nils-herrmann/clean_scirepeval huggingface dataset:
A real-time sensor fault detection, isolation and reconfiguration method for vector controlled induction motors based on Extended Kalman Filter

Vector controlled motor drives are widely used in industry application areas, usually they contain two current sensors and a speed sensor. A fault diagnosis and reconfiguration structure is proposed in this paper including current sensor measurement errors and sensors open-circuit fault. Sliding windows and special features are designed to real-time detect the measurement errors, compensations are made according to detected offset and scaling values. When open-circuit faults occur, sensor outputs are constant-zero, the residuals between the Extended Kalman Filter (EKF) outputs and the sensors outputs are larger than pre-defined close-to-zero thresholds, under healthy condition, the residuals are equal to zero, as a result, the residuals can be used for open circuit fault detection. In this situation, the feedback signals immediately switch to EKF outputs to realize reconfiguration. Fair robustness are evaluated under disturbance such as load torque changes and variable speed. Simulation results show the effectiveness and merits of the proposed methods in this paper.
The Use of Contour, Shape and Form in an Integrated Neural Approach for Object Recognition

How objects are recognised by humans is still an open research field. But, in general there is an agreement that humans recognise objects as established by the similarity principle – among othersof the Gestalt theory of visual perception, which states that things which share visual characteristics such as contour, shape, form, size, colour, texture, value or orientation will be seen as belonging together (Ellis, 1950). This principle applies to human operators; for instance, when an operator is given the task to pick up a specific object from a set of similar objects; the first approaching action will probably be guided solely by visual information clues such as shape similarity. But, if further information is given (i.e. type of surface), then a finer clustering could be accomplished to identify the target object.
SDN-Based Intrusion Detection System Literature review

The word of the network has been changed from a small group of interconnected devices to billions of devices servers, hosts, printers, Smartphone etc. This phenomena increase the requirements in term of network security. Decoupling the data and control planes Software Define Network (SDN) transforms traditional network architecture to reliable centralized manageable structure with programming ability. However, computer and network security is still the main concern for network and system administrator. Different types of software and hardware solutions are used to eliminate the dangers of attackers, but new type of attacks appear on daily bases. Intrusion Detection System (IDS) has the availability to locate and identify malicious activity in the network by examining network traffic in real time. It gives administrators visibility and reliability to monitor and control their systems. This paper present a survey of various research efforts towards the development of intrusion detection system based on software define network. SDN; IDS; OpenFlow
Document Filtering for Long-tail Entities

Filtering relevant documents with respect to entities is an essential task in the context of knowledge base construction and maintenance. It entails processing a time-ordered stream of documents that might be relevant to an entity in order to select only those that contain vital information. State-of-the-art approaches to document filtering for popular entities are entity-dependent: they rely on and are also trained on the specifics of differentiating features for each specific entity. Moreover, these approaches tend to use so-called extrinsic information such as Wikipedia page views and related entities which is typically only available only for popular head entities. Entity-dependent approaches based on such signals are therefore ill-suited as filtering methods for long-tail entities. In this paper we propose a document filtering method for long-tail entities that is entity-independent and thus also generalizes to unseen or rarely seen entities. It is based on intrinsic features, i.e., features that are derived from the documents in which the entities are mentioned. We propose a set of features that capture informativeness, entity-saliency, and timeliness. In particular, we introduce features based on entity aspect similarities, relation patterns, and temporal expressions and combine these with standard features for document filtering. Experiments following the TREC KBA 2014 setup on a publicly available dataset show that our model is able to improve the filtering performance for long-tail entities over several baselines. Results of applying the model to unseen entities are promising, indicating that the model is able to learn the general characteristics of a vital document. The overall performance across all entities---i.e., not just long-tail entities---improves upon the state-of-the-art without depending on any entity-specific training data.
Designed synthesis of uniformly sized iron oxide nanoparticles for efficient magnetic resonance imaging contrast agents.

Various magnetic nanoparticles have been extensively investigated as novel magnetic resonance imaging (MRI) contrast agents owing to their unique characteristics, including efficient contrast effects, biocompatibility, and versatile surface functionalization capability. Nanoparticles with high relaxivity are very desirable because they would increase the accuracy of MRI. Recent progress in nanotechnology enables fine control of the size, crystal structure, and surface properties of iron oxide nanoparticles. In this tutorial review, we discuss how MRI contrast effects can be improved by controlling the size, composition, doping, assembly, and surface properties of iron-oxide-based nanoparticles.
Intravascular papillary endothelial hyperplasia: histomorphological and immunohistochemical features

Intravascular papillary endothelial hyperplasia (IPEH) is a benign intravascular process with features mimicking other benign and malignant vascular proliferations. IPEH lesions predominate in the head-neck region and the extremities. The characteristic histomorphological feature of IPEH is a papillary structure covered with hyperplastic endothelial cells within the vascular lumen. It is critical that this clinically benign lesion should not be mistaken for well-differentiated vascular tumors. In addition to the characteristic histological features, other useful diagnostic features included the intra-luminal location of the lesion, an intimate association with the organizing thrombus, the absence of necrosis, cellular pleomorphism, and mitotic activity. In addition, immunohistochemistry may indicate the vascular origin and proliferative index. In this study, we evaluated histomorphological and immunohistochemical findings (CD31, CD34, FVIII, type IV collagen, SMA, MSA, CD105, and Ki-67 staining) of ten IPEH cases.



Ten IPEH cases were re-examined for a panel of histomorphological and immunohistochemical features. CD31, CD34, FVIII, Type IV collagen, SMA and MSA antibodies utilized for immunohistochemical analysis.The histomorphological and immunohistochemical findings were evaluated by two independent pathologists using light microscopy.



All ten cases involved intraluminal lesions with characteristic features of IPEH. All ten cases (100%) were stained positive for CD31 and CD34. The degree of staining with FVIII, type IV collagen, SMA, and MSA was variable.



In this series of specimens, CD31 and CD34 were the most sensitive markers indicating the vascular origin of the lesion. Staining for the other vascular markers (FVIII, type IV collagen, SMA and MSA) was variable. Different maturation degrees of lesions may account for the variation in immunohistochemical staining. Few previous investigations evaluated a wide range of antigen panels in IPEH sections. In our opinion, the evaluation of immune markers in a larger sample set will reveal new features in the maturity and developmental pathogenesis of vascular lesions and angiogenesis. IPEH is a benign lesion, which must be differentiated from malignant tumors such as angiosarcoma and Kaposi's sarcoma. Improved definition of IPEH lesions using immunohistochemical markers may enhance the ability to differentiate between various vascular lesions.



The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1381849312101856.
Prototyping nfv-based multi-access edge computing in 5G ready networks with open baton

With the increasing acceptance of Network Function Virtualization (NFV) and Software Defined Networking (SDN) technologies, a radical transformation is currently occurring inside network providers infrastructures. The trend of Software-based networks foreseen with the 5th Generation of Mobile Network (5G) is drastically changing requirements in terms of how networks are deployed and managed. One of the major changes requires the transaction towards a distributed infrastructure, in which nodes are built with standard commodity hardware. This rapid deployment of datacenters is paving the way towards a different type of environment in which the computational resources are deployed up to the edge of the network, referred to as Multi-access Edge Computing (MEC) nodes. However, MEC nodes do not usually provide enough resources for executing standard virtualization technologies typically used in large datacenters. For this reason, software containerization represents a lightweight and viable virtualization alternative for such scenarios. This paper presents an architecture based on the Open Baton Management and Orchestration (MANO) framework combining different infrastructural technologies supporting the deployment of container-based network services even at the edge of the network.
Use of the SINBAD classification system and score in comparing outcome of foot ulcer management on three continents.

To compare populations with and outcomes of diabetic foot ulcers managed in the U.K., Germany, Tanzania, and Pakistan and to explore the use of a new score of ulcer type in comparing outcomes among different countries.



Data from a series of 449 patients with diabetic foot ulcers managed in the U.K. were used to evaluate the new simplified system of classification and to derive an aggregate score. The use of the score was then explored using data from series managed in Germany (n = 239), Tanzania (n = 479), and Pakistan (n = 173).



A highly significant difference was found in time to healing between ulcers of increasing score in the U.K. series (Kruskal-Wallis test; P = 0). When data from all centers were examined, a step-up in days to healing was noted for those with scores of >or=3 (out of 6). Examination of baseline variables contributing to outcome revealed the following differences among centers: ischemia, ulcer area, and depth contributing to outcome in the U.K.; ischemia, area, depth, and infection in Germany; depth, infection, and neuropathy in Tanzania; and depth alone in Pakistan.



Any system of classification designed for general implementation must encompass all the variables that contribute to outcome in different communities. Adoption of a simple score based on these variables, the Site, Ischemia, Neuropathy, Bacterial Infection, and Depth (SINBAD) score, may prove useful in predicting ulcer outcome and enabling comparison among different centers.
Goal reasoning for autonomous underwater vehicles: Responding to unexpected agents

We describe preliminary work toward applying a goal reasoning agent for controlling an underwater vehicle in a partially observable, dynamic environment. In preparation for upcoming at-sea tests, our investigation focuses on a notional scenario wherein a autonomous underwater vehicle pursuing a survey goal unexpectedly detects the presence of a potentially hostile surface vessel. Simulations suggest that Goal Driven Autonomy can successfully reason about this scenario using only the limited computational resources typically available on underwater robotic platforms.
Combining Computational Analyses and Interactive Visualization for Document Exploration and Sensemaking in Jigsaw

Investigators across many disciplines and organizations must sift through large collections of text documents to understand and piece together information. Whether they are fighting crime, curing diseases, deciding what car to buy, or researching a new field, inevitably investigators will encounter text documents. Taking a visual analytics approach, we integrate multiple text analysis algorithms with a suite of interactive visualizations to provide a flexible and powerful environment that allows analysts to explore collections of documents while sensemaking. Our particular focus is on the process of integrating automated analyses with interactive visualizations in a smooth and fluid manner. We illustrate this integration through two example scenarios: An academic researcher examining InfoVis and VAST conference papers and a consumer exploring car reviews while pondering a purchase decision. Finally, we provide lessons learned toward the design and implementation of visual analytics systems for document exploration and understanding.
Advances in greenhouse automation and controlled environment agriculture : A transition to plant factories and urban agriculture

Greenhouse cultivation has evolved from simple covered rows of open-fields crops to highly sophisticated controlled environment agriculture (CEA) facilities that projected the image of plant factories for urban agriculture. The advances and improvements in CEA have promoted the scientific solutions for the efficient production of plants in populated cities and multi-story buildings. Successful deployment of CEA for urban agriculture requires many components and subsystems, as well as the understanding of the external influencing factors that should be systematically considered and integrated. This review is an attempt to highlight some of the most recent advances in greenhouse technology and CEA in order to raise the awareness for technology transfer and adaptation, which is necessary for a successful transition to urban agriculture. This study reviewed several aspects of a high-tech CEA system including improvements in the frame and covering materials, environment perception and data sharing, and advanced microclimate control and energy optimization models. This research highlighted urban agriculture and its derivatives, including vertical farming, rooftop greenhouses and plant factories which are the extensions of CEA and have emerged as a response to the growing population, environmental degradation, and urbanization that are threatening food security. Finally, several opportunities and challenges have been identified in implementing the integrated CEA and vertical farming for urban agriculture.
Managing home and access domains in modern broadband networks

Broadband use is booming around the globe as the infrastructure is built to provide high speed Internet and Internet Protocol television (IPTV) services. Driven by fierce competition and the search for increasing average revenue per user (ARPU), operators are evolving so they can deliver services within the home that involve a wide range of technologies, terminals, and appliances, as well as software that is increasingly rich and complex. “It should all work” is the key theme on the end user's mind, yet call centers are confronted with a multitude of consumer problems. The demarcation point between provider network and home network is blurring, in fact, if not yet in the consumer's mind. In this context, operators need to significantly rethink service lifecycle management. This paper explains how home and access support systems cover the most critical part of the network in service delivery. They build upon the inherent operation support features of access multiplexers, network termination devices, and home devices to allow the planning, fulfillment, operation, and assurance of new services.
Nonrevascularizable coronary artery disease following coronary artery bypass graft surgery: a population-based study in Olmsted County, Minnesota.

Therapeutic options for patients with recurrent cardiac ischemia after coronary artery bypass surgery may be limited and some patients may be considered nonrevascularizable. To further the understanding of this patient cohort, we performed a population-based study of post-coronary bypass patients who developed recurrent angina.



Patients who underwent coronary artery and bypass graft angiography at Mayo Clinic from 2001 to 2005 were identified. Medical records were reviewed to determine indication for angiography, and angiographic analysis was performed in all patients. Among 133 000 residents of Olmsted County, Minnesota, 347 post-bypass patients with angina underwent coronary angiography from 2001 to 2005. Of these, 177 patients received further revascularization (145 percutaneous coronary intervention and 32 redo coronary artery bypass grafting) and the remaining 170 patients were managed medically. Revascularization was not associated with improvement in all-cause or cardiac mortality. Multivariate analysis identified renal dysfunction, diabetes, and severe left ventricular dysfunction but not the lack of revascularization as predictors of mortality.



In this population-based study, we identified a yearly incidence range of 17.9-33.2 patients with nonrevascularizable angina after coronary artery bypass grafting per 100 000 population. Further revascularization was not associated with improved mortality or morbidity. Attempts to develop therapeutics for this population must consider the incidence and outcomes of this cohort.
Fractional-order controller design and digital implementation using FOMCON toolbox for MATLAB

In this paper, we present the suite of tools of the FOMCON (“Fractional-order Modeling and Control”) toolbox for MATLAB that are used to carry out fractional-order PID controller design and hardware realization. An overview of the toolbox, its structure and particular modules, is presented with appropriate comments. We use a laboratory object designed to conduct temperature control experiments to illustrate the methods employed in FOMCON to derive suitable parameters for the controller and arrive at a digital implementation thereof on an 8-bit AVR microprocessor. The laboratory object is working under a real-time simulation platform with Simulink, Real-Time Windows Target toolbox and necessary drivers as its software backbone. Experimental results are provided which support the effectiveness of the proposed software solution.
The Things of the Internet of Things in BPMN

The component "thing" of the Internet of Things does not yet exist in current business process modeling standards. The "thing" is the essential and central concept of the Internet of Things, and without its consideration we will not be able to model the business processes of the future, which will be able to measure or change states of objects in our real-world environment. The presented approach focuses on integrating the concept of the Internet of Things into the meta-model of the process modeling standard BPMN 2.0 as standard-conform as possible. By a terminological and conceptual delimitation, three components of the standard are examined and compared towards a possible expansion. By implementing the most appropriate solution, the new thing concept becomes usable for modelers, both as a graphical and machine-readable element.
Queuing Network Models to Predict the Completion Time of the Map Phase of MapReduce Jobs

Big Data processing is generally defined as a situation when the size of the data itself becomes part of the computational problem. This has made divide-and-conquer type algorithms implemented in clusters of multi-core CPUs in Hadoop/MapReduce environments an important data processing tool for many organizations. Jobs of various kinds, which consists of a number of automatically parallelized tasks, are scheduled on distributed nodes based on the capacity of the machines. A key challenge in provisioning such jobs in a Hadoop/MapReduce cluster is to be able to predict their completion times based on various job characteristics. Standard makespan computations that ignore the contention on compute nodes significantly underestimate a job’s completion time. This paper proposes a mathematically sound model based on closed Queuing Networks for predicting the execution time of the map phase of a MapReduce job. The model captures contention at compute nodes and parallelism gains due to increased number of slots available to map tasks. Experiments validated the model on a single as well as a 2-node Hadoop environment. We ran experiments for different input split sizes and different map slot sizes to validate our model.
Brain overgrowth in autism during a critical time in development: implications for frontal pyramidal neuron and interneuron development and connectivity

While abnormalities in head circumference in autism have been observed for decades, it is only recently that scientists have begun to focus in on the developmental origins of such a phenomenon. In this article we review past and present literature on abnormalities in head circumference, as well as recent developmental MRI studies of brain growth in this disorder. We hypothesize that brain growth abnormalities are greatest in frontal lobes, particularly affecting large neurons such as pyramidal cells, and speculate how this abnormality might affect neurofunctional circuitry in autism. The relationship to clinical characteristics and other disorders of macrencephaly are discussed.
Efficacy of 3 days/wk resistance training on myofiber hypertrophy and myogenic mechanisms in young vs. older adults.

Resistance training (RT) has shown the most promise in reducing/reversing effects of sarcopenia, although the optimum regime specific for older adults remains unclear. We hypothesized myofiber hypertrophy resulting from frequent (3 days/wk, 16 wk) RT would be impaired in older (O; 60-75 yr; 12 women, 13 men), sarcopenic adults compared with young (Y; 20-35 yr; 11 women, 13 men) due to slowed repair/regeneration processes. Myofiber-type distribution and cross-sectional area (CSA) were determined at 0 and 16 wk. Transcript and protein levels of myogenic regulatory factors (MRFs) were assessed as markers of regeneration at 0 and 24 h postexercise, and after 16 wk. Only Y increased type I CSA 18% (P < 0.001). O showed smaller type IIa (-16%) and type IIx (-24%) myofibers before training (P < 0.05), with differences most notable in women. Both age groups increased type IIa (O, 16%; Y, 25%) and mean type II (O, 23%; Y, 32%) size (P < 0.05). Growth was generally most favorable in young men. Percent change scores on fiber size revealed an age x gender interaction for type I fibers (P < 0.05) as growth among Y (25%) exceeded that of O (4%) men. Myogenin and myogenic differentiation factor D (MyoD) mRNAs increased (P < 0.05) in Y and O, whereas myogenic factor (myf)-5 mRNA increased in Y only (P < 0.05). Myf-6 protein increased (P < 0.05) in both Y and O. The results generally support our hypothesis as 3 days/wk training led to more robust hypertrophy in Y vs. O, particularly among men. However, this differential hypertrophy adaptation was not explained by age variation in MRF expression.