nils-herrmann/clean_scirepeval huggingface dataset:
Locality-Sensitive Bloom Filter for Approximate Membership Query

In many network applications, Bloom filters are used to support exact-matching membership query for their randomized space-efficient data structure with a small probability of false answers. In this paper, we extend the standard Bloom filter to Locality-Sensitive Bloom Filter (LSBF) to provide Approximate Membership Query (AMQ) service. We achieve this by replacing uniform and independent hash functions with locality-sensitive hash functions. Such replacement makes the storage in LSBF to be locality sensitive. Meanwhile, LSBF is space efficient and query responsive by employing the Bloom filter design. In the design of the LSBF structure, we propose a bit vector to reduce False Positives (FP). The bit vector can verify multiple attributes belonging to one member. We also use an active overflowed scheme to significantly decrease False Negatives (FN). Rigorous theoretical analysis (e.g., on FP, FN, and space overhead) shows that the design of LSBF is space compact and can provide accurate response to approximate membership queries. We have implemented LSBF in a real distributed system to perform extensive experiments using real-world traces. Experimental results show that LSBF, compared with a baseline approach and other state-of-the-art work in the literature (SmartStore and LSB-tree), takes less time to respond AMQ and consumes much less storage space.
Unsupervised deformable image registration with fully connected generative neural network

In this paper, a new deformable image registration method based on a fully connected neural network is proposed. Even though a deformation field related to the point correspondence between fixed and moving images are high-dimensional in nature, we assume that these deformation fields form a low dimensional manifold in many real world applications. Thus, in our method, a neural network generates an embedding of the deformation field from a low dimensional vector. This lowdimensional manifold formulation avoids the intractability associated with the high dimensional search space that most other methods face during image registration. As a result, while most methods rely on explicit and handcrafted regularization of the deformation fields, our algorithm relies on implicitly regularizing the network parameters. The proposed method generates deformation fields from latent low dimensional space by minimizing a dissimilarity metric between a fixed image and a warped moving image. Our method removes the need for a large dataset to optimize the proposed network. The proposed method is quantitatively evaluated using images from the MICCAI ACDC challenge. The results demonstrate that the proposed method improves performance in comparison with a moving mesh registration algorithm, and also it correlates well with independent manual segmentations by an expert.
An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination

This paper reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles, and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations.
Step-by-step design and control of LCL filter based three phase grid-connected inverter

This paper proposes a detailed step-by-step design procedure and control of an LCL filter for grid connected three phase sine PWM voltage source inverter. The goal of the design is to ensure high quality of grid current as well as to minimize the size of filter magnetics. In order to ensure unity power factor injection into grid a current controller is designed with a constraint that only the inverter side inductor current is sensed. Good agreement between simulation and experimental results verify the effectiveness of the designed controller and the LCL filter.
Dual Learning based Multi-Objective Pairwise Ranking

There are many different recommendation tasks in our real life. The item ranking task is ranking a set of items based on users’ preferences. The user ranking task is referred to as user retrieval, find the potential users and recommend items to them. We find every recommendation task has it’s own dual task, e.g., Recommend an item to a user versus the user is supposed to become the item’s potential interested user. In this paper, we propose a novel dual learning based ranking framework with the overall aim of learning users’ preferences over items and learning items’ preferences over users by minimizing a pairwise ranking loss. We generate effective feedback signal from close loop formed by dual task. Through a reinforcement learning process, we can iteratively update these two tasks’ models to catch relations between the item recommendation task and the user retrieval task. The experiments show that our method outperforms classical approaches for multi-object recommendation tasks, especially for user retrieval tasks.
Planar Helical Antenna of Circular Polarization

A planar helical antenna is presented for achieving wideband end-fire radiation of circular polarization while maintaining a very low profile. The helix is formed using printed strips with straight-edge connections implemented by plated viaholes. The currents flowing on the strips and along via-holes of the helix contribute to the horizontal and vertical polarizations, respectively. Besides, the current on the ground plane is utilized to weaken the strong amplitude of the horizontal electric field generated by the one on the strips. Thus, a good circular polarization can be achieved. Furthermore, a tapered helix and conducting side-walls are employed to broaden the axial ratio (AR) bandwidth as well as to improve the end-fire radiation pattern. The designed antenna operates at the center frequency of 10 GHz. Simulated results show that the planar helical antenna achieves wide-impedance bandwidth (|S11| <; -10 dB) from 7.4 to 12.8 GHz (54%) and 3-dB AR bandwidth from 8.2 to 11.6 GHz (34%), while retaining a thickness of only 0.11λ0 at the center frequency. A prototype of the proposed antenna is fabricated and tested. Measured results are in good agreement with simulated ones.
The Penn Arabic Treebank : Building a Large-Scale Annotated Arabic Corpus

From our three year experience of developing a large-scale corpus of annotated Arabic text, our paper will address the following: (a) review pertinent Arabic language issues as they relate to methodology choices, (b) explain our choice to use the Penn English Treebank style of guidelines, (requiring the Arabic-speaking annotators to deal with a new grammatical system) rather than doing the annotation in a more traditional Arabic grammar style (requiring NLP researchers to deal with a new system); (c) show several ways in which human annotation is important and automatic analysis difficult, including the handling of orthographic ambiguity by both the morphological analyzer and human annotators; (d) give an illustrative example of the Arabic Treebank methodology, focusing on a particular construction in both morphological analysis and tagging and syntactic analysis and following it in detail through the entire annotation process, and finally, (e) conclude with what has been achieved so far and what remains to be done.
Twitter Sentiment Classification on Sanders Data using Hybrid Approach

Sentiment analysis is very perplexing and massive issue in the field of social data mining. Twitter is one of the mostly used social media where people discuss on various issues in a dense way. The tweets about a particular topic give peoples’ views, opinions, orientations, inclinations about that topic. In this work, we have used pre-labeled (with positive, negative and neutral opinion) tweets on particular topics for sentiment classification. Opinion score of each tweet is calculated using feature vectors. These opinion score is used to classify the tweets into positive, negative and neutral classes. Then using various machine learning classifiers the accuracy of predicted classification with respect to actual classification is being calculated and compared using supervised learning model. Along with building a sentiment classification model, analysis of tweets is being carried out by visualizing the wordcloud of tweets using R.
Coseismic Deformation from the 1999 M w 7 . 1 Hector Mine , California , Earthquake as Inferred from InSAR and GPS Observations

We use interferometric synthetic aperture radar (InSAR) and Global Positioning System (GPS) observations to investigate static deformation due to the 1999 Mw 7.1 Hector Mine earthquake, that occurred in the eastern California shear zone. Interferometric decorrelation, phase, and azimuth offset measurements indicate regions of surface and near-surface slip, which we use to constrain the geometry of surface rupture. The inferred geometry is spatially complex, with multiple strands. The southern third of the rupture zone consists of three subparallel segments extending about 20 km in length in a N45 W direction. The central segment is the simplest, with a single strand crossing the Bullion Mountains and a strike of N10 W. The northern third of the rupture zone is characterized by multiple splays, with directions subparallel to strikes in the southern and central. The average strike for the entire rupture is about N30 W. The interferograms indicate significant alongstrike variations in strain which are consistent with variations in the ground-based slip measurements. Using a variable resolution data sampling routine to reduce the computational burden, we invert the InSAR and GPS data for the fault geometry and distribution of slip. We compare results from assuming an elastic half-space and a layered elastic space. Results from these two elastic models are similar, although the layered-space model predicts more slip at depth than does the half-space model. The layered model predicts a maximum coseismic slip of more than 5 m at a depth of 3 to 6 km. Contrary to preliminary reports, the northern part of the Hector Mine rupture accommodates the maximum slip. Our model predictions for the surface fault offset and total seismic moment agree with both field mapping results and recent seismic models. The inferred shallow slip deficit is enigmatic and may suggest that distributed inelastic yielding occurred in the uppermost few kilometers of the crust during or soon after the earthquake.
Motivational interviewing as a prelude to coaching in healthcare settings.

Motivational interviewing is a unique counseling technique that was developed to help individuals give up addictive behaviors and learn new behavioral skills. This counseling technique relies on using communication skills to understand an individual's motivation for change. Motivational interviewing uses techniques such as open-ended questions, reflective listening, affirmation, and summarization to help individuals express their concerns about change. For those willing to change, motivational interviewing provides an opportunity for coaching including helping individuals set goals and arrive at a change plan. A 3-step approach to coaching may simplify the process of change and offer techniques for healthcare professionals to better equip them facilitate the change process.
Heating the patient : a promising approach ?

There is a clear rationale for using hyperthermia in cancer treatment. Treatment at temperatures between 40 and 44°C is cytotoxic for cells in an environment with a low pO2 and low pH, conditions that are found specifically within tumour tissue, due to insufficient blood perfusion. Under such conditions radiotherapy is less effective, and systemically applied cytotoxic agents will reach such areas in lower concentrations than in well perfused areas. Therefore, the addition of hyperthermia to radiotherapy or chemotherapy will result in at least an additive effect. Furthermore, the effects of both radiotherapy and many drugs are enhanced at an increased temperature. Hyperthermia can be applied by several methods: local hyperthermia by external or internal energy sources, regional hyperthermia by perfusion of organs or limbs, or by irrigation of body cavities, and whole body hyperthermia. The use of hyperthermia alone has resulted in complete overall response rates of 13%. The clinical value of hyperthermia in addition to other treatment modalities has been shown in randomised trials. Significant improvement in clinical outcome has been demonstrated for tumours of the head and neck, breast, brain, bladder, cervix, rectum, lung, oesophagus, vulva and vagina, and also for melanoma. Additional hyperthermia resulted in remarkably higher (complete) response rates, accompanied by improved local tumour control rates, better palliative effects and/or better overall survival rates. Generally, when combined with radiotherapy, no increase in radiation toxicity could be demonstrated. Whether toxicity from chemotherapy is enhanced depends on sequence of the two modalities, and on which tissues are heated. Toxicity from hyperthermia cannot always be avoided, but is usually of limited clinical relevance. Recent developments include improvements in heating techniques and thermometry, development of hyperthermia treatment planning models, studies on heat shock proteins and an effect on anti-cancer immune responses, drug targeting to tumours, bone marrow purging, combination with drugs targeting tumour vasculature, and the role of hyperthermia in gene therapy. The clinical results achieved to date have confirmed the expectations raised by results from experimental studies. These findings justify using hyperthermia as part of standard treatment in tumour sites for which its efficacy has been proven and, furthermore, to initiate new studies with other tumours. Hyperthermia is certainly a promising approach and deserves more attention than it has received until now.
Characterizing and visualizing physical world accessibility at scale using crowdsourcing, computer vision, and machine learning

Poorly maintained sidewalks and street intersections pose considerable accessibility challenges for people with mobility-impairments [13,14]. According to the most recent U.S. Census (2010), roughly 30.6 million adults have physical disabilities that affect their ambulatory activities [22]. Of these, nearly half report using an assistive aid such as a wheelchair (3.6 million) or a cane, crutches, or walker (11.6 million) . Despite comprehensive civil rights legislation for Americans with Disabilities (e.g., [25,26]), many city streets, sidewalks, and businesses in the U.S. remain inaccessible. The problem is not just that street-level accessibility fundamentally affects where and how people travel in cities, but also that there are few, if any, mechanisms to determine accessible areas of a city a priori. Indeed, in a recent report, the National Council on Disability noted that they could not find comprehensive information on the "degree to which sidewalks are accessible" across the US [15]. This lack of information can have a significant negative impact on the independence and mobility of citizens [13,16] For example, in our own initial formative interviews with wheelchair users, we uncovered a prevailing view about navigating to new areas of a city: "I usually don't go where I don't know [about accessible routes]" (Interviewee 3, congenital polyneuropathy). Our overarching research vision is to transform the way in which street-level accessibility information is collected and used to support new types of assistive map-based tools.
HyFlex nickel-titanium rotary instruments after clinical use: metallurgical properties.

To analyse the type and location of defects in HyFlex CM instruments after clinical use in a graduate endodontic programme and to examine the impact of clinical use on their metallurgical properties.



A total of 468 HyFlex CM instruments discarded from a graduate endodontic programme were collected after use in three teeth. The incidence and type of instrument defects were analysed. The lateral surfaces of the defect instruments were examined by scanning electron microscopy. New and clinically used instruments were examined by differential scanning calorimetry (DSC) and x-ray diffraction (XRD). Vickers hardness was measured with a 200-g load near the flutes for new and clinically used axially sectioned instruments. Data were analysed using one-way anova or Tukey's multiple comparison test.



Of the 468 HyFlex instruments collected, no fractures were observed and 16 (3.4%) revealed deformation. Of all the unwound instruments, size 20, .04 taper unwound the most often (n = 5) followed by size 25, .08 taper (n = 4). The trend of DSC plots of new instruments and clinically used (with and without defects) instruments groups were very similar. The DSC analyses showed that HyFlex instruments had an austenite transformation completion or austenite-finish (Af ) temperature exceeding 37 °C. The Af temperatures of HyFlex instruments (with or without defects) after multiple clinical use were much lower than in new instruments (P < 0.05). The enthalpy values for the transformation from martensitic to austenitic on deformed instruments were smaller than in the new instruments at the tip region (P < 0.05). XRD results showed that NiTi instruments had austenite and martensite structure on both new and used HyFlex instruments at room temperature. No significant difference in microhardness was detected amongst new and used instruments (with and without defects).



The risk of HyFlex instruments fracture in the canal is very low when instruments are discarded after three cases of clinical use. New HyFlex instruments were a mixture of martensite and austenite structure at body temperature. Multiple clinical use caused significant changes in the microstructural properties of HyFlex instruments. Smaller instruments should be considered as single-use.
Cloudlet deployment in local wireless networks: Motivation, architectures, applications, and open challenges

In past few years, advancement in mobile applications and their integration with Cloud computing services has introduced a new computing paradigm known as Mobile Cloud Computing. Although Cloud services support a wide range of mobile applications, access to these services suffers from several performance issues such as WAN latency, jitter, and packet losses. Cloudlet frameworks are proposed to overcome these performance issues. More specifically, Cloudlets aim to bring the Cloud or a specific part of the Cloud closer to the mobile device by utilizing proximate computing resources to perform compute-intensive tasks. This paper presents a comprehensive survey on the state-of-the-art mobile Cloudlet architectures. We also classify the state-of-the-art Cloudlet solutions by presenting a hierarchical taxonomy. Moreover, the areas of Cloudlet applications are also identified and presented. Cloudlet discovery, resource management, data security, mobility, application offloading, and most importantly incentives to deploy a Cloudlet are areas that still needs to be investigated by the research community. The critical aspects of the current Cloudlet frameworks in Mobile Cloud Computing are analyzed to determine the strengths and weaknesses of the frameworks. The similarities and differences of the frameworks based on the important parameters, such as scalability, mobility support, Internet dependency, dynamic configuration, energy savings, and execution cost, are also investigated. The requirements for deploying the Cloudlet in a Local Wireless Network are also highlighted and presented. We also discuss open research challenges that Cloudlet deployments face in Local Wireless Networks. & 2015
A Study of Parsing Process on Natural Language Processing in Bahasa Indonesia

Research on Natural Language Processing (NLP) in Indonesian is still limited and the results of available research that can be used for further research are also limited. In a series of natural language processing, the initial step is parsing the sentence in a particular language based on the grammar in order to help understanding the meaning of a sentence. This research aims to produce a simulation of Indonesian parser by adapting the process which was conducted by using Collins Algorithm. The three main stages are: 1) preprocessing to generate corpus and events files, 2) lexical analysis to convert the corpus into tokens, and 3) syntax analysis to build parse tree that requires file events to calculate the probability of the grammar by count the occurrence frequency on file events to determine the best sentence trees. An evaluation was performed to the parser using 30 simple sentences and the outcomes were able to generate a corpus file, file events, parse-tree and probability calculations. Nevertheless some sentences could not be parsed completely true because of the limitations of the Tree bank file in Indonesian. Some future works are to develop complete and valid Tree bank and Lexicon files.
A Light Rule-based Approach to English Subject-Verb Agreement Errors on the Third Person Singular Forms

Verb errors are one of the most common grammar errors made by non-native writers of English. This work especially focus on an important type of verb usage errors, subject-verb agreement for the third person singular forms, which has a high proportion in errors made by non-native English learners. Existing work has not given a satisfied solution for this task, in which those using supervised learning method usually fail to output good enough performance, and rule-based methods depend on advanced linguistic resources such as syntactic parsers. In this paper, we propose a rule-based method to detect and correct the concerned errors. The proposed method relies on a series of rules to automatically locate subject and predicate in four types of sentences. The evaluation shows that the proposed method gives state-of-the-art performance with quite limited linguistic resources. ∗ Correspondence author † This work was partially supported by the National Natural Science Foundation of China (No. 61170114, and No. 61272248), the National Basic Research Program of China (No. 2013CB329401), the Science and Technology Commission of Shanghai Municipality (No. 13511500200), the European Union Seventh Framework Program (No. 247619), the Cai Yuanpei Program (CSC fund 201304490199 and 201304490171), and the art and science interdiscipline funds of Shanghai Jiao Tong University, No. 14X190040031, and the Key Project of National Society Science Foundation of China, No. 15-ZDA041.
Silicon nanostructures for photonics and photovoltaics.

Silicon has long been established as the material of choice for the microelectronics industry. This is not yet true in photonics, where the limited degrees of freedom in material design combined with the indirect bandgap are a major constraint. Recent developments, especially those enabled by nanoscale engineering of the electronic and photonic properties, are starting to change the picture, and some silicon nanostructures now approach or even exceed the performance of equivalent direct-bandgap materials. Focusing on two application areas, namely communications and photovoltaics, we review recent progress in silicon nanocrystals, nanowires and photonic crystals as key examples of functional nanostructures. We assess the state of the art in each field and highlight the challenges that need to be overcome to make silicon a truly high-performing photonic material.