Miracle-dz/UniFAR-FTUs huggingface dataset:
High operating temperature IR-modules with reduced pitch for SWaP sensitive applications

Low size, weight and power (SWaP) are the most critical requirements for portable thermal imagers like weapon sights or handheld observations devices. On the other hand due to current asymmetrical conflicts there are high requirements for the e/o performance of these devices providing the ability to distinguish between combatants and non-combatants in adequate ranges. Despite of all the success with uncooled technology, such requirements usually still require cooled detectors. AIM has developed a family of thermal weapon sights called HuntIR and RangIR based on high performance cooled IR-modules which are used e.g. in the infantryman of the future program of the German army (IdZ). The specific capability of these devices is a high ID range >1500m for tank targets being suitable in use as thermal sights for . 50 cal rifles like the G82, targeting units for the 40mm AGL or for night observation. While such ranges sound far beyond the operational needs in urban operations, the a.m. specific needs of asymmetric warfare require sometimes even more range performance. High operating temperature (HOT) is introduced in the AIM MCT 640x512/15μm MWIR or LWIR modules for further reduction of cooler power consumption, shorter cooldown times and higher MTTF. As a key component to keep performance while further reducing SWaP AIM is developing a new cooled MCT IR-module with reduced pitch of 12 μm operating at a temperature >120 K. The module will provide full TV format with 640x480 elements sensitive in the MWIR spectral band. The paper will show recent results of AIM IR-modules with high operating temperature and the impact of design regarding the IR-module itself and thermal sights making use of it.
The convex wrapping algorithm

Muscle-tendon lengths, their lengthening rates as well as their moment arms are the parameters of great utility for clinical interpretation purposes. These parameters depend on the paths that the muscles follow. It is, thus, necessary to determine accurate muscular paths during movement. The position of the muscles being inaccessible to direct measurement, various methods were proposed to evaluate their possible paths during the movement studied. They can be split into two categories: the wired models and the finite elements models. Taking into account the ‘wrapping surface’ algorithms (Van der Helm et al. 1992; Delp and Loan 2000; Garner and Pandy 2000), the ‘dynamic via-points’ algorithm (Carman and Milburn 2005) and Marai’s algorithm (Marai et al. 2004) that uses skeleton mesh, the present authors thus developed the ‘convex wrapping algorithm’ to determine the muscular paths, with the following objective: ‘Find the shortest path between the insertion and the origin of a muscle wrapping over the skeleton bone mesh while respecting possible non-sliding constraints’. This algorithm directly employs exact bone geometry, not simple geometrical forms, as the object of envelopment. Thus, this algorithm is detailed. It is then compared with the ‘straight line’ method and ‘wrapping surface’ algorithm by measuring the length and moment arm of the semitendinosus muscle during asymptomatic gait.
Synchronization of a Network Composed of Stochastic Hindmarsh–Rose Neurons

An algorithm for synchronization of a network composed of interconnected Hindmarsh–Rose neurons is presented. Delays are present in the interconnections of the neurons. Noise is added to the controlled input of the neurons. The synchronization algorithm is designed using convex optimization and is formulated by means of linear matrix inequalities via the stochastic version of the Razumikhin functional. The recovery and the adaptation variables are also synchronized; this is demonstrated with the help of the minimum-phase property of the Hindmarsh–Rose neuron. The results are illustrated by an example.
Improved description of base dynamics in the modelling of bipolar transistors

An improved non-linear high-frequency model for the bipolar transistor is presented, based on considerations of the dynamics of the charge stored in the base region. the model incorporates higher-order circuit elements in order to obtain increased accuracy in circuit simulation at high frequencies. the model is derived from device physics by solving the diffusion equation in the base region by means of a quasi-static expansion. the result is a more accurate circuit representation, which can be added to existing bipolar transistor models. Simulation examples are given and the possible convergence problems associated with the model are discussed.
Novel bandpass‐response power divider with high frequency selectivity using centrally stub‐lOaded resonators

This article presents a novel bandpass‐response power divider with high frequency selectivity. The centrally stub‐loaded resonators are applied to this power divider in order to provide bandpass‐filtering frequency response. In addition, the presented power divider has three transmission zeros, which can be used to improve the frequency selectivity. The measured results demonstrate the good performance of the fabricated bandpass‐response power divider with high selectivity. © 2013 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:1560–1562, 2013; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.27644
Occupant Dynamics: Towards a New Design Performance Measure

Abstract With the advent of more robust computer modeling techniques, the ability to model human behavior such as the movement of occupants in building spaces has become increasingly accurate. In the last thirty years, several research efforts have proposed models for pedestrian/occupant movements. This paper reports on recent research on occupant simulation in building spaces and specifically presents a proposed basic measure for analyzing the design of building spaces in terms of space accessibility. The proposed measure, namely the Random Access Measure (RAM), is presented as a useful and simple design analysis technique that relates to occupant movement as well as to space topology. A computerized prototype is developed and presented in this paper along with a simple example. A discussion of the RAM and similar analysis techniques such as visibility graphs and isovists is presented.
Closely spaced array of cavity backed slot antennas with pin curtains walls

An array of two cavity backed slot antennas with pin curtain walls is described. The use of pin curtains is shown to result in greatly reduced fabrication errors and improved repeatability. The effects of the pin curtain parameters on coupling between the array elements are investigated in order to establish design guidelines for achieving a mutual coupling performance which is as good as when using solid copper walls. It is found that these are not as strict as the general guidelines for pin curtains found in the literature. By means of extensive Finite Difference Time Domain simulations and measurements, the antenna performance characterised by impedance matching, radiation patterns and efficiency is shown to be unaffected when these pin curtains are used in place of solid copper walls. From this, a practical design has been arrived at.
A multi-conjugate adaptive optics testbed using two MEMS deformable mirrors

Adaptive optics (AO) systems are well demonstrated in the literature with both laboratory and real-world systems being developed. Some of these systems have employed MEMS deformable mirrors as their active corrective element. More recent work in AO for astronomical applications has focused on providing correction in more than one conjugate plane. Additionally, horizontal path AO systems are exploring correction in multiple conjugate planes. This provides challenges for a laboratory system as the aberrations need to be generated and corrected in more than one plane in the optical system. Our work with compact AO systems employing MEMS technology in addition to liquid crystal spatial light modulator (SLM) driven aberration generators has been scaled up to a two conjugate plane testbed. Using two SLM based aberration generators and two separate wavefront sensors, the system can apply correction with two MEMS deformable mirrors. The challenges in such a system are to properly match non-identical components and weight the correction algorithm for correcting in two planes. This paper demonstrates preliminary results and analysis with this system with wavefront data and residual error measurements.
Characterization of a MEMS deformable mirror by far field intensity evaluation

The performance of an adaptive optics (AO) system is typically measured using the wavefront sensor (WFS). However, another method is to use the point spread function (PSF), which is sensitive to scatter, does not act as a low pass filter and is not dependent on the WFS calibration. We decided to examine the performance of an AO system built for vision science that employed a micromechanical systems (MEMS) based deformable mirror (DM). Specifically, the MEMS DM consists of 489 actuators, resulting in 163 segments each with individual piston/tip/tilt control. Initial evaluation of the DM with a model eye included determining the ability of the DM to generate individual Zernike polynomials and evaluating the far field PSF to measure wavefront correction performance. For individual Zernike polynomial terms, the DM was found to be capable of correcting the aberration magnitudes expected from previously published human population studies.1, 2 Finally, the DM was used in an AO fundus camera to successfully acquire images of cone photoreceptors in a living human eye. This is part of ongoing work which will incorporate the MEMS DM into both an AO scanning laser ophthalmoscope (SLO) and an AO optical coherence tomography (OCT) system where the form of the PSF at the confocal pinhole/optical fiber is important for optimal imaging.
Earthquake vulnerability of Kathmandu: A product of failed building permits system and urban development

Numerous activities associated with present trend of rapid urbanisation and haphazard urban (re)development in the historic core area as well as in the peripheral agricultural lands of Kathmandu are responsible for increasing earthquake vulnerability, exposing higher percentage of population under seismic hazard, and decreasing the capacity of urban and emergency services to cope with disaster in many ways. Absence of disaster management institution at local and central levels, lack of earthquake mitigation and urban development related legislation together with low level of community preparedness and public awareness have not only intensified the rate of conversion of city into a hazardous zone but have also resulted in loss of the opportunity to build safer community in newly developed areas. As the geophysical processes of the natural hazard can not be changed, integration of earthquake mitigation component and technique into urban development process is the key in reducing earthquake vulnerability of Kathmandu. For it, establishment of disaster management institution at central level backed by new legislation to formulate earthquake mitigation technique, emergency response plan, and post reconstruction program by coordinating various concerned agencies, on one hand, and enhancement of community’s preparedness by retrofitting the existing buildings, preparing rescue and response plan, educating and training those involved in building industry together with bringing public awareness at local ward level, on the other hand, is essential. Nepalese Journal of Engineering Vol.1(1) 2005 pp.25-38
Botnet attack detection in Internet of Things devices over cloud environment via machine learning

With the arrival of the Internet of Things (IoT) many devices such as sensors, nowadays can communicate with each other and share data easily. However, the IoT paradigm is prone to security concerns as many attackers try to hit the network and make it vulnerable. In this scenario, security concerns are the most important and to address them various models have been designed to overcome these security issues, but still there exist many emerging variants of botnet attacks such as Mirai, Persirai, and Bashlite that exploits the security breaches. This research article aims to investigate cyber security in the advent of B‐IDS, DDOS, and malware attacks. For this purpose, different machine learning algorithms, namely, support vector machine, naive Bayes, linear regression, artificial neural network, decision tree, random forest, the fuzzy classifier, K‐nearest neighbor, adaptive boosting, gradient boosting, and tree ensemble have been implemented for botnet attack detection. For performance measures, these algorithms have been tested on nine sensor devices over N‐BaIoT datasets to measure the security and accuracy of the intrusion detection system. The results show that the tree‐based algorithm achieved more than 99% accuracy which is quite higher as compared to other tested methods on the same sensor devices.
Aerodynamic and Mechanical Performance: of a High Pressure Turbine Stage in a Transient Wind Tunnel

A new transient facility for the study of time mean and unsteady aerodynamics and heat transfer in a high-pressure turbine has been commissioned and results are available. A detailed study has been made of aspects of the performance and behavior relevant to turbine mechanical design, and an understanding of the variation of the turbine operating point during the test, crucial to the process of valid data acquisition, has been obtained. In this this paper the outline concept and mode of operation of the turbine test facility are given, and the key aerodynamic and mechanical aspects of the facility’s performance are presented in detail. The variations of the those parameters used to define the turbine operating point during facility operation are examined, and the accuracy with which the turbine’s design point was achieved calculated. Aspects of the mechanical performance presented include the results of a finite element stress analysis of the loads in the turbine under operating conditions, and the performance of the rotor bearing system under these arduous load conditions. Both of these aspects present more information than has been available hitherto. Finally, the future work program and possible plans for further facility improvement are given.
Highly Sensitive Biosensor Based on Partially Immobilized Silver Nanopillars in the Terahertz Band

In this paper, a highly sensitive biosensor based on partially immobilized silver nanopillars is proposed. The working frequency of this sensor is in the terahertz band, and the range of the detected refractive index is 1.33 to 1.38. We set air holes of two different sizes on the cross-section of the optical fiber and arranged them into a hexagon. In order to improve the sensitivity, silver nanopillars were immobilized on part of the surface of the fiber cladding. The method for detecting the change of refractive index of the bio-analyte was based on local surface plasmon resonance properties of noble metal. The research recorded valuable data about the values of loss peak and full width at half maximum as well as resonance frequency shift under different setting conditions. The data present the biosensor‘s final sensitivity as 1.749 THz/RIU.
Sparse Inverse Synthetic Aperture Radar Imaging Using Structured Low-Rank Method

There has been an increasing interest in addressing the issue of high-resolution inverse synthetic aperture radar (ISAR) imaging from sparse sampling data. Traditional compressed sensing (CS) and matrix completion (MC) methods are based on sparse and low-rank constraints, respectively, which do not make full use of the structure of ISAR data. In this article, a sparse ISAR imaging algorithm using a structured low-rank approach is proposed for enhanced imaging performance. Based on the observation that the structured Hankel matrix has better low-rank property, the proposed algorithm can outperform the group of conventional MC methods in terms of accuracy to data quality and quantity. Rather than using the traditional singular value decomposition (SVD) solution of nuclear norm minimization, the proposed algorithm restates the nuclear norm via an equivalent reformulation that the structured Hankel matrix can be decomposed into two disjointed parts to avoid the dimensional expansion of the Hankel matrix. Meanwhile, the alternative direction method of multipliers (ADMMs) is applied to effectively reduce the computational complexity. Finally, the effectiveness of the proposed algorithm is further validated using the experiments on simulated and measured data.
DENOVA: Predicting Five-Factor Model using Deep Learning based on ANOVA

Determining the personality dimensions of individuals is very important in psychological research. The most well-known example of personality dimensions is the Five-Factor Model (FFM). There are two approaches 1- Manual and 2- Automatic for determining the personality dimensions. In a manual approach, Psychologists discover these dimensions through personality questionnaires. As an automatic way, varied personal input types (textual/image/video) of people are gathered and analyzed for this purpose. In this paper, we proposed a method called DENOVA (DEep learning based on the ANOVA), which predicts FFM using deep learning based on the Analysis of variance (ANOVA) of words. For this purpose, DENOVA first applies ANOVA to select the most informative terms. Then, DENOVA employs Word2Vec to extract document embeddings. Finally, DENOVA uses Support Vector Machine (SVM), Logistic Regression, XGBoost, and Multilayer perceptron (MLP) as classifiers to predict FFM. The experimental results show that DENOVA outperforms on average, 6.91%, the state-of-the-art methods in predicting FFM with respect to accuracy.
Low‐cost wideband double‐layer microstrip coupled‐line directional coupler with high directivity

In this article, a low‐cost double‐layer microstrip structure with a gap space between the two substrate layers is used to develop a microstrip coupled‐line directional coupler with high directivity. The proposed design shows a high directivity (more than 20 dB) over a wide frequency bandwidth (more than 2 GHz). The double‐layer directional coupler, designed on FR4 substrate material at 2.4 GHz provides more than 30 dB isolation. The simulation and measurement results are in good agreement. By applying a simple and low‐cost fabrication process and design, the directivity of the directional coupler is enhanced by more than 10 dB compared with a microstrip structure. © 2014 Wiley Periodicals, Inc. Microwave Opt Technol Lett 56:1570–1575, 2014
A Hybrid Particle Swarm Optimization Algorithm Based on Immune Selection for Stochastic Loader Problem

The Particle Swarm Optimization Algorithm is a new computational method for the combinatorial optimization problem, it is simple and effective, but it does suffer from the premature convergence. For overcome this problem and finding the optimal solution of the Stochastic Loader problem, we presented a new hybrid Particle Swarm Optimization Algorithm that combines with Artificial Immune Algorithm, such as immune memory, antibody promotion and suppression, immune selection and so on. Numerical example illustrates the higher efficiency and reliability of the new hybrid PSO compared with the basic Particle Swarm Optimization Algorithm.
Prosumer Energy Management for Optimal Utilization of Bid Fulfillment With EV Uncertainty Modeling

This article emphasizes the operation of a microgrid for optimal utilization of its resources. A microgrid system with photovoltaic (PV) generators, electric vehicles (EVs), electrical loads, and energy storage system is considered for the present study. Bidirectional power flow from the prosumer to the grid is proposed to provide flexibility for excess energy generated/stored at the prosumer. To address the EV uncertainty, the Markov chain model is used to predict EV availability based on historical travel data of the user. EV prediction uncertainty and the PV power uncertainty are considered in the modeling of the algorithm. The aggregator moderates on behalf of prosumers as a single entity between prosumers and the grid. The aggregator takes part in energy trading by submitting bids of specific energy volume to supply or consume in the day-ahead market. The bids are made to purchase energy at minimum prices and sell energy at maximum price. If the committed bid volumes are violated, the grid utility penalizes the aggregator and restricts their participation in energy transactions. The proposed strategy considers the energy bids made by the aggregator to regulate the rate of charging/discharging of EV. The charging/discharging schedule to fulfill the energy commitments while minimizing the operational cost for optimal microgrid operation has been optimized using a novel hybrid ant colony optimization and cuckoo search technique. A comparative analysis of the proposed technique with other popular meta-heuristic techniques to validate the efficacy of the proposed technique.
The Political Economy of Merchant Empires: Transport Costs and Long-Range Trade, 1300–1800: Was There a European “Transport Revolution” in the Early Modern Era?

INTRODUCTION I t is now a commonplace among economic historians to argue that long-distance trade has been overemphasized by students of the early modern period. The international economy was poorly integrated before 1800, and trade between the numerous units (however defined) participating in long-range commerce was rarely a central dynamic in any of them. Some scholars even deny the utility of the concept of a world economy until more recent times, insisting that we have been misled by the relatively ample documentation generated by international, transoceanic, cross-cultural exchange to exaggerate its importance. We would be better advised, the argument runs, to focus on the internal organization of smaller-scale regional economic units, for it is in the everyday lives of ordinary people far removed from the glamor of the high seas and the counting houses of the great merchants that the roots of modern economic growth must be sought. That message has much to recommend it, but it too can be exaggerated. It is a mistake to argue that long-range trade and long-range trade alone drove the process of economic modernization, provided the capital and the markets necessary to industrialization. But it is also an error to dismiss long-distance trade altogether and to claim that a purely “internal” view is adequate to economic history. It is a mistake to argue for a perfectly integrated world market by 1800, but no one can deny that the enormous increase in long-range trade during the past four centuries had produced a good deal more integration than had been the case in 1400. Long-distance trade must have its due.