Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a storage system for connected homes

Homes are increasingly filled with connected devices such as wireless door locks, remotely controllable thermostats, and security cameras. Home automation systems, which used to be prohibitively expensive to average consumers, are now offered at an affordable price, accelerating the adoption of “smart” devices in the home. The advances in devices also enable researchers and practitioners to develop new services and applications for householders—PreHeat uses occupancy sensing to efficiently heat homes [19]; a DigiSwitch display supports elders who reside separately from their caregivers with whom they share sensed activity data in the home [5]; and a Digital Neighbourhood Watch (DNW) is proposed to help neighbors detect suspicious activities (e.g., previously unseen cars driving by several times) in the neighborhood by sharing security camera images [4]. To facilitate such home technology developments, platforms like HomeOS [6] and Mi Casa Verde [1] provide a standard way to communicate with a range of devices and a set of APIs to ease the implementation of applications. However, storage abstraction for applications in the home is not yet clearly defined. For instance, HomeOS exposes local file system APIs to HomeOS applications, but has no built-in support for sharing data with other applications that may run remotely. Commercial devices typically come with a tailored storage solution (e.g., Withings wireless scales transmit data to withings.com by default) and as a result, data from each device is stored in silos, causing a data management nightmare. We first discuss the key requirements for a storage system that supports connected devices and applications in the home. We ground our discussion with the use cases derived from the aforementioned examples—PreHeat, DigiSwitch, and DNW—as well as our own experience of building new applications using various in-home sensors. We then present Bolt, a storage system for data generated by connected devices and applications in the home. Bolt offers a stream based key-value abstraction with support for range queries over time and filtering based on application-specific keys. Bolt stores data on potentially untrusted cloud storage providers while ensuring confidentiality using decentralized access control. Storage policies in Bolt allow applications to prioritize their storage requirements of space, performance, cost, and reliability. After highlighting the key difference between Bolt and prior systems, we finally conclude the paper with a description of our ongoing efforts to build Bolt.
Outlier removal using duality

In this paper we consider the problem of outlier removal for large scale multiview reconstruction problems. An efficient and very popular method for this task is RANSAC. However, as RANSAC only works on a subset of the images, mismatches in longer point tracks may go undetected. To deal with this problem we would like to have, as a post processing step to RANSAC, a method that works on the entire (or a larger) part of the sequence. In this paper we consider two algorithms for doing this. The first one is related to a method by Sim & Hartley where a quasiconvex problem is solved repeatedly and the error residuals with the largest error is removed. Instead of solving a quasiconvex problem in each step we show that it is enough to solve a single LP or SOCP which yields a significant speedup. Using duality we show that the same theoretical result holds for our method. The second algorithm is a faster version of the first, and it is related to the popular method of L1-optimization. While it is faster and works very well in practice, there is no theoretical guarantee of success. We show that these two methods are related through duality, and evaluate the methods on a number of data sets with promising results.1
Effects of Olanzapine and Risperidone on Metabolic Factors in Children and Adolescents: A Retrospective Evaluation

Objective. To assess the effects of olanzapine and risperidone on metabolic factors in children and adolescents admitted to an inpatient psychiatric hospital. Methods. The study was a retrospective chart review of hospitalized patients younger than 18 years of age treated with olanzapine or risperidone. Data collected from medical charts were analyzed to assess weight gain, lipid profiles, blood pressure, and glucose levels in patients prescribed olanzapine or risperidone. Results. A total of 49 patients (25 receiving olanzapine and 24 receiving risperidone) with a mean age of 13 years were included in the study; the mean duration of treatment was 27 days. A significant increase in body mass index (BMI) from baseline to endpoint in both treatment groups was found (P<0.001); however, the change in BMI was not significantly different between the olanzapine and risperidone groups (P=0.425). Seven new cases (28%) in the olanzapine group and 4 new cases (17%) in the risperidone group met criteria for being overweight or at risk for being overweight. A significant increase in mean systolic blood pressure was found in subjects receiving olanzapine compared with those receiving risperidone (+5.4 mm Hg vs. −3.2 mm Hg; P=0.044), while diastolic blood pressure did not differ between the treatment groups. A significant increase in risk factors for diabetes mellitus (P=0.008) and in overall risk factors for metabolic syndrome (P=0.013) was found in the olanzapine group over the course of treatment, whereas no significant effect on risk factors for diabetes or metabolic syndrome was found in the risperidone group. Conclusions. Inpatient treatment with both olanzapine and risperidone was correlated with a significant increase in BMI. Olanzapine also resulted in increased risk factors for diabetes and metabolic syndrome (Journal of Psychiatric Practice 2009;15:320-328).
Molecular Mimics of the Tumour Antigen MUC1

A key requirement for the development of cancer immunotherapy is the identification of tumour-associated antigens that are differentially or exclusively expressed on the tumour and recognized by the host immune system. However, immune responses to such antigens are often muted or lacking due to the antigens being recognized as “self”, and further complicated by the tumour environment and regulation of immune cells within. In an effort to circumvent the lack of immune responses to tumour antigens, we have devised a strategy to develop potential synthetic immunogens. The strategy, termed mirror image phage display, is based on the concept of molecular mimicry as demonstrated by the idiotype/anti-idiotype paradigm in the immune system. Here as ‘proof of principle’ we have selected molecular mimics of the well-characterised tumour associated antigen, the human mucin1 protein (MUC1) from two different peptide phage display libraries. The putative mimics were compared in structure and function to that of the native antigen. Our results demonstrate that several of the mimic peptides display T-cell stimulation activity in vitro when presented by matured dendritic cells. The mimic peptides and the native MUC1 antigenic epitopes can cross-stimulate T-cells. The data also indicate that sequence homology and/or chemical properties to the original epitope are not the sole determining factors for the observed immunostimulatory activity of the mimic peptides.
PAC Optimal Planning for Invasive Species Management: Improved Exploration for Reinforcement Learning from Simulator-Defined MDPs

Often the most practical way to define a Markov Decision Process (MDP) is as a simulator that, given a state and an action, produces a resulting state and immediate reward sampled from the corresponding distributions. Simulators in natural resource management can be very expensive to execute, so that the time required to solve such MDPs is dominated by the number of calls to the simulator. This paper presents an algorithm, DDV, that combines improved confidence intervals on the Q values (as in interval estimation) with a novel upper bound on the discounted state occupancy probabilities to intelligently choose state-action pairs to explore. We prove that this algorithm terminates with a policy whose value is within epsilon of the optimal policy (with probability 1-delta) after making only polynomially-many calls to the simulator. Experiments on one benchmark MDP and on an MDP for invasive species management show very large reductions in the number of simulator calls required.
SimBench: A portable benchmarking methodology for full-system simulators

Full-system simulators are increasingly finding their way into the consumer space for the purposes of backwards compatibility and hardware emulation (e.g. for games consoles). For such compute-intensive applications simulation performance is paramount. In this paper we argue that existing benchmark suites such as SPEC CPU2006, originally designed for architecture and compiler performance evaluation, are not well suited for the identification of performance bottlenecks in full-system simulators. While their large, complex workloads provide an indication as to the performance of the simulator on ‘real-world’ workloads, this does not give any indication of why a particular simulator might run an application faster or slower than another. In this paper we present SimBench, an extensive suite of targeted micro-benchmarks designed to run bare-metal on a fullsystem simulator. SimBench exercises dynamic binary translation (DBT) performance, interrupt and exception handling, memory access performance, I/O and other performance-sensitive areas. SimBench is cross-platform benchmarking framework and can be retargeted to new architectures with minimal effort. For several simulators, including QEMU, Gem5 and SimIt-ARM, and targeting ARM and Intel x86 architectures, we demonstrate that SimBench is capable of accurately pinpointing and explaining real-world performance anomalies, which are largely obfuscated by existing application-oriented benchmarks.
A time slice based scheduler model for system level design

Efficient evaluation of design choices, in terms of selection of algorithms to be implemented as hardware or software, and finding an optimal HW/SW design mix is an important requirement in the design flow of embedded systems. Time-to-market, faster upgradability and flexibility are some of the driving points to put increasing amounts of functionality as software executed on general purpose processing elements. In this scenario, dividing a monolithic task into multiple interacting tasks, and scheduling them on limited processing elements has become very important for a system designer. The paper presents an approach to model time-slice based task schedulers in the designs where the performance estimate of hardware and software models is less than time-slice accurate. The approach aims to increase the simulation efficiency of designs modeled at system level. We used Metropolis (Balarin, F. et al., IEEE Computer, vol.36, no.4, p.45-52, 2003) as our codesign environment.
A Cycle-Based Data Aggregation Scheme for Grid-Based Wireless Sensor Networks

In a wireless sensor network (WSN), a great number of sensor nodes are deployed to gather sensed data. These sensor nodes are typically powered by batteries so their energy is restricted. Sensor nodes mainly consume energy in data transmission, especially over a long distance. Since the location of the base station (BS) is remote, the energy consumed by each node to directly transmit its data to the BS is considerable and the node will die very soon. A well-designed routing protocol is thus essential to reduce the energy consumption. In this paper, we propose a Cycle-Based Data Aggregation Scheme (CBDAS) for grid-based WSNs. In CBDAS, the whole sensor field is divided into a grid of cells, each with a head. We prolong the network lifetime by linking all cell heads together to form a cyclic chain so that the gathered data can move in two directions. For data gathering in each round, the gathered data moves from node to node along the chain, getting aggregated. Finally, a designated cell head, the cycle leader, directly transmits to the BS. CBDAS performs data aggregation at every cell head so as to substantially reduce the amount of data that must be transmitted to the BS. Only cell heads need disseminate data so that the number of data transmissions is greatly diminished. Sensor nodes of each cell take turns as the cell head, and all cell heads on the cyclic chain also take turns being cycle leader. The energy depletion is evenly distributed so that the nodes' lifetime is extended. As a result, the lifetime of the whole sensor network is extended. Simulation results show that CBDAS outperforms protocols like Direct, PEGASIS, and PBDAS.
Do Topic-Dependent Models Improve Microblog Sentiment Estimation?

A topic-independent sentiment model is commonly used to estimate sentiment in microblogs. But for movie and product reviews, domain adaptation has been shown to improve sentiment estimation performance. We examined whether topic-dependent models improve polarity estimation of microblogs. We considered both a model trained on Twitter tweets containing a target keyword and a model trained on an enlarged set of tweets containing terms related to a topic. Comparing the performance of the topic-dependent models to a topic-independent model trained on a general sample of tweets, we noted that for some topics, topic-dependent models performed better. We then propose a method for predicting which topics are likely to have better sentiment estimation performance when a topic-dependent sentiment model is used.
Conserved pattern of antisense overlapping transcription in the homologous human ERCC-1 and yeast RAD10 DNA repair gene regions

We report that the genes for the homologous Saccharomyces cerevisiae RAD10 and human ERCC-1 DNA excision repair proteins harbor overlapping antisense transcription units in their 3' regions. Since naturally occurring antisense transcription is rare in S. cerevisiae and humans (this is the first example in human cells), our findings indicate that antisense transcription in the ERCC-1-RAD10 gene regions represents an evolutionarily conserved feature.
A Novel Subband Decomposition Based Speckle Noise Reduction Algorithm for SAR Images

A new speckle reduction algorithm based on subband decomposition and multiscale edge detection is presented. The subband decomposition is performed using a DFT/RDFT-based symmetric, zero-phase, nonoverlapping digital filter bank. The noisy images are decomposed into sub-images using RDFT transform based subband decomposition, an edge image is obtained for each level using these sub-images, then a threshold value is estimated according to noise variance in each subband and soft-thresholding is applied on the non-edge regions of the subband images. The despeckled image is obtained from the thresholded subband images using the inverse RDFT transform. The proposed speckle reduction method is applied to several test images corrupted by speckle noise as well as experimental RADARSAT/SAR images. Despeckled images show that this method has better performance than the case where no edge information is used.
Correlation between discharge and water quality: Case study Nišava river: Serbia

The water quality and river discharges were surveyed at two sites in Nišava River basin (Dimitrovgrad and Niš) with complete data series for the ten-year period (2005–2014). For these stations SWQI was calculated and correlation analysis was applied. The index value is dimensionless and varies between 0 and 100 (best quality) It is derived from numerous physical, chemical, biological and microbiological parameters. At Niš station average annual value of SWQI is 78 (good) with a clear decrease trend over a ten-year period. On the other side, on Dimitrovgrad station, average annual SWQI is 89 (very good) with a clear positive trend. Goal of this paper was to determine if there is a correlation between river discharge and values of SWQI. Results of the Pearson correlation test between SWQI and daily discharge values for Dimitrovgrad station show a moderate linear relation was observed, r= -0.287, p = 0.002. On Niš station same test has shown that there is no statistically significant relation between discharge and water quality (r=0.103 p= 0.297). This study has shown that the correlation between SWQI and discharge is weak or not present at all at the investigated river.
Numerical Simulation of Hydraulic Jumps. Part 2: Recent Results and Future Outlook

During the past two decades, hydraulic jumps have been investigated using Computational Fluid Dynamics (CFD). The second part of this two-part study is devoted to the state-of-the-art of the numerical simulation of the hydraulic jump. First, the most widely-used CFD approaches, namely the Reynolds-Averaged Navier–Stokes (RANS), the Large Eddy Simulation (LES), the Direct Numerical Simulation (DNS), the hybrid RANS-LES method Detached Eddy Simulation (DES), as well as the Smoothed Particle Hydrodynamics (SPH), are introduced pointing out their main characteristics also in the context of the best practices for CFD modeling of environmental flows. Second, the literature on numerical simulations of the hydraulic jump is presented and discussed. It was observed that the RANS modeling approach is able to provide accurate results for the mean flow variables, while high-fidelity methods, such as LES and DES, can properly reproduce turbulence quantities of the hydraulic jump. Although computationally very expensive, the first DNS on the hydraulic jump led to important findings about the structure of the hydraulic jump and scale effects. Similarly, application of the Lagrangian meshless SPH method provided interesting results, notwithstanding the lower research activity. At the end, despite the promising results still available, it is expected that with the increase in the computational capabilities, the RANS-based numerical studies of the hydraulic jump will approach the prototype scale problems, which are of great relevance for hydraulic engineers, while the application at this scale of the most advanced tools, such as LES and DNS, is still beyond expectations for the foreseeable future. Knowledge of the uncertainty associated with RANS modeling may allow the careful design of new hydraulic structures through the available CFD tools.
Dwipa ontology II: A semi-automatic ontology population process for Bali Tourism based on the ontology population methodology

In this present study, we have found that the terms of linguistic methods (POS) gives higher relevance than the statistical method (TF-IDF). The relevance value is determined by the value of recall. The highest recall is 87.89. Factors affecting the value is the definition of ‘term’ used as reference in this study that focused on the ‘term’ related to classes and attributes that exist in the initial ontology DWIPA version 1, which is limited to: Attraction, Events, Accommodation and Regency. This limitation has led to the narrow scope of the terms sought from the corpus. This research also managed to populate the DWIPA I semi-automatically based on ontology population methodology. The populated ontology named DWIPA II. This ontology consists of 41 new instances added to the following class/ subclasses: Accommodation, Attraction, Event and Regency. Thus, the total instance of DWIPA II is 193 instances. As a part of ontology population, DWIPA II also evaluated by using description logic (DL) query. The result shown that the DWIPA II is consistent, as the number of DL query is the same as the number of instances in the ontology.
Central but not peripheral fat mass percentage is associated with blood pressure components in the elderly

Background: the human body composition changes with advances in age. Particularly, the central fat amount increases. Because the central fat mass is a cardiovascular risk factor, we investigated whether in an elderly population, fat mass (measured at different bodily locations) is associated with peripheral and central blood pressure components. Methods: cross-sectional design. Using dual-energy X-ray absorptiometry (DEXA), fat mass was measured within a geriatric outpatient clinic population. Blood pressure was measured with an oscillometric device, and aortic blood pressure and augmentation index (AIx) were obtained by radial artery tonometry, using the SphygmoCor system. Multivariate adjustment for confounders was performed using linear regression analyses. Results: totally, 216 subjects were included (age 77.3 years ± 6.1, 34.7% male). The truncal fat mass percentage, but not the peripheral fat mass percentage, was positively associated with the peripheral systolic blood pressure (SBP) [beta 0.07 (95% CI: 0.02 to 0.11)] and the peripheral pulse pressure (PP) [beta 0.07 (95% CI: 0.02 to 0.11)], but negatively with the peripheral diastolic blood pressure (DBP) [beta −0.16 (95% CI −0.27 to −0.04)]. The truncal fat mass percentage was similarly associated with estimated aortic blood pressure components, but no association was found between the truncal fat mass percentage and the AIx. Conclusion: in older persons, the truncal fat mass percentage as a reflection of the central fat mass percentage, but not the peripheral fat mass percentage is associated with peripheral and aortic blood pressure components.
Integrating deadline-modification SCAN algorithm to Xen-based cloud platform

Virtualization is a critical technology issue in cloud computing. Virtualization technology faces two major challenges, namely, poor I/O throughput and long latency for data access. To address the issues, we present a distributed deadline modification SCAN mechanism called DDM-SCAN. We integrate the DDM-SCAN mechanism to Xen-based cloud platform. The result of our simulations show DDM-SCAN improve the I/O response time of Xen-based cloud platform 20% comparing to Flubber [1] mechanism and it also guarantee same or better quality of service (QoS) as compared with Flubber mechanism in Xen-based hypervisor. In advance, this paper provides more easy method to implement DDM-SCAN on Xen-based hypervisor rather than Flubber mechanism.
Lateralisation of the white matter microstructure associated with the hemispheric spatial attention dominance

Objectives Healthy people have a slight leftward bias of spatial attention as measured on the Landmark task. Former studies indicated that lateralisation of brain activation contributes to this attentional bias. In this study we hypothesised that if the spatial bias was consistent over several measurements there would be structural background of it. Methods Reproducibility of the spatial bias of visuo-spatial attention was measured in twenty healthy subject in a Landmark task over three consecutive days. In order to evaluate the correlation between the spatial attentional bias and the white matter microstructure high angular resolution diffusion MRI was acquired for each subjects. The Track Based Spatial Statistics method was used to measure the hemispheric differences of the white matter microstructure. Probabilistic tractography was used to reveal the connection of the identified regions. Results The analysis showed correlation between the behavioural scores and the lateralisation of the white matter microstructure in the parietal white matter (p<0.05, corrected for multiple correlations). Higher FA values on the left are associated to rightward bias. The parietal cluster showed connectivity along the superior longitudinal fascicle on one end to posterior parietal cortex and anteriorly to the putative frontal eye field. From the frontal eye field some of the fibres run towards the nodes of the dorsal attention network to the intraparietal suclus, while some of the fibres travelled toward to ventral attention network to the temporo-parietal junction. Conclusions These results indicate that the structural integrity dorsal fronto-parietal network and the connection between the dorsal and ventral attention networks are responsible for the attentional bias in normal healthy controls.