nils-herrmann/clean_scirepeval huggingface dataset:
Using humans as sensors: An estimation-theoretic perspective

The explosive growth in social network content suggests that the largest "sensor network" yet might be human. Extending the participatory sensing model, this paper explores the prospect of utilizing social networks as sensor networks, which gives rise to an interesting reliable sensing problem. In this problem, individuals are represented by sensors (data sources) who occasionally make observations about the physical world. These observations may be true or false, and hence are viewed as binary claims. The reliable sensing problem is to determine the correctness of reported observations. From a networked sensing standpoint, what makes this sensing problem formulation different is that, in the case of human participants, not only is the reliability of sources usually unknown but also the original data provenance may be uncertain. Individuals may report observations made by others as their own. The contribution of this paper lies in developing a model that considers the impact of such information sharing on the analytical foundations of reliable sensing, and embed it into a tool called Apollo that uses Twitter as a "sensor network" for observing events in the physical world. Evaluation, using Twitter-based case-studies, shows good correspondence between observations deemed correct by Apollo and ground truth.
A VLSI Implementation of an Analog Neural Network Suited for Genetic Algorithms

The usefulness of an artificial analog neural network is closely bound to its trainability. This paper introduces a new analog neural network architecture using weights determined by a genetic algorithm. The first VLSI implementation presented in this paper achieves 200 giga connections per second with 4096 synapses on less than 1 mm silicon area. Since the training can be done at the full speed of the network, several hundred individuals per second can be tested by the genetic algorithm. This makes it feasible to tackle problems that require large multi-layered networks.
Three dual polarized 2.4GHz microstrip patch antennas for active antenna and in-band full duplex applications

This paper presents the design, implementation and interport isolation performance evaluation of three dual port, dual polarized 2.4GHz microstrip patch antennas. Input matching and interport isolation (both DC and RF) performance of implemented antennas has been compared by measuring the input return losses (Sii, S22) and interport isolation (S12) respectively at 2.4GHz. Two implemented single layer antennas provide around 40dB RF interport isolation while the multilayer antenna has 60dB isolation between transmit and receive ports at centre frequency with DC isolated ports. The multilayer antenna provides more than 55dB interport isolation for antenna's 10 dB input impedance bandwidth of 50MHz.
Does mindfulness meditation improve anxiety and mood symptoms? A review of the controlled research.

To review the impact of mindfulness-based stress reduction (MBSR) on symptoms of anxiety and depression in a range of clinical populations.



Our review included any study that was published in a peer-reviewed journal, used a control group, and reported outcomes related to changes in depression and anxiety. We extracted the following key variables from each of the 15 studies identified: anxiety or depression outcomes after the MBSR program, measurement of compliance with MBSR instructions, type of control group included, type of clinical population studied, and length of follow-up. We also summarized modifications to the MBSR program.



Measures of depression and anxiety were included as outcome variables for a broad range of medical and emotional disorders. Evidence for a beneficial effect of MBSR on depression and anxiety was equivocal. When active control groups were used, MBSR did not show an effect on depression and anxiety. Adherence to the MBSR program was infrequently assessed. Where it was assessed, the relation between practising mindfulness and changes in depression and anxiety was equivocal.



MBSR does not have a reliable effect on depression and anxiety.
An Approach to Extract Product Features from Chinese Consumer Reviews and Establish Product Feature Structure Tree

With the progress of e-commerce and web technology, a large volume of consumer reviews for products are generated from time to time, which contain rich information regarding consumer requirements and preferences. Although China has the largest e-commerce market in the world, but few of researchers investigated how to extract product feature from Chinese consumer reviews effectively, not to analyze the relations among product features which are very significant to implement comprehensive applications. In this research, a framework is proposed to extract product features from Chinese consumer reviews and construct product feature structure tree. Through three filtering algorithms and two-stage optimizing word segmantation process, phrases are identified from consumer reviews. And the expanded rule template, which consists of elements: phrase, POS, dependency relation, governing word, and opinion, is constructed to train the model of conditional random filed (CRF). Then the product features are extracted based on CRF. Besides, two index are defined to describe product feature quantitatively such as frequency and sentiment score. Based on these, product feature structure tree is established through a potential parent node searching process. Furthermore, categories of extensive experiments are conducted based on 5,806 experimental corpuses from taobao.com, suning.com, and zhongguancun.com. The results from these experiments provide evidences to guide product feature extraction process. Finally, an application of analyzing the influences among product features is conducted based on product feature structure tree. It provides valuable management connotations for designer, manufacturer, or retailer.  China Jiliang University E-mail: {lionkingxxs, linjing, xiaoying, yujianzhe}@cjlu.edu.cn The author for Correspondence is Xinsheng Xu. 54 Xinsheng Xu et al.
TAaaS: Trustworthy Authentication as a Service Based on Trusted Path

Authentication as a Service (AaaS) provides on-demand delivery of multi-factor authentication (MFA). However, current AaaS has left out of consideration the trustworthiness of user inputs at client evices and the risk of privacy exposure at the AaaS providers. To solve these concerns, we present TAaaS, Trustworthy Authentication as a Service, which offers a trusted path-based MFA service to the service provider in the cloud. TAaaS leverages the hypervisor-based trusted path to ensure the trustworthiness of user inputs, and addresses privacy concerns in the cloud by storing only the irreversible user account information. We implement two end-to-end prototypes and evaluate our work to show its feasibility and security.
Remarkable archaeal diversity detected in a Yellowstone National Park hot spring environment.

Of the three primary phylogenetic domains--Archaea (archaebacteria), Bacteria (eubacteria), and Eucarya (eukaryotes)--Archaea is the least understood in terms of its diversity, physiologies, and ecological panorama. Although many species of Crenarchaeota (one of the two recognized archaeal kingdoms sensu Woese [Woese, C. R., Kandler, O. & Wheelis, M. L. (1990) ]) have been isolated, they constitute a relatively tight-knit cluster of lineages in phylogenetic analyses of rRNA sequences. It seemed possible that this limited diversity is merely apparent and reflects only a failure to culture organisms, not their absence. We report here phylogenetic characterization of many archaeal small subunit rRNA gene sequences obtained by polymerase chain reaction amplification of mixed population DNA extracted directly from sediment of a hot spring in Yellowstone National Park. This approach obviates the need for cultivation to identify organisms. The analyses document the existence not only of species belonging to well-characterized crenarchaeal genera or families but also of crenarchaeal species for which no close relatives have so far been found. The large number of distinct archaeal sequence types retrieved from this single hot spring was unexpected and demonstrates that Crenarchaeota is a much more diverse group than was previously suspected. The results have impact on our concepts of the phylogenetic organization of Archaea.
Battling the digital forensic backlog through data deduplication

In recent years, technology has become truly pervasive in everyday life. Technological advancement can be found in many facets of life, including personal computers, mobile devices, wearables, cloud services, video gaming, web-powered messaging, social media, Internet-connected devices, etc. This technological influence has resulted in these technologies being employed by criminals to conduct a range of crimes — both online and offline. Both the number of cases requiring digital forensic analysis and the sheer volume of information to be processed in each case has increased rapidly in recent years. As a result, the requirement for digital forensic investigation has ballooned, and law enforcement agencies throughout the world are scrambling to address this demand. While more and more members of law enforcement are being trained to perform the required investigations, the supply is not keeping up with the demand. Current digital forensic techniques are arduously time-consuming and require a significant amount of man power to execute. This paper discusses a novel solution to combat the digital forensic backlog. This solution leverages a deduplication-based paradigm to eliminate the reacquisition, redundant storage, and reanalysis of previously processed data.
Lifetime Portfolio Selection By Dynamic Stochastic Programming

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Familial Severe Gigantomastia and Reduction with the Free Nipple Graft Vertical Mammoplasty Technique: Report of Two Cases

Gigantomastia, characterized by massive breast enlargement during adolescence or pregnancy, is thought to be caused by an abnormal and excessive end organ response to a normal hormonal milieu. The amputation technique with the free nipple–areola graft is the mainstay for severe macromastia, but it has been criticized because it results in a flattened, nonaesthetic breast with poor projection. This report presents two sisters with unusual, excessive breast enlargement. The measured distance from the sternal notch to the nipple was 50 cm for the first case and 55 cm for the second case. The free nipple graft transplantation based on the vertical mammoplasty technique was used, and an average of 4,200 g of breast tissue per breast was removed. To increase breast projection, superior dermoglandular flaps were used The follow-up period was 24 months. The patients had long-lasting, pronounced breast mound projection, and the level of satisfaction for both cases was very high. The ideal geometric structure of the breast is rather conical, and the authors believe that reshaping the breast tissue in a vertical plane using the vertical mammoplasty technique may be more effective in the long term and may provide better projection.
Angular position measurement using resolvers together with a robust linearization technique

Resolvers are used for both absolute angular and linear position sensing. A robust amplitude to phase converter is described for the determination of position from the sine and cosine output signals of the resolver. The scheme is based on a linearization technique for converting the co-sinusoids into a nearly perfect triangular signal from which the angle is determined using simple linear equation. Even though the amplitudes of the resolver output signals are proportional to that of the resolver excitation signal, the proposed amplitude to phase technique is robust to fluctuation and drift of the amplitude and frequency of the excitation signal. The theoretical absolute error of non-linearity of the converter is 0.0082 degree over the full 360 degree range. The converter may be implemented numerically or electronically. In this work, details are given for an implementation using basic analogue electronic circuitry The theory of operation and experimental results are given.
Consistency in Networks of Relations

Artificial intelligence tasks which can be formulated as constraint satisfaction problems, with which this paper is for the most part concerned, are usually solved by backtracking. By examining the thrashing behavior that nearly always accompanies backtracking, identifying three of its causes and proposing remedies for them we are led to a class of algorithms which can profitably be used to eliminate local (node, arc and path) inconsistencies before any attempt is made to construct a complete solution. A more general paradigm for attacking these tasks is the alternation of constraint manipulation and case analysis producing an OR problem graph which may be searched in any of the usual ways. Many authors, particularly Montanan i and Waltz, have contributed to the development of these ideas; a secondary aim of this paper is to trace that history. The primary aim is to provide an accessible, unified framework, within which to present the algorithms including a new path consistency algorithm, to discuss their relationships and the many applications, both realized and potential, of network consistency algorithms.
Timing attacks on Web privacy

We describe a class of attacks that can compromise the privacy of users’ Web-browsing histories. The attacks allow a malicious Web site to determine whether or not the user has recently visited some other, unrelated Web page. The malicious page can determine this information by measuring the time the user’s browser requires to perform certain operations. Since browsers perform various forms of caching, the time required for operations depends on the user’s browsing history; this paper shows that the resulting time variations convey enough information to compromise users’ privacy. This attack method also allows other types of information gathering by Web sites, such as a more invasive form of Web “cookies”. The attacks we describe can be carried out without the victim’s knowledge, and most “anonymous browsing” tools fail to prevent them. Other simple countermeasures also fail to prevent these attacks. We describe a way of reengineering browsers to prevent most of them.
Data Security in the World of Cloud Computing

Today, we have the ability to utilize scalable, distributed computing environments within the confines of the Internet, a practice known as cloud computing. In this new world of computing, users are universally required to accept the underlying premise of trust. Within the cloud computing world, the virtual environment lets users access computing power that exceeds that contained within their own physical worlds. Typically, users will know neither the exact location of their data nor the other sources of the data collectively stored with theirs. The data you can find in a cloud ranges from public source, which has minimal security concerns, to private data containing highly sensitive information (such as social security numbers, medical records, or shipping manifests for hazardous material). Does using a cloud environment alleviate the business entities of their responsibility to ensure that proper security measures are in place for both their data and applications, or do they share joint responsibility with service providers? The answers to this and other questions lie within the realm of yet-to-be-written law. As with most technological advances, regulators are typically in a "catch-up" mode to identify policy, governance, and law. Cloud computing presents an extension of problems heretofore experienced with the Internet. To ensure that such decisions are informed and appropriate for the cloud computing environment, the industry itself should establish coherent and effective policy and governance to identify and implement proper security methods.
Diversifying Web Service Recommendation Results via Exploring Service Usage History

The last decade has witnessed a tremendous growth of web services as a major technology for sharing data, computing resources, and programs on the web. With the increasing adoption and presence of web services, design of novel approaches for effective web service recommendation to satisfy users' potential requirements has become of paramount importance. Existing web service recommendation approaches mainly focus on predicting missing QoS values of web service candidates which are interesting to a user using collaborative filtering approach, content-based approach, or their hybrid. These recommendation approaches assume that recommended web services are independent to each other, which sometimes may not be true. As a result, many similar or redundant web services may exist in a recommendation list. In this paper, we propose a novel web service recommendation approach incorporating a user's potential QoS preferences and diversity feature of user interests on web services. User's interests and QoS preferences on web services are first mined by exploring the web service usage history. Then we compute scores of web service candidates by measuring their relevance with historical and potential user interests, and their QoS utility. We also construct a web service graph based on the functional similarity between web services. Finally, we present an innovative diversity-aware web service ranking algorithm to rank the web service candidates based on their scores, and diversity degrees derived from the web service graph. Extensive experiments are conducted based on a real world web service dataset, indicating that our proposed web service recommendation approach significantly improves the quality of the recommendation results compared with existing methods.
Performances of OpenFlow-Based Software-Defined Networks: An overview

Software Defined Networking (SDN) has gained significant attention from network researchers and industry in recent years. Indeed, the SDN concept provides many advantages such as programmability and easy management of the network. However, it generates new challenges as scalability and performances issues, understanding in-depth the performances and limitations of the SDN concept is a prerequisite to its implementation and deployment in real networks. In this paper, we aim to present in a comprehensive way, the most important works that focus on performances of SDN. As SDN separates the control plane from the data plane, we first present research efforts made to enhance the performances of data plane devices, then, we give an overview of different solutions proposed to improve controller performances. We provide also an overview on recent control plane architectures with multiple controllers that have been proposed to meet performances and scalability constraints. Finally, we present the different techniques and tools used in literature to evaluate the performances of software defined networks.
Serverless Cloud Computing : A Comparison Between "Function as a Service" Platforms

Cloud computing is moving fast and continually progressing. Beyond the microservices architecture, a new paradigm appears to be evolving and complementing it. By using a serverless computing architecture, faster and more reliable developments are possible in several fields such as the Internet of Things, industrial or mobility applications. In this paper, a serverless computing architecture is described and, in addition, a comparison of the most important "Function as a Service" platforms is given.
Blockchain Mining Games

We study the strategic considerations of miners participating in the bitcoin's protocol. We formulate and study the stochastic game that underlies these strategic considerations. The miners collectively build a tree of blocks, and they are paid when they create a node (mine a block) which will end up in the path of the tree that is adopted by all. Since the miners can hide newly mined nodes, they play a game with incomplete information. Here we consider two simplified forms of this game in which the miners have complete information. In the simplest game the miners release every mined block immediately, but are strategic on which blocks to mine. In the second more complicated game, when a block is mined it is announced immediately, but it may not be released so that other miners cannot continue mining from it. A miner not only decides which blocks to mine, but also when to release blocks to other miners. In both games, we show that when the computational power of each miner is relatively small, their best response matches the expected behavior of the bitcoin designer. However, when the computational power of a miner is large, he deviates from the expected behavior, and other Nash equilibria arise.
KPB-SIFT: a compact local feature descriptor

Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and object recognition. However, such descriptors are typically of high dimensionality, e.g. 128-dimension in the case of SIFT. This limits the performance of feature matching techniques in terms of speed and scalability. A new compact feature descriptor, called Kernel Projection Based SIFT (KPB-SIFT), is presented in this paper. Like SIFT, our descriptor encodes the salient aspects of image information in the feature point's neighborhood. However, instead of using SIFT's smoothed weighted histograms, we apply kernel projection techniques to orientation gradient patches. The produced KPB-SIFT descriptor is more compact as compared to the state-of-the-art, does not require pre-training step needed by PCA based descriptors, and shows superior advantages in terms of distinctiveness, invariance to scale, and tolerance of geometric distortions. We extensively evaluated the effectiveness of KPB-SIFT with datasets acquired under varying circumstances.