Miracle-dz/UniFAR-FTUs huggingface dataset:
Workload management for cloud databases via machine learning

As elastic IaaS clouds continue to become more cost efficient than on-site datacenters, a wide range of data management applications are migrating to pay-as-you-go cloud computing resources. These diverse applications come with an equally diverse set of performance goals, resource demands, and budget constraints. While existing research has tackled individual tasks such as query placement, scheduling, and resource provisioning to meet these goals and constraints, these techniques fail to provide end-to-end customizable workload management solutions, leading application developers to hand-craft custom heuristics that fit their workload specifications and performance goals. In this vision paper, we argue that workload management challenges can be addressed by leveraging machine learning algorithms. These algorithms can be trained on application-specific properties and performance metrics to automatically learn how to provision resources as well as distribute and schedule the execution of incoming query workloads. Towards this goal, we sketch our vision of WiSeDB, a learning-based service that relies on supervised and reinforcement learning to generate workload management strategies for both static and dynamic workloads.
Coherent Full-Duplex Double-Sided Two-Way Ranging and Velocity Measurement Between Separate Incoherent Radio Units

This paper presents a novel coherent full-duplex (FD) double-sided two-way ranging (CFDDS-TWR) technique for wireless locating and velocity measurement between separate radio units. The idea presented here is a quantum leap in wireless locating since it enables coherent ranging, continuous phase tracking, and velocity measurement between wireless units that operate incoherently with separate low-cost crystal oscillator clock sources. Frequency modulated continuous wave chirp sequences are exchanged in a FD manner between two radio units. The signals transmitted from two radio units are received, respectively, by each of the two units and down-converted in a mixer with the receiver’s own transmit signal to generate a beat signal in each unit. The two beat signals are then processed together, after one beat signal is transmitted to the partner unit. Phase coherent range and Doppler phase measurements can be conducted between incoherent radio units. The presented CFDDS-TWR technique also offers options for reducing noise-like distortions caused by mixing the products of uncorrelated phase noise. We show both analytically and experimentally that the described compensation method reduces the noise level and enhances the dynamic range of the ranging signals tremendously—as evidenced by an improvement of around 24 dB in our results. These unique signal and synchronization properties show that the CFDDS-TWR method is a highly accurate measurement approach. Results acquired with a 24-GHz test system in a 7- to 17-m range demonstrate a standard deviation in range and velocity of 0.25 mm and 0.05 mm/s, respectively.
Discriminating between HuR and TTP binding sites using the k-spectrum kernel method

Background The RNA binding proteins (RBPs) human antigen R (HuR) and Tristetraprolin (TTP) are known to exhibit competitive binding but have opposing effects on the bound messenger RNA (mRNA). How cells discriminate between the two proteins is an interesting problem. Machine learning approaches, such as support vector machines (SVMs), may be useful in the identification of discriminative features. However, this method has yet to be applied to studies of RNA binding protein motifs. Results Applying the k-spectrum kernel to a support vector machine (SVM), we first verified the published binding sites of both HuR and TTP. Additional feature engineering highlighted the U-rich binding preference of HuR and AU-rich binding preference for TTP. Domain adaptation along with multi-task learning was used to predict the common binding sites. Conclusion The distinction between HuR and TTP binding appears to be subtle content features. HuR prefers strongly U-rich sequences whereas TTP prefers AU-rich as with increasing A content, the sequences are more likely to be bound only by TTP. Our model is consistent with competitive binding of the two proteins, particularly at intermediate AU-balanced sequences. This suggests that fine changes in the A/U balance within a untranslated region (UTR) can alter the binding and subsequent stability of the message. Both feature engineering and domain adaptation emphasized the extent to which these proteins recognize similar general sequence features. This work suggests that the k-spectrum kernel method could be useful when studying RNA binding proteins and domain adaptation techniques such as feature augmentation could be employed particularly when examining RBPs with similar binding preferences.
Miniaturization of 2.4GHz SIW Antenna using Complementary Split Ring Resonator

This paper discusses the miniaturization of substrate integrated waveguide (SIW) antenna with complementary split ring resonator (CSRR). The proposed antenna is intended to operate at the frequency of 2.4GHz for wireless local area network (WLAN) application. The antenna which is fed using a microstrip line feeding technique is designed on an FR4 epoxy dielectric substrate with the relative permittivity of 4.2 and the thickness of 1.6mm. To demonstrate the size miniaturization, a conventional SIW antenna without CSRR is also designed using the same dielectric substrate to operate at the same resonant frequency. Characteristics of both antennas are then compared each other in terms of physical size, return loss, VSWR, gain, and radiation pattern. From the result, it is shown that the incorporation of CSRR can achieve the miniaturization of conventional SIW antenna up to 59.2%.
Design and Device Characteristic Analysis of A Triple Material Double Gate (TMDG) Strained Channel MOSFET

In this paper A Triple Material Double Gate (TMDG) n-MOSFET with strained Si (s-Si) channel is proposed. The proposed MOSFET consist of two gate electrodes. Both gate electrodes have three materials with different work-functions. Channel region of MOSFET has strained Si to enhance mobility of charge carriers. Using ATLAS, which is a 2 dimensional device simulator, we have extracted threshold voltage (Vth) of proposed device along with DG MOSFET and DG strained Si channel MOSFET from transfer characteristics of MOSFETs. Trans-conductance (gm) and DIBL analysis of the MOSFET structures is also done in this paper. The strain in Si channel affects effective mass and inversion layer mobility of electrons of Channel which leads to increased drain current. In DG strained MOSFET, As compared to DG MOSFET, improvement in current is observed but the threshold voltage (Vth) of the MOSFET reduces and also DIBL is increased. Reduced threshold voltage is a short channel effect (SCE) which takes place due to reduced potential barrier between source and drain in nanometer regime. TMDG structure leads to increased threshold voltage because of surface potential profile modifications. Surface potential profile of TMDG MOS shows two steps due to three materials used in both the gate electrodes, as a result drain conductance reduces. Reduced drain conductance leads to reduced SCEs like DIBL and Vth lowering. Maximum electric field at the drain electrode also reduces in TMDG structure which minimizes HCE. Threshold voltage also increases in the proposed structure as compared to DG strained MOSFET. Surface potential profile, threshold voltage (Vth), trans-conductance (gm) and DIBL variation are observed in TMDG s-Si n-MOSFET. Proposed MOS device incorporates advantages of both TMDG MOS and strained Si channel MOSFET device to increase performance of high density chips in MOS VLSI technology.
REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms

Outcomes of high-throughput biological experiments are typically interpreted by statistical testing for enriched gene functional categories defined by the Gene Ontology (GO). The resulting lists of GO terms may be large and highly redundant, and thus difficult to interpret. REVIGO is a Web server that summarizes long, unintelligible lists of GO terms by finding a representative subset of the terms using a simple clustering algorithm that relies on semantic similarity measures. Furthermore, REVIGO visualizes this non-redundant GO term set in multiple ways to assist in interpretation: multidimensional scaling and graph-based visualizations accurately render the subdivisions and the semantic relationships in the data, while treemaps and tag clouds are also offered as alternative views. REVIGO is freely available at http://revigo.irb. hr/.
Crush Your Data with ViC2ES Then CHISSL Away

Insider Threat Detection is one of the greatest challenges for organizational cybersecurity [2]. In this paper, we designed and evaluated visually compressed cyber event sequence (ViC2ES) to assist analysts with building mental models about user activity for Insider Threat Detection. Our visualizations, which show user activity on a daily level, are purpose-built to be embedded in our in-house active learning tool called "CHISSL. " [3], [4] We explored different visual compression techniques with binning or run length encoding, resulting in four unique designs built upon the same icon array presentation. We evaluated these four designs for both low-level and high-level tasks in two experiments: in Experiment I, participants performed perceptual tasks such as selecting the most and least similar activities for each of the designs; in Experiment II, participants used one of the designs in CHISSL for eleven reasoning tasks. The results suggest that participants preferred the high level of aggregation, but made the fewest errors with the low level of aggregation; they were able to interact with CHISSL and accomplish the tasks using both designs. We believe our aggregated designs are effective regarding both task performance and screen space; the high and low levels of aggregation designs are valid for user activity modeling.
Parallel K Nearest Neighbor Matching for 3D Reconstruction

In recent years, a 3D reconstruction based on structure from motion (SFM) has attracted much attention from the communities of computer vision and graphics. It is well known that the speed and quality of SFM systems largely depend on the technique of feature tracking. If a big volume of image data is inputted for SFM, the speed of this SFM system would become very slow. And, this problem becomes severer for large-scale scenes, which typically needs to capture several thousands of images to recover the point-cloud model of the scene. However, none of the existing methods fully addresses the problem of fast feature tracking. Brute force matching is capable of producing correspondences for small-scale scenes but often getting stuck in repeated features. Hashing matching can only deal with middle-scale scenes and is not capable of large-scale scenes. In this paper, we propose a new feature tacking method working in a parallel manner rather than in a single thread scheme. Our method consists of steps of keypoint detection, descriptor computing, descriptor matching by parallel $k$ -nearest neighbor (Parallel-KNN) search, and outlier rejecting. This method is able to rapidly match a big volume of keypoints and avoids to consume high computation time, then yielding a set of correct correspondences. We demonstrate and evaluate the proposed method on several challenging benchmark datasets, including those with highly repeated features, and compare to the state-of-the-art methods. The experimental results indicate that our method outperforms the compared methods in both efficiency and effectiveness.
Improving Performance of Product Recommendations Using User Reviews

Recommendation systems have gained importance with the rapid growth in e-commerce industry. Recommendation system utilizes user feedbacks to suggest products that might be useful to the user and also help in accessing the long tail products. Traditional recommendation systems rely on ratings provided by users. However, with advancement in data acquisition, most e-commerce websites today capture other useful feedbacks such as review and review helpfulness, etc. This paper proposes an approach to improve the performance of recommendation systems using user reviews. The experiments are performed on Amazon product dataset which consists of product ratings and reviews. A comparison between traditional rating-based and the proposed recommendation system shows improvement in the recall and root mean square error (RMSE) scores of recommendation system.
A New Topology of Multilevel Inverter with Reduced Number of Switches and Increased Efficiency

This paper proposes a new topology of multilevel inverter in which the number of switches are reduced as compared to cascaded H bridge inverter and with less control complexity. The new topology of multilevel inverter is having a 15 level basic unit and three asymmetrical voltage sources in the ratio 1:2:4. The efficiency analysis of the new topology is carried out in this paper and is compared with reported multilevel inverters. The study in MATLAB/SIMULINK platform and hardware is done for result verification and results validate the theoretical results obtained.
Migration of Bone Marrow-Derived Very Small Embryonic-Like Stem Cells toward An Injured Spinal Cord

Objective Bone marrow (BM) is one of the major hematopoietic organs in postnatal life that consists of a heterogeneous population of stem cells which have been previously described. Recently, a rare population of stem cells that are called very small embryonic-like (VSEL) stem cells has been found in the BM. These cells express several developmental markers of pluri- potent stem cells and can be mobilized into peripheral blood (PB) in response to tissue injury. In this study we have attempted to investigate the ability of these cells to migrate toward an injured spinal cord after transplantation through the tail vein in a rat model. Materials and Methods In this experimental study, VSELs were isolated from total BM cells using a fluorescent activated cell sorting (FACS) system and sca1 and stage specific embryonic antigen (SSEA-1) antibodies. After isolation, VSELs were cultured for 7 days on C2C12 as the feeder layer. Then, VSELs were labeled with 1,1´-dioctadecyl-3,3,3´,3´- tetramethylindocarbocyanine perchlorate (DiI) and transplanted into the rat spinal cord injury (SCI) model via the tail vein. Finally, we sought to determine the presence of VSELs in the lesion site. Results We isolated a high number of VSELs from the BM. After cultivation, the VSELs colonies were positive for SSEA-1, Oct4 and Sca1. At one month after transplantation, real-time polymerase chain reaction analysis confirmed a significantly increased expres- sion level of Oct4 and SSEA-1 positive cells at the injury site. Conclusion VSELs have the capability to migrate and localize in an injured spinal cord after transplantation.
Distributed Cooperative Path-Planning for Autonomous Vehicles Integrating Human Driver Trajectories

This paper considers the problem of cooperative optimal trajectory generation for autonomous driving involving a human driver vehicle (HDV) into the traffic scenario. A distributed model predictive control (MPC) approach to solve the cooperative path-planning problem is proposed. The novelty of this paper are in to enhance cooperative path-planning algorithms, that allows for cooperation between autonomous and human-driven vehicles. We integrate the trajectory prediction of the human driver model (HDM) into the framework, such that the human vehicle influence the behaviour of the other agents. Mixed-integer quadratic programming (MIQP) it is appealing to solve the cooperative planning. The proposed method is evaluated by computational simulations, which show the effectiveness of our approach for a cooperative overtaking scenario comprising three vehicles in a three-lane, one way road.
Modified Distributed Winding for Harmonic Reduction in Space MMF Distribution

This paper presents a modification in the conventional multi-phase distributed winding to reduce the space harmonics in the distribution of magneto-motive force (MMF) around the air-gap periphery. The technique used for modification in winding distribution includes the optimization of conductors per slots and the slot swapping in each phase. This method effectively reduces the dominant lower order harmonics, however, the number of harmonics reduced depends on the slots per pole per phase in the machine. The winding function approach is used to get the closed form expression of Fourier expansion of space MMF distribution. An example of 36 slot, 2 pole induction motor with both conventional single layer distributed winding (SLDW) and modified distributed winding (MDW), is used to compare the performance. The time-stepping Finite Element method is used to analyze the dynamic performance of the induction motor using the proposed winding scheme.
Understanding How Dominance Affects the Emergence of Agreement in a Social Network: The Case of Naming Game

We study the dynamics of the Naming Game as an opinion formation model on social networks. This agent-based model captures the essential features of the agreement dynamics by means of a memory-based negotiation process. Our study focuses on the impact of dominance of certain opinions over others in pursuit of faster agreement on social networks. We propose two models to incorporate dominance of the opinions. We observe that both these models lead to faster agreement among the agents on an opinion as compared to the base case reported in the literature. We perform extensive simulations on computer-generated networks as well as on a real online social network (Facebook) and in both cases the dominance based models converge significantly faster than the base case.
Mouse models of PAK function

p21-activated kinases are a family of highly conserved protein serine/threonine kinases that are increasingly recognized as playing essential roles in a variety of key signaling processes. Genetic analyses in mice, using constitutive or regulated gene disruption, have provided important new insights into PAK function. In this paper, we review the genetic analysis of all six PAK genes in mice. These data address the singular and redundant functions of the various PAK genes and suggest therapeutic possibilities for small molecule PAK inhibitors or „activators.
A Bayesian Approach to Estimation of Speaker Normalization Parameters

In this work, a Bayesian approach to speaker normalization is proposed to compensate for the degradation in performance of a speaker independent speech recognition system. The speaker normalization method proposed herein uses the technique of vocal tract length normalization (VTLN). The VTLN parameters are estimated using a novel Bayesian approach which utilizes the Gibbs sampler, a special type of Markov Chain Monte Carlo method. Additionally the hyperparameters are estimated using maximum likelihood approach. This model is used assuming that human vocal tract can be modeled as a tube of uniform cross section. It captures the variation in length of the vocal tract of different speakers more effectively, than the linear model used in literature. The work has also investigated different methods like minimization of Mean Square Error (MSE) and Mean Absolute Error (MAE) for the estimation of VTLN parameters. Both single pass and two pass approaches are then used to build a VTLN based speech recognizer. Experimental results on recognition of vowels and Hindi phrases from a medium vocabulary indicate that the Bayesian method improves the performance by a considerable margin.
Concurrent Cache-Oblivious B-Trees Using Transactional Memory

Cache-oblivious B-trees for data sets stored in external memory represent an application that can benefit from the use of tran sactional memory (TM), yet pose several challenges for existing TM implementations. Using TM, a programmer can modify a serial, in-memory cache-oblivious B-tree (CO B-tree) to support concurrent operations in a straightforward manner, by performing queries and updates as individual transactions. In this paper, we describe three obstacles that must be overcome, however, before one can implement an efficient external-memory concurrent CO B-tre e. First, CO B-trees must perform input/output (I/O) inside a transaction if the underlying data set is too large to fit in main mem ory. Many TM implementations, however, prohibit such transaction I/O. Second, a CO B-tree that operates on persistent data requires a TM system that supports durable transactions if the programmer wishes to be able to restore the data to a consistent state after a pro gram crash. Finally, CO B-trees operations generate megalithic transactions, i.e., transactions that modify the entire data struc ture, because performance guarantees on CO B-trees are only amortized bounds. In most TM implementations, these transactions create a serial bottleneck because they conflict with all other concurrent tran sactions operating on the CO B-tree. Of these three issues, we argue that a solution for the first tw o issues of transaction I/O and durability is to use a TM system that supports transactions on memory-mapped data. We demonstrate the feasibility of this approach by using LibXac, a library t hat supports memory-mapped transactions, to convert an existing serial implementation of a CO B-tree into a concurrent version with only a few hours of work. We believe this approach can be generalized, that memory-mapped transactions can be used for other applications that concurrently access data stored in external memory.
Sexual Function and Factors Affecting Menopause: A Systematic Review

The purpose of this review study is to evaluate sexual function and its effective factors in menopause. A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The key words of “menopause,” “postmenopause,” “postmenopausal,” “premenopause,” “pre-menopausal period,” “sexual function,” “sexual health,” “sexuality,” “sexual and gender disorders,” “sexual development,” “sexual dysfunction,” “sexual disorders,” “sexual behavior and “sexual activity” were used in combination with the Boolean operators OR and AND. After reviewing the selected articles, 27 papers were selected based on the criteria for entering the study and the goals set. The results of the reviewed articles showed that, in the physical domain, the factors affecting sexual function can be mentioned, age, hormonal changes, medical problems and reproductive history. Sexual disorders in menopause can be affected by some of the individual and social characteristics and psychological problems. Considering the fact that many psychological and social injuries occur in this period following sexual disorders; therefore, policies and programs for improving the quality of life of women in menopause should be aimed at eliminating sexual dysfunction, correcting attitudes and negative emotions and help to women for more comfortable in menopause.
The DEBS 2012 grand challenge

The goal of the DEBS Grand Challenge series is to contribute to the Event Processing Grand Challenge, that serves as a common goal and mechanism for coordinating research focusing on event processing. DEBS Grand Challenge series provides a common ground and evaluation criteria for a competition aimed at both research and industrial event-based systems. The goal of the DEBS Grand Challenge participants is to implement a solution to a specific problem provided by the DEBS Grand Challenge organizers. In this paper we present a description of the DEBS 2012 Grand Challenge problem focusing on the high-tech manufacturing domain. Moreover we provide a set of both: (1) real-life data and (2) queries which can be used by the DEBS 2012 Grand Challenge participants as well as research community at large.