Miracle-dz/UniFAR-FTUs huggingface dataset:
Rack-Scale Memory Pooling for Datacenters

The rise of web-scale services has led to a staggering growth in user data on the Internet. To transform such a vast raw data into valuable information for the user and provide quality assurances, it is important to minimize access latency and enable in-memory processing. For more than a decade, the only practical way to accommodate for ever-growing data in memory has been to scale out server resources, which has led to the emergence of large-scale datacenters and distributed non-relational databases (NoSQL). Such horizontal scaling of resources translates to an increasing number of servers that participate in processing individual user requests. Typically, each user request results in hundreds of independent queries targeting different NoSQL nodes - servers, and the larger the number of servers involved, the higher the fan-out. To complete a single user request, all of the queries associated with that request have to complete first, and thus, the slowest query determines the completion time. Because of skewed popularity distributions and resource contention, the more servers we have, the harder it is to achieve high throughput and facilitate server utilization, without violating service level objectives. This thesis proposes rack-scale memory pooling (RSMP), a new scaling technique for future datacenters that reduces networking overheads and improves the performance of core datacenter software. RSMP is an approach to building larger, rack-scale capacity units for datacenters through specialized fabric interconnects with support for one-sided operations, and using them, in lieu of conventional servers (e.g. 1U), to scale out. We define an RSMP unit to be a server rack connecting 10s to 100s of servers to a secondary network enabling direct, low-latency access to the global memory of the rack. We, then, propose a new RSMP design - Scale-Out NUMA that leverages integration and a NUMA fabric to bridge the gap between local and remote memory to only 5× difference in access latency. Finally, we show how RSMP impacts NoSQL data serving, a key datacenter service used by most web-scale applications today. We show that using fewer larger data shards leads to less load imbalance and higher effective throughput, without violating applications? service level objectives. For example, by using Scale-Out NUMA, RSMP improves the throughput of a key-value store up to 8.2× over a traditional scale-out deployment.
Maximizing Warung Tegal Profit with Branch and Bound Algorithm Wenny Yustalim

Choosing the raw ingredients in order to satisfy customers’ demand in a Warung Tegal needs several points of consideration. In business, the most important principle is extracting the maximum revenue out of the minimum expenses. But in order to maintain the sustainability of a warteg, one should never neglect the basic requirements that the customers should receive. We should not close our eyes towards the fullfilment of nutrition, especially coming from Warung Tegal, one of the most commonly found food station in our countries. This paper discusses the algorithmic strategy implemented in choosing the most profitable yet nutritionally balanced ingredients for Warung Tegal all around our beloved country. Keywords—Branch and Bound; Knapsack; maximum profit; warung Tegal.
AN ANALYSIS OF SYSTEM CALLS USING J 48 AND JRIP FOR MALWARE DETECTION

The evolution of malware possesses serious threat ever since the concept of malware took root in the technology industry. The malicious software which is specifically designed to disrupt, damage, or gain authorized access to a computer system has made a lot of researchers try to develop a new and better technique to detect malware but it is still inaccurate in distinguishing the malware activities and ineffective. To solve the problem, this paper proposed the integrated machine learning methods consist of J48 and JRip in detecting the malware accurately. The integrated classifier algorithm applied to examine, classify and generate rules of the pattern and program behaviour of system call information. The outcome then revealed the integrated classifier of J48 and JRip outperforming the other classifier with 100% detection of attack rate.
Determination of Glycemic Indices ( GI ) , Glycemic Load ( GI ) and Proximate Analysis of unripe Plantain ( Musa paradisiaca ) and Cocoyam ( Colocasia esculenta )

The results of the present study show the glycemic index GI values calculated using the trapezoidal rule, of fried plantain, boiled plantain, roasted plantain, fried cocoyam, boiled cocoyam and roasted cocoyam were 88.8, 96.5, 92.0, 88.5, 97.3 and 80.0, respectively. Maximum values (96.5 and 97.3) was recorded for boiled plantain and boiled cocoyam while minimum GI (80) was recorded for roasted cocoyam. As evident, most of these foods have a high GI value (i.e., GI=70 0r more). The glycemic load GL values of fried plantain, boiled plantain, roasted plantain, fried cocoyam, boiled cocoyam and roasted cocoyam were 44.4, 48.25, 46.0, 44.25, 48.65 and 40, respectively. The maximum value (48.65) was recorded for Boiled cocoyam while minimum glycemic load (40) was recorded for Roasted cocoyam. These data indicate that all the cereal foods investigated in current study have high GI and GL. The incremental area under the curve (iAUC) of samples showed values as; glucose (3.75), fried plantain (3.33), boiled plantain (3.62), roasted plantain (3.45), fried cocoyam (3.32), boiled cocoyam (3.65), and roasted cocoyam (3.00). Results also show the glycemic load GL of the pulses. The mean of the glycemic index for fried plantain (44.4), boiled plantain (48.25), roasted plantain (46.0), fried cocoyam (44.25), boiled cocoyam (48.65) and roasted cocoyam (40).
Early Paleozoic brachiopod larva: true larva, not a juvenile

The ontogeny of extinct brachiopods is often reconstructed from specimens with well-preserved juvenile shells. However, paleontological reconstructions based on the fossil material contradict the reconstruction of the evolution of brachiopod life cycles based on the analysis of the ontogeny of recent brachiopods. If the paleontological reconstructions suggest a planktotrophic stage with a shell as the initial type of the brachiopod ontogeny, the biologists suppose true planktotrophic larva to be the basic stage of the brachiopod life cycles. In the present paper, the paleontological data are considered in correspondence with the data on the different developmental stages of recent brachiopods. The large size and presence of the impressions of larval setal sacks are interpreted as evidence of the stage of true planktotrophic larva in the ontogeny of the Early Paleozoic brachiopods. How to cite this article: Madison A.A. , Kuzmina T.V. 2019. Early Paleozoic brachiopod larva: true larva, not a juvenile // Invert. Zool. Vol.16. No.1. P.41–47. doi: 10.15298/ invertzool.16. 1.05
APPLIED 11 , 014009 ( 2019 ) Digital Coherent Control of a Superconducting Qubit

High-fidelity gate operations are essential to the realization of a fault-tolerant quantum computer. In addition, the physical resources required to implement gates must scale efficiently with system size. A longstanding goal of the superconducting qubit community is the tight integration of a superconducting quantum circuit with a proximal classical cryogenic control system. Here we implement coherent control of a superconducting transmon qubit using a single-flux quantum (SFQ) pulse driver cofabricated on the qubit chip. The pulse driver delivers trains of quantized flux pulses to the qubit through a weak capacitive coupling; coherent rotations of the qubit state are realized when the pulse-to-pulse timing is matched to a multiple of the qubit oscillation period. We measure the fidelity of SFQ-based gates to be approximately 95% using interleaved randomized benchmarking. Gate fidelities are limited by quasiparticle generation in the dissipative SFQ driver. We characterize the dissipative and dispersive contributions of the quasiparticle admittance and discuss mitigation strategies to suppress quasiparticle poisoning. These results open the door to integration of large-scale superconducting qubit arrays with SFQ control elements for low-latency feedback and stabilization.
Creating the best development corpus for Statistical Machine Translation systems

We propose and study three different novel approaches for tackling the problem of development set selection in Statistical Machine Translation. We focus on a scenario where a machine translation system is leveraged for translating a specific test set, without further data from the domain at hand. Such test set stems from a real application of machine translation, where the texts of a specific e-commerce were to be translated. For developing our development-set selection techniques, we first conducted experiments in a controlled scenario, where labelled data from different domains was available, and evaluated the techniques both with classification and translation quality metrics. Then, the bestperforming techniques were evaluated on the e-commerce data at hand, yielding consistent improvements across two language directions.
A mobile world made of functions

We are currently living in a world dominated by mobile apps and connected devices. State-of-the-art mobile phones and tablets use apps to organize knowledge and information, control devices, and/or complete transactions via local, web, and cloud services. However, users are challenged to select a suite of apps, from the millions available today, that is right for them. Apps are increasingly differentiated only by the user experience and a few specialized functions; therefore, many apps are needed in order to cover all of the services a specific user needs, and the user is often required to frequently switch between apps to achieve a specific goal. User experience is further limited by the inability of apps to effectively interoperate, since relevant user data are often wholly contained within the app. This limitation significantly undermines the continuous (function) flow across apps to achieve a desired goal. The result is a disjointed user experience requiring app switching and replicating data among apps. With these limitations in mind, it appears as if the current mobile experience is nearing its full potential but failing to leverage the full power of modern mobile devices. In this paper, we present a vision of the future where apps are no longer the dominant customer interaction in the mobile world. The alternative that we propose would “orchestrate” the mobile experience by using a “moment-first” model that would leverage machine learning and data mining to bridge a user's needs across app boundaries, matching context, and knowledge of the user with ideal services and interaction models between the user and device. In this way, apps would be employed at a function level, while the overall user experience would be optimized, by liberating user data outside of the app container and intelligently orchestrating the user experience, to fulfill the needs of the moment. We introduce the concept of a functional entry-point and apply the simple label “FUNN” to it (which was named “FUNC” in (Wang, 2014)). We further discuss how a number of learning models could be utilized in building this relationship between the user, FUNN, and context to enable search, recommendations and presentation of FUNNs through a multi-modal human–machine interface that would better fulfill users' needs. Two examples are showcased to demonstrate how this vision is being implemented in home entertainment and driving scenarios. In conclusion, we envision moving forward into a FUNN-based mobile world with a much more intelligent user experience model. This in turn would offer the opportunity for new relationships and business models between software developers, OS providers, and device manufacturers.
Evolutionary relationships among squids of the family Gonatidae (Mollusca: Cephalopoda) inferred from three mitochondrial loci

The oceanic squid family Gonatidae (Mollusca: Cephalopoda) is widely distributed in subpolar and temperate waters, exhibiting behavioral and physiological specializations associated with reproduction. Females of several species undergo muscular degeneration upon maturation; origins of this complex morphogenic change are unknown, hindering our understanding of ecological and morpho-physiological adaptations within the family. To provide further information regarding the evolutionary relationships within Gonatidae, three mitochondrial loci (12S rRNA, 16S rRNA, and cytochrome c oxidase subunit I) were analyzed for 39 individuals representing fourteen gonatid and six outgroup cephalopod species. In addition to elucidating relationships among gonatids, molecular data provided more information than morphological data for problematic specimens. Although some data sets are incongruent or have low nodal support values, combined molecular analysis conWrms the presence of gonatid groups previously established by morphological characteristics (i.e., possessing radular teeth in seven longitudinal rows and muscular mantle tissue). These characteristics are basal to taxa possessing radular teeth in Wve longitudinal rows and less muscular mantle tissue, indicating that the derived forms are those species exhibiting physiological adaptation such as tissue degeneration upon maturation and egg brooding.  2005 Elsevier Inc. All rights reserved.
Feature Extraction for Non-frontal Faces

One of the most challenge tasks in building a face recognition system is how to represent and extract good quality features from face images. The difficulties come from variations in head poses, illumination conditions, and facial expression. Although many researches have been done, most were carried on under constrained environments. Most researches concentrated on dealing with frontal faces. Processing non-frontal faces encounters more challenge because some features on faces become occluded dramatically. In this paper, we propose two models to extract features from non-frontal faces in the range of 30o to 90o. First, we use the Viola-Jones detection method to identify the pose of face images. Then, we use Active Appearance Model (AAM) to interpret face images. Lastly, the models are trained to know how to fit new images. To improve the efficiency of fitting, we apply a nonlinear parameter update method. Experimental results show that using nonlinear fitting for non-frontal can increase the accuracy of the AAM fitting, compared with some previous methods.
Leadership in Startups

This article outlines a model of when, why, and how founder-CEOs’ leadership behavior influences startup performance. The model is tested using a sample of 102 startups and their founder-CEOs, and feedback from 372 employees, rating their founder-CEOs’ leadership behavior. The results indicate that transformational leadership has a significant positive effect on startup performance. For transactional leadership as well as laissez-faire leadership no significant direct effects on startup performance were found. Furthermore, the size of the startup has a significant positive moderating effect on the relationship between laissez-faire leadership and startup performance, as well as a significant positive moderating effect on the relationship between the transactional leadership dimension management by exception and startup performance.
Cutting stock waste reduction using genetic algorithms CONFERENCE

A new model for the One-dimensional Cutting Stock problem using Genetic Algorithms (GA) is developed to optimize construction steel bars waste. One-dimensional construction stocks (i.e., steel rebars, steel sections, dimensional lumber, etc.) are one of the major contributors to the construction waste stream. Construction wastes account for a significant portion of municipal waste stream. Cutting one-dimensional stocks to suit needed project lengths results in trim losses, which are the main causes of one-dimensional stock wastes. The model developed and the results obtained were compared with real life case studies from local steel workshops. Cutting schedules produced by our new GA model were tested in the shop against the current cutting schedules. The comparisons show the superiority of this new GA model in terms of waste minimization.
EVALUATION OF DECELLULARIZED PORCINE AORTIC VALVES : MATRIX CHANGES DUE TO DIFFERENT DECELLULARIZATION METHODS

Background Several decellularisation techniques have been developed to produce acellular matrix scaff olds for the purpose of tissue engineering, mostly comprising (non-)ionic detergents or enzymatic extraction methods. However, the eff ect of chemically induced decellularisation on the major structural and adhesion molecules as well as glycosaminoglycans, and the possible replenishment of lost compounds has escaped attention. Methods Porcine aortic valves were treated with two diff erent methods: detergent Triton X-100 and enzymatic Trypsine cell extraction. (Immuno-) histochemistry was used to address changes in extracellular matrix constitution (elastin, collagen, glycosaminoglycans, chondroitin sulfate, fi bronectin and laminin) and the production of extracellular matrix components by seeded endothelial cells. Results The Trypsine treated group showed a fragmentation and distortion of elastic fi bers. Changes in collagen distribution were observed in both groups. An almost complete washout of glycosaminoglycans and chondroitin sulfate was observed in the Triton and Trypsin treated group, but the latter with a smaller glycosaminoglycans reduction. Both treatments resulted in a considerable washout of the adhesion molecules laminin and fi bronectin. Furthermore, seeded endothelial cells were capable of synthesizing laminin, fi bronectin and chondroitin sulfate. Conclusions Chemically induced decellularisation by Triton or Trypsine resulted in changes in the extracellular matrix constitution, which could lead to problems in valve functionality and cell growth and migration. Seeded endothelial cells were capable of synthesizing extracellular matrix components lost by cell extraction. Further studies on tissue engineering should focus more on the eff ect of chemically induced cell extraction on the extracellular matrix of the remaining scaff old and the in vitro or in vivo replenishment of lost compounds.
THREE-DIMENSIONAL VELOCITY STRUCTURE OF UPPER MANTLE BENEATH THE ALPINE-HIMALAYAN OROGEN

Upper mantle beneath the Alpine-Himalayan orogen (AHO) at depths from 100 to 500 km has been studied using ITS inversion of teleseismic P travel times from earthquakes that occurred in the region and were recorded by the worldwide seismological network (ISC bulletins). 3D velocity maps were obtained as a sum of independent inversions in about sixty overlapping blocks 600–1000 km across. This approach is similar to high-frequency spatial filtration and provides a much higher resolution than the global tomography. High-velocity zones within the orogen have been interpreted as signature of continental or oceanic lithosphere sinking to the upper mantle under active regional compression. The maps show well pronounced traces of subduction in the regions of Cretan arc, Hindukush, and Burma, also confirmed by independent data, as well as other less certain evidence of subduction. Positive anomalies in the western part of the orogen are attributed to subduction in the area of Cyprus and along the Caucasus—Kopet Dagh—Lut belt. The lithosphere of the Indian plate subducted beneath the Himalayas and Tibet has a rather complicated structure. Zones of sinking lithosphere are traceable around the Tarim block. Distinct low-velocity anomalies in Mongolia, Tibet, and Southern Caspian basin may be produced by active mantle plumes. Three-dimensional velocity structure, upper mantle, collision, subduction, plume, Alpine-Himalayan orogen
Helicopter Teleoperation for Aerial Monitoring in the COMETS Multi-UAV System

This paper presents a helicopter teleoperation system and its integration in the COMETS multi-UAV system. COMETS (http://www.comets-uavs.org) is a project funded by the European Commission in the IST programme. The project will be demonstrated in forest fire detection and monitoring. Moreover results and video demonstration of the experiments carried out in May 2003, at Gestosa (near Coimbra, Portugal) involving monitoring of forest fires are also included.
UML 2 ALLOY : A TOOL FOR LIGHTWEIGHT MODELLING OF DISCRETE EVENT SYSTEMS

Alloy is a textual language developed by Daniel Jackson and his team at MIT. It is a formal language, which has a succinct syntax and allows specification and automatic analysis of a wide variety of systems. On the other hand, the Unified Modelling Language (UML) is a semi-formal language, which is accepted by the software engineering community as the defacto standard for modelling, specification and implementation of Object based systems. This paper studies the integration of the UML and Alloy into a single CASE tool, which aims to take advantage of the positive aspect of both the UML and Alloy. Alloy and UML specification provide two views of the system. In order to synchronise the two views, we make use of the MDA style transformation. In particular, we shall present a Meta Object Facility (MOF) compliant metamodel for Alloy and define a model transformation from the UML metamodel to the Alloy metamodel. Based on the approach presented in the paper, we have implemented a tool called UML2Alloy for the modelling and analysis of Discrete Event Systems. To evaluate the tool, the paper presents a case study involving the modelling and analysis of a prototype manufacturing system.
Estimating Tie Strength in Follower Networks to Measure Brand Perceptions

As public entities like brands and politicians increasingly rely on social media to engage their constituents, analyzing who follows them can reveal information about how they are perceived. Whereas most prior work considers following networks as unweighted directed graphs, in this paper we use a tie strength model to place weights on follow links to estimate the strength of relationship between users. We use conversational signals (retweets, mentions) as a proxy class label for a binary classification problem, using social and linguistic features to estimate tie strength. We then apply this approach to a case study estimating how brands are perceived with respect to certain issues (e.g., how environmentally friendly is Patagonia perceived to be? ). We compute weighted follower overlap scores to measure the similarity between brands and exemplar accounts (e.g., environmental non-profits), finding that the tie strength scores can provide more nuanced estimates of consumer perception.
Structured sparsity : towards a “ deep ” understanding

Although of proven interest for decomposition algorithms, structures in sparse representations are rarely known in practice. In this work, we propose to model structures through so-called restricted Boltzmann machines, for which efficient learning algorithms exist. The model is then exploited into a variational Bayesian procedure. The approach is shown to present a good behavior with regard to its nonstructured counterpart.
LOCAL ADAPTIVE BIVARIATE SHRINKAGE WITH REDUCED SENSITIVITY

The performance of image denoising algorithms using the Double Tree Complex Wavelet Transform, DTCWT, followed by a local adaptive bishrink filter can be improved by reducing the sensitivity of that filter with the local marginal variance of the wavelet coefficients. In this paper is proposed a solution for the sensitivity reduction based on enhanced diversity. The solution proposed in this paper will be used for the denoising of SONAR images and will be included into the soft SONARSCOPE, in construction at IFREMER-Brest and in evaluation at ENST-Bretagne and “Politehnica” University Timisoara.