Miracle-dz/UniFAR-FTUs huggingface dataset:
Ambulance detection using image processing and neural networks

Ambulance Detection using Image Processing and Neural Network is a vehicle detection and tracking system, which recognizes the vehicle (i.e., Ambulance in this case) amidst the traffic congestion. Due to the fact from past few years, the range of vehicles usage of the road is growing each day that results in traffic congestion, for better management of this traffic this system is useful. Traffic Congestion, as mentioned above, can be observed at an ever-growing pace in countries like India and Thailand, where the roads’ width and length make it impossible to make a separate lane for the emergency vehicle (like that of ambulance); Hence making it hard for the vehicle to pass through the traffic at the earliest possible time. The Ambulance tracking system is activated at the mapped junctions and that program detects the ambulance coming close to it and turns the traffic light to Green for the next 15 seconds. Geocoding is the practice of transforming addresses (like a physical address) to location information (like longitude and latitude) that can be used to locate a label on a map or to mark a grid. They plan to provide ambulances with this software to make it easy to transform addresses into a programmable format for review and retrieval. This data is converted to a system that shows all the crossings it must pass to meet the endpoint.
Human-Human Connected Dyads Learning a Visuomotor Rotation in a Targeted Reaching Task

Little is known about how two people physically coupled together (a dyad) can accomplish tasks. In a pilot study we tested how healthy inexperienced and experienced dyads learn to repeatedly reach to a target and stop while challenged with a 30 degree visuomotor rotation. We employed the Pantograph investigational device that haptically couples partners movements while providing cursor feedback, and we measured the amount and speed of learning to test a prevailing hypothesis: dyads with no experience learn faster than an experienced person coupled with a novice. We found significant straightening of movements for dyads in terms of amount of learning (2.662±0.102 cm and 2.576±0.024 cm for the novice-novice and novice-experienced groups) at rapid rates (time constants of 17.83 ± 2.85 and 18.17.17±6.72 movements), which was nearly half the learning time as solo individuals’ studies. However, we found no differences between the novice-novice and experienced-novice groups, though retrospectively our power was only 3 percent. This pilot study demonstrates new opportunities to investigate the advantages of partner-facilitated learning with solely haptic communication which and can lead to insights on control in human physical interactions and can guide the design of future human-robot-human interaction systems.
Reduction of the ERP Measurement Time by a Weighted Averaging Using Deep Learning

In clinical examination, event-related potentials (ERPs) are estimated by averaging across multiple responses, which suppresses background EEG. However, acquiring the number of responses needed for this process is time consuming. We therefore propose a method for shortening the measurement time using weighted-average processing based on the output of deep learning. Using P300 as a representative component, here we focused on the shape of the ERP and evaluated whether our method emphasizes the P300 peak amplitude more than conventional averaging, while still maintaining the waveform shape and the P300 peak latency. Thus, using either CNN or EEGNet, the correlation coefficient reflecting the waveform shape, the peak P300 amplitude, and the peak latency were evaluated and compared with the same factors obtained from conventional waveform averaging. Additionally, the degree of background EEG suppression provided by our method was evaluated using the root mean square of the pre-stimulation waveform, and the number of fewer responses required for averaging (i.e., the reduction in measurement time) was calculated.The results showed that compared with P300 values obtained through conventional averaging, our method allowed for the same shape and response latency, but with a higher amplitude, while requiring a smaller number of responses. Our method showed that by using EEGNet, measurement time could be reduced by 13.7%. This corresponds to approximately a 40-second reduction for every 5 minutes of measurement time.
CONCEPTS FOR ADAPTIVE WIND TURBINE BLADES

Bend-twist coupling in wind turbine blades has been shown to reduce both fatigue and extreme operating loads, especially when applied in conjunction with a pitch-controlled rotor. This type of coupling has been used in other industries, implemented either through biased lay-ups of fiber-reinforced materials, or with swept wings. The critical issues restricting the widespread implementation of this technology to wind turbines lies in the detailed design, manufacturing, and durability of the bend-twist-coupled blades. A series of industry contracts were initiated to evaluate/study these issues. The results of three of these studies are summarized in this paper. Global Energy Concepts (GEC) studied design issues from the perspective of traditional wind turbine blade conceptual design. Wichita State University investigated the use of braided composites with a multi-cellular blade structure. Finally, MDZ Consulting studied the possibilities of using sweep alone to achieve the desired bend-twist coupling. A common result of all the studies is that a higher stiffness fiber, such as carbon, has tremendous benefits in this application.Copyright © 2002 by ASME
A Review on Data Mining Techniques for Internet of Things

technical world. Improvement of IoT devices makes life easy for human being since it reduces the complexity in their lives through converting impossible things to possible things. However, the exponential growth of IoT devices generates large amount of information by requiring an efficient technique to handle the huge amount of data in IoT. Thus, data mining has become the best solution to extract the huge information in a large data warehouse. With this background, this paper provides a comprehensive literature review on different data mining techniques, algorithms and models which can be used in IoT with their pros and cons. Further, this paper investigates most popular applications in IoT which use data mining techniques. Finally, this review is concluded by addressing some challenges in data mining for IoT in order to open the path for future researches in this field.
Introduction of Boosting Algorithms in Continuous Non-Invasive Cuff-less Blood Pressure Estimation using Pulse Arrival Time

Blood Pressure (BP) is a critical biomarker for cardiorespiratory health. Conventional non-invasive BP measurement devices are mostly built on the principle of auscultation, oscillometry, or tonometry. The strong correlation between the Pulse Arrival Time (PAT) and BP has enabled unconstrained cuff-less BP monitoring. In this paper, we exploited that relationship for estimating Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Mean Arterial pressure (MAP) values. The proposed model involves extraction of PAT values by denoising the signals using advanced filtering techniques and finally employing machine learning algorithms to estimate cuff-less BP. The results are validated against Advancement of Medical Instrumentation (AAMI) standards and British Hypertension Society (BHS) protocols. The proposed method meets the AAMI standards in the context of estimating DBP and MAP values. The model’s accuracy achieved Grade A for both MAP and DBP values using the CatBoost algorithm, whereas it achieved grade A for MAP and Grade B for DBP using the XGBoost algorithm based on the BHS standards.
A REVIEW ON IN VITRO DETERMINATION OF BACTERICIDAL EFFECT OF GARLIC & GINGER ON STAPHYLOCOCCUS

Abstarct: The actual aim of this review article is to get a thoroughly search on different in vitro studies on bactericidal effect of staphylococcus on various extracts of garlic and ginger. Microbial pathogenecity and other infectious diseases have been controlled by use of commercially accessible antimicrobial drugs since last many years. In recent years, in sight of their valuable effects, utilize of spices or herbs is gradually increasing not only in developing countries but also in developed countries. Garlic (Allium sativum) that belongs to the family of Alliaceae is widely used in culinary and medicine. In new researches, it is reported that garlic extract has been proved to be proficient toward Streptococcus mutans, garlic extract mouth wash may be utilized as a recent line in inhibiting dental caries formation. Garlic is highly documented in exhibiting dominant antimicrobial activities. Garlic can provide proper management for bacterial growth ranging from disinfectant, antiseptic, bacteriostatic and even bactericidal characteristics. Zingiber officinale plays role as powerful food maintenance. In limited studies, ginger was found to have better usefulness than placebo in relieving disgust produced by sea dizziness, morning dizziness, despite ginger is not reported to be preferred on placebo in relieving surgical sickness. The plant is reported to have antibacterial, anti-oxidant, antiprotozoal, anti-fungal, anti-emetic, anti-rhinoviral, anti-inflammatory, anti-insecticidal activity. Staphylococcus aureus is the most medically important member in terms of pathogenicity of the group, two other less important members are Staphylococcus epidermis and Staphylococcus saprophyticus.
Ontology based adaptive systems. A case study: car environment

Rapid development of sensor devices and methods for man-machine interaction influenced the increased research in the area of adaptive, context- aware systems. In this paper we present such a system, which aims at seamlessly collecting information from humans and their domain specific surrounding,, processing this information by dynamically creating "self-organized awareness context", and reflecting the discovered context by offering appropriate services or actions in a pervasive manner. This system is based on the use of ontologies and rules. Ontologies are used for describing the characteristics of used devices (sensors and actuators), the constraints and requirements they need to comply with, while the rules are used for defining goals (actions) that need to be fulfilled as a reaction to the discovered context. The paper shows the way this adaptive, context-aware system works in the car environment. The car environment is chosen not only for the reason that an electronically equipped car can contribute to a safer driving, but also the fact that it may influence the driver's attitude and mood by observing the driver and adapting the car settings and ambient according to the driver's psycho-physiological state.
Dielectric elastomer–based energy harvesting: Material, generator design, and optimization

Electroactive polymers are soft capacitors made of thin elastic and electrically insulating films coated with compliant electrodes offering a large amount of deformation. They can either be used as actuators by applying an electric charge or used as energy converters based on the electrostatic principle. These unique properties enable the industrial development of highly efficient and environmentally sustainable energy converters, which opens up the possibility to further exploit large renewable and inexhaustible energy sources like wind and water that are widely unused otherwise. Compared to other electroactive polymer materials, polyurethanes have certain advantages over silicones and acrylates. Due to the inherently higher permittivity as well as the higher dielectric breakdown strength, the overall specific energy, a measure for the energy gain, is better by at least factor of 10, that is, more than 10 times the energy can be gained out of the same amount of material. In order to reduce conduction losses on the electrode during charging and discharging, a highly conductive bidirectional stretchable electrode has been developed. Other important material parameters like stiffness and bulk resistivity have been optimized to fit the requirements. We also report on different measures to evaluate and improve electroactive polymer materials for energy harvesting by, for example, reducing the defect occurrence and improving the electrode behavior.
Pattern transfer of directed self-assembly patterns for CMOS device applications

Abstract. A study on the optimization of etch transfer processes using 200-mm-scale production type plasma etch tools for circuit relevant patterning in the sub-30-nm pitch regime using directed self-assembly (DSA) line–space patterning is presented. This work focuses on etch stack selection and process tuning, such as plasma power, chuck temperature, and end point strategy, to improve critical dimension control, pattern fidelity, and process window. Results from DSA patterning of gate structures featuring a high-k dielectric, a metal nitride and poly Si gate electrode, and a SiN capping layer are also presented. These results further establish the viability of DSA pattern generation as a potential method for Complementary metal–oxide–semiconductor (CMOS) integrated circuit patterning beyond the 10-nm node.
A Wearable Bioimpedance Chest Patch for IoHT-Connected Respiration Monitoring

This paper presents a wearable sensor patch with real-time respiration monitoring by measuring the change in thoracic impedance resulting from breathing. A bioimpedance (BioZ) sensor with two sensing electrodes is employed to measure the chest impedance. In addition, a medical-grade infrared temperature sensor is utilized to detect body temperature. The recorded data is transmitted via a Bluetooth module to a computer for online data computation and waveform visualization. The breath-by-breath breathing rate is calculated using the time difference between two BioZ signal peaks, and the results are validated against a commercial respiration monitoring belt. Experimental tests have been conducted on five subjects in both static (i.e., sitting, supine, sleeping on the left side, sleeping on the right side, and standing) and dynamic (i.e., walking) conditions. The experiment measurements show that the BioZ sensor patch can be used to monitor the breathing rate accurately in static conditions with a low mean absolute error (MAE) of 0.71 breath-per-minute (bpm) and can detect breathing rate effectively in a dynamic environment as well. The results suggest the feasibility of using the proposed approach for respiration monitoring in daily life.
NEW PURPOSED HIGH PRECISION POWER SUPPLY FOR QUADRUPOLE MAGNETS OF ILSF USING LOW RESOLUTION DIGITAL PWM

A total number of 104 quadrupole magnets, split into 9 families, will be required for the ISLF storage ring lattice. Each quadrupole magnet has own independent power supply. In new design of quadrupole magnets, the output of two synchronized current-fed push-pull converters (one for coarse regulation and another for fine current regulation) will be added together before a synchronous rectification. By using this method, there isn't any requirement to use extra high-current output inductor. Also less power dissipation can be seen on power switches. To produce PWM signals at this design, special switching mode 16-bits microcontroller family from Microchip co was used.
Evaluation of a Motion Platform Combined with an Acoustic Virtual Reality Tool: a Spatial Orientation Test in Sighted and Visually Impaired People

To orient and move efficiently in the environment, we need to rely on multiple external and internal cues. Previous studies reported the combined use of spatialized auditory cues and self-motion information in spatial navigation and orientation. In this study, we investigated the feasibility of a setup composed of a motion platform and an acoustic virtual reality tool with sighted and visually impaired participants. We compared the performance in a self-motion discrimination task with and without auditory cues. The results revealed good usability of the setup and increased precision with auditory cues for visually impaired people.
Effects of alcoholic extract of walnut pulp on adult albino male rats fertility treated with Citalopram

This study was accomplished to explore the role of ethanol extract of walnut pulp on adult albino male rats fertility treated with Citalopram . Twenty eight male rats were divided into four equal groups. One served as control, and the others second and thired groups were given 10, 20,mg/kg B.Wt. of ethanolic extract of walnut pulp respectivly, in addition to 0.6mg/kg citalopram, while forht group was treated by 0.6mg/kg citalopram only. After 30 as well as 60 days of treatments we measured serum LH, FSH and Testosterone.The results showed a significant elevation in serum LH, FSH and Testosterone in animals of second and third groups after thirty days of treatment, while asignificant reduction in these parameters were recorded in rats of forth group after 60 days. Key word :Ethanol extract of walnut pulp , albino rats , Citalopram , LH , FSH ,Testosterone.
Between a Rock and a Hard Place: The Role of HE and Foundation Degrees in Workforce Development.

Purpose – The purpose of this article is to explore how higher education (HE) institutions are responding to the workforce remodelling agenda of public services and the emergence of “para‐professions” within traditionally low paid/low status employment. Design/methodology/approach – With reference to recent research, the article reviews the authors' experience of foundation degrees (FDs) in education and explores tensions in managing the competing needs of the varying stakeholders. Findings – A model of work‐based learning (WBL) results from the study, which includes consideration of the following key areas: employer engagement; CPD and professional bodies – external validation and professional recognition; progression into HE through the workforce; and pedagogy of WBL Research limitations/implications – This article identifies a need for the systematic examination of the issues raised by the implementation of FDs as CPD for employed staff. The assumption that FD provision for employees results in more effective WBL is challenged. The importance of FDs in accreditation for a range of occupations in the Children's Workforce also suggests a need for research into the ”professionalisation” of these occupations. Practical implications – The issue of employer engagement is fundamental and that paper argues that HE has a crucial role to play but that ensuring employer engagement requires responsiveness on the part of university structures, as well as the capacity to stimulate employer engagement and/or sanction lack of employer engagement at the level of individual programmes. Originality/value – This article provides information about the new phenomenon of implementation of FDs to support workforce development.
Field Testing of Water Source Heat Pump Systems in Chongqing of China

As an application technology of renewable energy resource, water source heat pump (WSHP) has been paid more attention on. WSHP have been practiced especially for saving building energy consumption in Chongqing of China since there is abound water resources. However, it was found that some systems were not operated very well without achieving expected energy efficiency. Taking three real projects which use WSHP for heating and cooling of buildings in Chongqing city to test in field, key parameters were measured and operation performances were analyzed. The influences of water temperature and partial load ratio on system energy efficiency were studied. Based on existing problems, strategies for improving system energy performance are suggested from aspects of design and operating. Dynamic load hourly simulation plays a key role to determine appropriately the size and the form of system. More efforts have to be put on water pumps arrangement to save energy consumed for water transportation which accounts for large part of system energy. The temperature difference and water quality of water source should be controlled according actual operating conditions. The integrated systems and operation strategies under partial load are also beneficial for efficiency improvement.
Analysis of Biometric Sensor Data for Predicting Fatigue: A Framework Towards Reducing Work-Related Musculoskeletal Disorders in Aviation Manufacturing Workers

Work-Related Musculoskeletal Disorders (WMSDs) transpire when injuries to the musculoskeletal system (e.g. muscles, ligaments, tendons, and nerves) occur due to high fatigue inducing work-related activities, where repetitive movements and muscle strain are prevalent. However, it is challenging to quantify the risk of injury due to the assortment of tasks that factory workers may perform. Nevertheless, wearable sensors are a viable outlet that can unobtrusively capture biometric data in order to calculate objective measures, such as fatigue, which increases the risk of developing WMSDs. This paper presents a novel wearable sensor-based ergonomic monitoring system (ErgoRelief), which has been designed to predict fatigue within the context of aviation factory work. An experiment has been undertaken whereby thirty participants completed a series of repetitive tasks whilst wearing our sensor system. Results of multiple linear regression models demonstrate a maximum Adjusted R2 Score of 0.9259.
A general class of current amplifier-based biquadratic filter circuits

A general class of current amplifier-based biquadratic filter circuits is presented which is capable of realizing arbitrary filter functions including the lowpass, highpass, and the bandpass transfer function. These realizations are derived from a class of well-known low sensitivity single amplifier biquadratic (SAB) filter circuits using the principle of adjoint networks. The salient features of the proposed current amplifier filter circuits are that they are synthesized using the same procedure circuits as their op-amp based SAB circuit counterparts, and furthermore, possess the same sensitivities to component variations as the original SAB circuits. <<ETX>>
Analysis of Skin-Worn Thermoelectric Generators for Body Heat Energy Harvesting to Power Wearable Devices

The rapid growth of wearable electronic devices motivates investigation of powering such devices using energy harvesting, with the long-term goal of continuous operation without the need to recharge or replace batteries. In this work, we present a study conducted using a wearable device to measure the voltage, power, and energy that can be harvested continuously from human body heat using a thermoelectric generator (TEG) worn on the skin surface. Using a TEG worn on the arm, we demonstrate an average of 22.9 μW continuous maximum power delivery across three subjects, corresponding to 1.43 μW/cm2 power density. Additionally, the large thermal gradient across the TEG when first placed on the skin provides sufficient voltage output across a matched load to enable cold start of state-of-the-art DC-DC boost converters. Overall, the results demonstrate sufficient power density and voltage output provided by centimeter-scale TEGs for operating battery-less, wearable sensor devices using body heat energy harvesting.