nils-herrmann/clean_scirepeval huggingface dataset:
An ISAR Imaging Method Based on MIMO Technique

With the inverse synthetic aperture radar (ISAR) imaging model, targets should move smoothly during the coherent processing interval (CPI). Since the CPI is quite long, fluctuations of a target's velocity and gesture will deteriorate image quality. This paper presents a multiple-input-multiple-output (MIMO)-ISAR imaging method by combining MIMO techniques and ISAR imaging theory. By using a special M-transmitter N-receiver linear array, a group of M orthogonal phase-code modulation signals with identical bandwidth and center frequency is transmitted. With a matched filter set, every target response corresponding to the orthogonal signals can be isolated at each receiving channel, and range compression is completed simultaneously. Based on phase center approximation theory, the minimum entropy criterion is used to rearrange the echo data after the target's velocity has been estimated, and then, the azimuth imaging will finally finish. The analysis of imaging and simulation results show that the minimum CPI of the MIMO-ISAR imaging method is 1/MN of the conventional ISAR imaging method under the same azimuth-resolution condition. It means that most flying targets can satisfy the condition that targets should move smoothly during CPI; therefore, the applicability and the quality of ISAR imaging will be improved.
PICO, PICOS and SPIDER: a comparison study of specificity and sensitivity in three search tools for qualitative systematic reviews

Qualitative systematic reviews are increasing in popularity in evidence based health care. Difficulties have been reported in conducting literature searches of qualitative research using the PICO search tool. An alternative search tool, entitled SPIDER, was recently developed for more effective searching of qualitative research, but remained untested beyond its development team.



In this article we tested the 'SPIDER' search tool in a systematic narrative review of qualitative literature investigating the health care experiences of people with Multiple Sclerosis. Identical search terms were combined into the PICO or SPIDER search tool and compared across Ovid MEDLINE, Ovid EMBASE and EBSCO CINAHL Plus databases. In addition, we added to this method by comparing initial SPIDER and PICO tools to a modified version of PICO with added qualitative search terms (PICOS).



Results showed a greater number of hits from the PICO searches, in comparison to the SPIDER searches, with greater sensitivity. SPIDER searches showed greatest specificity for every database. The modified PICO demonstrated equal or higher sensitivity than SPIDER searches, and equal or lower specificity than SPIDER searches. The modified PICO demonstrated lower sensitivity and greater specificity than PICO searches.



The recommendations for practice are therefore to use the PICO tool for a fully comprehensive search but the PICOS tool where time and resources are limited. Based on these limited findings the SPIDER tool would not be recommended due to the risk of not identifying relevant papers, but has potential due to its greater specificity.
Low-Voltage CMOS Current Feedback Operational Amplifier and Its Application

ETRI Journal, Volume 29, Number 2, April 2007 A novel low-voltage CMOS current feedback operational amplifier (CFOA) is presented. This realization nearly allows rail-to-rail input/output operations. Also, it provides high driving current capabilities. The CFOA operates at supply voltages of ±0.75 V with a total standby current of 304 μA. The circuit exhibits a bandwidth better than 120 MHz and a current drive capability of ±1 mA. An application of the CFOA to realize a new all-pass filter is given. PSpice simulation results using 0.25 μm CMOS technology parameters for the proposed CFOA and its application are given.
Computational Optimal Transport for 5G Massive C-RAN Device Association

The massive scale of future wireless networks will cause computational bottlenecks in performance optimization. In this paper, we study the problem of connecting mobile traffic to Cloud RAN (C-RAN) stations. To balance station load, we steer the traffic by designing device association rules. The baseline association rule connects each device to the station with the strongest signal, which does not account for interference or traffic hot spots, and leads to load imbalances and performance deterioration. Instead, we can formulate an optimization problem to decide centrally the best association rule at each time instance. However, in practice this optimization has such high dimensions, that even linear programming solvers fail to solve. To address the challenge of massive connectivity, we propose an approach based on the theory of optimal transport, which studies the economical transfer of probability between two distributions. Our proposed methodology can further inspire scalable algorithms for massive optimization problems in wireless networks.
Community-based topic modeling for social tagging

Exploring community is fundamental for uncovering the connections between structure and function of complex networks and for practical applications in many disciplines such as biology and sociology. In this paper, we propose a TTR-LDA-Community model which combines the Latent Dirichlet Allocation model (LDA) and the Girvan-Newman community detection algorithm with an inference mechanism. The model is then applied to data from Delicious, a popular social tagging system, over the time period of 2005-2008. Our results show that 1) users in the same community tend to be interested in similar set of topics in all time periods; and 2) topics may divide into several sub-topics and scatter into different communities over time. We evaluate the effectiveness of our model and show that the TTR-LDA-Community model is meaningful for understanding communities and outperforms TTR-LDA and LDA models in tag prediction.
ON LI-ION BATTERY AGEING ESTIMATION TECHNIQUES FOR GREEN ENERGY VEHICLES

Over the last few years, research scientists have proved that lithium-ion (Li-ion) battery can successfully compete as a rechargeable battery for green energy vehicles (electric vehicles or EVs, hybrid electric vehicles or HEVs) because of its higher energy density and lighter weight. However, capacity fade and battery pack failures remain a hindrance to its maximum utilisation. Failure not only leads in huge replacement cost but also prospective safety concerns such as short circuiting or overheating which may induce fire accidents and it becomes aggressive with ageing. That is why ageing estimation, health monitoring in terms of state of health (SoH) and end of life (EoL) estimation ability in battery equipped systems are of major concern. This paper critique novel research and development in the field of Li-ion battery ageing estimation and health monitoring. Various models, techniques and algorithms have been presented along with their pros and cons. The intent of this review and discussion is to prepare an inclusive perspective on progress and challenges in monitoring Li-ion battery ageing.
Honey as a Potential Natural Antioxidant Medicine: An Insight into Its Molecular Mechanisms of Action

Honey clasps several medicinal and health effects as a natural food supplement. It has been established as a potential therapeutic antioxidant agent for various biodiverse ailments. Data report that it exhibits strong wound healing, antibacterial, anti-inflammatory, antifungal, antiviral, and antidiabetic effects. It also retains immunomodulatory, estrogenic regulatory, antimutagenic, anticancer, and numerous other vigor effects. Data also show that honey, as a conventional therapy, might be a novel antioxidant to abate many of the diseases directly or indirectly associated with oxidative stress. In this review, these wholesome effects have been thoroughly reviewed to underscore the mode of action of honey exploring various possible mechanisms. Evidence-based research intends that honey acts through a modulatory road of multiple signaling pathways and molecular targets. This road contemplates through various pathways such as induction of caspases in apoptosis; stimulation of TNF-α, IL-1β, IFN-γ, IFNGR1, and p53; inhibition of cell proliferation and cell cycle arrest; inhibition of lipoprotein oxidation, IL-1, IL-10, COX-2, and LOXs; and modulation of other diverse targets. The review highlights the research done as well as the apertures to be investigated. The literature suggests that honey administered alone or as adjuvant therapy might be a potential natural antioxidant medicinal agent warranting further experimental and clinical research.
Sentiment Analysis of Steam Review Datasets using Naive Bayes and Decision Tree Classifier

Sentiment analysis or opinion mining is one of the major topics in Natural Language Processing and Text Mining. This paper will provide a complete process of sentiment analysis from data gathering and data preparation to final classification on a user-generated sentimental dataset with Naive Bayes and Decision Tree classifiers. The dataset used for analysis is the product reviews from Steam, a digital distribution platform. The performance of different feature selection models and classifiers will be compared. The trained classifier can be used to make prediction for unlabeled reviews and help companies to increase potential profits in global digital product market.
Using heterogeneous multilevel swarms of UAVs and high-level data fusion to support situation management in surveillance scenarios

The development and usage of Unmanned Aerial Vehicles (UAVs) quickly increased in the last decades, mainly for military purposes. This technology is also now of high interest in non-military contexts like logistics, environmental studies and different areas of civil protection. While the technology for operating a single UAV is rather mature, additional efforts are still necessary for using UAVs in fleets (or swarms). The Aid to SItuation Management based on MUltimodal, MUltiUAVs, MUltilevel acquisition Techniques (ASIMUT) project which is supported by the European Defence Agency (EDA) aims at investigating and demonstrating dedicated surveillance services based on fleets of UAVs. The aim is to enhance the situation awareness of an operator and to decrease his workload by providing support for the detection of threats based on multi-sensor multi-source data fusion. The operator is also supported by the combination of information delivered by the heterogeneous swarms of UAVs and by additional information extracted from intelligence databases. As a result, a distributed surveillance system increasing detection, high-level data fusion capabilities and UAV autonomy is proposed.
On-chip vs. off-chip memory: the data partitioning problem in embedded processor-based systems

Efficient utilization of on-chip memory space is extremely important in modern embedded system applications based on processor cores. In addition to a data cache that interfaces with slower off-chip memory, a fast on-chip SRAM, called Scratch-Pad memory, is often used in several applications, so that critical data can be stored there with a guaranteed fast access time. We present a technique for efficiently exploiting on-chip Scratch-Pad memory by partitioning the application's scalar and arrayed variables into off-chip DRAM and on-chip Scratch-Pad SRAM, with the goal of minimizing the total execution time of embedded applications. We also present extensions of our proposed memory assignment strategy to handle context switching between multiple programs, as well as a generalized memory hierarchy. Our experiments on code kernels from typical applications show that our technique results in significant performance improvements.
The rkd-Tree : An Improved kd-Tree for Fast n-Closest Point Queries in Large Point Sets

The kd-tree is used in various applications, such as photon simulation with photon maps, or normal estimation in point sets for reconstruction, in order to perform fast n-closest neighbour searches in huge, static data sets of point sets of arbitrary dimensions. In a number of cases, where lower dimensional point sets are embedded in higher dimensional spaces, it has been shown that the vantage point tree (vp-tree) can significantly outperform the kd-tree. In this paper we introduce the rkd-tree, a modified version of the kd-tree that applies ideas from the vp-tree to the kd-tree. This improved kd-tree version is shown to outperform both the kd-tree and the vp-tree in a number of artificial and real test-cases.
Interruption, Resumption and Domain Switching in In-Vehicle Dialogue

The use of dialogue systems in vehicles raises the problem of making sure that the dialogue does not distract the driver from the primary task of driving. Earlier studies have indicated that humans are very apt at adapting the dialogue to the traffic situation and the cognitive load of the driver. The goal of this paper is to investigate strategies for interrupting and resuming in, as well as changing topic domain of, spoken human-human in-vehicle dialogue. The results show a large variety of strategies being used, and indicate that the choice of resumption and domain-switching strategy depends partly on the topic domain being resumed, and partly on the role of the speaker (driver or passenger). These results will be used as a basis for the development of dialogue strategies for interruption, resumption and domain-switching in the DICO in-vehicle dialogue system.
Cancer statistics, 2009.

Each year, the American Cancer Society estimates the number of new cancer cases and deaths expected in the United States in the current year and compiles the most recent data on cancer incidence, mortality, and survival based on incidence data from the National Cancer Institute, Centers for Disease Control and Prevention, and the North American Association of Central Cancer Registries and mortality data from the National Center for Health Statistics. Incidence and death rates are standardized by age to the 2000 United States standard million population. A total of 1,479,350 new cancer cases and 562,340 deaths from cancer are projected to occur in the United States in 2009. Overall cancer incidence rates decreased in the most recent time period in both men (1.8% per year from 2001 to 2005) and women (0.6% per year from 1998 to 2005), largely because of decreases in the three major cancer sites in men (lung, prostate, and colon and rectum [colorectum]) and in two major cancer sites in women (breast and colorectum). Overall cancer death rates decreased in men by 19.2% between 1990 and 2005, with decreases in lung (37%), prostate (24%), and colorectal (17%) cancer rates accounting for nearly 80% of the total decrease. Among women, overall cancer death rates between 1991 and 2005 decreased by 11.4%, with decreases in breast (37%) and colorectal (24%) cancer rates accounting for 60% of the total decrease. The reduction in the overall cancer death rates has resulted in the avoidance of about 650,000 deaths from cancer over the 15-year period. This report also examines cancer incidence, mortality, and survival by site, sex, race/ethnicity, education, geographic area, and calendar year. Although progress has been made in reducing incidence and mortality rates and improving survival, cancer still accounts for more deaths than heart disease in persons younger than 85 years of age. Further progress can be accelerated by applying existing cancer control knowledge across all segments of the population and by supporting new discoveries in cancer prevention, early detection, and treatment.
Designing a universal keyboard using chording gloves

A universal input device for both text and Braille input was developed in a Glove-typed interface using all the joints of the four fingers and thumbs of both hands. The glove-typed device works as of now for input of Korean characters, numbers, and Braille characters using mode conversion. Considering the finger force and the fatigue from repeated finger motions, the input switch was made of conductible silicon ink, which is easy to apply to any type of surface, light, and enduring. The usability testing with (1) blind subjects showed the performance matching with a commercial Braille keypad, and (2) non-blind subjects for Korean characters showed comparable performance with cellular phone input keypads, but inferior to conventional keyboard. Subjects' performance showed that the chording gloves can input approximately 122 Braille characters per minute and 108 words per minute in Korean character. The chording gloves developed in our study is expected to be used with common computing devices such as PCs and PDAs, and can contribute to replacing the Braille-based note-takers with less expensive computing devices for blind users.
Component-Based Software Engineering

ick up just about any software trade journal, and you'll find yourself inundated with something about components: there's Microsoft's DNA, Sun's Enterprise JavaBeans and Java Platform for the Enterprise, IBM's San Francisco project, the componentization of SAP's R/3—the list goes on. It's easy to see that a discipline is emerging, and yet there's little agreement on what " components " and " component-based software engineering " are. We thought it would be both interesting and useful to take a snapshot of this emerging domain so as to help IEEE Software's readers understand some of its key aspects. In the last few years, components and component-based software engineering have gained substantial interest in the software community. Conceptually, CBSE unifies concepts from a number of software domains, such as object-oriented programming , megaprogramming, software architecture, and distributed computing. Indeed, it appears that the two main drivers for CBSE are the emergence of commercial distributed-computing infrastructures such as DCOM and Corba, and the increasing need for interoperability of independently developed software " chunks. " The rate of change in the software world is such that shortly after the ink dries on this issue, we can only hope to have captured a snapshot of a rapidly maturing domain. To this end, we were pleasantly surprised at the large number of Components are " hot, " and changing at a fast pace. Here are industry forecasts from t wo leaders in the field, followed by a state-of-the-practice over view and some of the latest work in CBSE.
An Outer-Rotor Flux-Switching Permanent-Magnet-Machine With Wedge-Shaped Magnets for In-Wheel Light Traction

This paper proposes a novel outer-rotor flux-switching permanent-magnet (OR-FSPM) machine with specific wedge-shaped magnets for in-wheel light-weight traction applications. First, the geometric topology is introduced. Then, the combination principle of stator slots and rotor poles for OR-FSPM machines is investigated. Furthermore, to demonstrate the relationship between performance specifications (e.g., torque and speed) and key design parameters and dimensions (e.g., rotor outer diameter and stack length) of OR-FSPM machines at preliminary design stage, an analytical torque-sizing equation is proposed and verified by two-dimensional (2-D) finite-element analysis (FEA). Moreover, optimizations of key dimensions are conducted on an initially designed proof-of-principle three-phase 12-stator-slot/22-rotor-pole prototyped machine. Then, based on 2-D-FEA, a comprehensive comparison between a pair of OR-FSPM machines with rectangular- and wedge-shaped magnets and a surface-mounted permanent-magnet (SPM) machine is performed. The results indicate that the proposed OR-FSPM machine with wedge-shaped magnets exhibits better flux-weakening capability, higher efficiency, and wider speed range than the counterparts, especially for torque capability, where the proposed wedge-shaped magnets-based one could produce 40% and 61.5% more torque than the rectangular-shaped magnets-based machine and SPM machine, respectively, with the same rated current density (5 A/mm2). Finally, the predicted performance of the proposed OR-FSPM machine is verified by experiments on a prototyped machine.
Enhancing Root Extractors Using Light Stemmers

The rise of Natural Language Processing (NLP) opened new possibilities for various applications that were not applicable before. A morphological-rich language such as Arabic introduces a set of features, such as roots, that would assist the progress of NLP. Many tools were developed to capture the process of root extraction (stemming). Stemmers have improved many NLP tasks without explicit knowledge about its stemming accuracy. In this paper, a study is conducted to evaluate various Arabic stemmers. The study is done as a series of comparisons using a manually annotated dataset, which shows the efficiency of Arabic stemmers, and points out potential improvements to existing stemmers. The paper also presents enhanced root extractors by using light stemmers as a preprocessing phase.
Reconstruction of floor of mouth defects by the facial artery musculo-mucosal flap following cancer ablation.

The purpose of this study is to review our experience with the use of the facial artery musculo-mucosal (FAMM) flap for floor of mouth (FOM) reconstruction following cancer ablation to assess its reliability, associated complications, and functional results.



This was a retrospective analysis of 61 FAMM flaps performed for FOM reconstruction from 1997 to 2006.



No total flap loss was observed. Fifteen cases of partial flap necrosis occurred, with 2 of them requiring revision surgery. We encountered 8 other complications, with 4 of them requiring revision surgery for an overall rate of revision surgery of 10% (6/61). The majority of patients resumed to a regular diet (85%), and speech was considered as functional and/or understandable by the surgeon in 93% of the patients. Dental restoration was successful for 83% (24/29) of the patients.



The FAMM flap is well suited for FOM reconstruction because it is reliable, has few significant complications, and allows preservation of oral function.
Choice of osseous and osteocutaneous flaps for mandibular reconstruction

Microvascular free flap transfer currently represents one of the most popular methods for mandibularreconstruction. With the various free flap options nowavailable, there is a general consensus that no single kindof osseous or osteocutaneous flap can resolve the entire spectrum of mandibular defects. A suitable flap, therefore, should be selected according to the specific type of bone and soft tissue defect. We have developed an algorithm for mandibular reconstruction, in which the bony defect is termed as either “lateral” or “anterior” and the soft-tissue defect is classified as “none,” “skin or mucosal,” or “through-and-through.” For proper flap selection, the bony defect condition should be considered first, followed by the soft-tissue defect condition. When the bony defect is “lateral” and the soft tissue is not defective, the ilium is the best choice. When the bony defect is “lateral” and a small “skin or mucosal” soft-tissue defect is present, the fibula represents the optimal choice. When the bony defect is “lateral” and an extensive “skin or mucosal” or “through-and-through” soft-tissue defect exists, the scapula should be selected. When the bony defect is “anterior,” the fibula should always be selected. However, when an “anterior” bone defect also displays an “extensive” or “through-and-through” soft-tissue defect, the fibula should be usedwith other soft-tissue flaps. Flaps such as a forearm flap, anterior thigh flap, or rectus abdominis musculocutaneous flap are suitable, depending on the size of the soft-tissue defect.