Miracle-dz/UniFAR-FTUs huggingface dataset:
A directly modulated pulse-compressed and time-multiplexed optical source for high-speed multiple-access networks

A compact multiplexing scheme for high-capacity gigabit-per-second time-division multiple-access (TDMA) networks is described. The optical data pulses from an array of surface-emitting lasers are individually modulated, time compressed, relatively time delayed, and bit interleaved to form a single high-speed data stream, all in one simple process requiring a minimum of hardware. <<ETX>>
Overhauling a Failed Project Using Out of the Box Scrum

A software solutions company out-sourced a ground-up application build to a team of globally distributed independent consultants. The project eventually exceeded time and cost expectations and failed to deliver production ready tested software according to a planned market release window. The asserted reasons for this planned versus actual delta varied with time including failure of leadership, failure of project oversight, to design and implementation flaws and so on. Out of the box Scrum was implemented by a newly contracted consultant and the project delivered 153% of plan by the end of four two-week sprints. This report discusses the problem, the implemented solution, and the results while challenging what really made the difference.
A GPS-Less Localization and Mobility Modelling (LMM) System for Wildlife Tracking

Existing wildlife tracking solutions typically use sensor nodes with specialised facilities, such as long-range radio, solar array of cells and Global Positioning System (GPS). This introduces additional manufacturing cost, increased energy and memory consumptions and increased sensor node weight. This paper proposes a novel Localization and Mobility Modelling (LMM) system, that can carry out wildlife tracking by merely using low-cost, lightweight sensor nodes and using short-range peer-to-peer communication facilities only, i.e. without the need for any specialised facilities. This is done by using two computationally simple operations, which are: (i) aggregated data collections from sensor nodes via peer-to-peer communications in a distributed manner, and (ii) estimation of sensor nodes’ movement traces using trilateration. The computational load placed on each sensor node is just that of data collection and aggregation, whereas movement traces estimation is carried out on a backend server, separated from the sensor nodes. In the design of the LMM system, we have: (i) carried out an empirical evaluation of different parameter value settings for data collection to develop a Multi-Zone Multi-Hierarchy (MZMH) communication structure, (ii) demonstrated a novel use of an Aggregation based Topology Learning (ATL) protocol for collecting sensor nodes’ topology data using peer-to-peer multi-hop communications, and (iii) used a novel Location Estimation (LE) method for estimating sensor nodes’ movement traces from the collected topology data. The evaluation results show that the LMM system can accurately estimate sensor nodes’ movement traces but with significantly less energy and memory costs, demonstrating its cost-efficiency as compared to the related wildlife tracking solutions.
Spoofing Detection by Distortion of the Correlation Function

Open service GNSS signals are vulnerable to a spoofing attack where counterfeit signals are transmitted to deliberately mislead a user receiver. When the spoofer tries to capture the receiver's tracking loops or pull them away from the genuine signals the correlation function becomes distorted or multiple correlation peaks are present. This effect is utilised by a special class of GNSS receiver which uses block processing with FFT correlators on each satellite tracking channel. The Airbus Multiple Tracking Locked Loop (MTLL) receiver is such a receiver and has the full 2D delay-Doppler correlation function available. To detect a spoofing attack, this paper proposes a method of decomposing the correlation function to estimate the parameters of the radio propagation channel experienced by a GNSS satellite signal. Once the channel parameters have been established, a maximum likelihood ratio test is performed to identify anomalous channel conditions and raise a spoofing alarm. The method has been tested against the simulations of representative scenarios. In addition the University of Texas Spoofing Battery data sets and data from a live signal testing have been included. From the test results, an evaluation is made of the false alarm and missed detection probabilities along with the time to alert. This allows conclusions to be drawn about the potential of the proposed method as an anti-spoofing countermeasure in safety-critical GNSS applications.
A Fault-Tolerant Control approach to friction compensation

The control of systems that involve friction presents interesting challenges. Recent research has focused on detailed modeling of friction phenomena in order to use robust on-line friction compensation procedures, attempting to cancel out the friction force effect in the feedback control. The friction modeling problem remains a very difficult challenge. The friction effect acting in a dynamic system can be viewed as an actuator fault with time-varying characteristics to be estimated and compensated within a Fault-Tolerant Control (FTC) scheme, so that the limitations arising from the use of a friction model are obviated. This work is motivated by the combined use of sliding mode estimation and sliding mode control theories providing an effective and robust FTC strategy. The approach is illustrated using a non-linear inverted pendulum with Stribeck friction. Necessary and sufficient conditions for estimation (as a matched uncertainty) and output feedback stability are from [1, 2]. New ideas are two-fold (a) the concept of viewing friction as a fault-effect and (b) the combined use of sliding mode friction estimation and control.
Authentication of Remote IoT Users Based on Deeper Gait Analysis of Sensor Data

In IoT based systems, authentication of users and devices is a major challenge where the traditional authentication mechanisms such as login-password are no longer supportable. It requires continuous authentication methods to ensure authenticity of the users and devices specifically for long sessions. The authentication through the IoT-Sensors based data has already gained the attention of a considerable number of researchers as it does not require direct involvement of the users and provide an extra layer of security and user privacy. Due to the instability of IoT-Sensor data, the authentication techniques need to extract a large number of features to produce high-accurate results. Moreover, the limited capabilities of computation, communication, storage, and the small battery power of IoT devices further makes its implementation hard. In this paper, we have introduced a user authentication framework for remote IoT users based on unique walking patterns to extract gait-related features with minimum data samples and cycle length. For an in-depth analysis of the distinctive features of the sensor-based gait profiles, we have applied an ECG signal processing technique. The proposed approach applies to a diverse range of IoT devices such as cellphones, smartwatches, and wearable sensors. The main contribution of the proposed approach is the deeper gait analysis with the least number of features and data for authentication purposes. We have introduced an authentication algorithm for feature comparison. The machine learning models have been applied to the gait based profiles for validation of the proposed approach. The detailed experimental analysis of different data sets has achieved an accuracy of 94% and an equal error rate (EER) of 6% higher than the existing approaches.
Longitudinal fuzzy control for autonomous overtaking

Cooperative maneuver among autonomous and conventional vehicles can be considered one of the next steps for obtaining a safer and more comfortable driving. Some examples of these maneuvers are: Adaptive Cruise Control (ACC), intelligent intersection management or automatic overtaking maneuvering, among others. One of the most important aims of the Intelligent Transportation Systems (ITS) is to use roads without substantial modifications of the current infrastructure. The overtaking maneuver demands special attentions, in particular when it is carried out on two-way roads. For this reason, a fuzzy decision system based on fuzzy logic able to execute an autonomous overtaking in two-way roads has been implemented in this paper. The experiments are focused on the longitudinal control when an autonomous vehicle is overtaking to other. Moreover, different cases have been considered using an oncoming vehicle from the other direction on a two-way road. Several trials with three real vehicles communicated via a wireless network were carried out, showing a good behavior.
Nutrition and energy balance on the 'Footsteps of Scott' expedition 1984-86.

Nineteen-Eighty-Seven marks the 75th anniversary of the expedition to the South Pole led by Captain R.F. Scott, during which he and his party died. Between November 1985 and January 1986, three men manhauled sledges 875 miles, following Scott's original route to the South Pole. They consumed an energy dense diet which provided 20.5 MJ/man/day of which 57 per cent came from fat. Despite the diet being well tolerated and allowing for dehydration, the men lost between 6.7 and 10.5 kg, indicating a daily energy expenditure of 25 MJ/man/day. Estimates from daily diary records of periods spent in different classes of activity and the literature values for energy consumption assigned to those classes, suggest a daily energy expenditure of 29 MJ/man/day. These estimates of energy expenditure were higher than expected and suggest that on Scott's last expedition, emaciation, secondary to a diet grossly inadequate in energy content, might have been a more important factor in his demise than has previously been thought.
Managing the radio spectrum

In this article, we focus on the vision of spectrally aware CR that comprises handsets automatically making use of under-utilized spectrum by sequentially hopping into spectrum gaps across a broad frequency range. The topics discussed in this article are based on a project funded by Ofcom (the U.K. Communications Regulator) to investigate the issues surrounding the introduction of CR technology.
Automated Inference with Adaptive Batches

Classical stochastic gradient methods for optimization rely on noisy gradient approximations that become progressively less accurate as iterates approach a solution. The large noise and small signal in the resulting gradients makes it di cult to use them for adaptive stepsize selection and automatic stopping. We propose alternative “big batch” SGD schemes that adaptively grow the batch size over time to maintain a nearly constant signal-to-noise ratio in the gradient approximation. The resulting methods have similar convergence rates to classical SGD, and do not require convexity of the objective. The high fidelity gradients enable automated learning rate selection and do not require stepsize decay. Big batch methods are thus easily automated and can run with little or no oversight.
Studies of factors in relapse to alcohol, drug and nicotine use: a critical review of methodologies and findings.

OBJECTIVE To critically review the methodologies used to study relapse in substance abusers and compare some of the findings these methodologies have produced. METHOD Representative studies that have used retrospective, prospective, or near real time methodologies to study antecedents or consequences of relapse are presented and the strengths and weaknesses of each methodology are reviewed. Limitations in the ability of substance abusers to accurately report internal states are considered. Degree of convergence in findings across methodologies is examined. RESULTS Retrospective reports can provide perhaps the most detailed accounts of circumstances and experiences leading up to relapse, but are also more likely to be inaccurate due to the limitations of memory. Prospective studies are less likely to be affected by memory problems, but may not capture factors that immediately precede relapse. The near real time methodology, which uses palm-top computers to gather data, has many advantages over other methodologies, but a number of limitations as well. The two studies in which retrospective reports were directly compared to either prospective or near real time reports yielded mixed results regarding degree of agreement. Findings from several areas of research suggest that some substance abusers may have difficulty recognizing and reporting internal states. CONCLUSIONS Despite memory problems and other limitations of self-report, all three methodologies have produced findings that implicate negative affect states, increased craving, cognitive factors, interpersonal problems, and lack of coping as factors in relapse. Future relapse studies should make use of all three methodologies to obtain data on relapse and consequences, and steps should be taken to enhance the accuracy of the self-reports that are gathered with each method.
Elastically Coupled Two-Level Systems as a Model for Biopolymer Extensibility

We present Monte Carlo simulations for the elasticity of biopolymers consisting of segments that can undergo conformational transitions. Based on the thermodynamics of an elastically coupled twolevel system, the probability for a transition and a related change in length of each segment was calculated. Good agreement between this model description and measured data was found for both the polysaccharide dextran where the conformational changes are fast and the muscle protein titin where the marked rate dependence of the transition forces could be explained by nonequilibrium processes. [S0031-9007(98)07735-7]
Statistical characteristics of pedestrians' motion and effects on teletraffic of mobile communication networks

Motion of mobile terminals greatly affects traffic characteristics (cell dwell time, handoff rates, channel occupancy lime of each base station, etc.) in mobile communication networks. Motion of vehicles was previously measured and characterized using the Global Positioning System, and its effects on traffic characteristics were examined. In this study, the authors measured pedestrian motion using an autonomous navigation system, analyzed cell dwell time and other statistical parameters by overlaying a hypothetical cellular communication system on the measured loci. The cell dwell time distribution was found to follow a lognormal distribution. Self-similarity was also discovered in the cell dwell time sequence. The impact of the self-similarity on the traffic characteristics was discussed.
CEO Perceptions of Competition and Strategic Response in Hospital Markets

Physician-organization integration (POI) has emerged as a key issue for hospitals and health systems seeking to improve the quality and cost-effectiveness of care. Although competition and managed care are often cited as primary market drivers of the adoption of POI strategies, prior research has shown only weak associations between these market attributes and POI. This article argues that the role of key organizational decision makers has not been adequately accounted for in explaining strategic change. The study examines the role of hospital CEO perceptions of competition in predicting the adoption of five different approaches to POI. CEO perceptions of general market competition are explained by a combination of market and organizational attributes. Furthermore, when controlling for objective characteristics of the environment and organization, CEO perceptions of competition have consistent, statistically significant associations with four of five measures of POI examined.
Executive Summary 1 Microbial Community Optimization for Electricity Generation in Microbial Fuel Cells

Microbial fuel cells (MFCs) are a type of fuel cells that use bacteria as biocatalyst to oxidize an organic substrate to release electrons, which can be harvested in an external circuit to produce electric energy. This technology hold the potential to help overcome energetic problems and at the same time treat waste water more efficiently than the current employed techniques. Despite all this potential, process and reactor design optimization are still necessary to apply the MFC technology in real situations. This study focused into optimize the microbial community and MFC performance, by testing three different inoculum sources, and afterwards analyze the effect of external resistance and substrate concentration in biofilm formation and MFC performance. Results indicate that lake sediment is the best inoculum source, with higher power densities (955 mW.m) and CE (30% and 23% with acetate and xylose, respectively). Furthermore, biofilms formed with this inoculum source showed greater enrichment in G. sulfurreducens. The 200 Ω resistance showed the best overall performances both in terms of biofilm formation (CE: 61%; COD removal: 55%) and MFC performance (Power density: 1 W.m). The substrate concentration was concluded to have no effect in biofilm and MFC performance, being only relevant to define the cycle’s duration. It’s then possible to conclude that inoculum source plays a major role in microbial community development and MFC performance. Moreover, they can be further improved by adjusting the external resistance, which optimization showed to be higher with lower resistances values.
Quantitative autoradiography of mu-,delta- and kappa1 opioid receptors in kappa-opioid receptor knockout mice.

Mice deficient in the kappa-opioid receptor (KOR) gene have recently been developed by the technique of homologous recombination and shown to lack behavioural responses to the selective kappa1-receptor agonist U-50,488H. We have carried out quantitative autoradiography of mu-, delta- and kappa1 receptors in the brains of wild-type (+/+), heterozygous (+/-) and homozygous (-/-) KOR knockout mice to determine if there is any compensatory expression of mu- and delta-receptor subtypes in mutant animals. Adjacent coronal sections were cut from the brains of +/+, +/- and -/- mice for the determination of binding of [3H]CI-977, [3H]DAMGO (D-Ala2-MePhe4-Gly-ol5 enkephalin) or [3H]DELT-I (D-Ala2 deltorphin I) to kappa1-, mu- and delta-receptors, respectively. In +/- mice there was a decrease in [3H]CI-977 binding of approximately 50% whilst no kappa1-receptors could be detected in any brain region of homozygous animals confirming the successful disruption of the KOR gene. There were no major changes in the number or distribution of mu- or delta-receptors in any brain region of mutant mice. There were, however some non-cortical regions where a small up-regulation of delta-receptors was observed in contrast to an opposing down-regulation of delta-receptors evident in mu-knockout brains. This effect was most notable in the nucleus accumbens and the vertical limb of the diagonal band, and suggests there may be functional interactions between mu- and delta-receptors and kappa1- and delta-receptors in mouse brain.
Discrete particle swarm optimization for materials acquisition in multi-unit libraries

With limited budget and inflation rate, the materials acquisition in multi-unit libraries has been a challenging issue all over the world. The materials acquisition for multi-unit libraries can be regarded as a generalized version of the knapsack problem, which was known to be NP-hard, with much more constraints. Thus, it can be computationally expensive to solve the problem. In this paper, the materials acquisition problem in multi-unit libraries is formulated as an integer programming model, and two different constraint-handling mechanisms applied in discrete particle swarm optimization algorithm for obtaining the near optimal solution are presented. It is evident from our computational results that one constraint-handling mechanism can solve the problem effectively and efficiently, while the other one takes more time.
Molecular Dynamics of Interactions between Rigid and Flexible Antifolates and Dihydrofolate Reductase from Pyrimethamine‐Sensitive and Pyrimethamine‐Resistant Plasmodium falciparum

Currently, the usefulness of antimalarials such as pyrimethamine (PYR) is drastically reduced due to the emergence of resistant Plasmodium falciparum (Pf) caused by its dihydrofolate reductase (PfDHFR) mutations, especially the quadruple N51I/C59R/S108N/I164L mutations. The resistance was due to the steric conflict of PYR with S108N. WR99210 (WR), a dihydrotriazine antifolate with a flexible side chain that can avoid such conflict, can overcome this resistance through tight binding with the mutant. To understand factors contributing to different binding affinities of PYR/WR to the wild type (WT) and quadruple mutant (QM), we performed simulations on WR‐WT, WR‐QM, PYR‐WT, and PYR‐QM complexes and found that Ile14 and Asp54 were crucial for PYR/WR binding to PfDHFR due to strong hydrogen bonds. The quadruple mutations cause PYR to form, on average, fewer hydrogen bonds with Ile14 and Leu164, and to be displaced from its optimal orientation for Asp54 interaction. The predicted binding affinity ranking (WR‐QM ≈ WR‐WT ≈ PYR‐WT >> PYR‐QM) reasonably agrees with the inhibition constant (Ki) ranking. Our results reveal important residues for tight binding of PYR/WR to WT/QM, which may be used to evaluate the inhibition effectiveness of antimalarials and to provide fundamental information for designing new drugs effective against drug‐resistant P. falciparum.
New Method for Estimation of Mobile Location Based on Signal Attenuation and Hata Model Signal Prediction

This paper proposes a new algorithm, based on the received signal strength, for mobile location estimation. The algorithm, considering path loss and shadowing for the channel, estimates the distance between the mobile and the home and neighboring base stations, and computes an improved form of the weighted gravity center of the above estimated distances. Simulation results show that the mean error estimation of the mobile location obtained by the proposed algorithm is much smaller than that of the cell-ID, and it is at least 15% better than that of the weighted gravity center method
Data Stream Media Compression and Transmission Framework for Intelligent Communication Equipment Based on Android System

Data stream media compression and transmission framework for intelligent communication equipment based on the Android system is implemented in this paper. We analyzed the transmission and error recovery strategies of MPEG streams based on RTP, established an experimental model, and analyzed the role of the flap protocol in MPEG video stream transmission. The congestion control mechanism of core streaming media transmission is usually closed-loop control. The receiving end is responsible for congestion detection. If congestion occurs, it is fed back to the sending end. The sending end adjusts the sending speed according to the feedback. Because the network is dynamically changing, the route chosen by each packet may be different, so the time delay to reach the client will be different, even It is possible to send the first data packet later. Based on this characteristic, we enhance the Android to assist creating the robust and efficient system. The simulation has proven that the designed system has the better transmission efficiency.