Miracle-dz/UniFAR-FTUs huggingface dataset:
Clock-Gating in FPGAs: A Novel and Comparative Evaluation

Clock-gating has been employed in low-power FPGA designs based on an emulated and compromised method. So far in literature the actual efficiency of savings in power consumption is not thoroughly studied for this method. In this paper we evaluated the clock-gating technique in FPGAs, based on a novel and comparative process. For a set of design cases, both the FPGA and ASIC clock-gating methods were implemented. Figures of power consumption were obtained using the corresponding FPGA/ASIC power estimation tools and devices. The results show that in FPGAs, the efficiency of savings in dynamic power consumption is about 50% to 80% of its ASIC counterparts. However, we also found that compared to ASICs, clock-gating for FPGAs in terms of the efficiency of savings in total average power consumption was only about 6% to 30% of its ASIC counterparts due to FPGA's large static power consumption
Detecting Revelation of Private Information on Online Social Networks

Online social networks are being used by more and more people. While they enable rich communication, they cause privacy problems. One problem that has not been previously researched is the revelation of private information on blogs and comment parts of online social networks. This paper describes a new disclosure control system for natural language information that automatically checks blogs and comments uploaded onto online social networks, detects words that might reveal private information, and modifies the text by replacing the problematic words with more abstract words so that it no longer reveals the private information. The granularity of the proposed disclosure control is not the text but each word in it. Consequently, it is not tiresome for the user and balances the protection of privacy with the enjoyment of communication.
BitMat – Scalable Indexing and Querying of Large RDF Graphs ( Technical Report )

The growing size of Semantic Web data expressed in the form of Resource Description Framework (RDF) has made it necessary to develop effective ways of storing this data to save space and to query it in a scalable manner. SPARQL – the query language for RDF data – closely follows SQL syntax. As a natural consequence most of the RDF storage and querying engines are based on modern database storage and query optimization techniques. Previous work has tried to use vertical partitioning using column stores (C-Store, MonetDB) and 6-way indexing (RDF-3X, Hexastore) for storage and querying of RDF data. Although these approaches perform well for highly selective queries, for queries having low-selectivity triple patterns, scalability of the querying method and optimizations still remain a challenge. In this paper we present a new way of storing RDF graphs in run-length-encoded bit-vector format called BitMat, and we propose a novel two-phase SPARQL join query processing algorithm. In the first phase it prunes the candidate RDF triples, and in the next phase, it stitches the pruned RDF triples together to generate final results. Our query processing method does not build intermediate join tables and works directly on the compressed data. Our evaluation shows that BitMat not only provides an efficient method of storage of the RDF graphs, but our join query processing algorithm scales well for low-selectivity join queries, where state-of-the-art RDF query processors face problems.
Screening Genetic Resources of Capsicum Peppers in Their Primary Center of Diversity in Bolivia and Peru

For most crops, like Capsicum, their diversity remains under-researched for traits of interest for food, nutrition and other purposes. A small investment in screening this diversity for a wide range of traits is likely to reveal many traditional varieties with distinguished values. One objective of this study was to demonstrate, with Capsicum as model crop, the application of indicators of phenotypic and geographic diversity as effective criteria for selecting promising genebank accessions for multiple uses from crop centers of diversity. A second objective was to evaluate the expression of biochemical and agromorphological properties of the selected Capsicum accessions in different conditions. Four steps were involved: 1) Develop the necessary diversity by expanding genebank collections in Bolivia and Peru; 2) Establish representative subsets of ~100 accessions for biochemical screening of Capsicum fruits; 3) Select promising accessions for different uses after screening; and 4) Examine how these promising accessions express biochemical and agromorphological properties when grown in different environmental conditions. The Peruvian Capsicum collection now contains 712 accessions encompassing all five domesticated species (C. annuum, C. chinense, C. frutescens, C. baccatum, and C. pubescens). The collection in Bolivia now contains 487 accessions, representing all five domesticates plus four wild taxa (C. baccatum var. baccatum, C. caballeroi, C. cardenasii, and C. eximium). Following the biochemical screening, 44 Bolivian and 39 Peruvian accessions were selected as promising, representing wide variation in levels of antioxidant capacity, capsaicinoids, fat, flavonoids, polyphenols, quercetins, tocopherols, and color. In Peru, 23 promising accessions performed well in different environments, while each of the promising Bolivian accessions only performed well in a certain environment. Differences in Capsicum diversity and local contexts led to distinct outcomes in each country. In Peru, mild landraces with high values in health-related attributes were of interest to entrepreneurs. In Bolivia, wild Capsicum have high commercial demand.
The Pins that Bind: Content Appropriation, Social Norms, and Networks on Pinterest

This study investigates how online content appropriation is affected by the content type and the social environment, i.e., the norms imposed by the website, and the social relationships. My analysis uses Pinterest data from April and November 2012 with a differences-in-differences methodology to uncover that 1) content that breaches the site’s social etiquette receives is less widely adopted, and 2) the content adoption spillovers from breaching the social etiquette differ for the general public and users’ social network neighbors. This study has implications for our understanding of content adoption and the construction of user profiles in the presence of website etiquette and social network relationships.
International Journal of Innovative Research in Computer and Communication Engineering a Power -balancing Approach for Coverage Time Optimization in Clustered Networks

The rapid transition to nano scale ICs has led to the integration of high performance processors and high speed, digital wireless communication circuits. For a large WSN (Wireless Sensor Network), sensors are often hierarchically organized into clusters, each having its own cluster head (CH). Within a cluster, sensors transmit data to their CH, which in turn forwards the data to the sink, either directly or through a multi hop path through other intermediate CHs. The coverage time of the network is defined as the time until one of the CHs runs out of battery, resulting in an incomplete coverage of the sensing region. The maximization of the coverage time for a clustered wireless sensor network by optimal balancing of power consumption among cluster heads (CHs). Clustering significantly reduces the energy consumption of individual sensors, but it also increases the communication burden on CHs. To investigate this tradeoff, the analytical model incorporates both the intra and the inter cluster traffic. Using a Rayleigh fading channel model for inter-cluster communications, we provide optimal power allocation strategies that guarantee (in a probabilistic sense) an upper bound on the end-to-end (inter-CH) path reliability. Our allocation strategies account for the interaction between routing and clustering by considering the impacts of intra-and inter-cluster traffic at each CH. Two mechanisms are proposed for achieving balanced power consumption: the routing-aware optimal cluster planning and the clustering-aware optimal random relay. For both mechanisms, the problem is formulated as a signomial optimization, which can be efficiently solved using generalized geometric programming. I. INTRODUCTION Recent technological advances in micro-electronic-mechanics (MEMs) and the low-power wireless communications have paved the way for the deployment of dense wireless sensor networks (WSNs). Such networks are expected to play an important role in a wide range of applications, including motion detection, environment monitoring, military surveillance and reconnaissance, etc. [1]. Mass production of low-cost sensors necessitates powering them with limited-energy, often non-rechargeable batteries [2]. This makes energy consumption a critical factor in the design of a WSN and calls for energy-efficient communication protocols that maximize the lifetime of the network subject to a given energy budget. In this paper, we investigate the maximization of the coverage time for a clustered wireless sensor network by optimal balancing of power consumption among cluster heads (CHs). Clustering significantly reduces the energy consumption of individual sensors, but it also increases the communication burden on CHs. For this, our analytical models incorporate …
Automatic speech recognition experiments with articulatory data

In this paper we investigate the use of articulatory data for speech recognition. Recordings of the articulatory movements originate from the MOCHA corpus, a database which contains speech, EGG, EMA and EPG recordings. It was found that in a Hidden Markov Model (HMM) based recognition framework careful processing of these signals can yield significantly better performance than that obtained by decoding of the acoustic signals. We present detailed results on the processing of the signals and the associated performance of monophone and triphone systems. Experimental evidence shows that acoustic-signal-to-word mappings and articulatory-signal-to-word mappings are equally complex. However, for the latter, evidence of short-comings of standard HMM based modelling is visible and should be addressed in future systems.
Restricted 132-Involutions and Chebyshev Polynomials

We study generating functions for the number of involutions in $S_n$ avoiding (or containing once) 132, and avoiding (or containing once) an arbitrary permutation $\tau$ on $k$ letters. In several interesting cases the generating function depends only on $k$ and is expressed via Chebyshev polynomials of the second kind. In particular, we establish that involutions avoiding both 132 and $12. k$ have the same enumerative formula according to the length than involutions avoiding both 132 and any {\em double-wedge pattern} possibly followed by fixed points of total length $k$. Many results are also shown with a combinatorial point of view.
Towards Building Flexible and Reliable Electronic Commerce Systems � A Distributed Transactional Activity Approach

In electronic commerce over the Internet business transactions are fre quently long duration activities exhibit complex interaction dependencies and are prone to failures or unpredictable situations As an adaptive en gineering approach to developing exible and reliable electronic commerce systems we present the distributed transactional activity model TAM in this paper and report our experience in designing and implementing TAM A distinct feature of this approach is the utilization of a family of dynamic activity restructuring operations that allow ongoing transactional activi ties to bypass some unexpected execution bottlenecks and the notion of validity that provides correctness guarantees for the activity restructuring operations Another advantage of TAM is its facilities that help business process designers to deal with business structure changes adaptively and incrementally Our implementation method is based on component tech nology and using plug in adaptors on top of commercial OLTP systems We argue that TAM its dynamic activity restructuring operations and our implementation method together provide a viable and practical foundation towards e ectively building and e ciently managing electronic commerce applications
Policy-Based Data Downgrading: Toward a Semantic Framework and Automated Tools to Balance Need-to-Protect and Need-to-Share Policies

We describe a new paradigm for articulating need-to-protect and need-to-share policies that shows promise for enabling automated derivation of the downgrading rulesets needed to comply with these policies in systems that share data. This new paradigm is based on fine-grained semantic policy specifications in terms of context, content, Purpose, and Anti-purpose that are expressed in a machine-understandable language. Our approach is based on an existing reasoning capability that can handle simple downgrading cases. Extensions to handle more complex cases are discussed. Although not yet a complete, turnkey solution to the overall data sharing and privacy problem, we posit that our approach provides an auspicious research vector for future work towards achieving that goal.
Policy Processing: Don't Take it for Granted

The new advanced services and limitations of current Internet have driven a lot of initiatives in architectures for Future Internet. Ambient Networks is one of these initiatives, focused in providing a seamless cooperation of resources in an environment with a multitude of access technologies, network operators and business actors. There are many efforts using Policy based Management as a practical solution for addressing the challenges for the management of Future Internet such as cross-domain management, integration and manipulation of data across the world, seamless mobility, reliability, performance and heterogeneity support. However, not much attention has been given to the policy processing itself. In this paper we present our policy processing system, currently used in the PBMAN project, a policy based management architecture and prototype for Ambient Networks. The primary contribution of this paper is to give real attention to the components of policy systems that can determine its performance as well as its successful adoption.
Practical User Identification for Masquerade Detection

Masquerade detection discovers suspicious activities in a computer system by creating userspsila normal profiles, then raising an alert when the audited behavior does not fit. We propose to apply the SVM algorithm to the concurrently employed patterns that have been weighted according to their frequencies in order to identify masquerading attacks. Our approach not only reduces the complexity of the system but also is more robust in controlling noisy instances of the audited behavior.
FREE ENERGY STUDIES OF FREEZING IN SLIT PORES : AN ORDER-PARAMETER APPROACH USING MONTE CARLO SIMULATION

We report a molecular simulation study of freezing transitions for simple fluids in narrow slit pores. A major stumbling block in previous studies of freezing in pores has been the lack of any method for calculating the free energy difference between the confined solid and liquid phases. Conventional thermodynamic integration methods often fail for confined systems, due to the difficulty in choosing a suitable path of integration. We use a different approach that involves calculating the Landau free energy as a function of a suitable order parameter, using the grand canonical Monte Carlo simulation method. The grand free energy for each phase can then be obtained by one-dimensional integration of the Landau free energy over the order parameter. These calculations are carried out for two types of wall—fluid interaction, a hard wall and a strongly attractive wall modelled on carbon. The grand free energy results for both cases clearly indicate a first order fluid to solid transition. In the case of the attr.
Information Transmission by Means of Chaos-Based Frequency Modulation and Adaptive Identification

The problem of information transmitting using chaotic signals is considered. New method of information coding by means of frequency modulation of the chaotic signal is proposed. Chaotic generator is modulated by information signal by means of its time scaling. The receiver recovering algorithm, using ideas of Lion's and speed-gradient method, based on the adaptive identification procedure and augmented signals is built up. Robustified adaptation law applicable for noisy transmission channel is presented. The example of signal transmission by means of the frequency modulation of the Chua system is given. The simulation results for signal transmission of the audio frequency range signals are demonstrated.
Effective and Steady Differentiation of a Clonal Derivative of P19CL6 Embryonal Carcinoma Cell Line into Beating Cardiomyocytes

The P19CL6 cell line is a useful model to study cardiac differentiation in vitro. However, large variations were noticed in the differentiation rates among previous reports as well as our individual experiments. To overcome the unstable differentiation, we established P19CL6-A1, a new clonal derivative of P19CL6 that could differentiate into cardiomyocytes more efficiently and stably than the parent using the double stimulation with 5-Aza and DMSO based on the previous report. We also introduced a new software, Visorhythm, that can analyze the temporal variations in the beating rhythms and can chart correlograms displaying the oscillated rhythms. Using P19CL6-A1-derived cardiomyocytes and the software, we demonstrated that the correlograms could clearly display the enhancement of beating rates by cardiotonic reagents. These indicate that a combination of P19CL6-A1 and Visorhythm is a useful tool that can provide invaluable assistance in inotropic drug discovery, drug screening, and toxicity testing.
Asymptotic efficiency and finite-sample properties of the generalized profiling estimation of parameters in ordinary differential equations

Ordinary differential equations (ODEs) are commonly used to model dynamic behavior of a system. Because many parameters are unknown and have to be estimated from the observed data, there is growing interest in statistics to develop efficient estimation procedures for these parameters. Among the proposed methods in the literature, the generalized profiling estimation method developed by Ramsay and colleagues is particularly promising for its computational efficiency and good performance. In this approach, the ODE solution is approximated with a linear combination of basis functions. The coefficients of the basis functions are estimated by a penalized smoothing procedure with an ODE-defined penalty. However, the statistical properties of this procedure are not known. In this paper, we first give an upper bound on the uniform norm of the difference between the true solutions and their approximations. Then we use this bound to prove the consistency and asymptotic normality of this estimation procedure. We show that the asymptotic covariance matrix is the same as that of the maximum likelihood estimation. Therefore, this procedure is asymptotically efficient. For a fixed sample and fixed basis functions, we study the limiting behavior of the approximation when the smoothing parameter tends to infinity. We propose an algorithm to choose the smoothing parameters and a method to compute the deviation of the spline approximation from solution without solving the ODES.
Acyl-ACP Substrate Recognition in Burkholderia mallei BmaI1 Acyl-Homoserine Lactone Synthase

The acyl-homoserine lactone (AHL) autoinducer mediated quorum sensing regulates virulence in several pathogenic bacteria. The hallmark of an efficient quorum sensing system relies on the tight specificity in the signal generated by each bacterium. Since AHL signal specificity is derived from the acyl-chain of the acyl-ACP (ACP = acyl carrier protein) substrate, AHL synthase enzymes must recognize and react with the native acyl-ACP with high catalytic efficiency while keeping reaction rates with non-native acyl-ACPs low. The mechanism of acyl-ACP substrate recognition in these enzymes, however, remains elusive. In this study, we investigated differences in catalytic efficiencies for shorter and longer chain acyl-ACP substrates reacting with an octanoyl-homoserine lactone synthase Burkholderia mallei BmaI1. With the exception of two-carbon shorter hexanoyl-ACP, the catalytic efficiencies of butyryl-ACP, decanoyl-ACP, and octanoyl-CoA reacting with BmaI1 decreased by greater than 20-fold compared to the native octanoyl-ACP substrate. Furthermore, we also noticed kinetic cooperativity when BmaI1 reacted with non-native acyl-donor substrates. Our kinetic data suggest that non-native acyl-ACP substrates are unable to form a stable and productive BmaI1·acyl-ACP·SAM ternary complex and are thus effectively discriminated by the enzyme. These results offer insights into the molecular basis of substrate recognition for the BmaI1 enzyme.
Virtual Mediums Used as a Conduit for Soft-Skill Development

The purpose of this chapter is to elucidate the potential of online mediums such as massive multiplayer online role-playing games (MMORPGs) and other virtual immersive mediums that hold the potential to build social connections for individuals with autism and related disabilities. Further, this chapter will relate the skills used in the context of the virtual environments to essential soft-skill development and generalization to participation within inclusive STEM classes and postsecondary education.
Supplier Selection with Multiple Criteria under Fuzzy Environment

Selection of suppliers is the precondition and foundation of supply chain operation. It is an important aspect to choose the best supplier for supply chain management. This paper is aimed to present a fuzzy decision-making approach to deal with the supplier selection problem in supply chain system. In this paper, we can convert the decision matrix into a fuzzy decision matrix and then we use fuzzy VIKOR which is combined with fuzzy set theory to select the best suppliers.
Augmenting the landscape scene: students as participatory evaluators of mobile geospatial technologies

ABSTRACT This paper provides a two-phase study to compare alternative techniques for augmenting landscape scenes on geography fieldtrips. The techniques were: a pre-prepared acetate overlay; a custom-designed mobile field guide; a locative media app on a smartphone; a virtual globe on a tablet PC; a head-mounted virtual reality display, and a geo-wand style mobile app. In one field exercise the first five techniques were compared through analysis of interviews and student video diaries, combined with direct observation. This identified a particular challenge of how to direct user attention correctly to relevant information in the field of view. To explore this issue in more detail, a second field exercise deployed “Zapp”, a bespoke geo-wand-style app capable of retrieving information about distant landscape features. This was evaluated using first-person video and spatial logging of in-field interactions. This paper reflects upon the relative merits of these approaches and highlights particular challenges of using technology to mimic a human field guide in pointing out specific aspects of the landscape scene. We also explore the role of students acting as design informants and research co-participants, which can be mutually beneficial in promoting a critical appreciation of the role of technology to support learning about the landscape.