nils-herrmann/clean_scirepeval huggingface dataset:
Abductive Reasoning with Description Logics: Use Case in Medical Diagnosis

Ontologies have been increasingly used as a core representation formalism in medical information systems. Diagnosis is one of the highly relevant reasoning problems in this domain. In recent years this problem has captured attention also in the description logics community and various proposals on formalising abductive reasoning problems and their computational support appeared. In this paper, we focus on a practical diagnostic problem from a medical domain – the diagnosis of diabetes mellitus – and we try to formalize it in DL in such a way that the expected diagnoses are abductively derived. Our aim in this work is to analyze abductive reasoning in DL from a practical perspective, considering more complex cases than trivial examples typically considered by the theoryor algorithm-centered literature, and to evaluate the expressivity as well as the particular formulation of the abductive reasoning problem needed to capture medical diagnosis.
Zero-Example Event Search using MultiModal Pseudo Relevance Feedback

We propose a novel method MultiModal Pseudo Relevance Feedback (MMPRF) for event search in video, which requires no search examples from the user. Pseudo Relevance Feedback has shown great potential in retrieval tasks, but previous works are limited to unimodal tasks with only a single ranked list. To tackle the event search task which is inherently multimodal, our proposed MMPRF takes advantage of multiple modalities and multiple ranked lists to enhance event search performance in a principled way. The approach is unique in that it leverages not only semantic features, but also non-semantic low-level features for event search in the absence of training data. Evaluated on the TRECVID MEDTest dataset, the approach improves the baseline by up to 158% in terms of the mean average precision. It also significantly contributes to CMU Team's final submission in TRECVID-13 Multimedia Event Detection.
The influence of match location, quality of opposition, and match status on possession strategies in professional association football.

The aim of this study was to examine the effects of match location, quality of opposition, and match status on possession strategies in a professional Spanish football team. Twenty-seven matches from the 2005-2006 domestic league season were notated post-event using a computerized match analysis system. Matches were divided into episodes according to evolving match status. Linear regression analysis showed that possession of the ball was greater when losing than when winning (P < 0.01) or drawing (P < 0.05), and playing against strong opposition was associated with a decrease in time spent in possession (P < 0.01). In addition, weighted mean percentage time spent in different zones of the pitch (defensive third, middle third, attacking third) was influenced by match status (P < 0.01) and match location (P < 0.05). A combination of these variables and their interactions can be used to develop a model to predict future possession in football. The findings emphasize the need for match analysts and coaches to consider independent and interactive potential effects of match location, quality of opposition, and match status during assessments of technical and tactical components of football performance. In particular, the findings indicate that strategies in soccer are influenced by match variables and teams alter their playing style during the game accordingly.
Remarks on Signal Processing in HF Radars Using FMCW Modulation

Besides the well known microwave radar systems mainly used in navigation, surveillance, and control applications, High-Frequency (HF) radars gain increased attention during the last decades. These HF radars are operated in the 3-30 MHz frequency range and due to ground-wave or sky-wave propagation provide over-the-horizon (OTH) capabilities. Many of these OTH radars apply frequency modulated continuous wave (FMCW) modulation for range resolution, which enables them to operate with a relatively low transmit power of a few watts only. Sometimes these types of radars are referred to as “silent radar”. This paper discusses the signal processing chain from deramping the received signal down to processing of range-Doppler-azimuth spectra. Some steps which are critical for the overall system performance are discussed in detail and a new technique to derive the structure of radio frequency interference (RFI), which is superposed to the radar echoes, is described.
Vertical and horizontal proportions of the face in young adult North American Caucasians: revision of neoclassical canons.

The validity of nine neoclassical formulas of facial proportions was tested in a group of 153 young adult North American Caucasians. Age-related qualities were investigated in six of the nine canons in 100 six-year-old, 105 twelve-year-old, and 103 eighteen-year-old healthy subjects divided equally between the sexes. The two canons found to be valid most often in young adults were both horizontal proportions (interorbital width equals nose width in 40 percent and nose width equals 1/4 face width in 37 percent). The poorest correspondences are found in the vertical profile proportions, showing equality of no more than two parts of the head and face. Sex does not influence the findings significantly, but age-related differences were observed. Twenty-four variations derived from three vertical profile, four horizontal facial, and two nasoaural neoclassical canons were identified in the group of young adults. For each of the new proportions, the mean absolute and relative differences were calculated. The absolute differences were greater between the facial profile sections (vertical canons) and smaller between the horizontally oriented facial proportions. This study shows a large variability in size of facial features in a normal face. While some of the neoclassical canons may fit a few cases, they do not represent the average facial proportions and their interpretation as a prescription for ideal facial proportions must be tested.
Image processing techniques for lemons and tomatoes classification

Vegetable quality is frequently referred to size, shape, mass, firmness, color and bruises from which fruits can be classified and sorted. However, technological by small and middle producers implementation to assess this quality is unfeasible, due to high costs of software, equipment as well as operational costs. Based on these considerations, the proposal of this research is to evaluate a new open software that enables the classification system by recognizing fruit shape, volume, color and possibly bruises at a unique glance. The software named ImageJ, compatible with Windows, Linux and MAC/OS, is quite popular in medical research and practices, and offers algorithms to obtain the above mentioned parameters. The software allows calculation of volume, area, averages, border detection, image improvement and morphological operations in a variety of image archive formats as well as extensions by means of “plugins” written in Java.
Protection: principles and practice

The protection mechanisms of computer systems control the access to objects, especially information objects. The range of responsibilities of these mechanisms includes at one extreme completely isolating executing programs from each other, and at the other extreme permitting complete cooperation and shared access among executing programs. Within this range one can identify at least seven levels at which protection mechanisms can be conceived as being required, each level being more difficult than its predecessor to implement:
 1. No sharing at all (complete isolation).
 2. Sharing copies of programs or data files.
 3. Sharing originals of programs or data files.
 4. Sharing programming systems or subsystems.
 5. Permitting the cooperation of mutually suspicious subsystems---e.g., as with debugging or proprietary subsystems.
 6. Providing "memoryless" subsystems---i.e., systems which, having performed their tasks, are guaranteed to have kept no secret record of the task performed (an income-tax computing service, for example, must be allowed to keep billing information on its use by customers but not to store information secretly on customers' incomes).
 7. Providing "certified" subsystems---i.e., those whose correctness has been completely validated and is guaranteed a priori.
Dyslexia: cultural diversity and biological unity.

The recognition of dyslexia as a neurodevelopmental disorder has been hampered by the belief that it is not a specific diagnostic entity because it has variable and culture-specific manifestations. In line with this belief, we found that Italian dyslexics, using a shallow orthography which facilitates reading, performed better on reading tasks than did English and French dyslexics. However, all dyslexics were equally impaired relative to their controls on reading and phonological tasks. Positron emission tomography scans during explicit and implicit reading showed the same reduced activity in a region of the left hemisphere in dyslexics from all three countries, with the maximum peak in the middle temporal gyrus and additional peaks in the inferior and superior temporal gyri and middle occipital gyrus. We conclude that there is a universal neurocognitive basis for dyslexia and that differences in reading performance among dyslexics of different countries are due to different orthographies.
2 A 28 GHz 32-Element Phased-Array Transceiver IC with Concurrent Dual Polarized Beams and 1 . 4 Degree Beam-Steering Resolution for 5 G Communication

Next-generation mobile technology (5G) aims to provide an improved experience through higher data-rates, lower latency, and improved link robustness. Millimeter-wave phased arrays offer a path to support multiple users at high datarates using high-bandwidth directional links between the base station and mobile devices. To realize this vision, a phased-array-based pico-cell must support a large number of precisely controlled beams, yet be compact and power efficient. These system goals have significant mm-wave radio interface implications, including scalability of the RFIC+antenna-array solution, increase in the number of concurrent beams by supporting dual polarization, precise beam steering, and high output power without sacrificing TX power efficiency. Packaged Si-based phased arrays [1-3] with nonconcurrent dual-polarized TX and RX operation [2,3], concurrent dual-polarized RX operation  and multi-IC scaling [3,4] have been demonstrated. However, support for concurrent dual-polarized operation in both RX and TX remains unaddressed, and high output power comes at the cost of power consumption, cooling complexity and increased size. The RFIC reported here addresses these challenges. It supports concurrent and independent dualpolarized operation in TX and RX modes, and is compatible with a volume-efficient, scaled, antenna-in-package array. A new TX/RX switch at the shared antenna interface enables high output power without sacrificing TX efficiency, and a t-line-based phase shifter achieves <1° RMS error and <5° phase steps for precise beam control.
Finexus: Tracking Precise Motions of Multiple Fingertips Using Magnetic Sensing

With the resurgence of head-mounted displays for virtual reality, users need new input devices that can accurately track their hands and fingers in motion. We introduce Finexus, a multipoint tracking system using magnetic field sensing. By instrumenting the fingertips with electromagnets, the system can track fine fingertip movements in real time using only four magnetic sensors. To keep the system robust to noise, we operate each electromagnet at a different frequency and leverage bandpass filters to distinguish signals attributed to individual sensing points. We develop a novel algorithm to efficiently calculate the 3D positions of multiple electromagnets from corresponding field strengths. In our evaluation, we report an average accuracy of 1.33 mm, as compared to results from an optical tracker. Our real-time implementation shows Finexus is applicable to a wide variety of human input tasks, such as writing in the air.
Rollup: Non-Disruptive Rolling Upgrade with Fast Consensus-Based Dynamic Reconfigurations

Rolling upgrade consists of upgrading progressively the servers of a distributed system to reduce service downtime.Upgrading a subset of servers requires a well-engineered cluster membership protocol to maintain, in the meantime, the availability of the system state. Existing cluster membership reconfigurations, like CoreOS etcd, rely on a primary not only for reconfiguration but also for storing information. At any moment, there can be at most one primary, whose replacement induces disruption. We propose Rollup, a non-disruptive rolling upgrade protocol with a fast consensus-based reconfiguration. Rollup relies on a candidate leader only for the reconfiguration and scalable biquorums for service requests. While Rollup implements a non-disruptive cluster membership protocol, it does not offer a full-fledged coordination service. We analyzed Rollup theoretically and experimentally on an isolated network of 26 physical machines and an Amazon EC2 cluster of 59 virtual machines. Our results show an 8-fold speedup compared to a rolling upgrade based on a primary for reconfiguration.
A Blockchain-based Access Control for Big Data

Big Data era is upon us, a huge amount of data is generated daily, analyzing and making use of this huge amount of information is a top priority for all kinds of businesses. However, one of the most important problems that hinders the unanimous adoption of Big Data is the lack of security and privacy protection of information in the Big Data tools. In this paper we contribute to reinforcing the security of Big Data platforms by proposing a blockchain-based access control framework. We define the concept of blockchain and breakdown the mechanism and principles of the access control framework.
Machine learning classification of medication adherence in patients with movement disorders using non-wearable sensors

Medication non-adherence is a major concern in the healthcare industry and has led to increases in health risks and medical costs. For many neurological diseases, adherence to medication regimens can be assessed by observing movement patterns. However, physician observations are typically assessed based on visual inspection of movement and are limited to clinical testing procedures. Consequently, medication adherence is difficult to measure when patients are away from the clinical setting. The authors propose a data mining driven methodology that uses low cost, non-wearable multimodal sensors to model and predict patients' adherence to medication protocols, based on variations in their gait. The authors conduct a study involving Parkinson's disease patients that are "on" and "off" their medication in order to determine the statistical validity of the methodology. The data acquired can then be used to quantify patients' adherence while away from the clinic. Accordingly, this data-driven system may allow for early warnings regarding patient safety. Using whole-body movement data readings from the patients, the authors were able to discriminate between PD patients on and off medication, with accuracies greater than 97% for some patients using an individually customized model and accuracies of 78% for a generalized model containing multiple patient gait data. The proposed methodology and study demonstrate the potential and effectiveness of using low cost, non-wearable hardware and data mining models to monitor medication adherence outside of the traditional healthcare facility. These innovations may allow for cost effective, remote monitoring of treatment of neurological diseases.
Batch Bayesian Optimization via Local Penalization

The popularity of Bayesian optimization methods for efficient exploration of parameter spaces has lead to a series of papers applying Gaussian processes as surrogates in the optimization of functions. However, most proposed approaches only allow the exploration of the parameter space to occur sequentially. Often, it is desirable to simultaneously propose batches of parameter values to explore. This is particularly the case when large parallel processing facilities are available. These could either be computational or physical facets of the process being optimized. Batch methods, however, require the modeling of the interaction between the different evaluations in the batch, which can be expensive in complex scenarios. We investigate this issue and propose a highly effective heuristic based on an estimate of the function’s Lipschitz constant that captures the most important aspect of this interaction— local repulsion—at negligible computational overhead. A penalized acquisition function is used to collect batches of points minimizing the non-parallelizable computational effort. The resulting algorithm compares very well, in run-time, with much more elaborate alternatives.
Iris Recognition Using Possibilistic Fuzzy Matching on Local Features

In this paper, we propose a novel possibilistic fuzzy matching strategy with invariant properties, which can provide a robust and effective matching scheme for two sets of iris feature points. In addition, the nonlinear normalization model is adopted to provide more accurate position before matching. Moreover, an effective iris segmentation method is proposed to refine the detected inner and outer boundaries to smooth curves. For feature extraction, the Gabor filters are adopted to detect the local feature points from the segmented iris image in the Cartesian coordinate system and to generate a rotation-invariant descriptor for each detected point. After that, the proposed matching algorithm is used to compute a similarity score for two sets of feature points from a pair of iris images. The experimental results show that the performance of our system is better than those of the systems based on the local features and is comparable to those of the typical systems.
Personification of the Amazon Alexa: BFF or a Mindless Companion

The conversational nature of intelligent personal assistants (IPAs) has the potential to trigger personification tendencies in users, which in turn can translate into consumer loyalty and satisfaction. We conducted a study of Amazon Alexa usage and explored the manifestations and possible correlates of users' personification of Alexa. The data were collected via diary instrument from nineteen Alexa users over four days. Less than half of the participants reported personification behaviors. Most of the personification reports can be characterized as mindless politeness (saying 'thank you' and 'please' to Alexa). Two participants expressed deeper personification by confessing their love and reprimanding Alexa. A new study is underway to understand whether expressions of personifications are caused by users' emotional attachments or skepticism about technology's intelligence.
Design of dual band wearable antenna using metamaterials.

This paper presents two types of dual band (2.4 and 5.8 GHz) wearable planar dipole antennas, one printed on a conventional substrate and the other on a two-dimensional metamaterial surface (Electromagnetic Bandgap (EBG) structure). The operation of both antennas is investigated and compared under different bending conditions (in E and H-planes) around human arm and leg of different radii. A dual band, Electromagnetic Band Gap (EBG) structure on a wearable substrate is used as a high impedance surface to control the Specific Absorption Rate (SAR) as well as to improve the antenna gain up to 4.45 dBi. The EBG inspired antenna has reduced the SAR effects on human body to a safe level (< 2W/Kg). I.e. the SAR is reduced by 83.3% for lower band and 92.8% for higher band as compared to the conventional antenna. The proposed antenna can be used for wearable applications with least health hazard to human body in Industrial, Scientific and Medical (ISM) band (2.4 GHz, 5.2 GHz) applications. The antennas on human body are simulated and analyzed in CST Microwave Studio (CST MWS).
Low-Precision Batch-Normalized Activations

Artificial neural networks can be trained with relatively low-precision floating-point and fixed-point arithmetic, using between one and 16 bits. Previous works have focused on relatively wide-but-shallow, feed-forward networks. We introduce a quantization scheme that is compatible with training very deep neural networks. Quantizing the network activations in the middle of each batch-normalization module can greatly reduce the amount of memory and computational power needed, with little loss in accuracy.
Optimized cabin power supply with a +/− 270 V DC grid on a modern aircraft

This paper deals with an onboard power supply of +/− 270 V DC (HVDC, high voltage DC). Conventional aircraft grids have a main voltage level of 115 V AC with a variable frequency of 360…800 Hz. In the future, fuel cells might replace the conventional auxiliary power unit (APU) to optimize the eco efficiency. With that technology HVDC-grids can be integrated in an aircraft. Changing to a HVDC-grid has a lot of advantages. Higher voltage means lower cable weight. Furthermore, the electrical converter architecture can be optimized. Especially the converters inside the loads can be build much lighter when using a +/− 270 V DC supply. This paper gives an overview of the electrical architecture on a modern short- and midrange aircraft and the effect of a +/− 270 V DC power grid thus focusing on the converter architecture in a modern aircraft. Concluding all benefits are summarized.
Blind Navigation Support System based on Microsoft Kinect

This paper presents a system which extends the use of the traditional white cane by the blind for navigation purposes in indoor environments. Depth data of the scene in front of the user is acquired using the Microsoft Kinect sensor which is then mapped into a pattern representation. Using neural networks, the proposed system uses this information to extract relevant features from the scene, enabling the detection of possible obstacles along the way. The results show that the neural network is able to correctly classify the type of pattern presented as input.
Extended VIKOR method in comparison with outranking methods

The VIKOR method was developed to solve MCDM problems with conflicting and noncommensurable (different units) criteria, assuming that compromising is acceptable for conflict resolution, the decision maker wants a solution that is the closest to the ideal, and the alternatives are evaluated according to all established criteria. This method focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria, and on proposing compromise solution (one or more). The VIKOR method is extended with a stability analysis determining the weight stability intervals and with trade-offs analysis. The extended VIKOR method is compared with three multicriteria decision making methods: TOPSIS, PROMETHEE, and ELECTRE. A numerical example illustrates an application of the VIKOR method, and the results by all four considered methods are compared.