Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonparametric Technique Based High-Speed Road Surface Detection

It has been well recognized that detecting road surface in a realistic environment is a challenging problem that is also computationally intensive. Existing road surface detection methods attempt to fit the road surface into rigid models (e.g., planar, clothoid, or B-Spline), thereby restricting to road surfaces that match specific models. In addition, the curve-fitting strategies employed in such techniques incur high computational complexity, making them unsuitable for in-vehicle deployments. In this paper, we propose an efficient nonparametric road surface detection algorithm that exploits the depth cue. The proposed method relies on four intrinsic road scene attributes observed under stereo geometry and has been shown to reliably detect both planar and nonplanar road surfaces efficiently. Extensive evaluations are performed on three widely used benchmarks (i.e., enpeda, KITTI, and Daimler), encompassing many complex road scenarios. The experimental results show that the proposed algorithm significantly outperforms the well-known techniques both in terms of detection accuracy and runtime performance.
Constructing smart portfolios from data driven quantitative investment models

In this paper we present a smart portfolio management methodology, which advances existing portfolio management techniques at two distinct levels. First, we develop a set of investment models that target regimes found in the data over different time horizons. We then build a meta-model which uses the Kelly criterion to determine an optimal allocation over these investment strategies, thus simultaneously capturing regimes operating in the data over different time horizons. Finally, in order to detect changes in the relevant data regime, and hence investment allocations, we use a forecasting algorithm which relies on a Kalman filter. We call our combined method, that uses both the Kelly criterion and the Kalman filter, the K2 algorithm. Using a large-scale historical dataset of both stocks and indices, we show that our K2 algorithm gives better risk adjusted returns in terms of the Sharpe ratio, better average gain to average loss ratio and higher probability of success compared to existing benchmarks, when measured in out-of-sample tests.
Keap1-Knockdown Decreases Fasting-Induced Fatty Liver via Altered Lipid Metabolism and Decreased Fatty Acid Mobilization from Adipose Tissue

Aims The purpose of this study was to determine whether Nrf2 activation, via Keap1-knockdown (Keap1-KD), regulates lipid metabolism and mobilization induced by food deprivation (e.g. fasting). Methods and Results Male C57BL/6 (WT) and Keap1-KD mice were either fed ad libitum or food deprived for 24 hours. After fasting, WT mice exhibited a marked increase in hepatic lipid accumulation, but Keap1-KD mice had an attenuated increase of lipid accumulation, along with reduced expression of lipogenic genes (acetyl-coA carboxylase, stearoyl-CoA desaturase-1, and fatty acid synthase) and reduced expression of genes related to fatty acid transport, such as fatty acid translocase/CD36 (CD36) and Fatty acid transport protein (FATP) 2, which may attribute to the reduced induction of Peroxisome proliferator-activated receptor (Ppar) α signaling in the liver. Additionally, enhanced Nrf2 activity by Keap1-KD increased AMP-activated protein kinase (AMPK) phosphorylation in liver. In white adipose tissue, enhanced Nrf2 activity did not change the lipolysis rate by fasting, but reduced expression of fatty acid transporters — CD36 and FATP1, via a PPARα-dependent mechanism, which impaired fatty acid transport from white adipose tissue to periphery circulation system, and resulted in increased white adipose tissue fatty acid content. Moreover, enhanced Nrf2 activity increased glucose tolerance and Akt phosphorylation levels upon insulin administration, suggesting Nrf2 signaling pathway plays a key role in regulating insulin signaling and enhanced insulin sensitivity in skeletal muscle. Conclusion Enhanced Nrf2 activity via Keap1-KD decreased fasting-induced steatosis, pointing to an important function of Nrf2 on lipid metabolism under the condition of nutrient deprivation.
Impacts of business vision, top management support, and external expertise on ERP success

Purpose – The purpose of this paper is to investigate the impact of such contingency factors as top management support, business vision, and external expertise, on the one hand, and enterprise resource planning (ERP) system success, on the other.Design/methodology/approach – A conceptual model was developed and relevant hypotheses formulated. Surveys were conducted in two Northern European countries and a structural equation modeling technique used to analyze the data.Findings – It was found that the three contingency factors positively influence ERP system success. More importantly, the relative importance of quality external expertise over the other two factors for ERP initiatives was underscoredOriginality/value – It is argued that ERP systems are different from other information technology implementations; as such, there is a need to provide insights as to how the aforementioned factors play out in the context of ERP system success evaluations for adopting organizations. As was predicted, the results .
Charging Electric Vehicles in the Smart City: A Survey of Economy-Driven Approaches

Electric vehicles (EVs), as their penetration increases, do not only challenge the sustainability of the power grid but also stimulate and promote its upgrading. Indeed, EVs can actively reinforce the development of the smart grid if their charging processes are properly coordinated through two-way communications, possibly benefiting all types of actors. Because grid systems involve a large number of actors with nonaligned objectives, we focus on the economic and incentive aspects, where each actor behaves in its own interest. We indeed believe that the market structure will directly impact the actors' behaviors, and as a result, the total benefits that the presence of EVs can earn in the society, hence the need for a careful design. This survey provides an overview of economic models considering unidirectional energy flows and bidirectional energy flows, i.e., with EVs temporarily providing energy to the grid. We describe and compare the main approaches, summarize the requirements on the supporting communication systems, and propose a classification to highlight the most important results and lacks.
Path Integral Policy Improvement with Covariance Matrix Adaptation

There has been a recent focus in reinforcement learning on addressing continuous state and action problems by optimizing parameterized policies. PI2 is a recent example of this approach. It combines a derivation from first principles of stochastic optimal control with tools from statistical estimation theory. In this paper, we consider PI2 as a member of the wider family of methods which share the concept of probability-weighted averaging to iteratively update parameters to optimize a cost function. We compare PI2 to other members of the same family - Cross-Entropy Methods and CMAES - at the conceptual level and in terms of performance. The comparison suggests the derivation of a novel algorithm which we call PI2-CMA for "Path Integral Policy Improvement with Covariance Matrix Adaptation". PI2-CMA's main advantage is that it determines the magnitude of the exploration noise automatically.
Risks and Benefits of Green Spaces for Children: A Cross-Sectional Study of Associations with Sedentary Behavior, Obesity, Asthma, and Allergy

Background: Green spaces have been associated with both health benefits and risks in children; however, available evidence simultaneously investigating these conflicting influences, especially in association with different types of greenness, is scarce. Objectives: We aimed to simultaneously evaluate health benefits and risks associated with different types of greenness in children, in terms of sedentary behavior (represented by excessive screen time), obesity, current asthma, and allergic rhinoconjunctivitis. Methods: We conducted a cross-sectional study of a population-based sample of 3,178 schoolchildren (9–12 years old) in Sabadell, Spain, in 2006. Information on outcomes and covariates was obtained by questionnaire. We measured residential surrounding greenness as the average of satellite-derived Normalized Difference Vegetation Index (NDVI) in buffers of 100 m, 250 m, 500 m, and 1,000 m around each home address. Residential proximity to green spaces was defined as living within 300 m of a forest or a park, as separate variables. We used logistic regression models to estimate associations separately for each exposure–outcome pair, adjusted for relevant covariates. Results: An interquartile range increase in residential surrounding greenness was associated with 11–19% lower relative prevalence of overweight/obesity and excessive screen time, but was not associated with current asthma and allergic rhinoconjunctivitis. Similarly, residential proximity to forests was associated with 39% and 25% lower relative prevalence of excessive screen time and overweight/obesity, respectively, but was not associated with current asthma. In contrast, living close to parks was associated with a 60% higher relative prevalence of current asthma, but had only weak negative associations with obesity/overweight or excessive screen time. Conclusion: We observed two separable patterns of estimated health benefits and risks associated with different types of greenness. Citation: Dadvand P, Villanueva CM, Font-Ribera L, Martinez D, Basagaña X, Belmonte J, Vrijheid M, Gražulevičienė R, Kogevinas M, Nieuwenhuijsen MJ. 2014. Risks and benefits of green spaces for children: a cross-sectional study of associations with sedentary behavior, obesity, asthma, and allergy. Environ Health Perspect 122:1329–1335; http://dx.doi. org/10.1289/ehp.1308038
Resource-based reluctance, reversed asymmetry, and non-trade integration incentives: theory and evidence from European neighbourhood

Among ENP countries, Azerbaijan is outstanding because it leans on its resource base and sees the EU at the receiving end of bilateral relations. At the other extreme, Ukraine depends on EU cooperation, especially with respect to trade. We develop a comprehensive theoretical concept for analyzing both types of asymmetries. We do this by considering both rational cost-benefit as well as constructivist norm oriented national strategies. Furthermore, we contrast the both national strategies to bilateral, regional, and multilateral EU strategies for democracy promotion, economic cooperation, justice and home affairs cooperation, and conflict resolution in European neighbourhood. It turns out that EU strategies of Neighbourhood Europeanization have to be increasingly based on non-tangible tools, on packages of regional and multilateral initiatives which balance out asymmetries, and on other than trade issues, such as security, in order to be more effective.
It is your fault! How blame attributions of breach predict employees’ reactions

Purpose Using insights from attributions, planned behavior, and fairness theories, this study examines the effect of blame attributions of psychological contract breach on employees’ attitudes (affective organizational commitment) and behaviors (organizational citizenship behavior (OCB)). The purpose of this paper is to understand whether employees’ reactions depend on the attributions they make concerning who is responsible for the breach. Design/methodology/approach Cross-lagged design in which data were collected from 220 employees and their supervisors in a public company at two times. Moderated mediation was tested using the bootstrapping analysis outlined by Hayes (2012). Findings The results supported the authors’ predictions: employees’ blame attributions to the organization have a negative impact on OCBs (as rated by supervisors in time 2) through decreased affective organizational commitment, but blame attributions to the economic context act as a buffer to the relationship between blame attributions to organization and affective organizational commitment, with consequences for OCBs. Research limitations/implications Attributions can also be made to concrete persons (i.e. supervisor, coworker, self) rather than to just the organization or context. Practical implications When hiring, recruiters should provide accurate and realistic promises to the candidates. When facing hard times, managers should provide additional information to employees and adjust their expectations to the current situation of the firm. Originality/value This study makes a unique contribution to the literature by questioning the “single story” perspective about reactions to psychological contract breach, in which it is assumed that employees always respond negatively to such event.
State of the Art of Web Usability Guidelines

interpretation Concrete interpretation General guidelines Specific guidelines Standards Compilations of guidelines Style guides Ergonomic algorithms Design rules Figure 7 Guideline interpretation according to guideline source 6 Conclusion In this chapter, we highlighted that a profusion of web usability guidelines exists that does not facilitate the designer’s task to select and apply appropriate guidelines. Usability guidelines dedicated to the web should be clearly differentiated from guidelines for traditional GUI applications. Some sources, as standards, pretend to be general, embracing enough to accommodate a wide variety of design issues. While this assumption is probably true for traditional applications, it is unlikely to be the case for Web usability. Differences discussed in UI design and development both for GUI and the Web, the emergence of new questions for the web that were unprecedented, the rapid evolution of guideline types suggest that web usability guidelines should be treated separately. For example, GUI mainly focuses on guidelines for controls, while the Web divides guidelines for the navigation (the privileged interaction mode) and for forms, although Java applications can be considered similarly to GUI applications. Many wholes in usability knowledge still exist for the Web. To identify them, Basden (2003) used Dooyeweerd’s notion of irreducible aspects: the philosopher introduced a series of 15 aspect, each having a set of laws that enable meaningful functioning in everyday living. Basden (2003) then compared the Yale Style Guide (Lynch & Horton, 1999) with other style guides for the web to discover (Fig. 8) that some aspects are largely represented (e.g., spatial and movement in a web site are well described), while others remain underrepresented (e.g., the juridical aspect that discusses legal issues for the Web is rarely found, as well as ethical issues). Fig. 8 shows potential areas where a need for guidelines exists that is not filled, thus providing an opportunity for researchers.
Fixed Point DSP Implementation of Low-Density Parity Check Codes

It has been shown earlier and rediscovered recently that Low-Density Parity Check Codes can achieve bit error rate near to Shannon limit. They can be decoded using soft decision iterative decoding scheme. As low cost, high performance DSPs are widespread, DSP implementation for LDPC decoder is a viable option. Floating point implementation has higher costs and so fixed point DSP implementation is considered. Various optimal and sub-optimal implementations of the algorithm are considered. Various algorithms are compared for performance loss and low complexity trade off. It is shown that there is no performance loss as compared to floating point software approach. A lowered complexity and higher speed implementation of the LDPC decoder can thus be achieved using fixed point DSP implementation.
Absorbing boundary conditions for acoustic and elastic wave equations

Boundary conditions are derived for numerical wave simulation that minimize artificial reflections from the edges of the domain of computation. In this way acoustic and elastic wave propagation in a limited area can be efficiently used to describe physical behavior in an unbounded domain. The boundary conditions are based on paraxial approximations of the scalar and elastic wave equations. They are computationally inexpensive and simple to apply, and they reduce reflections over a wide range of incident angles.
Optimal design of FIR frequency-response-masking filters using second-order cone programming

Since Lim's 1986 paper on the frequency-response masking (FRM) technique for the design of FIR digital filters with very small transition widths, the analysis and design of FRM filters have been a subject of study. In this paper, a new optimization technique for the design of FRM filters is proposed. Central to the new design method is a sequence of linear updates for the design variables, with each update carried out by second-order cone programming. Design simulations are presented to illustrate the proposed algorithms and to evaluate the design performance.
Changes in Mice Brain Spontaneous Electrical Activity during Cortical Spreading Depression due to Mobile Phone Radiation

The objective of the present study was to investigate changes in spontaneous EEG activity during cortical spreading depression (CSD) in mice brain. The cortical region of anaesthetized mice were exposed to the electromagnetic fields (EMFs) emitted from a mobile phone (MP, 935.2-960.2 MHz, 41.8 mW/cm2). The effect of EMFs on EEG was investigated before and after exposure to different stimuli (MP, 2% KCl, and MP & 2% KCl). The records of brain spontaneous EEG activity, slow potential changes (SPC), and spindle shaped firings were obtained through an interfaced computer. The results showed increases in the amplitude of evoked spindles by about 87%, 17%, and 226% for MP, 2% KCl, and MP & 2% KCl; respectively, as compared to values for the control group. These results showed that the evoked spindle is a more sensitive indicator of the effect of exposure to EMFs from MP.
Perimeter-Based Data Replication in Mobile Sensor Networks

This paper assumes a set of n mobile sensors that move in the Euclidean plane as a swarm. Our objectives are to explore a given geographic region by detecting spatio-temporal events of interest and to store these events in the network until the user requests them. Such a setting finds applications in mobile environments where the user (i.e., the sink) is infrequently within communication range from the field deployment. Our framework, coined SenseSwarm, dynamically partitions the sensing devices into perimeter and core nodes. Data acquisition is scheduled at the perimeter, in order to minimize energy consumption, while storage and replication takes place at the core nodes which are physically and logically shielded to threats and obstacles. To efficiently identify the nodes laying on the perimeter of the swarm we devise the Perimeter Algorithm (PA), an efficient distributed algorithm with a low communication complexity. For storage and fault-tolerance we devise the Data Replication Algorithm (DRA), a voting-based replication scheme that enables the exact retrieval of events from the network in cases of failures. Our trace-driven experimentation shows that our framework can offer significant energy reductions while maintaining high data availability rates. In particular, we found that when failures are less than 60% failure then we can recover over 80% of generated events exactly.
S-SAC: Towards a Scalable Secure Access Control Framework for Cloud Storage

Outsourcing data backup to third-party cloud storage services is always a cost effective choice and doesn't require much technical knowledge from users. However, security concerns arise in terms of ensuring the privacy and integrity of the outsourced data. Many frameworks have been introduced to address these concerns by adopting huge number of encryption/decryption process based on the number of users and files to control users access policies. However, with the exponential growth of both users and files, current techniques impose huge overload. In this paper, we propose S-SAC, a Scalable-Secure Access Control cloud storage framework that carefully overcomes the drawbacks of the current frameworks. S-SAC introduce a fine grained access control based on group policy using attribute based encryption to efficiently handle any increase in either users or files size. The extensive simulation studies conducted on top of Amazon S3 proved the outstanding performance of the proposed framework in comparison with the current frameworks.
Holistic and Scalable Ontology Alignment for Linked Open Data

The Linked Open Data community continuously releases massive amounts of RDF data that shall be used to easily create applications that incorporate data from dierent sources. Inter-operability across dierent sources requires links at instance- and at schema-level, thus connecting entities on the one hand and relating concepts on the other hand. State-of-the-art entity- and ontology-alignment methods produce high quality alignments for two \nicely structured" individual sources, where an identication of relevant and meaningful pairs of ontologies is a precondition. Thus, these methods cannot deal with heterogeneous data from many sources simultaneously, e.g., data from a linked open data web crawl. To this end we propose Holistic Concept Matching (HCM). HCM aligns thousands of concepts from hundreds of ontologies (from many sources) simultaneously, while maintaining scalability and leveraging the global view on the entire data cloud. We evaluated our approach against the OAEI ontology alignment benchmark as well as on the 2011 Billion Triple Challenge data and present high precision results created in a scalable manner.
Research on the improvement of MongoDB Auto-Sharding in cloud environment

With the rapid development of the Internet Web 2.0 technology, the demands of large-scale distributed service and storage in cloud computing have brought great challenges to traditional relational database. NoSQL database which breaks the shackles of RDBMS is becoming the focus of attention. In this paper, the principles and implementation mechanisms of Auto-Sharding in MongoDB database are firstly presented, then an improved algorithm based on the frequency of data operation is proposed in order to solve the problem of uneven distribution of data in auto-sharding. The improved balancing strategy can effectively balance the data among shards, and improve the cluster's concurrent reading and writing performance.
Ieee Ipas'14: International Image Processing Applications and Systems Conference 2014 Pedestrian Detection Using Covariance Features

—Detecting pedestrians is a challenging problem owing to the motion of the subjects, the camera and the background and to variations in pose, appearance, clothing, illumination and background clutter. The Region Covariance Matrix (RCM) descriptors show experimentally significantly out-performs existing feature sets for pedestrian detection. In this paper, we present an efficient features extraction scheme: the Integral CovReg, inspired from Region Covariance Matrix (RCM) descriptors, combined with SVM classifier for pedestrian detection.