Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Scheduling Technique for the Improvement of WSN with Network Lifetime & Delay Constraint

This paper highlight about the maximization of network lifetime & minimization of delay parameter which is important to improve the performance of the wireless sensor network as effective and reliable Wireless mostly energy is used when communication radios are on. The network lifetime is usually defined as the time until the first node fails because of energy depletion. So sleep-wake scheduling is effective mechanism to increase network lifetime. Sleep-wake scheduling is efficient to increase network lifetime but it could result in substantial delays because a transmitting node needs to wait for its next-hop relay node to wake up. We attempts to reduce these delays by developing "anycast"-based packet forwarding schemes, where each node opportunistically forwards a packet to the first neighboring node that wakes up among multiple candidate nodes such set of nodes called forwarding node set. We used anycast forwarding schemes to forward the data packet to next hop node which minimizes the expected packet-delivery delays from the sensor nodes to the sink node. Based on this result, we provide a solution to the problem of how to optimally control the system parameters of the sleep-wake scheduling protocol and the anycast packet forwarding protocol to maximize the network lifetime and minimize the delay with constraint on the expected end-to-end packet-delivery delay.
Use of mtDNA Direct Polymerase Chain Reaction (PCR) Sequencing and PCR-Restriction Fragment Length Polymorphism Methodologies in Species Identification of Canned Tuna

Identification of six canned tuna species using DNA-based methodology was studied. DNA was degraded during the canning process of fish muscle: DNA fragment sizes that ranged from <100 up to 200 bp were obtained from canned tuna muscle, whereas DNA sizes for frozen tuna muscle ranged from <100 up to 20 000 bp. Amplification of DNA from canned tuna muscle was carried out using primers flanking a region of cytochrome b gene of 126 bp. Sequences from PCR-amplified DNA of six tuna species were studied for polymorphic sites; seven diagnostic positions were identified in this fragment for the species studied. The suitability of a genetic distance measurement with phylogenetic tree construction method for the identification of canned tuna species using two cytochrome b sequences (299 and 126 bp) was studied. PCR-amplified DNA from canned tuna was also analyzed by using three restriction endonucleases, BsiYI, MboI, and MnlI. The restriction fragments allowed for the identification of the six tuna species studied.
Effects of the number of speech-bands and envelope smoothing condition on the ability to identify intonational patterns through a simulated cochlear implant speech processor

Though many investigations have been performed into the way that dividing the speech spectrum into a number of channels effects the intelligibility of speech, there appear to be few studies that have examined the effects of manipulating the number of channels on the ability to recognise and identify intonational patterns in speech. Secondly, many studies have demonstrated that voice fundamental frequency plays a significant role in the perception of speech intonation patterns; available evidence also suggests that changes in signal processing (in terms of simplifying the input waveform) could improve the perception of voice pitch changes for users of hearing aids and cochlear implants. In this study the ability to identify five intonational modes was assessed using sentences produced by a single male talker. The identification scores from seven normally-hearing subjects were examined with speech presented through 1, 4, 8, and 16-band simulations of cochlear implant signal processors (noiseband vocoders). Additionally, three different envelope conditions were utilised with each processor; this allowed the salience of temporal envelope cues to fundamental frequency to be manipulated and the consequent effect on identification performance to be examined. Significant improvements in identification ability were observed with both increased salience of temporal envelope cues to fundamental frequency and with increasing number of speech-bands (although the improvement in scores from the 8band condition to the 16-band condition was not statistically significant). However, the level of identification improvement was found to vary significantly with intonational mode, suggesting that the overall identification scores may have been a reflection of subjects’ ability to disambiguate one or two intonational modes from the rest.
Workload characterization using lightweight system call tracing and reexecution

This paper shows how system call traces can be obtained with minimal interference to the system being characterized, and used as realistic, repeatable workloads for experiments to evaluate operating system and file system designs and configuration alternatives. Our system call trace mechanism, called ULTra, captures a complete trace of each UNIX process's calls to the operating system. The performance impact is normally small, and it runs in user mode without special privileges. We show how the resulting traces can be used to drive full, repeatable reexecution of the captured behaviour, and present a case study which shows the usefulness and accuracy of the tool for predicting the impact of file system caching on a WWW server's performance.
Importance sampling for the simulation of highly reliable Markovian systems

In this paper we investigate importance sampling techniques for the simulation of Markovian systems with highly reliable components. The need for simulation arises because the state space of such systems is typically huge, making numerical computation inefficient. Naive simulation is inefficient due to the rarity of the system failure events. Failure biasing is a useful importance sampling technique for the simulation of such systems. However, until now, this technique has been largely heuristic. We present a mathematical framework for the study of failure biasing. Using this framework we derive variance reduction results which explain the orders of magnitude of variance reduction obtained in practice. We show that in many cases the magnitude of the variance reduction is such that the relative errors of the estimates remain bounded as the failure rates of components tend to zero. We also prove that the failure biasing heuristic in its original form may not give bounded relative error for a large class of systems and that a modification of the heuristic works for the general case. The theoretical results in this paper agree with experiments on the subject which have been reported in a previous paper.
4 . 5 A Pedagogical Model for CyberParks

This chapter discusses the recent conceptual developments about CyberParks and their educational potential. Key learning characteristics and pedagogical principles will be identified through a review of learning theories and studies from cognitive neuroscience. Relevant pedagogical models are reviewed to develop one that describes learning in CyberParks, which will be used to design and evaluate learning in such context. An innovative connectivistinspired process-oriented pedagogical model is proposed to serve as a signpost in the process of developing adaptive expertise through which new pedagogies and innovative uses of CyberParks address the evolving needs of citizens.
Provably efficient adaptive scheduling of parallel jobs on multiprocessors

This thesis presents feedback-driven adaptive algorithms for efficient scheduling of parallel jobs on multiprogrammed multiprocessors. Multiprocessor scheduling is often structured in two levels, where a kernel-level OS allocator allots processors to jobs and a user-level thread scheduler schedules the ready threads of a job on the allotted processors. In the context of adaptive scheduling, the number of processors allotted to a particular job may vary during the job's execution, and the thread scheduler must adapt to these changes in processor resources. For overall system efficiency, the thread scheduler should provide parallelism feedback to the OS allocator to avoid the situation where a job is either allotted too many processors to use productively or it is allotted too few processors to complete without undue delay. Since the future parallelism of a job is generally unknown, however, how to provide a suitable parallelism feedback and allocate processors efficiently is a challenge. This thesis investigates adaptive scheduling algorithms, including adaptive thread schedulers, OS allocators, and the two-level schedulers that combine them. The schedulers operate in an online nonclairvoyant manner, oblivious to the future characteristics of the job. For adaptive thread scheduling, I introduce A-GREEDY and A-STEAL, which provide history-based feedback about the job's parallelism without assuming the knowledge of the job's future parallelism. These thread schedulers provably complete the jobs in near-optimal time while guaranteeing low waste. For OS allocator, I present and analyze RAD, which combines the space-sharing OS allocator Dynamic Equipartitioning with the time-sharing round-robin algorithm. When using instantaneous parallelism as feedback, RAD achieves 3-competitiveness with mean response time for hatched parallel jobs. It offers the best competitive ratio to date. For two-level scheduling, I present G-RAD and W-RAD. Both achieve 0(1)competitiveness with respect to makespan and mean response time for non-hatched jobs and hatched jobs respectively. They are the first nonclairvoyant schedulers to guarantee provable efficiency, fairness, and minimal overhead. ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library
Income Inequality and the Labour Market in Britain and the US 1

We study household income inequality in both Great Britain and the United States and the interplay between labour market earnings and the tax system. While both Britain and the US have witnessed secular increases in 90/10 male earnings inequality over the last three decades, this measure of inequality in net family income has declined in Britain while it has risen in the US. To better understand these comparisons, we examine the interaction between labour market earnings in the family, assortative mating, the tax and welfare-benefit system and household income inequality. We find that both countries have witnessed sizeable changes in employment which have primarily occurred on the extensive margin in the US and on the intensive margin in Britain. Increases in the generosity of the welfare system in Britain played a key role in equalizing net income growth across the wage distribution, whereas the relatively weak safety net available to non-workers in the US mean this growing group has seen particularly adverse developments in their net incomes. 1 Acknowledgments: Prepared for the Special Issue of the Journal of Pubic Economics to honour the contributions of Tony Atkinson. Data from the UK Households Below Average Income dataset and Family Resources Survey were made available by the Department for Work and Pensions. These data are available from the UK Data Archive. The Labour Force Survey is produced by the Office for National Statistics, and these data are available from the UK data archive. Support from the UK Economic and Social Research Council through the Centre for the Microeconomic Analysis of Public Policy (CPP) at IFS, grant reference ES/M010147/1, is gratefully acknowledged. Any errors and all views expressed are those of the authors. 2 University College London and Institute for Fiscal Studies: r.blundell@ucl.ac. uk 3 Institute for Fiscal Studies. 4 Institute for Fiscal Studies and University College London. 5 University of Kentucky and Institute for Fiscal Studies.
Learning temporal patterns in recurrent neural networks

General learning algorithms for recurrent neural networks that can be used for both discrete-time and continuous-time models are described. They are based on the notion of the derivatives of mappings between functions of time. Simulation results for learning rhythmical sequences are shown. The method can also be applied to networks of higher-order neuron models and multiple time delay connections. <<ETX>>
Labview Based Sliding Mode Voltage Control of PEM Fuel Cell System

This paper presents the simulation of a dynamic model of PEM (Proton Exchange Membrane) fuel cell in Matlab and Labview which provides an easy to use and understand simulator with GUI. The open circuit output voltage, activation losses, ohmic losses, concentration losses and temperature dynamics are modeled and analyzed for change in the input parameters. Power conditioning unit for the cell are modeled and control strategy is implemented for them. The simulation results are then scaled down for hardware implementation. 
DETECTION OF HUMAN FACIAL BEHAVIORAL EXPRESSION USING IMAGE PROCESSING

The paper presents Haar feature extraction classifier based image processing technique for the analysis of human facial behavioral expressions. As an improvisation, some of instances misclassified by Haar classifier are further detected by subsequent classifier adaptive algorithm (Adaboost). Careful attention is paid while generating the templates of various facial behavioral expressions including eye open, close, drowsy and smile. The obtained results create the possibilities of adapting an embedded image processor with the developed algorithms for the real time applications. The image processing algorithm is implemented by using Matlab.
Enhanced Expression of the S 100 A 8 / A 9 Complex in Acute Myocardial Infarction Patients

he S100A8/A9 complex is a heterodimeric molecule of the S100 family and is composed of S100A8 (10.8 kD) and S100A9 (13.2 kD), containing 2 calcium-binding sites per molecule. The 2 subunits are expressed in activated human neutrophils and macrophages in inflammatory lesions. S100A8 and S100A9 noncovalently associate to quickly form a heterodimer, the S100A8/A9 complex.1 Translocation of the complex from the cytosol to the membrane is induced by activation of a novel pathway requiring an intact microtubule network.2
Assessment of ERS-1 SAR data for rice crop mapping and monitoring

The current study investigates the potential of ERS-1 SAR data for rice field mapping and rice crop monitoring. The selected study area is approximately 15/spl times/15 km in size and is located in Kanchanaburi province, West-Thailand. The rice growing area is irrigated, flat, homogeneously managed, and has large individual fields of at least one hectare size. As regards rice field mapping a digital classification based on multi-temporal, speckle-filtered ERS-1 SAR images was carried out to determine rice field acreage. The classification accuracy for rice fields is 89%. As regards rice crop monitoring the radar backscattering coefficient /spl sigma//sup 0/ [dB] of rice fields was related to various phenological parameters on a field-by-field basis, such as plant height, plant moisture content, stalk diameter, leaf size, occurrence of standing water and crop yield. It was found that there is a good correlation between plant height and /spl sigma//sup 0/ and between crop yield and /spl sigma//sup 0/, respectively.
Neural Networks with Input Specified Thresholds

In this project report, we propose a method to modify the ReLU layers in neural networks. The modification involves two stages: we first convert the bias parameters into threshold parameters, and then increase the number of threshold parameters to balance the “linear side” and the “nonlinear side” of the model, which could potentially make the model more flexible and powerful. Image classification tests are performed on the Tiny ImageNet dataset.
MULTI-GROUP ANALYSIS OF FACTORS DETERMINING USER’S COMMITMENT IN MOBILE SOCIAL NETWORK GAMES

Social Network Game genre is a game in which people connect to each other by utilizing a mobile platform, and interact with each other while enjoying related contents. It has now become a popular game. The purpose of this study is to find significant factors that have effects on the commitment of M-SNGs. We also conduct multi-group comparison test to study the difference in factors of models between 2012 and 2016. We use structural equation model analysis with SmartPLS 3.0 and compare models of different times. This study is to give academicians and practitioners insight about its effects and implications. The results showed that there was a significant difference between the two groups only in the relationship between competition-commitment and social interaction-commitment. This study is to give academicians and practitioners insight about its effects and implications.
Diffusion of nano particles in viscous sublayer

in this paper, diffusion of nano particles from a point source in the viscous sub-layer of turbulent shear flow is considered. the equation of motion of particles including the brownian effects is used and ensembles of 500 particle trajectories are numerically evaluated and statistically analysed. effects of size on particle dispersion and wall deposition processes are studied. the effect of turbulent near a wall is also considered. the results are compared with the exact solution of corresponding eulerian convective diffusion equation in the absence of turbulent fluctuations. the results show that the brownian diffusion play a significant role in the diffusion of nano particles at distances less than 2 wall units from the solid wall. [M. Mahdavimanesh, A. R. Noghrehabadi, M. Behbahaninejad, G. Ahmadi, M. H. Nirooei, A. Etminan . Diffusion of nano particles in viscous sub-layer. Life Sci J 2013;10(8s):105-109] (ISSN:1097-8135). http://www.lifesciencesite. com. 13
Effect of DSR-based internal sinus floor elevation with implantation on atrophic maxilla

This study examined natural occlusion due to atrophic maxilla using a disc-up sinus reamer (DSR). The enrollment criterion was a vertical height of residual bone < 5 mm, as measured using X-ray and CBCT. Totally, 28 patients aged 42-75 years were accepted from December 2013 to 2016. A total of 41 internal sinus floor elevation procedures were performed using DSR-based implantation, which was followed by radiographic assessment, clinical examination, safety evaluation, and pain assessment. The estimated healing time for success of the submerged implants was 6-9 months, which also included temporal and terminal prosthesis rehabilitation. Patients were followed up at 3-month intervals for up to 24 months due to the acquired height of the endo-sinus bone and natural remodeling of the microstructure as shown on X-ray (CBCT). The mean final acquired height was 8.63 ± 1.08 mm; one (3.03%) perforation occurred. A significant survival rate of 97.56% was observed compared to other reported approaches of sinus floor lifting. The average pain index was 0.82, which was much lower than previous studies. Temporary reduction of the alveolar bone was observed during the first 3 months (P < 0.05), but remodeling stabilized after 6 months. More importantly, complications such as peri-implant infection and sinusitis did not occur when physical and radiography diagnosis were used. DSR-based sinus floor elevation with implantation combined in severely atrophic maxilla extends the implications for edentulous repair. In conclusion, the procedure is safer and less invasive.
CONFESS OR DIE : WHY THREATENING A SUSPECT WITH THE DEATH PENALTY SHOULD RENDER CONFESSIONS INVOLUNTARY

Williams v. Brown, 208 F. Supp. 3d 713, 717 (E.D. Va. 2016); Jeffrey Toobin, The Wrong Guys, NEW YORKER (Aug. 24, 2009), https://www.newyorker. com/magazine/2009/08/24/the-wrong-guys. These men became known as the “Norfolk Four. ” A Norfolk detective, with a history of eliciting false confessions, interrogated the four sailors. Each confessed to the crime, “alter[ing] their confessions to accommodate details fed to them by the police. ” Nearly twenty years later, a federal judge vacated two of the convictions.
Identification of Differentially Expressed miRNAs and mRNAs in Vestibular Schwannoma by Integrated Analysis

Background Vestibular schwannoma (VS) is benign, slow-growing brain tumor that negatively impacts patient quality of life, which may cause even death. This study aimed to explore key genes and microRNAs (miRNAs) associated with VS. Methods The mRNA and miRNA expression profiles of VS downloaded from Gene Expression Omnibus (GEO) database were included in this study to perform an integrated analysis. The differentially expressed mRNAs (DEmRNAs) and miRNAs (DEmiRNAs) were identified. Then, functional annotation and protein-protein interaction networks (PPI) of DEmRNAs were constructed. DEmiRNA-target DEmRNAs analysis and functional annotation of DEmiRNA-target DEmRNAs were performed. Results A total of 2627 DEmRNAs (1194 upregulated and 1433 downregulated DEmRNAs) and 21 DEmiRNAs (12 upregulated and 9 downregulated DEmiRNAs) were identified. ISG15, TLE1, and XPC were three hub proteins of VS-specific PPI network. A total of 2970 DEmiRNAs-DEmRNAs pairs were obtained. Among which, hsa-miR-181a-5p, hsa-miR-106-5p, and hsa-miR-34a-5p were the top three DEmiRNAs that covered most DEmRNAs. The functional annotation of DEmiRNA-target DEmRNAs revealed that the DEmiRNA-target DEmRNAs were significantly enriched in cGMP-PKG signaling pathway, adrenergic signaling in cardiomyocytes, and pathways in cancer. Conclusion The results of this present study may provide a comprehensive understanding for the roles of DEmRNAs and DEmiRNAs in the pathogenesis of VS and developing potential biomarkers of VS.
Extracting Web Facial Images for Quest-Based Face Annotation

Auto face annotation is playing important role in many real-world knowledge management systems and multimedia information. Auto face annotation can be beneficial to many real world applications. Face annotation related to face detection and recognition Recently research interests in mining weakly-labeled facial images on the internet to resolve research challenge in computer vision and image understanding. This paper provides various techniques or methods that are used to annotating facial images. In this article, we have gone through the issues of duplicatehuman names and explore supervised/semi-supervisedlearning techniques to further enhance the label qualitywith affordable human manual refinement efforts.
STDP Forms Associations between Memory Traces in Networks of Spiking Neurons

Memory traces and associations between them are fundamental for cognitive brain function. Neuron recordings suggest that distributed assemblies of neurons in the brain serve as memory traces for spatial information, real-world items, and concepts. However, there is conflicting evidence regarding neural codes for associated memory traces. Some studies suggest the emergence of overlaps between assemblies during an association, while others suggest that the assemblies themselves remain largely unchanged and new assemblies emerge as neural codes for associated memory items. Here we study the emergence of neural codes for associated memory items in a generic computational model of recurrent networks of spiking neurons with a data-based rule for spike-timing-dependent plasticity (STDP). The model depends critically on two parameters, which control the excitability of neurons and the scale of initial synaptic weights. By modifying these two parameters, the model can reproduce both experimental data from the human brain on the fast formation of associations through emergent overlaps between assemblies, and rodent data where new neurons are recruited to encode the associated memories. Hence our findings suggest that the brain can use both of these two neural codes for associations, and dynamically switch between them during consolidation.