Miracle-dz/UniFAR-FTUs huggingface dataset:
A rigorous analysis of two bi-criteria problem families with scalable curvature of the pareto fronts

The problems presented and analyzed in this paper are interesting testproblems for multi-objective optimization. The aim is to find the distance to two points in a d-dimensional space. Closed analytical expressions of all pareto-optimal fronts and pareto-optimal sets will be derived in this paper. Moreover, a discussion of the characteristics of the properties of these sets is given. Depending on the formulation of the distance function, different structures of the pareto front and pareto optimal set can be obtained. Both are characterized by strong symmetries. Furthermore, the curvature of the pareto fronts can be scaled by means of a continuous parameter, ranging from extremely concave functions to extremely concave functions. Instead of giving a detailed introduction to multi-objective optimization in general, and pareto optimization in particular, we refer the interested reader to the text books by Deb [1] and Zitzler [2]. The book by Deb also contains standard benchmarks for bi-criteria optimization. The ZDT test-suite contains problems that are scalable in dimension. In addition, both concave and convex pareto fronts are included in the ZDT benchmark. However, neither the degree of curvature can be scaled for these functions, nor do these function provide an intuitive understanding of the objectives. Moreover, the functions are highly asymmetric. Thus, it would be interesting to derive some new test functions. We demand for families of test functions with: • Scalable degree of curvature of the pareto fronts • Simplicity, i. e. to allow for an intuitive understanding of the geometry of the function and solution sets • Scalability, i. e. it should be possible to formulate the functions for arbitrary search space dimensions With the EBN family of problems and the Generalized Schaffer problem we propose familes of test functions that meet the aforementioned conditions. The problems and their rigorous analysis will be presented next. We start with the discussion of the generalized Schaffer problem. Then we introduce the EBN family of functions and discuss it.
Aligning Words from Speech Recognition and Shots for Video Information Retrieval

In this paper we propose an approach to improve video information retrieval by finding the relationships between ASR tokens and the high-level feature tokens. We employ WordNet hierarchical relationship to calculate word-to-word distances, and align the related words in ASR to the corresponding shots. Finally we define a representative document for each shot, which contains the original ASR, high-level features and the aligned words. Adopting Okapi as our IR system to access the representative documents, we tested different parameters on TRECVID 2003 search task and choose two sets of parameters to test on TRECVID 2004 task ( M_C_2_NLP_Lab1_1 and M_C_2_NLP_Lab1_2 ) along with one ASR baseline run ( M_C_1_NLP_Lab1_1 ). The experimental results show that in some cases our algorithm does resolve the time-delay problem, so that the IR performance is improved. In those cases the news scripts talk about an event , and do not contain words related to the object we want to find, our alignment algorithm does not have significant effects. In summary, the alignment algorithm can improve the overall video IR performance when the high-level features are annotated.
Robust Mean-Covariance Solutions for Stochastic Optimization

We provide a method for deriving robust solutions to certain stochastic optimization problems, based on mean-covariance information about the distributions underlying the uncertain vector of returns. We prove that for a general class of objective functions, the robust solutions amount to solving a certain deterministic parametric quadratic program. We first prove a general projection property for multivariate distributions with given means and covariances, which reduces our problem to optimizing a univariate mean-variance robust objective. This allows us to use known univariate results in the multidimensional setting, and to add new results in this direction. In particular, we characterize a general class of objective functions (the so-called one- or two-point support functions), for which the robust objective is reduced to a deterministic optimization problem in one variable. Finally, we adapt a result from Geoffrion (1967a) to reduce the main problem to a parametric quadratic program. In particular, our results are true for increasing concave utilities with convex or concave-convex derivatives. Closed-form solutions are obtained for special discontinuous criteria, motivated by bonus- and commission-based incentive schemes for portfolio management. We also investigate a multiproduct pricing application, which motivates extensions of our results for the case of nonnegative and decision-dependent returns.
Characterizing the velocity field in hydrodynamical simulations of low-mass star formation using spectral line profiles

Context. When low-mass stars form, the collapsing cloud of gas and dust goes through several stages which are usually characterized by the shape of their spectral energy distributions. Such classifi cation is based on the cloud morphology only and does not address the dynamical state of the object. Aims. In this paper we investigate the initial cloud collapse and s ubsequent disk formation through the dynamical behavior as reflected in the sub-millimeter spectral emission line profiles. If a young s tellar object is to be characterized by its dynamical struct ure it is important to know how accurately information about the velocity field can be ex tracted and which observables provide the best description of the kinematics. Of particular interest is the transition from infalling envel ope to rotating disk, because this provides the initial cond itions for the protoplanetary disk, such as mass and size. Methods. We use a hydrodynamical model, describing the collapse of a core and formation of a disk, to produce synthetic observables which we compare to calculated line profiles of a simple param eterized model. Because we know the velocity field from the hy drodynamical simulation we can determine in a quantitative way how well our best-fit parameterized velocity field reproduces the origi nal. We use a molecular line excitation and radiation transfer code to pr oduce spectra of both our hydrodynamical simulation as well as our parameterized model. Results. We find that information about the velocity field can reasonab ly well be derived by fitting a simple model to either single-d ish (15 ′′ resolution) lines or interferometric data (1 ′′ resolution), but preferentially by using a combination of t he two. The method does not rely on a specific set of tracers, but we show that some tracers work bet ter than others. Our result shows that it is possible to estab lish relative ages of a sample of young stellar objects using this method, independently of the details of the hydrodynamical model.
Transmit power allocation for BER performance improvement in multicarrier systems

In a multicarrier system, transmit power allocation over different subchannels is an effective means of improving the performance. In this paper, the optimal transmit power allocation scheme is developed to improve bit error rate (BER) performance in a multicarrier system with diversity reception. A simple suboptimal scheme is also derived from the optimal one, and an asymptotic case referred to as the equal SNR scheme is discussed. Numerical results show that the optimal and suboptimal power allocation schemes significantly outperform the equal power allocation scheme. The effects of the modulation level, the number of receiving antennas, and the number of subchannels on the BER performance are also investigated.
Second Order Properties of Error Surfaces: Learning Time and Generalization

The learning time of a simple neural network model is obtained through an analytic computation of the eigenvalue spectrum for the Hessian matrix, which describes the second order properties of the cost function in the space of coupling coefficients. The form of the eigenvalue distribution suggests new techniques for accelerating the learning process, and provides a theoretical justification for the choice of centered versus biased state variables.
Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.

There are many sources of systematic variation in cDNA microarray experiments which affect the measured gene expression levels (e.g. differences in labeling efficiency between the two fluorescent dyes). The term normalization refers to the process of removing such variation. A constant adjustment is often used to force the distribution of the intensity log ratios to have a median of zero for each slide. However, such global normalization approaches are not adequate in situations where dye biases can depend on spot overall intensity and/or spatial location within the array. This article proposes normalization methods that are based on robust local regression and account for intensity and spatial dependence in dye biases for different types of cDNA microarray experiments. The selection of appropriate controls for normalization is discussed and a novel set of controls (microarray sample pool, MSP) is introduced to aid in intensity-dependent normalization. Lastly, to allow for comparisons of expression levels across slides, a robust method based on maximum likelihood estimation is proposed to adjust for scale differences among slides.
Long Tail Behavior of Queue Lengths in Broadband Networks: Tsallis Entropy Framework

A maximum entropy framework based on Tsallis entropy is proposed to depict long tail behavior of queue lengths in broadband networks. Queue length expression as measured in terms of number of packets involves Hurwitz-zeta function. When the entropy parameter q in Tsallis entropy is less than unity, the distribution of packets yields power law behavior. In the limit q tending to unity, Tsallis entropy expression reduces to one due to Shannon and well-known results of M/M/1 queuing system are recovered. Relationship between Tsallis entropy parameter q and Hurst parameter H (measure of self-similarity) is postulated. A numerical procedure based on Newton-Raphson method is outlined to compute Lagrange's parameter b. Various relationships between traffic intensity r and Lagrange's parameter b are examined using data generated from mean number of packets from storage model due to Norros. It is found that best fit corresponds to r being a linear combination of decaying exponential and power exponent in b for different values of entropy parameter q. Explicit expression for the probability that queue size exceeds a certain value is derived and it is established that it asymptotically follows power law for q less than one. The system utilization shows an interesting behavior when the parameter r is varied. It attains lower values than that of M/M/1 system for smaller values of r whereas situation reverses for higher values of r.
Fusing Remote Control Usages and Facial Expression for Emotion Recognition

This paper proposes a fusion model that merges the context-aware multimodal information of JADE (Java Agent DEvelopment Framework). The context-aware multimodal information system is developed from the multi-heterogeneous context sensing devices. This multimodal not only gathers multidimensional data that aims to recognize and analyze the collected emotion information, but also emotion manages the context-aware information. According to the collections of users use remote control usages during watching TV and the face recognition technology, we developed a context-aware multimodal information system to recognize emotions. The emotion information is reasoned from the action data of remote control usages that combines with the emotion information gathered from the face recognition. These two information fuses with the feedback mechanism of real emotion to acquire the information of personal emotion representation. This fusion model of context-aware multimodal information provides personal emotion information and learning mechanism to reason the information from context aware ubiquitous environment applied on personal emotion prediction.
Skewed Coordinate System for Dense Point Correspondences Inside Articulated Shapes

This report considers using a non-rigid coordinate system to find corresponding points in different poses of the same articulated 2D shape. The shape-centered coordinate system is mapped on top of the eccentricity transform of the shape, which uses maximal geodesic distances and is bounded under articulation. The isolines of the eccentricity transform are used as one of the coordinates, the radial-like, and the other one, the angular-like, is stretched to compensate for changes in the widths of parts. The polar-like coordinate system is first computed on inter-pixel isolines and then mapped to the pixels. The angular-like coordinates are aligned using the 1D signals of the eccentricity values along the boundaries of the two shapes. Correspondences between points are established by minimizing the difference of their coordinates. Detecting failed correspondences is done using an adaptive threshold which adjusts to the changing local variation of the coordinates. Experimental results are shown on a set of hand poses, ranging from minor movement to touching or missing fingers.
Creating an Appropriate Corpus for PP Attachment Training

This paper describes work in progress that is identifying shortcomings of existing Prepositional Phrase (PP) attachment algorithms and producing a new resource derived from the Penn TreeBank (PTB) corpus. The aim is to use this new resource (PTB Prime) to improve the accuracy of PP attachment algorithms and use this in an existing text processing system ( LaSIE-II).
Robust Ground Control System Development for Unmanned Arial Vehicle Collision Avoidance

The rise in Unmanned Aerial Vehicle (UAV) technology necessitates the growth and exploration of algorithms to prevent UAV collisions. Alongside this exploration, software must be developed for testing these algorithms under real-world computational and software constraints. The software discussed in this paper takes the form of a Ground Control Station (GCS) that manages both real and simulated UAVs as they attempt to complete missions and avoid each other. We discuss the software designs decisions we used to improve an existing GCS that is built on the ROS framework. The design and implementation follow an agile process to provide a modular and efficient framework for the needs of UAV collision avoidance research. This procedure was carried out using the design principles of low coupling and high cohesion. To this end, we refactored an existing GCS to reduce its interaction complexity and to strongly define each modules role and definition.
A 7.4-mW 200-MS/s Wideband Spectrum Sensing Digital Baseband Processor for Cognitive Radios

A digital baseband cognitive radio spectrum sensing processor with 200-kHz resolution over 200-MHz bandwidth is integrated in 1.64 mm2 in 65-nm CMOS. The processor uses adaptive channel-specific threshold and sensing time to achieve detection probability ≥ 0.9 and false-alarm probability ≤ 0.1 for -5-dB SNR and adjacent-band interferers of 30-dB INR within a 50-ms sensing time. The chip power and area are minimized by jointly considering algorithm, architecture, and circuit parameters. The chip dissipates 7.4 mW for a 200-MHz sensing bandwidth, which is a 22× reduction in power per sensing bandwidth compared with prior work.
QoS-driven scheduling approach using optimal slot allocation for Wireless Body Area Networks

Wireless Body Area Network (WBAN) is a promising type of networks that mainly targets at applications in ubiquitous communication and e-Health services. Different from other types of networks, one important challenge for WBAN is that its quality of service (QoS) requirement, in terms of delivery probability and data rate, will be time varying since human body is a highly dynamic physical environment. Another significant challenge for WBAN is that energy efficiency needs to be guaranteed in such a resource-limited network. In this paper, a QoS-driven scheduling approach is proposed to address these challenges. We model the WBAN channel as a Markov model as suggested by the emerging IEEE 802.15. 6 BAN standard and propose a threshold-based scheme to adjust the transmission order of nodes. The number of slots for each node is optimally assigned according to the QoS requirement while minimizing the energy consumption of nodes. The results from extensive simulations show that the proposed approach can provide high QoS and energy efficiency under different network conditions, especially in highly heterogeneous ones in WBAN.
Probabilistic Constraints in Language Acquisition

An approach to language acquisition is described in which the foundational questions are about how the child acquires adult-like language processing capacities. This approach assumes that the child’s primary task is not to identify the grammar of the target language, but rather to learn to comprehend and produce utterances in the service of communicating with others. In this framework the input to the child is seen as providing a rich source of probabilistic information, and notions of the target language are provided by constraint satisfaction models of adult performance. The methodology involves implementing connectionist models that simulate detailed aspects of performance.
Comparison of Two Methods for the Measurement of Medial and Lateral Metapodial Bones in Karagouniko Sheep (Ovis aries, L. 1758) and Hellenic Goat (Capra hircus, L. 1758)

The objective of this study was to compare the metapodial lengths of sheep and goats measured with a caliper with those measured using a 2-dimensional digital method. Complementarily, the lengths of medial and lateral metapodials in these species were compared. The limbs of 30 ewes and 30 goats were used. After preparation, the lateral and medial length of the metacarpals and metatarsals were measured twice with a caliper. Afterwards, each bone was scanned and the same lengths were digitally measured twice using commercial software. Data analysis revealed strong linear relationship between the two methods but the absolute relative deviation of the measurements with the caliper was significantly higher than those with the 2-dimensional method (P < 0.05). All lengths measured with the caliper were significantly higher compared to those measured with the 2-dimensional method (P < 0.05). In goats, the lateral length of both metacarpals and metatarsals was significantly higher than medial length (P < 0.05); in sheep the lateral length was significantly higher compared to the medial one only in metatarsal bones (P < 0.05). In conclusion, the 2-dimensional method is more accurate for the measurement of the metapodials' length than the caliper and there is asymmetry between the medial and lateral metapodials in these species.
Impact of Nonfarm Participation on Household Welfare: Empirical Evidence from Pakistan

This article employs propensity score matching approach toestimate the impact of nonfarm participation on rural household welfarein Punjab province of Pakistan. For the study cross sectional data set wascollected from 325 households from the southern Punjab province. Thedata was collected from both categories of farmers having participatedin the nonfarm activities and not participated in the nonfarm activities.The propensity score matching approach was employed to correct forpotential sample selection biased ness, which may arise due to systematicdifferences between the participants and non participants. A numberof matching algorithms were employed to check the robustness of theresults. The empirical results indicate that education play a significantrole regarding nonfarm participation. The nonfarm participants’households have higher incomes and have lesser poverty levels in therange of 9-18 percent. Key Words: Nonfarm; Poverty; Income; Propensity Score Matching;Pakistan.
Drug Discovery Chemistry: a Primer for the Non-specialist

REVIEWS This review seeks to explain some of the common terminology used by medicinal and synthetic chemists. Aimed at the non-specialist, its intent is to help facilitate discussions between chemists and their counterparts from other disciplines. Like all scientific disciplines, drug discovery chemistry is rife with terminology and methodology that can seem intractable to those outside the sphere of synthetic chemistry. Derived from a successful in-house workshop, this Foundation Review aims to demystify some of this inherent terminology, providing the non-specialist with a general insight into the nomenclature, terminology and workflow of medicinal chemists within the pharmaceutical industry. Owing to its multidisciplinary nature, those working within drug discovery are exposed to a considerable quantity of terminology, drawn from a wide variety of specialisms. From analysts to computational scientists, toxicologists and pharmacologists, each scientific area tends to develop its own dialogue and vocabulary that, to the outsider, can be complex and sometimes overwhelming when trying to collaborate and communicate across disciplines and projects. The synthetic chemist is by no means exempt from this endemic use of jargon. Aside from terminology for the specific chemical entities produced in the laboratory and the functionality these entities contain, chemists make frequent reference to the names of the reactions, techniques and methodology used to assemble them. Though second nature to the practicing chemist, this terminology is frequently referred to with little or no explanation or clarification to those outside the chemistry community. Within Vernalis, a series of informal discussions clearly highlighted the ways in which different scientists visualise, and thus describe, key candidate compounds. For example, crystallographers would refer to electron densities, while modellers would discuss compounds in terms of their intermolecular interactions with their desired targets. These and other colleagues outside chemistry would often despair as the project chemists discussed seemingly endless lists of functional groups, core ring systems and reaction types. It quickly became apparent that while chemists had, as part of their training, often picked up sufficient biology to allow them to at least partly follow the biological discussions within project meetings, the non-chemists often found chemical discussions considerably more difficult to follow, despite their best efforts. From this starting point, we developed, implemented and evolved an in-house workshop, which we loosely entitled 'chemistry for non-chemists'. This allowed those interested parties to understand a little better the mindset of the synthetic chemist, their terminology, nomenclature and the 'toolbox' of reactions commonly used …