Miracle-dz/UniFAR-FTUs huggingface dataset:
GENCO behavior model and simulation in electricity market by FCM-approach

Simulation can be implemented in various field of electricity market. There are many reasons that market players and regulators are very interested in anticipating the behavior of the market. Behavior of a generation company (GENCO) in electricity market is an important factor affecting the market behavior. Many factors affect on GENCO's behavior directly and indirectly. In this study, a new approach based on fuzzy cognitive map (FCM) is introduced to model and simulate GENCO's behavior in the electricity market with respect to profit maximization. The complicated relations between strategic goals and associated factors can be understood by decision makers using of FCM. This paper examines how effective factors affect on a GENCO's profit. Analyst can build and then analyze a FCM for recognizing key factors corresponding to the goal. To analyze this problem, two cases as simple FCM and weighted FCM are considered. Simple FCM show how determined factors affect on goal. A hidden pattern is obtained by this case. Weighted FCM helps sensitive analysis of the model. In addition, analyst can advantageously use the weighted FCM to clearly quantifying the composite resulted effects from multiple factors changes. This application is shown by a numerical example.
Predicting driving behavior using inverse reinforcement learning with multiple reward functions towards environmental diversity

Predicting defensive driving is a promising technology for novel advanced driver assistance systems. In recent years, modeling driving behavior in residential roads through inverse reinforcement learning (IRL) has been attracting attention in intelligent vehicle community thanks to the superiority of this approach providing long-term prediction of fine-grained driving behavior. However, it suffers from poor performance in diverse environment due to the fact that the single reward function could not handle all the environment with large diversity. Towards this issue, a novel IRL framework with multiple reward functions to deal with environmental diversity is proposed in the paper. Specifically, the model employs Dirichlet process mixtures as a flexible and powerful Bayesian model to divide the environment into clusters and learns the parameters in each cluster simultaneously. Experimental result with expert driver behavior data shows that our model with multiple reward functions provides superior performance over the IRL model with single reward function. It also suggests that the clustering of environments based on the driving behavior of professional drivers could be useful on evaluating driving environments.
Real - time Minor Deformations that Result from Collisions Using Bump and Normal Mapping

This paper presents a method for simulating minor deformations that result from collisions on objects’ surfaces. The method alters only bump maps and leaves mesh geometry unchanged; it is suited to real-time applications where the primary concern is computational efficiency. The paper provides a representative model for deformable objects. Texture mapping and computer graphics techniques based on lighting are referenced as well. Finally, results are provided, along with the most noteworthy findings obtained with the use of this method.
Music summarization using key phrases

Systems to automatically provide a representative summary or 'key phrase' of a piece of music are described. For a 'rock' song with 'verse' and 'chorus' sections, we aim to return the chorus or in any case the most repeated and hence most memorable section. The techniques are less applicable to music with more complicated structure although possibly our general framework could still be used with different heuristics. Our process consists of three steps. First we parameterize the song into features. Next we use these features to discover the song structure, either by clustering fixed-length segments or by training a hidden Markov model (HMM) for the song. Finally, given this structure, we use heuristics to choose the key phrase. Results for summaries of 18 Beatles songs evaluated by ten users show that the technique based on clustering is superior to the HMM approach and to choosing the key phrase at random.
RATT-ECC

This article proposes a rate-adaptive, two-tiered error-correction scheme (RATT-ECC) that provides strong reliability (1010x reduction in raw FIT rate) for an HBM-like 3D DRAM system. The tier-1 code is a strong symbol-based code that can correct errors due to small granularity faults and detect errors caused by large granularity faults; the tier-2 code is an XOR-based code that corrects errors detected by the tier-1 code. The rate-adaptive feature of RATT-ECC enables permanent bank failures to be handled through sparing. It can also be used to significantly reduce the refresh power consumption without decreasing reliability and timing performance.
Characterization of the Small Exported Plasmodium falciparum Membrane Protein SEMP1

Survival and virulence of the human malaria parasite Plasmodium falciparum during the blood stage of infection critically depend on extensive host cell refurbishments mediated through export of numerous parasite proteins into the host cell. The parasite-derived membranous structures called Maurer's clefts (MC) play an important role in protein trafficking from the parasite to the red blood cell membrane. However, their specific function has yet to be determined. We identified and characterized a new MC membrane protein, termed small exported membrane protein 1 (SEMP1). Upon invasion it is exported into the RBC cytosol where it inserts into the MCs before it is partly translocated to the RBC membrane. Using conventional and conditional loss-of-function approaches we showed that SEMP1 is not essential for parasite survival, gametocytogenesis, or PfEMP1 export under culture conditions. Co-IP experiments identified several potential interaction partners, including REX1 and other membrane-associated proteins that were confirmed to co-localize with SEMP1 at MCs. Transcriptome analysis further showed that expression of a number of exported parasite proteins was up-regulated in SEMP1-depleted parasites. By using Co-IP and transcriptome analysis for functional characterization of an exported parasite protein we provide a new starting point for further detailed dissection and characterisation of MC-associated protein complexes.
Vehicle and Person Tracking in UAV Videos

This paper presents two tracking approaches from Sarnoff Corporation to detect moving vehicles and person in the videos taken from Unmanned Aerial Vehicles (UAV). In the first approach, we combine layer segmentation approach with background stabilization and post track refinement to reliably detect small moving objects at the relatively low processing speed. Our second approach employ a fast tracking algorithm that has been optimized for real-time application. To classify vehicle and person from the detected objects, a HOG based vehicle v.s. person classifier is designed and integrated with the tracking postprocessing. Finally, we report the results of our algorithms on a large scale data set collected from VIVID program and the scores evaluated by NIST CLEAR program.
Acquisition of 3 D Indoor Environments with Variability and Repetition

Large-scale acquisition of exterior urban environments is by now a well-established technology, supporting many applications in search, navigation, and commerce. The same is not true for indoor environments, however: access is often restricted and the spaces may be cluttered. In addition, such environments typically contain a high density of repeated objects (e.g., tables, chairs, monitors, etc.) in regular or non-regular arrangements with significant pose variations and articulations. In this paper, we exploit the special structure of indoor environments to accelerate their 3D acquisition and recognition with a low-end handheld scanner. Our approach runs in two phases: (i) a learning phase, where we acquire 3D models of frequently occurring objects and capture their variability modes from only a few scans, and (ii) a recognition phase, where from a single scan of new areas, we identify previously seen objects, but in varying poses and locations. This greatly accelerates the capture process (average recognition time of 200ms/model). We demonstrate our framework with the acquisition of typical areas of a university building including cubicle or desk areas, auditoriums, etc., using a Microsoft Kinect sensor.
Lessons learned from the use of interactive workspaces for student team design project meetings

SUMMARY: An Interactive Collaboration Laboratory (ICL) has been established at the University of New Brunswick (UNB) to research the application of interactive information and communication environments for the architectural, engineering, and construction (AEC) industry. This paper provides a quick overview of the laboratory within the wider context of interactive collaborative workspaces. It identifies opportunities to enhance information communication, and group decision-making offered by the laboratory, and focuses on lessons learned to date from its use. The paper reports on a survey conducted among senior year undergraduate students who used the environment over the course of three months for their senior design project meetings. A questionnaire was administered to those students to investigate the relative impact of the environment upon the effectiveness of their meetings and decisions, the issues and processes where the environment was more or less useful, and the relative value and usefulness of the environment for the team’s needs. Students found the laboratory to be conducive to learning and collaboration. The environment was effective in preventing loss of information, and information representation. It increased participation, and encouraged decision-making by consensus. Students found it useful in explaining and presenting information to others, and in promoting greater understanding among members of the team. They also felt that the technology was easy to use and operate, requiring minimal external assistance. Nevertheless, they were not always sure about how available technology could be used to improve their work. The environment also seemed less effective in improving work productivity and decision-making. There was less agreement on the speed with which meetings progressed, and the extent to which meeting agendas were followed. It was also less effective in facilitating the access, retrieval and capture of information. The environment was more prohibitive in terms of individual expression. It was also less useful in generating and developing new information and in predicting the impact of changes on interim decisions. While results might vary from one user group to another and from one meeting scenario to another, it is imperative that additional tools and techniques are provided to address those imperfections for that particular group of users and that particular meeting purpose.
EXPLAINING INEQUALITY AND WELFARE STATUS OF HOUSEHOLDS IN RURAL NIGERIA: EVIDENCE FROM EKITI STATE

A number of studies have shown that inequality is increasing in the rural and urban areas of Nigeria and this can be linked to the growing dimension of poverty. The study focused on analysing inequality and welfare status of rural households in Ekiti State, Nigeria. The result presented was based on primary data collected from a random sample of 240 households selected from four rural communities in the state. Descriptive statistics, Lorenz curve, Gini coefficient and regression analysis were employed as analytical techniques. Both the Lorenz curve and Gini coefficient were used to examine the distribution of households' income and estimate the level of inequality respectively. However, the regression analysis was used to examine the determinants of households' expenditure on food and non-food items (proxy for welfare). The Lorenz curve analysis showed that there's an unequal distribution in the income and other indicators of welfare with a Gini coefficient of 0.3570. The regression analysis revealed that income (8.518E-05**), household size (1.336E-02*) and size of farmland cultivated (1.084E-04*) were positively related to the welfare status of the households while marital status (-2.51E-02) and primary occupation (-2.95E-02) were negatively related to it. The recommendations arising from the study were that there is a need to upgrade technologies for increased agricultural production in order to further improve income levels of households and equity in the distribution of income arising from farming activities since this remains the major source of income of households in the study area. More so, there should be provision of infrastructural facilities in order to improve the welfare status of the households.
Altered Stoichiometry of FKBP12.6 Versus Ryanodine Receptor as a Cause of Abnormal Ca2 Leak Through Ryanodine Receptor in Heart Failure

BackgroundIn the pathogenesis of cardiac dysfunction in heart failure, a decrease in the activity of the sarcoplasmic reticulum (SR) Ca2+-ATPase is believed to be a major determinant. Here, we report a novel mechanism of cardiac dysfunction revealed by assessing the functional interaction of FK506–binding protein (FKBP12.6) with the cardiac ryanodine receptor (RyR) in a canine model of pacing-induced heart failure. Methods and ResultsSR vesicles were isolated from left ventricular muscles (normal and heart failure). The stoichiometry of FKBP12.6 per RyR was significantly decreased in failing SR, as assessed by the ratio of the Bmax values for [3H]dihydro-FK506 to those for [3H]ryanodine binding. In normal SR, the molar ratio was 3.6 (≈1 FKBP12.6 for each RyR monomer), whereas it was 1.6 in failing SR. In normal SR, FK506 caused a dose-dependent Ca2+ leak that showed a close parallelism with the conformational change in RyR. In failing SR, a prominent Ca2+ leak was observed even in the absence of FK506, and FK506 produced little or no further increase in Ca2+ leak and only a slight conformational change in RyR. The level of protein expression of FKBP12.6 was indeed found to be significantly decreased in failing SR. ConclusionsAn abnormal Ca2+ leak through the RyR is present in heart failure, and this leak is presumably caused by a partial loss of RyR-bound FKBP12.6 and the resultant conformational change in RyR. This abnormal Ca2+ leak might possibly cause Ca2+ overload and consequent diastolic dysfunction, as well as systolic dysfunction.
Environmental Influences on Mate Preferences as Assessed by a Scenario Manipulation Experiment

Many evolutionary psychology studies have addressed the topic of mate preferences, focusing particularly on gender and cultural differences. However, the extent to which situational and environmental variables might affect mate preferences has been comparatively neglected. We tested 288 participants in order to investigate the perceived relative importance of six traits of an ideal partner (wealth, dominance, intelligence, height, kindness, attractiveness) under four different hypothetical scenarios (status quo/nowadays, violence/post-nuclear, poverty/resource exhaustion, prosperity/global well-being). An equal number of participants (36 women, 36 men) was allotted to each scenario; each was asked to allocate 120 points across the six traits according to their perceived value. Overall, intelligence was the trait to which participants assigned most importance, followed by kindness and attractiveness, and then by wealth, dominance and height. Men appraised attractiveness as more valuable than women. Scenario strongly influenced the relative importance attributed to traits, the main finding being that wealth and dominance were more valued in the poverty and post-nuclear scenarios, respectively, compared to the other scenarios. Scenario manipulation generally had similar effects in both sexes, but women appeared particularly prone to trade off other traits for dominance in the violence scenario, and men particularly prone to trade off other traits for wealth in the poverty scenario. Our results are in line with other correlational studies of situational variables and mate preferences, and represent strong evidence of a causal relationship of environmental factors on specific mate preferences, corroborating the notion of an evolved plasticity to current ecological conditions. A control experiment seems to suggest that our scenarios can be considered as realistic descriptions of the intended ecological conditions.
Spatial constraints underlying the retinal mosaics of two types of horizontal cells in cat and macaque

Abstract Most types of retinal neurons are spatially positioned in non-random patterns, termed retinal mosaics. Several developmental mechanisms are thought to be important in the formation of these mosaics. Most evidence to date suggests that homotypic constraints within a type of neuron are dominant, and that heterotypic interactions between different types of neuron are rare. In an analysis of macaque H1 and H2 horizontal cell mosaics, Wässle et al. (2000) suggested that the high regularity index of the combined H1 and H2 mosaic might be caused by heterotypic interactions during development. Here we use computer modeling to suggest that the high regularity index of the combined H1 and H2 mosaic is a by-product of the basic constraint that two neurons cannot occupy the same space. The spatial arrangement of type A and type B horizontal cells in cat retina also follow this same principle.
DCS: Diagonal Coding Scheme for Enhancing the Endurance of SSD-Based RAID Arrays

To guarantee high reliability, solid-state drive (SSD)-based storage systems require data redundancy schemes, e.g., redundant array of independent disks (RAID) schemes. Traditional RAID-5, RAID-6, and Reed-Solomon codes can tolerate one, two, and an arbitrary number of device failures, respectively. However, some SSDs under those redundant configurations may age much faster than others because of the high skewness and locality of workloads. The uneven aging rates may make some SSDs wear out very quickly and decrease the endurance of SSD-based RAID arrays. To address this problem, we first come up with a diagonal coding scheme (DCS) by distributing the updating dependencies evenly among devices to improve the system-level wear-leveling. DCS can efficiently improve the array endurance if requests are aligned with the stripe size, i.e., when data symbols in the same stripe receive the same number of writes, while the number could be different for different stripes. To relax the above assumption, we further propose an enhanced scheme, DCS+. With a buffer design, DCS+ can improve the wear-leveling among devices under general access patterns via triggering different responses to different kinds of requests. We conduct extensive trace-driven evaluations based on real-world workloads, and results show that our design efficiently enhances the endurance of SSD-based RAID arrays.
An application of chance-constrained model predictive control to inventory management in Hospitalary Pharmacy

Inventory management is one of the main tasks that the pharmacy department has to carry out in a hospital. It is a complex problem that requires to establish a tradeoff between different and contradictory optimization criteria. The complexity of the problem is increased due to the constraints that naturally arise in this type of applications. In this paper, which corresponds to preliminary works performed to implement advanced control techniques for pharmacy management in two Spanish hospitals, we propose and assess chance-constrained model predictive control (CC-MPC) as a mean to relieve this issue.
Retinoic acid-induced gene expression in normal and leukemic myeloid cells

Retinoic acid has been shown to induce large accumulations of tissue transglutaminase in cultured myeloid cells. Addition of retinoic acid to mouse resident peritoneal macrophages increased the level of tissue transglutaminase mRNA within 30-60 min. Retinoic acid also increased tissue transglutaminase mRNA levels in human promyelocytic leukemia (HL- 60) cells. These studies show that retinoic acid can induce acute alterations in specific gene expression in both normal and leukemic myeloid cells.
Recent progress with BOXES

The BOXES algorithm of Michie and Chambers (1968) has proved to be an effective and flexible method for learning to control dynamic systems. The algorithm, in its original form has been used a benchmark for many experiments in control tasks such as pole balancing. Recent work in our laboratory has shown that the BOXES algorithm can be improved to yield very good learning rates. We describe experiments on a variety of update functions and discuss their robustness. We also develop the notion of freezing of BOXES, suggested by Michie and implemented by Bain (1990). We have also been concerned with synthesising a readable account of the control strategy employed by a set of boxes. Some preliminary work has begun in combining decision tree learning algorithms with BOXES. Using this method, we regard BOXES as the acquirer of sub-cognitive skills and the decision tree induction as a means of introspecting on the learned strategy to generate understandable control rules.
Domain Ontology Building Process Based on Text Mining from Medical Structured Corpus

Ontologies have become an important means for structuring knowledge and building knowledgeintensive systems. With the advent of ontologies being used in many different fields of computer science, developing appropriate methods to automate ontology engineering become an increasingly important goal. For this purpose, efforts have been made to facilitate the ontology engineering process, in particular the construction of ontology from domain texts. Hence, we present an extraction and building process to generate and evaluate domain ontology using text-mining techniques. We exploit domain specific texts collected from medical reports in order to automatically extract terms. These terms are sets o f concepts/relations which have either taxonomic or non-taxonomic relationships among them. We have developed an extensive and detailed ontology in the field of gynaecology using this process.
Energy Efficiency in Large Scale Interference Limited wireless ad hoc networks

This paper presents an analytical approach to quantify energy efficiency (EE), i.e., the bits per Joule performance of a large scale interference limited random wireless ad hoc network. Energy consumption is investigated at physical, medium access control (MAC) and routing layers. Communication between a user and its destination is facilitated by multihop relaying and Slotted ALOHA based MAC protocol. Energy consumption of user's communication hardware platform is analyzed considering the transceiver architecture. Geometry of the forwarding areas resulting from two different long hop routing protocols is explicitly considered in the analysis. The link model is formulated to cater for user's desired QoS while considering the network interference and the spatial/channel uncertainties. EE performance of the network is quantified from single-hop forward progress, node isolation and hop statistics. Optimal MAP which maximizes the network EE is also investigated. Analytical results are supported by Monte Carlo simulations. It is shown that several hypothesis established in existing literature which ignores network interference and fading do not hold in large scale interference limited ad hoc network.
UBC-UPC: Sequential SRL Using Selectional Preferences. An approach with Maximum Entropy Markov Models

We present a sequential Semantic Role Labeling system that describes the tagging problem as a Maximum Entropy Markov Model. The system uses full syntactic information to select BIO-tokens from input data, and classifies them sequentially using state-of-the-art features, with the addition of Selectional Preference features. The system presented achieves competitive performance in the CoNLL-2005 shared task dataset and it ranks first in the SRL subtask of the Semeval-2007 task 17.