nils-herrmann/clean_scirepeval huggingface dataset:
Gender classification from hand shape

Many social interactions and services today depend on gender. In this paper, we investigate the problem of gender classification from hand shape. Our work has been motivated by studies in anthropometry and psychology suggesting that it is possible to distinguish between male and female hands by considering certain geometric features. Our system segments the hand silhouette into six different parts corresponding to the palm and fingers. To represent the geometry of each part, we use region and boundary features based on Zernike moments and Fourier descriptors. For classification, we compute the distance of a given part from two different eigenspaces, one corresponding to the male class and the other corresponding to female class. We have experimented using each part of the hand separately as well as fusing information from different parts of the hand. Using a small database containing 20 males and 20 females, we report classification results close to 98% using score-level fusion and LDA.
The Boeing 777: no Chainsaw Massacres, please!

Iterative life cycle models have become popular in software engineering, e.g. in agile development. In contrast, the waterfall model appears to prevail in manufacturing engineering disciplines. This includes aircraft engineering and Boeing’s project for developing its most recent passenger aircraft, the 777. The paper walks through the phases of the 777’s development and compares this process to iterative development. The comparison suggests two observations: Firstly, the over-all waterfall approach in the 777 project appears to be well-motivated by the physical, manufactured nature of aircraft components such as wings, in addition to safety concerns. Secondly, several iterative elements in the development of the 777 can also be identified. A major source of these is digitalization of development, in particular the use of CAD tools for a process called digital preassembly.
Expertise for cars and birds recruits brain areas involved in face recognition

Expertise with unfamiliar objects (‘greebles’) recruits face-selective areas in the fusiform gyrus (FFA) and occipital lobe (OFA). Here we extend this finding to other homogeneous categories. Bird and car experts were tested with functional magnetic resonance imaging during tasks with faces, familiar objects, cars and birds. Homogeneous categories activated the FFA more than familiar objects. Moreover, the right FFA and OFA showed significant expertise effects. An independent behavioral test of expertise predicted relative activation in the right FFA for birds versus cars within each group. The results suggest that level of categorization and expertise, rather than superficial properties of objects, determine the specialization of the FFA.
Infant grasp learning: a computational model

This paper presents ILGM (the Infant Learning to Grasp Model), the first computational model of infant grasp learning that is constrained by the infant motor development literature. By grasp learning we mean learning how to make motor plans in response to sensory stimuli such that open-loop execution of the plan leads to a successful grasp. The open-loop assumption is justified by the behavioral evidence that early grasping is based on open-loop control rather than on-line visual feedback. Key elements of the infancy period, namely elementary motor schemas, the exploratory nature of infant motor interaction, and inherent motor variability are captured in the model. In particular we show, through computational modeling, how an existing behavior (reaching) yields a more complex behavior (grasping) through interactive goal-directed trial and error learning. Our study focuses on how the infant learns to generate grasps that match the affordances presented by objects in the environment. ILGM was designed to learn execution parameters for controlling the hand movement as well as for modulating the reach to provide a successful grasp matching the target object affordance. Moreover, ILGM produces testable predictions regarding infant motor learning processes and poses new questions to experimentalists.
Non-parametric Similarity Measures for Unsupervised Texture Segmentation and Image Retrieval

In this paper we propose and examine non–parametric statistical tests to define similarity and homogeneity measure s for textures. The statistical tests are applied to the coeffi cients of images filtered by a multi–scale Gabor filter bank. We will demonstrate that these similarity measures are useful for both, texture based image retrieval and for unsupervised texture segmentation, and hence offer an unified approach to these closely related tasks. We present results on Brodatz–like micro–textures and a collection of real–word images.
Cross-language identification of consonants. Part 1. Korean perception of English.

Twenty native Korean-speaking subjects heard 22 English word-initial consonants in three vowel contexts produced by three native English talkers. The subjects orthographically labeled each English consonant as the closest Korean consonant. They then judged how similar the English consonant was to the Korean consonant on a scale of 1 to 5. Some English consonants were labeled consistently as a single Korean consonant and judged to be very similar. Other English consonants were labeled consistently as a single Korean consonant but judged to be less similar. Still other English consonants were inconsistently labeled. Korean acoustic cues, vowel context, and token differences appeared to influence labeling choices.
2-Dimensional Singular Value Decomposition for 2D Maps and Images

For a set of 1D vectors, standard singular value decomposition (SVD) is frequently applied. For a set of 2D objects such as images or weather maps, we form 2DSVD, which computes principal eigenvectors of rowrow and column-column covariance matrices, exactly as in the standard SVD. We study optimality properties of 2DSVD as low-rank approximation and show that it provides a framework unifying two recent approaches. Experiments on images and weather maps illustrate the usefulness of 2DSVD.
Organizational Transformation through Business Models: A Framework for Business Model Design

Organizations are increasingly inter-connected as they source talent, goods and services from other organizations located in disparate parts of the world. They seek new ways of creating value for themselves, customers and partners. They operate outside and across traditional industry boundaries and definitions. These innovations have lead to a focus on business models as a fundamental statement of direction and identity. This paper highlights what is known about the business model concept and where and why it differs from more established concepts of business strategy. It illustrates how the application of business models has transformed organizations. The contribution of this paper is the guidance that it provides for business model design and the insight it provides into business models and their effects on organizations. Following an analysis of how business models can transform organizations, this paper concludes with practical recommendations for business model design.
On Learning, Representing, and Generalizing a Task in a Humanoid Robot

We present a programming-by-demonstration framework for generically extracting the relevant features of a given task and for addressing the problem of generalizing the acquired knowledge to different contexts. We validate the architecture through a series of experiments, in which a human demonstrator teaches a humanoid robot simple manipulatory tasks. A probability-based estimation of the relevance is suggested by first projecting the motion data onto a generic latent space using principal component analysis. The resulting signals are encoded using a mixture of Gaussian/Bernoulli distributions (Gaussian mixture model/Bernoulli mixture model). This provides a measure of the spatio-temporal correlations across the different modalities collected from the robot, which can be used to determine a metric of the imitation performance. The trajectories are then generalized using Gaussian mixture regression. Finally, we analytically compute the trajectory which optimizes the imitation metric and use this to generalize the skill to different contexts
The use of semantic-based predicates implication to improve horizontal multimedia database fragmentation

Database fragmentation allows reducing irrelevant data accesses by grouping data frequently accessed together in dedicated segments. In this paper, we address multimedia database fragmentation to take into account the rich characteristics of multimedia objects. We particularly discuss multimedia primary horizontal fragmentation and focus on semantic-based textual predicates implication required as a pre-process in current fragmentation algorithms in order to partition multimedia data efficiently. Identifying semantic implication between similar queries (if a user searches for the images containing a car, he would probably mean auto, vehicle, van or sport-car as well) will improve the fragmentation process. Making use of the neighborhood concept in knowledge bases to identify semantic implications constitutes the core of our proposal. A prototype has been implemented to evaluate the performance of our approach.
Design and Implementation of Single Phase Inverter

A microcontroller based advanced technique of generating sine wave with lowest harmonics is designed and implemented in this paper. The main objective of our proposed technique is to design a low cost, low harmonics voltage source inverter. In our project we used PIC16F73 microcontroller to generate 4 KHz pwm switching signal. The design is essentially focused upon low power electronic appliances such as light, fan, chargers, television etc. In our project we used STP55NF06 NMOSFET, which is a depletion type N channel MOSFET. For driving the MOSFET we used TLP250 and totem pole configuration as a MOSFET driver. The inverter input is 12VDC and its output is 220VAC across a transformer. The complete design is modeled in proteus software and its output is verified practically.
In-air gestures around unmodified mobile devices

We present a novel machine learning based algorithm extending the interaction space around mobile devices. The technique uses only the RGB camera now commonplace on off-the-shelf mobile devices. Our algorithm robustly recognizes a wide range of in-air gestures, supporting user variation, and varying lighting conditions. We demonstrate that our algorithm runs in real-time on unmodified mobile devices, including resource-constrained smartphones and smartwatches. Our goal is not to replace the touchscreen as primary input device, but rather to augment and enrich the existing interaction vocabulary using gestures. While touch input works well for many scenarios, we demonstrate numerous interaction tasks such as mode switches, application and task management, menu selection and certain types of navigation, where such input can be either complemented or better served by in-air gestures. This removes screen real-estate issues on small touchscreens, and allows input to be expanded to the 3D space around the device. We present results for recognition accuracy (93% test and 98% train), impact of memory footprint and other model parameters. Finally, we report results from preliminary user evaluations, discuss advantages and limitations and conclude with directions for future work.
Automatic Transcription of Flamenco Singing From Polyphonic Music Recordings

Automatic note-level transcription is considered one of the most challenging tasks in music information retrieval. The specific case of flamenco singing transcription poses a particular challenge due to its complex melodic progressions, intonation inaccuracies, the use of a high degree of ornamentation, and the presence of guitar accompaniment. In this study, we explore the limitations of existing state of the art transcription systems for the case of flamenco singing and propose a specific solution for this genre: We first extract the predominant melody and apply a novel contour filtering process to eliminate segments of the pitch contour which originate from the guitar accompaniment. We formulate a set of onset detection functions based on volume and pitch characteristics to segment the resulting vocal pitch contour into discrete note events. A quantised pitch label is assigned to each note event by combining global pitch class probabilities with local pitch contour statistics. The proposed system outperforms state of the art singing transcription systems with respect to voicing accuracy, onset detection, and overall performance when evaluated on flamenco singing datasets.
Student observations: Introducing iPads into university classrooms

This paper explores the growing trend of using mobile technology in university classrooms, exploring the use of tablets in particular, to identify learning benefits faced by students. Students, acting on their efficacy beliefs, make decisions regarding technology’s influence in improving their education. We construct a theoretical model in which internal and external factors affect a student’s self-efficacy which in turn affects the extent of adoption of a device for educational purposes. Through qualitative survey responses of university students who were given an Apple iPad to keep for the duration of a university course we find high levels of self-efficacy leading to positive views of the technology’s learning enhancement capabilities. Student observations on the practicality of the technology, off-topic use and its effects, communication, content, and perceived market advantage of using a tablet are also explored.
Having trouble with your strategy? Then map it.

If you were a military general on the march, you'd want your troops to have plenty of maps--detailed information about the mission they were on, the roads they would travel, the campaigns they would undertake, and the weapons at their disposal. The same holds true in business: a workforce needs clear and detailed information to execute a business strategy successfully. Until now, there haven't been many tools that can communicate both an organization's strategy and the processes and systems needed to implement that strategy. But authors Robert Kaplan and David Norton, cocreators of the balanced scorecard, have adapted that seminal tool to create strategy maps. Strategy maps let an organization describe and illustrate--in clear and general language--its objectives, initiatives, targets markets, performance measures, and the links between all the pieces of its strategy. Employees get a visual representation of how their jobs are tied to the company's overall goals, while managers get a clearer understanding of their strategies and a means to detect and correct any flaws in those plans. Using Mobil North American Marketing and Refining Company as an example, Kaplan and Norton walk through the creation of a strategy map and its four distinct regions--financial, customer, internal process, and learning and growth--which correspond to the four perspectives of the balanced scorecard. The authors show step by step how the Mobil division used the map to transform itself from a centrally controlled manufacturer of commodity products to a decentralized, customer-driven organization.
End-to-End Non-Factoid Question Answering with an Interactive Visualization of Neural Attention Weights

1 data -module: data.insuranceqa.v2 2 model -module: model.ap_lstm 3 training -module: training.dynamic 4 evaluation -module: evaluation.default 5 6 data: 7 embeddings: data/glove.6B.100d.txt 8 insuranceqa: data/insuranceQA 9 lowercased: true 10 .. 11 12 model: 13 lstm_cell_size: 141 14 margin: 0.2 15 trainable_embeddings: true 16 .. 17 18 training: 19 batchsize: 20 20 epochs: 100 21 save_folder: checkpoints/ap_lstm 22 dropout: 0.3 23 optimizer: adam 24 initial_learning_rate: 0.001 25 scorer: accuracy 26 .. 27 28 evaluation: 29 skip:
A 300-MS/s, 1.76-ps-Resolution, 10-b Asynchronous Pipelined Time-to-Digital Converter With on-Chip Digital Background Calibration in 0.13-µm CMOS

This paper presents an asynchronous pipelined all-digital 10-b time-to-digital converter (TDC) with fine resolution, good linearity, and high throughput. Using a 1.5-b/stage pipeline architecture, an on-chip digital background calibration is implemented to correct residue subtraction error in the seven MSB stages. An asynchronous clocking scheme realizes pipeline operation for higher throughput. The TDC was implemented in standard 0.13-μm CMOS technology and has a maximum throughput of 300 MS/s and a resolution of 1.76 ps with a total conversion range of 1.8 ns. The measured DNL and INL were 0.6 LSB and 1.9 LSB, respectively.
Automating Reading Comprehension by Generating Question and Answer Pairs

Neural network-based methods represent the state-of-the-art in question generation from text. Existing work focuses on generating only questions from text without concerning itself with answer generation. Moreover, our analysis shows that handling rare words and generating the most appropriate question given a candidate answer are still challenges facing existing approaches. We present a novel two-stage process to generate question-answer pairs from the text. For the first stage, we present alternatives for encoding the span of the pivotal answer in the sentence using Pointer Networks. In our second stage, we employ sequence to sequence models for question generation, enhanced with rich linguistic features. Finally, global attention and answer encoding are used for generating the question most relevant to the answer. We motivate and linguistically analyze the role of each component in our framework and consider compositions of these. This analysis is supported by extensive experimental evaluations. Using standard evaluation metrics as well as human evaluations, our experimental results validate the significant improvement in the quality of questions generated by our framework over the state-of-the-art. The technique presented here represents another step towards more automated reading comprehension assessment. We also present a live system to demonstrate the effectiveness of our approach.
The view from the left

Pattern matching has proved an extremely powerful and durable notion in functional programming. This paper contributes a new programming notation for type theory which elaborates the notion in various ways. First, as is by now quite well-known in the type theory community, definition by pattern matching becomes a more discriminating tool in the presence of dependent types, since it refines the explanation of types as well as values. This becomes all the more true in the presence of the rich class of datatypes known as inductive families (Dybjer, 1991). Secondly, as proposed by Peyton Jones (1997) for Haskell, and independently rediscovered by us, subsidiary case analyses on the results of intermediate computations, which commonly take place on the right-hand side of definitions by pattern matching, should rather be handled on the left. In simply-typed languages, this subsumes the trivial case of Boolean guards; in our setting it becomes yet more powerful. Thirdly, elementary pattern matching decompositions have a well-defined interface given by a dependent type; they correspond to the statement of an induction principle for the datatype. More general, user-definable decompositions may be defined which also have types of the same general form. Elementary pattern matching may therefore be recast in abstract form, with a semantics given by translation. Such abstract decompositions of data generalize Wadler’s (1987) notion of ‘view’. The programmer wishing to introduce a new view of a type T , and exploit it directly in pattern matching, may do so via a standard programming idiom. The type theorist, looking through the Curry–Howard lens, may see this as proving a theorem, one which establishes the validity of a new induction principle for T . We develop enough syntax and semantics to account for this high-level style of programming in dependent type theory. We close with the development of a typechecker for the simply-typed lambda calculus, which furnishes a view of raw terms as either being well-typed, or containing an error. The implementation of this view is ipso facto a proof that typechecking is decidable.
A 21nm high performance 64Gb MLC NAND flash memory with 400MB/s asynchronous toggle DDR interface

A monolithic 64Gb MLC NAND flash based on 21nm process technology has been developed for the first time. The device consists of 4-plane arrays and provides page size of up to 32KB. It also features a newly developed DDR interface that can support up to the maximum bandwidth of 400MB/s. To address performance and reliability, on-chip randomizer, soft data readout, and incremental bit line precharge scheme have been developed.
Efficient 3D Room Shape Recovery from a Single Panorama

We propose a method to recover the shape of a 3D room from a full-view indoor panorama. Our algorithm can automatically infer a 3D shape from a collection of partially oriented superpixel facets and line segments. The core part of the algorithm is a constraint graph, which includes lines and superpixels as vertices, and encodes their geometric relations as edges. A novel approach is proposed to perform 3D reconstruction based on the constraint graph by solving all the geometric constraints as constrained linear least-squares. The selected constraints used for reconstruction are identified using an occlusion detection method with a Markov random field. Experiments show that our method can recover room shapes that can not be addressed by previous approaches. Our method is also efficient, that is, the inference time for each panorama is less than 1 minute.
The kinesiology of the thumb trapeziometacarpal joint.

To measure the motions of the trapeziometacarpal joint of the thumb quantitatively, a roentgenographic method was developed and tested using T-shaped metal markers, a special cassette-holder, and biplane roentgenograms. Two experiments were performed. In the first one, the metal markers were fixed to the trapezium and third metacarpal in ten cadaver specimens, and a fixed spatial relationship between the trapezium and the third metacarpal was identified roentgenographically. This relationship was that the reference axes of the trapezium were aligned at median angles of 48 degrees of flexion, 38 degrees of abduction, and 80 degrees of pronation with reference to the reference axes of the third metacarpal. In the second experiment, in the dominant hand of nine male and ten female subjects (average age, twenty-six years) T-shaped markers were fixed to the skin overlying the third metacarpal and the metacarpal and phalanges of the thumb. Using the same roentgenographic technique and coordinate systems employed in the first study, the average total motions of the trapeziometacarpal joint (determined as motions of the first metacarpal with reference to the third metacarpal) were 53 degrees of flexion-extension, 42 degrees of abduction-adduction, and 17 degrees of axial rotation (pronation-supination). In addition, six functional positions of the thumb were studied: rest, flexion, extension, abduction, tip pinch, and grasp. A position of adduction and flexion of the trapeziometacarpal joint was most common during thumb function, and both the trapeziometacarpal and metacarpophalangeal joints contributed to rotation of the thumb.