Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis and Design Strategy of On-Chip Charge Pumps for MicroPower Energy Harvesting Applications

Charge balance law based on conservation of charge is stated and employed to analyze on-chip linear, Fibonacci and exponential charge pumps. For micro-power on-chip implementations, both the positiveand the negativeplate parasitic capacitors have to be considered. Voltage conversion ratios and efficiencies can be obtained in closed form for singleand dual-branch linear charge pumps, but not for Fibonacci and exponential charge pumps. Instead, a first iteration approximation analysis for computing voltage conversion ratio is proposed. For the linear charge pump, efficiency optimization is achieved by first computing the optimal number of stages, and then obtaining from the required output voltage the reduction factor that is a function of load current, flying capacitor and switching frequency. Using a 0.35m CMOS process, 8X linear, Fibonacci and exponential charge pumps are designed and their performances are compared and confirmed by extensive Cadence Spectre simulations. It is concluded that linear charge pumps attain the best efficiency.
On the Primordial Helium Abundance and the ∆ Y/∆ O Ratio

We present a review on the determination of the primordial helium abundance, Yp, based on the study of hydrogen and helium recombination lines in extragalactic H ii regions. We also discuss the observational determinations of the increase of helium to the increase of oxygen by mass ∆Y/∆O, and compare them with predictions based on models of galactic chemical evolution.
Compressive Spectral Estimation for Nonstationary Random Processes

Estimating the spectral characteristics of a nonstationary random process is an important but challenging task, which can be facilitated by exploiting structural properties of the process. In certain applications, the observed processes are underspread, i.e., their time and frequency correlations exhibit a reasonably fast decay, and approximately time-frequency sparse, i.e., a reasonably large percentage of the spectral values are small. For this class of processes, we propose a compressive estimator of the discrete Rihaczek spectrum (RS). This estimator combines a minimum variance unbiased estimator of the RS (which is a smoothed Rihaczek distribution using an appropriately designed smoothing kernel) with a compressed sensing technique that exploits the approximate time-frequency sparsity. As a result of the compression stage, the number of measurements required for good estimation performance can be significantly reduced. The measurements are values of the ambiguity function of the observed signal at randomly chosen time and frequency lag positions. We provide bounds on the mean-square estimation error of both the minimum variance unbiased RS estimator and the compressive RS estimator, and we demonstrate the performance of the compressive estimator by means of simulation results. The proposed compressive RS estimator can also be used for estimating other time-dependent spectra (e.g., the Wigner-Ville spectrum), since for an underspread process most spectra are almost equal.
Market-driven bandwidth allocation in selfish overlay networks

Selfish overlay networks consist of autonomous nodes that develop their own strategies by optimizing towards their local objectives and self-interests, rather than following prescribed protocols. It is thus important to regulate the behavior of selfish nodes, so that system-wide properties are optimized. In this paper, we investigate the problem of bandwidth allocation in overlay networks, and propose to use a market-driven approach to regulate the behavior of selfish nodes that either provide or consume services. In such markets, consumers of services select the best service providers, taking into account both the performance and the price of the service. On the other hand, service providers are encouraged to strategically decide their respective prices in a pricing game, in order to maximize their economic revenues and minimize losses in the long run. In order to overcome the limitations of previous models towards similar objectives, we design a decentralized algorithm that uses reinforcement learning to help selfish nodes to incrementally adapt to the local market, and to make optimized strategic decisions based on past experiences. We have simulated our proposed algorithm in randomly generated overlay networks, and have shown that the behavior of selfish nodes converges to their optimal strategies, and resource allocations in the entire overlay are near-optimal, and efficiently adapts to the dynamics of overlay networks.
An efficient algorithm for the genus problem with explicit construction of forbidden subgraphs

We give an algorithm for imbedding a graph G of n vertices onto an oriented surface of minimal genus g. If g > 0 then we also construct a forbidden subgraph of G which is homeomorphic to a graph of size exp(O(g)! ) which cannot be imbedded on a surface of genus g-1. Our algorithm takes sequential time exp(O(g)! )nO(1). Since exp(O(g)! ) = exp(exp(O(glog(g)))), our algorithm is polynomial time for genus g=O(loglog(n)/logloglog(n)). A simple parallel implementation of our algorithm takes parallel time (logn)O(1)+O(g)! using exp(O(g)! )nO(1) processors. We give also the smallest known upper bound, namely exp(O(g)! ), on the number F(g) of homeomorphic distinct forbidden subgraphs for graph imbeddings onto a surface of genus g. The two best previous algorithms [Filotti, Miller, Reif,79] and [Robertson and Seymour,86] for graph imbedding onto a surface of genus g, required nO(g) and f(g)n2 sequential time, respectively. The work of [Robertson and Seymour,86] also gave a finite bound for F(g). However their proof spanned many papers and were highly nonconstructive; f(g) and F(g) were bounded by some (large) tower of exponents of g. Our work provides a distinct constructive approach giving considerably improved bounds for f(g) and F(g) and vastly simplified proofs. In particular, we use a “bootstrap” technique that uses a discovered forbidden subgraph for given genus g'<g to to aid us in determination of genus g'+1 imbeddings. It seems likely that our techniques can be extended to many other problems on graphs with bounded tree width.
On the diversity analysis of the sequential slotted amplify-decode-and-forward protocol

In this paper, we review the sequential slotted amplify-decode-and-forward (SADF) protocol with half-duplex single-antenna and evaluate its performance in terms of pairwise error probability (PEP). We obtain the PEP upper bound of the protocol and find out that the achievable diversity order of the protocol is two with arbitrary number of relay terminals. To achieve the maximum achievable diversity order, we propose a simple precoder that is easy to implement with any number of relay terminals and transmission slots. Simulation results show that the proposed precoder achieves the maximum achievable diversity order and has similar BER performance compared to some of the existing precoders.
ROTATION AND STABILITY OF THE TOROIDAL MAGNETIC FIELD IN STELLAR RADIATION ZONES

The stability of the magnetic field in radiation zones is of crucial importance for mixing and angular momentum transport in the stellar interior. We consider the stability properties of stars containing a predominant toroidal field in spherical geometry by means of a linear stability in the Boussinesq approximation taking into account the effect of thermal conductivity. We calculate the growth rate of instability and analyze in detail the effects of stable stratification and heat transport. We argue that the stabilizing influence of gravity can never entirely suppress the instability caused by electric currents in radiation zones. However, the stable stratification can essentially decrease the growth rate of instability.
A design framework for wireless MANET QoS gateway

The peculiar nature of the mobile ad-hoc networks (MANET) imposes several challenges when designing quality of service solutions. Traffic traveling on a MANET network can be local traffic arriving from and targeting a node within the ad-hoc network. Traffic that is not local to MANET is likely to travel over fixed topology networks that employ, typically, DiffServ. This paper proposes employing a new framework at the gateway between the ad-hoc domain and the DiffServ access domain. The proposed framework facilitates a homogeneous seamless QoS interaction between both networks built over heterogeneous components. The objective is to achieve a high level of performance and autonomy with a lightweight implementation, if any, on mobile nodes. In this paper we propose the framework solution to the cross-domain QoS problem and use the aggregate resource reservation (ARSVP) for collective resource reservations, combined with a simple sponsorship mechanism.
Virtual machine placement in cloud systems through migration process

Cloud computing is an emerging technology that greatly shapes our lives, where users run their jobs on virtual machines (VMs) on physical machines (PMs) provided by a cloud service provider, saving the investment in upfront infrastructures. Due to the heterogeneity of various jobs, different VMs on the same PMs could have different job completion times. Meanwhile, the PMs are also heterogeneous. Therefore, different VM placements have different job completion times, and our objective is to minimise the total job completion time of the input VM requests through a reasonable VM placement schedule. This problem is NP-hard, since it can be reduced to a knapsack problem. We propose an off-line VM placement method through an emulated VM migration process, while the on-line VM placement is solved by a real VM migration process. The migration algorithm is a heuristic approach, in which we place the VM to its best PM directly, if this PM has enough capacity. Otherwise, we migrate another VM from this PM to accommodate the new VM, if a pre-specified migration constraint is satisfied. Furthermore, we study a hybrid scheme where a batch is employed to accept upcoming VMs for the on-line scenario. Evaluation results validate the high efficiency of the proposed algorithms.
Predicting Quantitative Functional Dependency Metric based upon the Interface Complexity Metric in Component based Software Systems: A New Approach

ABSTRACT One of the major issues in component based software systems structuring and quality prediction is the interdependencies of system components. This paper proposes a novel technique for determining the strength of functional coupling in component based software systems. Authors propose Strength of Functional Dependency (SFD) metric, which is based upon two new metrics Operational Coupling complexity Index (OCI), and Instance Coupling complexity Index (ICI). It allows us to quantify the functional dependencies, formed by different kinds of operations and instances between these components. Compared to other existing dependency metrics, which are often based on number of operations or instance variables between the components only, authors consider operational complexity and instance variables complexity as a measure to how strong this dependency is and therefore promote a more systematic approach to the reasoning about modularity in component based software systems. This paper can be divided broadly into two parts. The first part quantifies interface operations and instance variables. The quantification is performed by considering the number of input, output parameters and their types. Based upon these factors of operations and instance variables, authors used analytical hierarchy approach (AHP) to assign weights to these factors and outcomes OCI, ICI and SFD. The second part shows the experimentation and validation of the proposed metrics. The advantages of the proposed method are discussed as well through a case study in this paper.
Associating and recalling news events with visual suggestions

As more and more information including news articles, personal stories and so on gathered on the Internet, how a user perceives and memorizes every details of what he or she reads is of significant challenge. In view of this information overload problem, recent advances in the research field of information retrieval have resolved most difficulties when a user is able to provide appropriate keywords of his/her search target. Nevertheless, some important events which are etched deeply in one's memory may not be clearly defined as a few keywords or even easily recalled. Thus, we propose in this work to provide some visual suggestions to help users associate and recall their own stories from the memory while reading current news articles. In addition to the usage of fragment text, we propose to extract similarities from news photos. Consequently, resulting suggestions are effective for a user to associate current news event with previous ones. As such implicit relationships are gradually found, the topic map is then constructed to help a user organize relevant concepts he or she has ever known or learned.
Design 8-Bit Neural ADC with Exponential Variable Controlling Threshold

For overcoming shortcoming on the local minima and neuron quantity at the hidden layer in which several neural-based analogue-digital convertors (ADCs), a novel 8-bit ADC based on a new algorithm is designed. The new algorithm is similar to successive approximation method, but to attribute parallel algorithm. It adjusts weighting by the exponential alterable threshold. The global circuit is a two-step 8-bit ADC been made up of coarse ADC and fine ADC. In which comparators threshold adjust to use single neuron-MOS achieved. The neuron-MOS as simple DAC is applied to all what is needed in two-step ADC. In the architecture, comparator quantity has a linear relation with the digits of ADC that achieved trade off between speeds and die areas.
Survey-based Comparison of Chord Overlay Networks

Chord is a structured peer-to-peer (P2P) overlay network in which participating peers share resources as equals. To find a specific data item within the network, Chord system provide a lookup mechanism that matches a given key to a network node responsible for the value associated with that key. Chord is recently proposed to become one of the new approaches for building large-scale Internet applications. This paper aims to survey the Chord network, study its main characteristics, and compare its original performance with the performance of the enhancements being deployed over the original Chord. General Terms Distributed systems.
Tagged-MapReduce: A General Framework for Secure Computing with Mixed-Sensitivity Data on Hybrid Clouds

This paper presents tagged-MapReduce, a general extension to MapReduce that supports secure computing with mixed-sensitivity data on hybrid clouds. Tagged-MapReduce augments each key-value pair in MapReduce with a sensitivity tag. This enables fine-grained dataflow control during execution to prevent data leakage as well as supporting expressive security policies and complex MapReduce computations. Security constraints for preventing data leakage impose restrictions on computation and data storage/transfer, hence, we present scheduling strategies that can exploit properties of the map and reduce functions to rearrange the computation for greater efficiency under these constraints while maintaining MapReduce correctness. We present a general security framework for analyzing MapReduce computations in the hybrid cloud which captures how dataflow can leak information through execution. Experiments on Amazon EC2 with our prototype in Hadoop show that we are able to obtain security while effectively outsourcing computation to the public cloud and reducing inter-cloud communication.
Coding for the Slepian-Wolf problem with turbo codes

This paper proposes a practical coding scheme for the Slepian-Wolf problem of separate encoding of correlated sources. Finite-state machine (FSM) encoders, concatenated in parallel, are used at the transmit side and an iterative turbo decoder is applied at the receiver. Simulation results of system performance are presented for binary sources with different amounts of correlation. Obtained results show that the proposed technique outperforms by far both an equivalent uncoded system and a system coded with traditional (non-concatenated) FSM coding.
Drawing Semi-bipartite Graphs in Anchor+Matrix Style

A bipartite graph consists of a set of nodes that can be divided into two partitions such that no edge has both endpoints in the same partition. A semi-bipartite graph is a bipartite graph with edges in one partition. Anchored map is a graph drawing technique for bipartite graphs and provides aesthetically pleasing layouts of graphs with high readability by restricting the positions of nodes in a partition. For this research, the objects of the anchored map technique were extended to semi-bipartite graphs. A hybrid layout style of anchored maps and matrix representations are proposed, and an automatic drawing technique is shown. The proposed technique arranges the nodes in one partition on a circumference like the anchored map of bipartite graphs. It also divides nodes in the other partition with edges into clusters and represents them in the matrix representations to make it easy to see connective subsets.
A digitally tuned resonant capacitance control with narrow range frequency modulation for ZCS high voltage X-ray power supply

This paper presents the use of a digitally tuned resonant capacitance control with narrow range frequency modulation to regulate the output voltage of a zero current switching series resonant (ZCS-SR) inverter-fed transformer-linked DC-DC converter for X-ray power supply application. In this control scheme, the series resonant inverter consists of several capacitors which are switched into and out of resonant tank circuit by relays. The capacitance of the resonant tank is modulated digitally by controlling the closure of relays which causes the output voltage to increase or decrease in steps. The output voltage in between any two adjacent steps is adjusted by varying the switching frequency in a narrow range. By modulating both resonant tank capacitance and switching frequency, it is able to regulate the output voltage over a wide range. Furthermore, the switching losses of the proposed system are eliminated with all switches operating under soft switching conditions over the entire range of output voltage. Verification of the proposed system is done by computer simulation using Orcad PSPICE.
The Structure of the Synaptic Vesicle-Plasma Membrane Interface Constrains SNARE Models of Rapid, Synchronous Exocytosis at Nerve Terminals

Contemporary models of neurotransmitter release invoke direct or indirect interactions between the Ca2+ sensor, synaptotagmin and the incompletely zippered soluble, N-ethyl-maleimide-sensitive factor attachment protein receptor (SNARE) complex. However, recent electron microscopic (EM) investigations have raised pragmatic issues concerning the mechanism by which SNAREs trigger membrane fusion at nerve terminals. The first issue is related to the finding that the area of contact between a “fully primed” synaptic vesicle and the plasma membrane can exceed 600 nm2. Approximately four-thousands lipid molecules can inhabit this contact zone. Thus, renewed efforts will be needed to explain how the zippering of as few as two SNARE complexes mobilizes these lipids to achieve membrane fusion. The second issue emerges from the finding that “docking filaments” are sandwiched within the area of vesicle-plasma membrane contact. It is challenging to reconcile the location of these filaments with SNARE models of exocytosis. Instead, this commentary outlines how these data are more compatible with a model in which a cluster of synaptotagmins catalyzes exocytotic membrane fusion.
Petschek-type reconnection at the magnetopause: A comparison of theory with data from ISEE 2 on September 11, 1979

We study the process of magnetic field line reconnection at the Earth’s dayside magnetopause from the theoretical point of view and compare model predictions with observations made by the ISEE 2 spacecraft on its outbound magnetopause crossing on September 11, 1979. During the process of magnetic field line reconnection all types of magnetohydrodynamic waves can be excited. An analytical treatment of this process is performed in a generalized Petschek–type model. In this approach all wave structures are considered to be steepened and/or sufficiently thin so that they can be described as discontinuities. A direct comparison is made between the predicted structures and spacecraft data, and we show the influence of heavy ions on the mass density, and correspondingly the structure of the reconnection layer.
Integration and Prediction in Language Processing: A Synthesis of Old and New

Current theories of language processing emphasize prediction as a mechanism to facilitate comprehension, which contrasts with the state of the field a few decades ago, when prediction was rarely mentioned. We argue that the field of psycholinguistics would benefit from revisiting these earlier theories of comprehension that attempted to explain integration and the processes underlying the formation of rich representations of linguistic input and that emphasized informational newness over redundancy. We suggest further that integration and anticipation may be complementary mechanisms that operate on elaborated, coherent discourse representations, supporting enhanced comprehension and memory. In addition, the traditional emphasis on language as a tool for communication implies that much linguistic content will be nonredundant; moreover, the purpose of anticipation is probably not to permit the prediction of exact lexical or syntactic forms but instead to induce a state of preparedness that allows the comprehender to be receptive to new information, thus facilitating its processing.
A proposal of software maintainability model using code smell measurement

Maintenance is a very important phase in a software's life cycle. More than half of the effort and cost of software is in the maintenance phase. Code smell is one of the problems that need to be dealt with in this phase. Code smell can be caused by bad design and implementation choice. In the end, it has the potential to degrade code maintainability. This paper proposes a new software maintainability model using measurement of code smell. Code smell has been used to indicate problems in software code which could be the results of bad design and may lead to bad maintenance. Our proposed model is then validated against the density of design patterns in 6 open source applications. The design patterns have been known to give positive impact on maintainability. Our result proves a strong relationship with correlation value of 0.51 between our model to the design patterns density. It shows that our model can become an alternative to measure a maintainability quality of an application.