Miracle-dz/UniFAR-FTUs huggingface dataset:
Context Aware Concurrent Execution Framework for Web Browsers

Computing hungry multimedia web applications need to efficiently utilize all the resources of a device. HTML5 web workers is a non-sharing concurrency platform that enables multimedia web application to utilize the available multicore hardware. HTML5 web workers are implemented by major browser vendors to facilitate concurrent execution in web clients and enhance the quality of ambitious web applications. The concurrent execution in web workers allows parallel processing using available cores at the expense of communication overhead and extra computation. The benefits of concurrent execution can be maximized by balancing load across workers/CPU cores. This work presents load-balancing algorithms between web workers using parameters such as scheduler throughput, computation priority and game entities locality. An award-winning web-based multimedia game (raptjs.com) is used to evaluate the performance of load balancing algorithms. The preliminary results indicated that the performance of game improved with the proposed load-balancing across web workers. The load balancing algorithms were developed on top of DOHA [1], an open source JavaScript execution This paper was made possible by NPRP grant #8-519-1-108 from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are solely the responsibility
Chapter 12 An NLP & IR Approach to Topic Detection

This paper presents algorithms for Chinese and English-Chinese topic detection. Named entities, other nouns and verbs are cue patterns to relate news stories describing the same event. Lexical translation and name transliteration resolve lexical differences between English and Chinese. A two-threshold scheme determines relevance (irrelevance) between a news story and a topic cluster. Lookahead information deals with ambiguous cases in clustering. The least-recently-used removal strategy modelsthetimefactor in such away that older and unimportant terms will have no effect on clustering. Experimental results show that nouns and verbs as well as the least-recently-used removal strategy outperform other models. The performance of the named-entity-only approach decreases slightly, but it has no overhead of nouns-and-verbs approach with the least-recently-used removal strategy.
Immunohistochemical detection of metallothionein

thereby influencing the function of numerous enzymes and transcription factors that control cell proliferation, apoptosis and signalling pathways [4,5]. Abnormal MT function and expression have been implicated in various human diseases, including cancer [6]. There are at least 10 isoforms of MT in human body, which are expressed in a tissue specific pattern and may play distinct roles in the various cell types. MT-I and MT-II isoforms are present in all cells throughout the body, MT-III was first isolated as a growth inhibiting factor (GIF) from brain neurons, MT-IV is located in stratified epithelium [6]. Transcription of MT-I and MT-II can be induced by inflammatory cytokines (IL-6, TNF-α, interferons), lipopolysaccharids, glucocorticoids, free radicals, antioxidants or Immunohistochemical detection of metallothionein Gabriella Emri1*, Eszter Emri1, Livia Beke2, Gábor Boros1, Csaba Hegedűs1, Eszter Janka1, Emese Gellén1, Gábor Méhes2 and Éva Remenyik1
Semantic Profiling for Heterogeneous Parallel Languages • 1 : 3 2 BACKGROUND AND MOTIVATION 2 . 1 Why Formal Profiling Methods ?

In today’s world parallelism is ubiquitous, and di erent types of parallel models and processors are becoming increasingly common. Moreover, while our programs become increasingly heterogeneous in the parallelism they employ, user-visible parallelism in our languages become increasingly homogeneous, with the parallelization onus put more-and-more on the compiler or runtime. This increasing divide between what is and what happens in our languages makes being able to determine the costs of running the same program on di erent types of hardware increasingly important. However, while there are formal means for pro ling parallel programs written for the CPU, there are still no means to formally pro le and reason about parallel programs that use multiple types of parallel processor. In this paper, we present a theory that allows pro ling for both time and space in heterogeneous parallel programs, while also allowing higher-order constructs on the GPU. We go on to show how this work could be useful in the eld of compiler optimizations for parallel languages that support CPU and GPU parallelism, and how it could be used to guide optimization and rewrite searches in compilers.
FusionInsight LibrA: Huawei's Enterprise Cloud Data Analytics Platform

Huawei Fusion Insight Libr A (FI-MPPDB) is a petabyte scale enterprise analytics platform developed by the Huawei data-base group. It started as a prototype more than five years ago, and is now being used by many enterprise customers over the globe, including some of the world's largest financial institutions. Our product direction and enhancements have been mainly driven by customer requirements in the fast evolving Chinese market. This paper describes the architecture of FI-MPPDB and some of its major enhancements. In particular, we focus on top four requirements from our customers related to data analytics on the cloud: system availability, auto tuning, query over heterogeneous data models on the cloud, and the ability to utilize powerful modern hardware for good performance. We present our latest advancements in the above areas including online expansion, auto tuning in query optimizer, SQL on HDFS, and intelligent JIT compiled execution. Finally, we present some experimental results to demonstrate the effectiveness of these technologies.
Developing a Scoring Model to Evaluate Project Management Software Packages Based on ISO/IEC Software Evaluation Criterion

Since the mid 1980s, an increasing number of project management software packages (PMSP) have appeared in the market to support project management organizations. Currently there are more than 500 software tools available. They vary widely both in their prices and capabilities. Despite the wide spread of PMSP, project-based organizations are left unguided as to how they should select the most appropriate software tool for their intended business use. The aim of this paper was to develop an evaluation/scoring module suitable for comparing different project management software packages to help select the most appropriate package. The evaluation model is based on the ISO/IEC evaluation criterion that takes into consideration all the necessary features and characteristics required in project management software. The evaluation model will provide software users and project organizations with a useful tool to compare various packages available in the market and select the best that suits their business needs.
The Role of Syntax During Pronoun Resolution: Evidence from fMRI

The current study examined the role of syntactic structure during pronoun resolution. We correlated complexity measures derived by the syntax-sensitive Hobbs algorithm and a neural network model for pronoun resolution with brain activity of participants listening to an audiobook during fMRI recording. Compared to the neural network model, the Hobbs algorithm is associated with larger clusters of brain activation in a network including the left Broca’s area.
Technologies for metadata management in scientific a

The use of Semantic Web technologies has been increasing, so it is common using them in different ways. This article evaluates how these technologies can contribute to improve the indexing in articles in scientific journals. Initially, there is a conceptual review about metadata. Later, studying the most important technologies for the use of metadata in Web and, this way, choosing one of them to apply it in the case of study of scientific articles indexing, in order to determine the metadata based in those used in impact research journals, and building a model for indexing scientific articles using Semantic Web technologies.
Habitat and Nest Site Selection in the Common Gull Larus canus in Southern Poland: Significance of Man-Made Habitats for Conservation of an Endangered Species

The Common Gull is a rare and endangered breeding species at inland habitats in Poland as well as in some other countries in Europe. Breeding biology, habitat and nest site selection were studied in this species in southern Poland. Almost all birds nested on industrial water bodies (gravel pits, sedimentation basins), although fishponds and reservoirs were the most abundant habitat in the study area. Birds built their nests mainly on islets, man-made constructions and dry land on the shores of water bodies. The islets occupied by birds were smaller and were covered by lower vegetation than the unoccupied ones. When occupied islets on industrial water bodies were compared with a random sample of islets on fishponds, the latter were found to be larger, with taller and denser vegetation. This may explain why Common Gulls did not breed on fishponds in southern Poland. Shore-breeding birds nested in open areas with sparse vegetation, occupying sites with less vegetation cover and closer to shrubs or trees than randomly selected points. Breeding performance (mean date of clutch initiation, clutch size, clutch volume, hatching success and breeding success) did not differ among nests built on islets, man-made constructions or on the shores of the water bodies. Breeding success was more than twice as high as in large riverine colonies. Industrial water bodies may become important alternative breeding habitats for this species in Poland.
PolarFS: An Ultra-low Latency and Failure Resilient Distributed File System for Shared Storage Cloud Database

PolarFS is a distributed file system with ultra-low latency and high availability, designed for the POLARDB database service, which is now available on the Alibaba Cloud. PolarFS utilizes a lightweight network stack and I/O stack in user-space, taking full advantage of the emerging techniques like RDMA, NVMe, and SPDK. In this way, the end-to-end latency of PolarFS has been reduced drastically and our experiments show that the write latency of PolarFS is quite close to that of local file system on SSD. To keep replica consistency while maximizing I/O throughput for PolarFS, we develop ParallelRaft , a consensus protocol derived from Raft, which breaks Raft's strict serialization by exploiting the out-of-order I/O completion tolerance capability of databases. ParallelRaft inherits the understand-ability and easy implementation of Raft while providing much better I/O scalability for PolarFS. We also describe the shared storage architecture of PolarFS, which gives a strong support for POLARDB.
Voltage Standardization of DC Distribution System for Residential Buildings

 Abstract—The renewable energy sources (RES) such as photovoltaic (PV) are basically DC power sources. In the present scenario, the integration of RES to power distribution infrastructure necessitates the DC-AC converter. Moreover the DC loads in the buildings is ever increasing with the use of CFL, LED, refrigerator, TV, fan, air conditioner, laptop, and other electronics in workplaces and homes. This forced to introduce the internal or external AC-DC converter to tie the DC load to AC distribution infrastructure of existing power system. This is further adding losses and complexity. This AC-DC converter stage can be reduces up to a certain level by DC distribution system (DCDS). Secondly the multi voltage rating of RES and DC load insists to introduce DC-DC converter in DCDS infrastructure. This will further add losses and complexity. In this paper a standard voltage level DCDS is proposed to minimize the system losses, complexity. To verify the simulated results in terms of building load and converter losses, a DCDS equipped with different energy sources like solar panel (PV), public utility (PU) and battery bank (BB) is compared with ACDS.
Learning Subjective Language : Feature Engineered vs . Deep Models

Treatment of subjective language is a vital component of a sentiment analysis system. However, detection of subjectivity (i.e., subjective vs. objective content) has attracted far less attention than sentiment recognition (i.s., positive vs. negative language). Particularly, online social context and the structural attributes of communication therein promise to help improve learning of subjective language. In this work, we describe successful models exploiting a rich and comprehensive feature set based on the structural and social context of the Twitter domain. In light of the recent successes of deep learning models, we also effectively experiment with deep gated recurrent neural networks (GRU) on the task. Our models exploiting structure and social context with an SVM achieve > 12% accuracy higher than a competitive baseline on a blind test set. Our GRU model yields even better performance, reaching 77.19 (i.e., ∼ 14.50% higher than the baseline on the same test set, p < 0.001).
A research review: how technology helps to improve the learning process of learners with dyslexia

Dyslexia is a language disorder that leads to difficulty with words and it is the most common type of learning disability. This study is a systematic review on the current state of technologies used in improving the learning process of learners with dyslexia. A total of twenty-five journals articles and international conference papers published between 2000 and 2014 were included in the review. The research articles were collected from twelve databases and being analyzed according to cyclical process. The findings show that majority of the studies focused on children and adolescents. There are four main research themes derived and discussed for the technologies used in the learning process of learners with dyslexia, namely, text-to-speech technologies, eye-tracking technologies, virtual learning environments, and games. Additionally, there are another four main research themes revolve around the purpose of the assistive technologies, namely, reading, writing, memory, and mathematics. Furthermore, text-to-speech technology is the most common technology used by learners with dyslexia. Moreover, a majority of the studies mention and focus the use of technologies on the improvement of reading in learners with dyslexia. This study is expected to provide a clearer view on the current state of technologies used in improving the learning process of learners with dyslexia.
HOG-based Pedestriant Detector Training

This paper describes how to train a pedestrian detection classifier based on HOG and how to use the training results to confgure the logiPDET IP core. logiPDET is HOG/SVM-based pedestrian detector optimized for Xilinx R ©devices. The core is developed for real-time vision-based embedded applications such as Automotive Driving Assistance. The algorithm follows a discriminative approach combining a HOG descriptor and a SVM classifier. logiPDET is a configurable detector suitable for different classes of objects. Pedestrian is just the most popular example. The training process presented in this paper is valid in general, for different objects, and not only to train the logiPDET IP core. An example of C++ source code for training the pedestrian detector is also provided. The IP core is sourced from eVS embedded Vision Systems Srl and is part of the logicBRICKS IP core library provided by Xylon doo. It can be evaluated on the logiADAK Automotive Driving Assistance Kit . It is a Xilinx Zynq-7000 All Programmable SoC based development platform for advanced vision-based automotive Driver Assistance (DA) applications. For more information about the logiPDET and logiADAK visit http://www.logicbricks. com/.
LIVING WITH THE ENEMY: JUMPING SPIDERS THAT MIMIC WEAVER ANTS

Abstract Ants prey on salticids, and encounters with weaver ants (Oecophylla smaragdina (Fabricius 1775)) appear to be especially dangerous for many salticids. In the Philippines, Myrmarachne assimilis Banks 1930 is a salticid that mimics Oecophylla smaragdina. We tested for the abilities of four categories of salticids, plus M. assimilis, to survive in the proximity of weaver ants. The four categories were: (1) myrmecomorphic (ant-like species other than M. assimilis); (2) myrmecophagic (ant-eating species); (3) myrmecophilic (a species that is either myrmecophagic nor myrmecophagic, but is known to associate with ants) and (4) ordinary (species that are neither ant-like nor ant-eating, and are not known to associate with ants). The hypothesis investigated here is that M. assimilis has, compared with other salticids, especially pronounced ability to survive in close proximity with this particular ant species. The individual salticids used in our experiments had not had previous contact with weaver ants or any other ants. When confined with groups of 10 weaver ants, the myrmecomorphic, myrmecophagic and myrmecophilic species survived significantly more often than ordinary salticids, but Myrmarachne assimilis survived significantly more often than all other categories. When kept with groups of 20 ants, there was a proportional decrease in the number of salticids that survived within each salticid category. However, few salticids survived when confined with groups of 40 ants, regardless of category.
A Method for Constructing Open-Domain Chinese Entity Hypernym Hierarchical Structure

Entity relation is an essential component of some famous knowledge bases, such as Freebase, Yago and Knowledge Graph, while the hyponymy plays an important role in entity relations that show the relationship between the more general terms (hypernyms) and the more specific instances of the terms (hyponyms). In this paper, we present a comprehensive scheme of open⁃domain Chinese entity hypernym hierarchical construction. Some of the most important unsupervised and heuristic approaches for building hierarchical structure are covered in sufficient detail along with reasonable analyses. We experimentally evaluate the proposed methods and com⁃ pare them with other baselines. The result shows high preci⁃ sion of our method and the proposed scheme will be further improved with larger scale corpora.
Skill-biased technological knowledge without scale effects

In the skill-biased technological change literature, the technological-knowledge bias, which drives wage inequality, is determined by the market-size channel. Motivated by the literature on scale effects since Jones (1995a, b), the standard R&D technology is modified so that wage inequality results similarly from the technological-knowledge bias, which is instead induced by the price channel. Thus, by solving the transitional dynamics numerically, it is shown that the recent rise of the skill premium, which is highlighted by, e.g., Acemoglu (2002a), arises from the price-channel effect, complemented with a mechanism that can be called technological-knowledge-absorption effect.
Population dynamics of the common shrew and pygmy shrew (Soricomorpha: Soricidae) in a clear-cut of a mixed forest in eastern Lithuania

Population dynamics (density, age structure, and sex ratio) of Sorex araneus and S. minutus was studied in late summers of 1987-1993 during small mammal community formation in a growing-up clear-cut area within a mixed forest in eastern Lithuania (Molėtai District; 55°09' N, 25°20' E). In the studied area the density of the common shrew was significantly greater and its multi-annual variation in density was more stable compared with the pygmy shrew (18.64 ± 2.49 and 5.57 ± 2.75 ind./ha, p < 0.0017; s = 0.258 and s = 0.625, respectively). Changes in the age structure (subadults/adults) and sex ratio of both shrew species correlated with density variations.
Is photosynthesis limited by decreased Rubisco activity and RuBP content under progressive water stress?

• Whether decreases in Rubisco activity and the availability of ribulose-1,5-bisphosphate (RuBP) regeneration are responsible for drought-induced depression of photosynthesis is under debate. • Here, leaf water potential and relative water content, gas exchange, chlorophyll fluorescence, initial and total Rubisco activity and RuBP content were determined during the time course of drought development in five C3 species: Rhamnus alaternus, Rhamnus ludovici-salvatoris, Nicotiana sylvestris, Phaseolus vulgaris and Vitis vinifera. Water was withheld until photosynthesis approached zero (between 6 and 12 d depending on the species). • Relative water content and water potential progressively dropped with drought in Rhamnus and Vitis, but not in the other two species. While RuBP content and Rubisco activity remained constant, declining eventually only in the more severe drought situations, light-saturated stomatal conductance (gs ) and photosynthesis (AN ) decreased progressively during drought in all species. This strongly suggests a dominant role of decreased gs in photosynthesis downregulation during drought in these species, which is supported by increased electron transport to AN ratio. • It is concluded that impairment of Rubisco activity and RuBP content do not limit photosynthesis until drought is very severe. Moreover, the relative water content at which these mechanisms are impaired is strongly species-dependent.
Deep Learning Systems for Estimating Visual Attention in Robot-Assisted Therapy of Children with Autism and Intellectual Disability

Recent studies suggest that some children with autism prefer robots as tutors for improving their social interaction and communication abilities which are impaired due to their disorder. Indeed, research has focused on developing a very promising form of intervention named Robot-Assisted Therapy. This area of intervention poses many challenges, including the necessary flexibility and adaptability to real unconstrained therapeutic settings, which are different from the constrained lab settings where most of the technology is typically tested. Among the most common impairments of children with autism and intellectual disability is social attention, which includes difficulties in establishing the correct visual focus of attention. This article presents an investigation on the use of novel deep learning neural network architectures for automatically estimating if the child is focusing their visual attention on the robot during a therapy session, which is an indicator of their engagement. To study the application, the authors gathered data from a clinical experiment in an unconstrained setting, which provided low-resolution videos recorded by the robot camera during the child–robot interaction. Two deep learning approaches are implemented in several variants and compared with a standard algorithm for face detection to verify the feasibility of estimating the status of the child directly from the robot sensors without relying on bulky external settings, which can distress the child with autism. One of the proposed approaches demonstrated a very high accuracy and it can be used for off-line continuous assessment during the therapy or for autonomously adapting the intervention in future robots with better computational capabilities.