure using real-world data from an oil well from Petrobras based only on topside platform measurements. Both tasks are tackled by employing Echo State Networks (ESN) as an efficient technique for training Recurrent Neural Networks. We show that a single ESN is capable of robustly modeling both the slugging flow behavior and a steady state based only on a square wave input signal representing the production choke opening in the vertical riser. Besides, we compare the performance of a standard network to the performance of a multiple timescale hierarchical architecture in the second task and show that the latter architecture performs better in modeling both large irregular transients and more commonly occurring small oscillations.
XIS-mobile: a DSL for mobile applications

Mobile applications are becoming increasingly more present in our daily life, allowing people to perform several tasks through the use of smartphones or tablets. Despite fostering the innovation, the rapid growth of the mobile market resulted in some fragmentation of the mobile platforms. The existence of different mobile operating systems with different programming languages and tools can be a problem when someone wants to release an application in multiple platforms. Rewriting the application for each platform is usually impracticable either in terms of budget or time, requiring a great effort. Therefore, a solution that could generate cross-platform applications without compromising the quality, would decrease the time to market and increase the number of potential users. This paper presents the XIS-Mobile language, defined as a UML profile in the context of the Sparx Systems Enterprise Architect, and discusses its main challenges and benefits in the context of the cross-platform mobile application development.
Hardware software co-design in Haskell

We present a library in Haskell for programming Field Programmable Gate Arrays (FPGAs), including hardware software co-design. Code for software (in C) and hardware (in VHDL) is generated from a single program, along with the code to support communication between hardware and software. We present type-based techniques for the simultaneous implementation of more than one embedded domain specific language (EDSL). We build upon a generic representation of imperative programs that is loosely coupled to instruction and expression types, allowing the individual parts to be developed and improved separately. Code generation is implemented as a series of translations between progressively smaller, typed EDSLs, safeguarding against errors that arise in untyped translations. Initial case studies show promising performance.
Location disclosure to social relations: why, when, & what people want to share

Advances in location-enhanced technology are making it easier for us to be located by others. These new technologies present a difficult privacy tradeoff, as disclosing one's location to another person or service could be risky, yet valuable. To explore whether and what users are willing to disclose about their location to social relations, we conducted a three-phased formative study. Our results show that the most important factors were who was requesting, why the requester wanted the participant's location, and what level of detail would be most useful to the requester. After determining these, participants were typically willing to disclose either the most useful detail or nothing about their location. From our findings, we reflect on the decision process for location disclosure. With these results, we hope to influence the design of future location-enhanced applications and services.
Design and Analysis of a DC–43.5-GHz Fully Integrated Distributed Amplifier Using GaAs HEMT–HBT Cascode Gain Stage

Design and analysis of a dc-43.5-GHz fully integrated distributed amplifier (DA) using a GaAs high electron-mobility transistor (HEMT) heterojunction bipolar transistor (HBT) cascode gain stage is presented in this paper. The proposed DA is fabricated in a stacked 2-μm InGaP/GaAs HBT, 0.5-μm AlGaAs/GaAs enhancement- and depletion-mode HEMT monolithic microwave integrated circuit technology. A modified m -derived network and an HEMT-HBT cascode amplifier with inductive peaking technique are investigated to enhance the bandwidth of the DA. The bias networks of the DA are fully integrated in a single chip without off-chip bias-T or bias components. The measured average small-signal gain is 8.5 dB. The measured minimum noise figure is 4.2 dB. The measured maximum output 1-dB compression point (P1 dB) and the maximum output third-order intercept point are 8 and 18 dBm, respectively. Moreover, the DA is successfully evaluated with an eye diagram measurement, and demonstrates good transmission quality.
Improved phase unwrapping algorithm based on NVIDIA CUDA

The paper presents an improved version of the region-growing algorithm for the interferometric phase unwrapping of the radar images. A method for packing/unpacking indices of points in a photograph that is based on bitwise operations is developed. A fast algorithm for generating a growth ring of target pixels and an algorithm for merging regions are created. Software implementation of the algorithm can be run on platforms using graphics devices that support the NVIDIA CUDA technology.
IRFs: master regulators of signalling by Toll-like receptors and cytosolic pattern-recognition receptors

The interferon-regulatory factor (IRF) family of transcription factors was initially found to be involved in the induction of genes that encode type I interferons. IRFs have now been shown to have functionally diverse roles in the regulation of the immune system. Recently, the crucial involvement of IRFs in innate and adaptive immune responses has been gaining much attention, particularly with the discovery of their role in immunoregulation by Toll-like receptors and other pattern-recognition receptors.
Internet of Things (IoT): Smart and Secure Service Delivery

The Internet of Things (IoT) is the latest Internet evolution that incorporates a diverse range of things such as sensors, actuators, and services deployed by different organizations and individuals to support a variety of applications. The information captured by IoT present an unprecedented opportunity to solve large-scale problems in those application domains to deliver services; example applications include precision agriculture, environment monitoring, smart health, smart manufacturing, and smart cities. Like all other Internet based services in the past, IoT-based services are also being developed and deployed without security consideration. By nature, IoT devices and services are vulnerable to malicious cyber threats as they cannot be given the same protection that is received by enterprise services within an enterprise perimeter. While IoT services will play an important role in our daily life resulting in improved productivity and quality of life, the trend has also “encouraged” cyber-exploitation and evolution and diversification of malicious cyber threats. Hence, there is a need for coordinated efforts from the research community to address resulting concerns, such as those presented in this special section. Several potential research topics are also identified in this special section.
The Classic: Congenital Club Foot: The Results of Treatment

This Classic article is a reprint of the original work by Ignacio V. Ponseti and Eugene N. Smoley, Congenital Club Foot: The Results of Treatment. An accompanying biographical sketch on Ignacio V. Ponseti, MD, is available at DOI 10.1007/s11999-009-0719-8 and a second Classic article is available at 10.1007/s11999-0090721-1. This article is 1963 by the Journal of Bone and Joint Surgery, Inc., and is reprinted with permission from Ponseti IV, Smoley EN. Congenital Club Foot: The Results of Treatment.  The Association of Bone and Joint Surgeons 2009 Richard A. Brand MD & Clinical Orthopaedics and Related Research, 1600 Spruce Street, Philadelphia, PA 19103, USA e-mail: dick.brand@clinorthop.org Since 1948, a uniform system of treatment has been applied to all cases of congenital club foot on the Orthopedic Service of the State University of Iowa. Our aim has been to obtain a supple, well corrected foot in the shortest possible time. An end-result study of severe club-foot deformities in otherwise normal children treated initially in this department from 1948 to 1956, with a follow-up period from five to twelve years, is here presented. Three hundred and twenty-two patients with club-foot deformity were treated during this period. The following were not included in this study: One hundred and fortynine patients had been originally treated in other clinics and were referred to us for further correction. Ten patients had arthrogryposis; four had a complete or partial absence of the tibia; and eighteen had a myelomeningocele. The sacrum was absent in two and congenital constriction was present in the legs above the malleoli in two patients. In forty-six patients, the foot deformity was mild and was corrected by simple manipulations or the application of one to three plaster casts. Of the remaining ninety-one otherwise normal children with severe untreated club-foot deformities, twenty-four were lost to follow-up, usually at the end of the initial treatment. We were able to evaluate the results of treatment in only sixty-seven patients with a total of ninety-four club feet. All these deformities were severe, although many variations in the degree of rigidity of the feet were present. The age of the patient at the onset of treatment ranged from one week to six months, and the average age was one month. Of the sixty-seven patients studied, ten were female and fifty-seven were male. The deformity was, therefore, almost six times as prevalent in male as in female children. Forty patients had only one foot deformed (60 per cent) and twenty-seven patients had both feet deformed (40 per cent). In the patients with unilateral involvement, the right foot was deformed in eighteen and the left foot in twenty-two cases. Anteroposterior and lateral roentgenograms and photographs of the feet of all patients were made at the onset of treatment and again at the time of the final
Intelligent code reviews using deep learning

Peer code review is a best practice in Software Engineering where source code is reviewed manually by one or more peers(reviewers) of the code author. It is widely acceptable both in industry and open-source software (OSS) systems as a process for early detection and reduction of software defects. A larger chunk of reviews given during peer reviews are related to common issues such as coding style, documentations, and best practices. This makes the code review process less effective as reviewers focus less on finding important defects. Hence, there is a need to automatically find such common issues and help reviewers perform focused code reviews. Some of this is solved by rule based systems called linters but they are rigid and needs a lot of manual effort to adapt them for a new issue. In this work, we present an automatic, flexible, and adaptive code analysis system called DeepCodeReviewer (DCR). DCR learns how to recommend code reviews related to common issues using historical peer reviews and deep learning. DCR uses deep learning to learn review relevance to a code snippet and recommend the right review from a repository of common reviews. DCR is trained on histroical peer reviews available from internal code repositories at Microsoft. Experiments demonstrate strong performance of developed deep learning model in classifying relevant and non-relevant reviews w.r.t to a code snippet, and ranking reviews given a code snippet. We have also evaluated DCR recommentations using a user study and survey. The results of our user study show good acceptance rate and answers of our survey questions are strongly correlated with our system’s goal of making code reviews focused on finding defects.
COMPARATIVE ANALYSIS FOR KINEMATICS OF 5-DOF INDUSTRIAL ROBOTIC MANIPULATOR

This paper gives the kinematic analysis of a 5-DOF industrial robotic manipulator while considering wrist in motion. Analytical solutions have been obtained for forward kinematics and inverse kinematics to accurately position the end-effector of robotic manipulator in three dimensional spaces. For the first time, a hybrid neuro-fuzzy intelligent technique with two different membership functions has been studied and their performances are comparatively evaluated with analytical solutions. An experiment has been performed for a desired trajectory. It is seen that the results for the intelligent technique are reasonably in agreement with experiment. Also, the results obtained highlight the importance of selection of a particular membership function for robotic manipulators of industrial use.
FPMR: MapReduce Framework on FPGA A Case Study of RankBoost Acceleration

Machine learning and data mining are gaining increasing attentions of the computing society. FPGA provides a highly parallel, low power, and flexible hardware platform for this domain, while the difficulty of programming FPGA greatly limits its prevalence. MapReduce is a parallel programming framework that could easily utilize inherent parallelism in algorithms. In this paper, we describe FPMR, a MapReduce framework on FPGA, which provides programming abstraction, hardware architecture, and basic building blocks to developers. An on-chip processor scheduler is implemented to maximize the utilization of computation resources and achieve better load balancing. An efficient data access scheme is carefully designed to maximize data reuse and throughput. Meanwhile, the FPMR framework hides the task control, synchronization, and communication away from designers so that more attention can be paid to the application itself. A case study of RankBoost acceleration based on FPMR demonstrates that FPMR efficiently helps with the development productivity; and the speedup is 31.8x versus CPU-based implementation. This performance is comparable to a fully manually designed version, which achieves 33.5x speedup. Two other applications: SVM, PageRank are also discussed to show the generalization of the framework.
Alzheimer disease therapy—moving from amyloid-β to tau

Disease-modifying treatments for Alzheimer disease (AD) have focused mainly on reducing levels of amyloid-β (Aβ) in the brain. Some compounds have achieved this goal, but none has produced clinically meaningful results. Several methodological issues relating to clinical trials of these agents might explain this failure; an additional consideration is that the amyloid cascade hypothesis—which places amyloid plaques at the heart of AD pathogenesis—does not fully integrate a large body of data relevant to the emergence of clinical AD. Importantly, amyloid deposition is not strongly correlated with cognition in multivariate analyses, unlike hyperphosphorylated tau, neurofibrillary tangles, and synaptic and neuronal loss, which are closely associated with memory deficits. Targeting tau pathology, therefore, might be more clinically effective than Aβ-directed therapies. Furthermore, numerous immunization studies in animal models indicate that reduction of intracellular levels of tau and phosphorylated tau is possible, and is associated with improved cognitive performance. Several tau-related vaccines are in advanced preclinical stages and will soon enter clinical trials. In this article, we present a critical analysis of the failure of Aβ-directed therapies, discuss limitations of the amyloid cascade hypothesis, and suggest the potential value of tau-targeted therapy for AD.
Integrated system of face recognition and sound localization for a smart door phone

This paper proposes a smart system using both face recognition and sound localization techniques to identify foreign faces through a door phone in a more efficient and accurate way. In particular, a visitor's voice is used to localize the proper location of the speaker. The location information is then used to adjust the door phone camera position to frame the face in its field of view. In order to accurately locate the facial position of the visitor, 4 microphones are positioned in a cross configuration. Furthermore, face detection and face recognition algorithms as well as a wireless interface are used to recognize the visitor and send the information to the home owner's phone. The entire control system is built using an FPGA chip and tested for actual use in door phone environments1.
A Patch-Based Saliency Detection Method for Assessing the Visual Privacy Levels of Objects in Photos

Photo privacy protection has recently received increasing attention from the public. However, the overprotection of photo privacy by hiding too much visual information can make photos meaningless. To avoid this, visual information with different degrees of privacy sensitivity can be filtered out using various image-processing techniques. Objects in a photo usually contain visual information that can potentially reveal private information; this potential depends on both the visual saliency of the objects and on the specific categories to which the objects belong. In this paper, we aim to quantitatively evaluate the influence of visual saliency information on privacy and objectively evaluate the levels of visual privacy that objects contain. Meeting this objective faces two challenges: 1) determining a method of effectively detecting generic objects in a photo for the extraction of saliency information and 2) determining a scientific method for assessing the visual private information contained in objects. To cope with these challenges, we first propose a hierarchical saliency detection method that combines a patch-based saliency detection strategy with an objectness estimation strategy to effectively locate salient objects and obtain the saliency information of each object. The proposed method results in a small set of class-independent locations with high quality and a mean average best overlap score of 0.627 at 1150 locations, which is superior to the score of other saliency detection methods. Second, we build a computational privacy assessment system to scientifically calculate and rank the privacy risks of objects in a photo by creating an improved risk matrix and using the Borda count method. The proposed computational privacy assessment method matches human evaluations to a relatively high degree.
A Survey of the Functional Splits Proposed for 5 G Mobile Crosshaul Networks Line

Pacing the way towards 5G has lead researchers and industry in the direction of centralized processing known from Cloud-Radio Access Networks (C-RAN). In C-RAN research, a variety of different functional splits is presented by different names and focusing on different directions. The functional split determines how many Base Station (BS) functions to leave locally, close to the user, with the benefit of relaxing fronthaul network bitrate and delay requirements, and how many functions to centralize with the possibility of achieving greater processing benefits. This work presents for the first time a comprehensive overview systematizing the different work directions for both research and industry, while providing a detailed description of each functional split option and an assessment of the advantages and disadvantages. This work gives an overview of where the most effort has been directed in terms of functional splits, and where there is room for further studies. The standardization currently taking place is also considered and mapped into the research directions. It is investigated how the fronthaul network will be affected by the choice of functional split, both in terms of bitrates and latency, and as the different functional splits provide different advantages and disadvantages, the option of flexible functional splits is also looked into. Functional Split; Crosshaul; X-haul; C-RAN; Fronthaul; standardization; industry; network architecture; Please refer to the list of acronyms provided in the end of the paper, right before the references.