Miracle-dz/UniFAR-FTUs huggingface dataset:
A Modified Migrating Bird Optimization For University Course Timetabling Problem

University course timetabling problem is a dilemma which educational institutions are facing due to various demands to be achieved in limited resources. Migrating bird optimization (MBO) algorithm is a new meta-heuristic algorithm which is inspired by flying formation of migrating birds. It has been applied successfully in tackling quadratic assignment problem and credit cards fraud detection problem. However, it was reported that MBO will get stuck in local optima easily. Therefore, a modified migrating bird optimization algorithm is proposed to solve post enrolment-based course timetabling. An improved neighbourhood sharing mechanism is used with the aim of escaping from local optima. Besides that, iterated local search is selected to be hybridized with the migrating bird optimization in order to further enhance its exploitation ability. The proposed method was tested using Socha’s benchmark datasets. The experimental results show that the proposed method outperformed the basic MBO and it is capable of producing comparable results as compared with existing methods that have been presented in literature. Indeed, the proposed method is capable of addressing university course timetabling problem and promising results were obtained.
4.3.3 Systems Engineering Implications of Neuroscience Discoveries

Systems engineering practices and heuristics generally reflect implicit assumptions that participants in the systems engineering process behave rationally, and that communications between stakeholders work effectively. Sometimes these assumptions prove accurate, and the systems engineering process is successful. But many times the systems engineering process does not obtain the intended results, even though practitioners and stakeholders have good intentions, extensive knowledge, and impressive skills. Developments in cognitive neuroscience and behavioral economics over recent decades offer insights into how and why humans may behave irrationally, and why human communication may not work as intended. The purpose of this paper is to highlight some interesting discoveries in cognitive neuroscience and behavioral economics, and discuss their implications for systems engineering.
Adjustable Autonomy for Human-Centered Autonomous Systems on Mars

We expect a variety of autonomous systems, from rovers to life-support systems, to play a critical role in the success of manned Mars missions. The crew and ground support personnel will want to control and be informed by these systems at varying levels of detail depending on the situation. Moreover, these systems will need to operate safely in the presence of people and cooperate with them effectively. We call such autonomous systems human-centered in contrast with traditional Oblack-boxO autonomous systems. Our goal is to design a framework for human-centered autonomous systems that enables users to interact with these systems at whatever level of control is most appropriate whenever they so choose, but minimize the necessity for such interaction. This paper discusses on-going research at the NASA Ames Research Center and the Johnson Space Center in developing human-centered autonomous systems that can be used for a manned Mars mission.
Impacts of stocking density rates on welfare, growth, and hemato-biochemical profile in broiler chickens

Objective: The study investigated the effect of different stocking density (SD) rates on the welfare, growth, and hemato-biochemical parameters in broiler chickens. Materials and Methods: 106 broiler chicks of 10 days old were used and assigned into four groups: A, B, C, and D. The chicks of group A were reared in floor space containing one bird per square foot area (SD1.0). The chicks of groups B, C, and D were reared at 1.5, 2.0, and 2.5 birds per square foot area (SD1.5, SD2.0, and SD2.5). Welfare, body weight, and hemato-biochemical parameters were assessed and monitored by physical observation and laboratory methods. Results: The birds reared at SD2.0, and SD2.5 rates showed increased panting breathing. Wet feces adhered below the vent. There were a significant number of birds showing dirtiness of body and feathers. Birds reared in SD2.5 were familiar with moist litters and high ammonia smell. Foot-pad dermatitis, scratches, and blister formation were detected in the leg. The study revealed that the higher SD negatively correlated to the welfare behavior indicators. Live body weight was significantly (p < 0.05) decreased in birds reared at higher SD rates. Birds housed in SD1.0 and SD1.5 are optimum for body weight and improved feed conversion ratio. The hemato-biochemical parameters of birds reared at various SD rates did not differ. The total leucocyte count increased significantly, while total serum proteins decreased gradually as SD rates increased. Conclusion: This work explores that higher SD negatively affects welfare and growth performance in broiler chickens.
Active filter control using a sliding mode approach

Load distortion currents in the three phase system can be suppressed by employing active power filters. This paper describes a sliding mode control strategy of the three phase voltage source converter. The validity of the control circuit is verified by simulation results. Considering the new control approach, the dynamics of the active filter as well as its compensating characteristics are also analyzed through energy storage elements. The system performance is valid for steady and transient states in the three phase circuits. <<ETX>>
MEASURING THE PERFORMANCE OF VOLUNTARY

In the cur rent pol itical and econom ic climat e, the re are ra pidly es cal ating dem ands from publ ic fu nders an d ot her stake hol der s for indi ca tor s wh ich c an cap tur e the ac hievem ent s and impa cts of the vo lunta ry se cto r. Having clar ified the c ont ext of the se d emands , the pr im ar y aim of this ar tic le is to deve lop cr iteria fo r meas uring th e ‘per for m anc e of vol unt ar y or gani zat ions. Thi s is under taken b y mar rying relevant int er nat ional the ore tica l literatur e s ugges tive of the ir roles and c ont ribut ions with a ‘p roduc tion of we lfare appro ach, which ha s a pr oven track recor d in the eva luat ion of hum an ser vices. Eight doma ins of per for manc e ar e sugge sted (econom y, effect ivenes s, efficie ncy; choi ce /p luralism; equi ty; part icipat ion; innova tion and a dvoca cy) , em bra cing twe nty -two separ ate indi ca tor se ts.
A dual-b and RF front-end of direct conversion receiver for wireless CDMA cellular phones with GPS capability

A highly integrated direct conversion receiver for cellular code division multiple access (CDMA) and GPS applications is successfully developed using a 0.5-/spl mu/m SiGe BiCMOS technology. The receiver consists of two low-noise amplifiers (LNAs), a dual-band mixer, two voltage-controlled oscillators (VCOs), a local-oscillator signal generation block, and channel filters. The CDMA LNA achieves a noise figure of 1.3 dB, an input-referred third-order intercept point (IIP3) of 10.9 dBm, and a gain of 15.3 dB with a current consumption of 9.8 mA in the high-gain mode. The mixer for the CDMA mode achieves an uncalibrated input-referred second-order intercept point of 53.7 dBm, an IIP3 of 6.4 dBm, a noise figure of 7.2 dB and a voltage gain of 37.2 dB. The phase noise of the CDMA VCO is approximately -133 dBc/Hz at a 900-kHz offset from a 1.762-GHz operating frequency. It exceeds all the CDMA requirements when tested on a handset.
The Application of Image Processing Technology to Flow Discrimination from Float Flowmeters

A new method to get flow rate from a float flow meter automatically by image processing technique is put forward. Images of float flowmeters which are captured by a camera link are cropped, strengthened, filtered and binaried by certain pre-processings. Firstly, one-dimensional array is generated by the binary-picture. An accumulation by its columns and averaged the peak formed by the accumulation is made. Finally, the accurate position of the float can be recognized. Some simulation experiments show that the resolution of measurement by the image technique can be 1/10 of the minimum scale of glass float flowmeters. Some errors which include the angle of elevation and depression caused by cameras are discussed.
Peltzman Revisited: Quantifying 21st Century Opportunity Costs of FDA Regulation

This paper revisits Peltzman (1973) in light of two recent opportunities to quantitatively assess tradeoffs in drug regulation. First, reduced regulatory barriers to drug manufacturing associated with the 2017 reauthorization of Generic Drug User Fee Amendments were followed by significantly more entry and lower consumer prices for prescription drugs. Using a simple and versatile industry model and historical data on entry, I find that easing generic restrictions discourages innovation, but this welfare cost is more than offset by consumer benefits from enhanced competition, especially after 2016. Second, accelerated vaccine approval in 2020 had unprecedented net benefits as it not only improved health but substantially changed the trajectory of the wider economy. The evidence suggests that cost-benefit analysis of FDA regulation is incomplete without accounting for substitution toward potentially unsafe and ineffective treatments that are both outside FDA jurisdiction and heavily utilized prior to FDA approval. Moreover, the policy processes initiating these 21st century regulatory changes show a clear influence of Peltzman’s 1973 findings. Casey B. Mulligan University of Chicago Department of Economics 1126 East 59th Street Chicago, IL 60637 and NBER c-mulligan@uchicago.edu
Biomimetic Artificial Joints Based on Multi-Material Pneumatic Actuators Developed for Soft Robotic Finger Application

To precisely achieve a series of daily finger bending motions, a soft robotic finger corresponding to the anatomical range of each joint was designed in this study with multi-material pneumatic actuators. The actuator as a biomimetic artificial joint was developed on the basis of two composite materials of different shear modules, and the pneumatic bellows as expansion parts was restricted by frame that made from polydimethylsiloxane (PDMS). A simplified mathematical model was used for the bending mechanism description and provides guidance for the multi-material pneumatic actuator fabrication (e.g., stiffness and thickness) and structural design (e.g., cross length and chamber radius), as well as the control parameter optimization (e.g., the air pressure supply). An actuation pressure of over 70 kPa is required by the developed soft robotic finger to provide a full motion range (MCP = 36°, PIP = 114°, and DIP = 75°) for finger action mimicking. In conclusion, a multi-material pneumatic actuator was designed and developed for soft robotic finger application and theoretically and experimentally demonstrated its feasibility in finger action mimicking. This study explored the mechanical properties of the actuator and could provide evidence-based technical parameters for pneumatic robotic finger design and precise control of its dynamic air pressure dosages in mimicking actions. Thereby, the conclusion was supported by the results theoretically and experimentally, which also aligns with our aim to design and develop a multi-material pneumatic actuator as a biomimetic artificial joint for soft robotic finger application.
A 0.61-μJ/Frame Pipelined Wired-logic DNN Processor in 16-nm FPGA Using Convolutional Non-Linear Neural Network

A pipelined wired-logic deep neural network (DNN) processor implemented in a 16-nm field-programmable gate array (FPGA) is presented. The latency and power required for memory access are minimized by utilizing the wired-logic architecture, thus enabling low power and high throughput operation. One technical issue with the wired-logic architecture is that it requires a lot of hardware resources. To reduce them, two core technologies are developed: (1) a convolutional non-linear neural network (CNNN) and (2) a pipeline-type neuron cell. The CNNN optimizes both the network structure and the non-linear activation function of each neuron by using a newly developed back-propagation-based training method. While conventional reinforcement learning can train only a small size network thus limiting its application to handwritten number recognition, the proposed CNNN enables a larger network size making it applicable to object recognition. The pipeline-type neuron cell has a small look-up table (LUT) to process non-linear functions using only a small amount of hardware resources. These two technologies enable the implementation of the entire network on a single FPGA chip with the wired-logic architecture. Three types of CNNN trained on the CIFAR-10 dataset are implemented in 16-nm FPGAs. An energy efficiency of 0.09, 0.12, and $0.61~\mu \text{J}$ /frame is achieved with 70%, 75%, and 82% accuracy, respectively. Compared with a state-of-the-art accelerator using a binary neural network (BNN), the energy efficiency is improved by more than two orders of magnitude.
Closed-Form Expressions for the Design of BAW CRF Acoustic Inverters

A bulk acoustic wave coupled resonator filter is a device in which two thin film bulk acoustic wave resonators are stacked on top of each other separated by a set of passive layers which control the degree of acoustic interaction between resonators contributing to the conformation of the radiofrequency passband response. The set of passive layers implements an impedance inverter which has to fulfill the desired coupling value. The variation of the acoustic lengths of the coupling layers gives the degree of freedom to implement the desired inverter. In this work, a set of closed-form expressions are provided to obtain the coupling layers thicknesses without any time-consuming optimization procedure. The provided solution gives an explanation to the underlying fundamentals that take place in a successful optimization procedure.
Wideband low noise CMOS transimpedance amplifier for gigaHertz operation

A novel low noise CMOS common gate transimpedance amplifier is presented. Simulated performances gives a 1.2 GHz bandwidth, 1.6 kΩ transimpedance gain, and very low input referred current noise. Results are comparable to those of a recent common base BiCMOS transimpedance amplifier.
Design, Modeling, and Initial Experiments on Microscale Amplification Device

This article proposes the design of several microelectromechanical amplification devices formed of many identical microunits that are connected in a serial–parallel configuration, each being individually actuated and amplifying its own input motion. The microdevices realize the border-crossing from the micro-to the meso-scale displacement domain as they combine the micron-level individual inputs into millimeter-range output levels. The base structural unit is a flexure-based compliant device that is capable of transforming the input from a thermal actuator into an amplified displacement, about a direction perpendicular to the input one. The base unit is designed based on performance criteria, such as displacement amplification, input stiffness and output stiffness by utilizing finite element simulation, and an algorithm based on closed-form compliance equations of the incorporated flexure hinges. The microelectromechanical amplification device is monitored by means of embedded capacitive displacement sensors for the input port. The feasibility of the device design was verified through a numerical simulation and some initial experimental results are presented.
Verification of Vibration Power Generator Model for Prediction of Harvested Power

This paper deals with modeling of a vibrational power generator and verification of a complex generator model for prediction of harvested power. The power generator is an electromagnetic device, which uses ambient energy of mechanical vibrations for generating useful electrical energy. This energy harvesting device constitutes a complex mechatronic system consisting of a resonance mechanism, electromechanical converter, power management (electronics and energy storage) and a powered device. When this system is placed in environment with sufficient mechanical vibration, the generator harvests energy and it can be used as autonomous source of electrical energy for powering of wireless sensors in remote applications. The verified simulation model of this device can provide a prediction of possible harvested power without any physical position of this device in a vibratory environment (only acceleration measurement is used as input).
PHOTOVOLTAIC PERFORMANCE OF A-SI:H HOMOJUNCTION P-I-N SOLAR CELLS : A COMPUTER SIMULATION STUDY

A first principles computer model for simulating the performance of amorphous semiconductor solar cells has been developed. With a suitable choice of parameters, the calculated results for the illuminated J‐V characteristics and solar cell quantum efficiencies are shown to agree well with experiments. The model has been used in this paper to study the sensitivity of the light J‐V characteristics to various device and material parameters in p‐i‐n homojunction solar cells. The single most important factor controlling the open circuit voltage, short circuit current, fill factor, and cell efficiency is the transparent conducting oxide/p‐a‐Si:H contact barrier height φbo, when φbo is less than a certain critical value. Also shown is that practically no improvement in cell performance can be achieved by decreasing the dangling‐bond midgap state density, described by Gaussian distribution functions, to lower than 1016 cm−3, unless the valence‐band tail states are also reduced. Moreover, results indicate that lig.
Interpretable Retinal Disease Classification from OCT Images Using Deep Neural Network and Explainable AI

Deep Learning Models (DNN) are being used extensively for medical image classification such as MRI, OCT, x-ray in recent years. The proposed model revolves around the analysis of macular Optical Coherence Tomography (OCT) images to distinguish three eye-related anomalies: Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME), and accumulation of Drusen from OCT images of patients. At first, the dataset was acquired and various pre-processing steps were performed on it. Then we performed a split on the dataset into train-test-validation sets with different numbers of images in each of them. Afterward, we applied pre-trained Resnet, Inception V3, and EfficientNet models in order to classify the images. From our experiment, we achieved the best accuracy of 96.9% from ResNet. Finally, we applied Explainable AI (XAI) framework though the LIME framework in an attempt to explain the reasons for misclassifications. Alongside achieving slightly better accuracy compared to the base model, the purpose of our research is to explain the reasons behind classification errors which can be utilized in the future to develop better models.
Reconocimiento automatizado de señales bioacústicas: Una revisión de métodos y aplicaciones

During the past decade, numerous research studies and applications on automated bioacoustic monitoring have been published; however, such studies are scattered in the literature of engineering and life sciences. This paper presents a review on fundamental concepts of automated acoustic monitoring. Our aim is to compare and categorize —in a taxonomy of techniques DSP/PR— the contributions of published research studies and applications; in order to suggest some directions for future research and highlight challenges and opportunities related to the deployment of this technology in Colombia. PACS: 43.60. -c, 43.60. Lq, 43.80. -n
Shear Strength Model for Steel Fiber Reinforced Concrete Beams without Stirrup Reinforcement

A simple model is presented to estimate the shear strength of steel fiber reinforced concrete (FRC) beams without stirrup reinforcement. The model was developed on the basis of observations from tests of 27 large-scale beams under monotonically increased concentrated loading. Three types of hooked steel fibers were evaluated in volume fractions ranging between 0.75% (59 kg/m3 or 100 lb/yd3) and 1.5% (118 kg/m3 or 200 lb/yd3). All but one beam failed in shear either prior to or after flexural yielding. In the proposed model, shear in steel FRC beams is assumed to be resisted by shear stress carried in the compression zone and tension transferred across diagonal cracks by steel fibers. Shear carried in the compression zone is estimated by using the failure criterion for concrete subjected to combined compression and shear proposed by Bresler and Pister. The contribution from fiber reinforcement to shear strength, on the other hand, is tied to material performance obtained through standard ASTM 1609 four.
A hybrid method of FEM, modified NSGAII and TOPSIS for structural optimization of sandwich panels with corrugated core

Low weight and high load capacity are remarkable advantages of sandwich panels which make them more considerable by structure designers. In this paper, multi-objective optimization of sandwich panels with corrugated core is carried out using modified Non-dominated Sorting Genetic Algorithm (NSGAII) considering two objective functions: the structure’s weight and deflection. Deflection of the panel as one of the objective functions is calculated using finite element analysis by commercial software ANSYS. To employ this FE model in the multi-objective optimization process, the software products ANSYS and MATLAB have been coupled together during the run time. Finally, nearest to ideal point (NIP) method and technique for ordering preferences by similarity to ideal solution (TOPSIS) method are used to find the some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts.
Repulsive force actuated rotary micromirror

In this paper, a novel repulsive force based rotary micromirror is proposed. A repulsive force is produced in the rotary micromirror and the mirror plate is pushed up and away from the substrate. Therefore the rotation angle of the micromirror is not limited to the space underneath the mirror plate and thus the "pull-in" effect is completely circumvented. The novel rotary micromirror can achieve a large rotation angle with a large mirror plate. In addition the novel micromirror has a very simple structure and can be fabricated by standard surface micromachining technology. Numerical simulation is used to verify the working principle of the novel micromirror. A prototype of the novel rotary micromirror is fabricated by a commercially available surface microfabrication process called MUMPs. The prototype has a mirror size of 300μm x 300μm. The experimental measurements show that the prototype can achieve a mechanical rotation of 2.25 degrees (an optical angle of 4.5 degrees) at a driving voltage of 170 volts. A conventional surface micromachined attractive force based rotary micromirror of the same size can only achieve an angle of 0.1~0.2 degree.
Labor Productivity Growth and Industrialization in Africa

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.