Search results for: automatic voltage regulator

Authors: Fatima Zohra Rahou, A.Guen Bouazza, B. Bouazza

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SOI TRI GATE FinFET transistors have emerged as novel devices due to its simple architecture and better performance: better control over short channel effects (SCEs) and reduced power dissipation due to reduced gate leakage currents. As the oxide thickness scales below 2 nm, leakage currents due to tunneling increase drastically, leading to high power consumption and reduced device reliability. Replacing the SiO2 gate oxide with a high-κ material allows increased gate capacitance without the associated leakage effects. In this paper, SOI TRI-GATE FinFET structure with use of high K dielectric materials (HfO2) and SiO2 dielectric are simulated using the 3-D device simulator Devedit and Atlas of TCAD Silvaco. The simulated results exhibits significant improvements in the performances of SOI TRI GATE FinFET with gate oxide HfO2 compared with conventional gate oxide SiO2 for the same structure. SOI TRI-GATE FinFET structure with the use of high K materials (HfO2) in gate oxide results into the increase in saturation current, threshold voltage, on-state current and Ion/Ioff ratio while off-state current, subthreshold slope and DIBL effect are decreased.

Keywords: technology SOI, short-channel effects (SCEs), multi-gate SOI MOSFET, SOI-TRI Gate FinFET, high-K dielectric, Silvaco software

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Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio

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Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.

Keywords: prediction, hyaluronic acid, treatment, artificial intelligence

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Authors: Nouh Zeggai, Lucas Debrux, Fabien Parrain, Brahim Dkhil, Martino Lobue, Morgan Almanza

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Refrigeration and air conditioning are some of the most used energies in our daily life, especially vapor compression refrigeration. Electrocaloric material might appears as an alternative towards solid-state cooling. polyvinylidene fluoride (PVDF) based polymer has shown promising adiabatic temperature change (∆T) and entropy change (∆S). There is practically no limit to the electric field that can be applied, except the one that the material can withstand. However, when working with a large surface as required in a device, the chance to have a defect is larger and can drastically reduce the voltage breakdown, thus reducing the electrocaloric properties. In this work, we propose to study how the characteristic of a single film are transposed when going to multilayer. The laminator and the hot press appear as two interesting processes that have been investigating to achieve a multilayer film. The study is mainly focused on the breakdown field and the adiabatic temperature change, but the phase and crystallinity have also been measured. We process one layer-based PVDF and assemble them to obtain a multilayer. Pressing at hot temperature method and lamination were used for the production of the thin films. The multilayer film shows higher breakdown strength, temperature change, and crystallinity (beta phases) using the hot press technique.

Keywords: PVDF-TrFE-CFE, multilayer, electrocaloric effect, hot press, cooling device

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Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

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Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

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Authors: Samson Mil'shtein, Dhawal N. Asthana

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The presented heterostructure n-p-n bipolar transistor is comprised of Ge/GaAs heterojunctions consisting of 0.15µm thick emitter and 0.65µm collector junctions. High diffusivity of carriers in GaAs base was major motivation of current design. We avoided grading of the base which is common in heterojunction bipolar transistors, in order to keep the electron diffusivity as high as possible. The electrons injected into the 0.25µm thick p-type GaAs base with not very high doping (1017cm-3). The designed HBT enables cut off frequency on the order of 150GHz. The Ge/GaAs heterojunctions presented in our paper have proved to work better than comparable HBTs having GaAs bases and emitter/collector junctions made, for example, of AlGaAs/GaAs or other III-V compound semiconductors. The difference in lattice constants between Ge and GaAs is less than 2%. Therefore, there is no need of transition layers between Ge emitter and GaAs base. Significant difference in energy gap of these two materials presents new scope for improving performance of the emitter. With the complete structure being modelled and simulated using TCAD SILVACO, the collector/ emitter offset voltage of the device has been limited to a reasonable value of 63 millivolts by the dint of low energy band gap value associated with Ge emitter. The efficiency of the emitter in our HBT is 86%. Use of Germanium in the emitter and collector regions presents new opportunities for integration of this vertical device structure into silicon substrate.

Keywords: Germanium, Gallium Arsenide, heterojunction bipolar transistor, high cut-off frequency

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Authors: Kathryn H. Yull, Lina T. Al Kury, Frank Christopher Howarth

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Cardiovascular diseases are frequently reported in patients with Type-1 Diabetes mellitus (DM). In addition to changes in cardiac muscle inotropy, electrical abnormalities are also commonly observed in these patients. In the present study, using streptozotocin (STZ) rat model of Type-1 DM, we have characterized the changes in L-type calcium channel activity in single atrioventricular nodal (AVN) myocytes. Ionic currents were recorded from AVN myocytes isolated from the hearts of control rats and from those with STZ-induced diabetes. Patch-clamp recordings were used to assess changes in cellular electrical activity in individual myocytes. Type-1 DM significantly altered the cellular characteristics of L-type calcium current (ICaL). A reduction in peak ICaL density was observed, with no corresponding changes in the activation parameters of the current. ICaL also exhibited faster time-dependent inactivation in AVN myocytes from diabetic rats. A negative shift in the voltage dependence of inactivation was also evident. These findings demonstrate that experimentally–induced type-1 DM significantly alters AVN L-type calcium channel cellular electrophysiology. The changes in ion channel activity may underlie the abnormalities in the cardiac electrical function that contribute to the high mortality levels in patients with DM.

Keywords: cardiac, ion-channel, diabetes, atrioventricular node, calcium channel

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Authors: M. Ghanbari, S. Hossainpour, G. Rezazadeh

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In this paper, longitudinal vibration of a micro-beam in micro-scale fluid media has been investigated. The proposed mathematical model for this study is made up of a micro-beam and a micro-plate at its free end. An AC voltage is applied to the pair of piezoelectric layers on the upper and lower surfaces of the micro-beam in order to actuate it longitudinally. The whole structure is bounded between two fixed plates on its upper and lower surfaces. The micro-gap between the structure and the fixed plates is filled with fluid. Fluids behave differently in micro-scale than macro, so the fluid field in the gap has been modeled based on micro-polar theory. The coupled governing equations of motion of the micro-beam and the micro-scale fluid field have been derived. Due to having non-homogenous boundary conditions, derived equations have been transformed to an enhanced form with homogenous boundary conditions. Using Galerkin-based reduced order model, the enhanced equations have been discretized over the beam and fluid domains and solve simultaneously in order to obtain force response of the micro-beam. Effects of micro-polar parameters of the fluid as characteristic length scale, coupling parameter and surface parameter on the response of the micro-beam have been studied.

Keywords: micro-polar theory, Galerkin method, MEMS, micro-fluid

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Authors: Zhongyang Sun, Shu Zhang, Manjiang Xie

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Emerging evidence indicates that microRNAs (miRNAs) play important roles in modulating osteoblast function and bone formation. However, the influence of miRNA on osteoblast proliferation and the possible mechanisms underlying remain to be defined. In this study, we aimed to investigate whether miR-103 regulates osteoblast proliferation under simulated microgravity condition through regulating Cav1.2, the primary subunit of L-type voltage sensitive calcium channels (LTCCs). We first investigated the effect of simulated microgravity on osteoblast proliferation and the outcomes clearly demonstrated that the mechanical unloading inhibits MC3T3-E1 osteoblast-like cells proliferation. Using quantitative Real-Time PCR (qRT-PCR), we provided data showing that miR-103 was up-regulated in response to simulated microgravity. In addition, we observed that up-regulation of miR-103 inhibited and down-regulation of miR-103 promoted osteoblast proliferation under simulated microgravity condition. Furthermore, knocking-down or over-expressing miR-103, respectively, up- or down-regulated the level of Cav1.2 expression and LTCCs currents, suggesting that miR-103 acts as an endogenous attenuator of Cav1.2 in osteoblasts under the condition of simulated microgravity. More importantly, we showed that the effect of miR-103 on osteoblast proliferation was diminished in simulated microgravity, when co-transfecting miR-103 mimic or inhibitor with Cav1.2 siRNA. Taken together, our data suggest that miR-103 inhibits osteoblast proliferation mainly through suppression of Cav1.2 expression under simulated microgravity condition. This work may provide a novel mechanism of microgravity-induced detrimental effects on osteoblast, identifying miR-103 as a novel possible therapeutic target in bone remodeling disorders in this mechanical unloading.

Keywords: microRNA, osteoblasts, cell proliferation, Cav1.2, simulated microgravity

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Authors: Magali Mari, Fabrice Clement

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The present study investigated the influence of implicit stereotypes on adults’ visual information processing, using an eye-tracking device. Implicit stereotyping is an automatic and implicit process; it happens relatively quickly, outside of awareness. In the presence of a member of a social group, a set of expectations about the characteristics of this social group appears automatically in people’s minds. The study aimed to shed light on the cognitive processes involved in stereotyping and to further investigate the use of eye movements to measure implicit stereotypes. With an eye-tracking device, the eye movements of participants were analyzed, while they viewed everyday scenes depicting women and men in congruent or incongruent gender role activities (e.g., a woman ironing or a man ironing). The settings of these scenes had to be analyzed to infer the character’s role. Also, participants completed an implicit association test that combined the concept of gender with attributes of occupation (home/work), while measuring reaction times to assess participants’ implicit stereotypes about gender. The results showed that implicit stereotypes do influence people’s visual attention; within a fraction of a second, the number of returns, between stereotypical and counter-stereotypical scenes, differed significantly, meaning that participants interpreted the scene itself as a whole before identifying the character. They predicted that, in such a situation, the character was supposed to be a woman or a man. Also, the study showed that eye movements could be used as a fast and reliable supplement for traditional implicit association tests to measure implicit stereotypes. Altogether, this research provides further understanding of implicit stereotypes processing as well as a natural method to study implicit stereotypes.

Keywords: eye-tracking, implicit stereotypes, social cognition, visual attention

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Authors: Aminu Yakubu Umar

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X-ray is the major contributor to the effective dose of both the patient and the personnel. Because of the radiological risks involved, it is usually recommended that dose to patient from X-ray be kept as low as reasonably achievable (ALARA) with adequate image quality. The implementation of quality assurance in diagnostic radiology can help greatly in achieving that, as it is a technique designed to reduce X-ray doses to patients undergoing radiological examination. In this study, quality control was carried out in six hospitals, which involved KVp test, evaluation of total filtration, test for constancy of radiation output, and check for mA linearity. Equipment used include KVp meter, Rad-check meter, aluminum sheets (0.1–1.0 mm) etc. The results of this study indicate that, the age of the X-ray machines in the hospitals ranges from 3-13 years, GHI and GH2 being the oldest and FMC being the newest. In the evaluation of total filtration, the HVL of the X-ray machines in the hospitals varied, ranging from 2.3-5.2 mm. The HVL was found to be highest in AHC (5.2 mm), while it was lowest in GH3 (2.3 mm). All HVL measurements were done at 80 KVp. The variation in voltage accuracy in the hospitals ranges from 0.3%-127.5%. It was only in GH1 that the % variation was below the allowed limit. The test for constancy of radiation output showed that, the coefficient of variation ranges from 0.005–0.550. In GH3, FMC and AHC, the coefficient of linearity were less than the allowed limit, while in GH1, GH2 and GH4 the coefficient of linearity had exceeded the allowed limit. As regard to mA linearity, FMC and AHC had their coefficients of linearity as 0.12 and 0.10 respectively, which were within the accepted limit, while GH1, GH3 and GH4 had their coefficients as 0.16, 0.69 and 0.98 respectively, which exceeded the allowed limit.

Keywords: radiation, X-ray output, quality control, half-value layer, mA linearity, KVp variation

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Authors: Ashok Kalagura

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This paper presents a data-mining model for fault-zone identification of flexible AC transmission systems (FACTS)-based transmission line including a thyristor-controlled series compensator (TCSC) and unified power-flow controller (UPFC), using ensemble decision trees. Given the randomness in the ensemble of decision trees stacked inside the random forests model, it provides an effective decision on the fault-zone identification. Half-cycle post-fault current and voltage samples from the fault inception are used as an input vector against target output ‘1’ for the fault after TCSC/UPFC and ‘1’ for the fault before TCSC/UPFC for fault-zone identification. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network, including noisy environment providing a reliability measure of 99% with faster response time (3/4th cycle from fault inception). The results of the presented approach using the RF model indicate the reliable identification of the fault zone in FACTS-based transmission lines.

Keywords: distance relaying, fault-zone identification, random forests, RFs, support vector machine, SVM, thyristor-controlled series compensator, TCSC, unified power-flow controller, UPFC

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Authors: Shweta Maheshwari, Anish Dua

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Hematological changes reflect the adverse effects of heavy metals on fish. Hematology is a valuable tool to evaluate pathological condition of the fish. It helps in diagnosing the structural and functional status of fish exposed to toxicants. Morphological alteration in erythrocytes due to environmental stress can be studied through ultra-structural analysis. The aim of the present study was to assess the toxicity of mercuric chloride on red blood cells of an air breathing fish, Channa punctatus. Fish were subjected to chronic experiments using three sublethal concentration of mercuric chloride (0.020mg/L, 0.027mg/L, 0.040mg/L) for a period of 15, 30 and 60 days. Exposed fish of all the three concentrations were subjected to a recovery period of 30 days. A control was maintained in tap water simultaneously. For SEM analysis, blood from caudal vein of fish was taken and examined at an accelerating voltage of 20kV. Scanning electron micrographs revealed elliptical shaped erythrocytes of control fish. Alterations in the erythrocyte morphology such as presence of spherocytes, membrane internalization, crenation of membrane and development of lobopodial projections were observed in the exposed fish. The study revealed that ultra-structural analysis appears to be a sensitive method to evaluate the toxicity of various toxicants to fish.

Keywords: Channa punctatus, erythrocytes, mercuric chloride, scanning electron microscopy

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Authors: Pedro Esteban

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Today’s electrical networks, including microgrids, are evolving into smart grids. The smart grid concept brings the idea that the power comes from various sources (continuous or intermittent), in various forms (AC or DC, high, medium or low voltage, etc.), and it must be integrated into the electric power system in a smart way to guarantee a continuous and reliable supply that complies with power quality and energy efficiency standards and grid code requirements. This idea brings questions for the different players like how the required power will be generated, what kind of power will be more suitable, how to store exceeding levels for short or long-term usage, and how to combine and distribute all the different generation power sources in an efficient way. To address these issues, there has been lots of development in recent years on the field of on-grid and off-grid hybrid power systems (HPS). These systems usually combine one or more modes of electricity generation together with energy storage to ensure optimal supply reliability and high level of energy security. Hybrid power systems combine power generation and energy storage technologies together with real-time energy management and innovative power quality and energy efficiency improvement functionalities. These systems help customers achieve targets for clean energy generation, they add flexibility to the electrical grid, and they optimize the installation by improving its power quality and energy efficiency.

Keywords: microgrids, hybrid power systems, energy storage, power quality improvement

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Authors: Jun-ya Nagase

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Recently, the need of colonoscopy is increasing because of the rise of colonic disorder including cancer of the colon. However, current colonoscopy depends on doctor's skill strongly. Therefore, a large intestine endoscope that does not depend on the techniques of a doctor with high safety is required. In this research, we aim at development a novel large intestine endoscope that can realize safe insertion without specific techniques. A wheel movement type robot, a snake-like robot and an earthworm-like robot are all described in the relevant literature as endoscope robots that are currently studied. Among them, the tracked crawler robot can travel by traversing uneven ground flexibly with a crawler belt attached firmly to the ground surface. Although conventional crawler robots have high efficiency and/or high ground-covering ability, they require a comparatively large space to move. In this study, a small cylindrical crawler robot inspired by amoeba locomotion, which does not need large space to move and which has high ground-covering ability, is proposed. In addition, we developed a prototype of the large intestine endoscope using the proposed crawler mechanism. Experiments have demonstrated smooth operation and a forward movement of the robot by application of voltage to the motor. This paper reports the structure, drive mechanism, prototype, and experimental evaluation.

Keywords: tracked-crawler, endoscopic robot, narrow path, amoeba locomotion.

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Authors: Tien-Li Chang, Huang-Chi Huang, Zhao-Chi Chen, Wun-Yi Chen

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The droplet-based microfluidic are used as micro-reactors for chemical and biological assays. Hence, the precise addition of reagents into the droplets is essential for this function in the scope of lab-on-a-chip applications. To obtain the characteristics (size, velocity, pressure, and frequency of production) of droplets, this study describes an integrated on-chip method of real-time signal detection. By controlling and manipulating the fluids, the flow behavior can be obtained in the droplet-based microfluidics. The detection method is used a type of infrared sensor. Through the varieties of droplets in the microfluidic devices, the real-time conditions of velocity and pressure are gained from the sensors. Here the microfluidic devices are fabricated by polydimethylsiloxane (PDMS). To measure the droplets, the signal acquisition of sensor and LabVIEW program control must be established in the microchannel devices. The devices can generate the different size droplets where the flow rate of oil phase is fixed 30 μl/hr and the flow rates of water phase range are from 20 μl/hr to 80 μl/hr. The experimental results demonstrate that the sensors are able to measure the time difference of droplets under the different velocity at the voltage from 0 V to 2 V. Consequently, the droplets are measured the fastest speed of 1.6 mm/s and related flow behaviors that can be helpful to develop and integrate the practical microfluidic applications.

Keywords: microfluidic, droplets, sensors, single detection

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Authors: B. Pavan Kumar Reddy, P. Michael Preetam Raj, Souri Banerjee, Souvik Kundu

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In this work, the fabrication and characterization of copper-doped zinc oxide (Cu:ZnO) based memristor devices with aluminum (Al) and indium tin oxide (ITO) metal electrodes are reported. The thin films of Cu:ZnO was synthesized using low-cost and low-temperature chemical process. The Cu:ZnO was then deposited onto ITO bottom electrodes using spin-coater technique, whereas the top electrode Al was deposited utilizing physical vapor evaporation technique. Ellipsometer was employed in order to measure the Cu:ZnO thickness and it was found to be 50 nm. Several surface and materials characterization techniques were used to study the thin-film properties of Cu:ZnO. To ascertain the efficacy of Cu:ZnO for memristor applications, electrical characterizations such as current-voltage (I-V), data retention and endurance were obtained, all being the critical parameters for next-generation memory. The I-V characteristic exhibits switching behavior with asymmetrical hysteresis loops. This work imputes the resistance switching to the positional drift of oxygen vacancies associated with respect to the Al/Cu:ZnO junction. Further, a non-linear curve fitting regression techniques were utilized to determine the equivalent circuit for the fabricated Cu:ZnO memristors. Efforts were also devoted in order to establish its potentiality for different electronic applications.

Keywords: copper doped, metal-oxides, oxygen vacancies, resistive switching

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Authors: Hamilton V. Niculescu

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Following a three year study conducted on eighteen Irish people that are involved in growing vegetables in various community gardens around Dublin, Republic of Ireland, it was revealed that addition of some automated features aimed at improving agricultural practices represented a process which was regarded as potentially beneficial, and as a great tool to closely monitor climate conditions inside the greenhouses. The participants were provided with a free custom-built mobile app through which they could remotely monitor and control features such as irrigation, air ventilation, and windows to ensure optimal growing conditions for vegetables growing inside purpose-built greenhouses. While the initial interest was generally high, within weeks, the participants' level of interaction with the enclosures slowly declined. By employing a constructivist grounded theory methodology, following focus group discussions, in-depth semi-structured interviews, and observations, it was revealed that participants' trust in newer technologies, and renewables, in particular, was low. There are various reasons for this, but because the participants in this study consist of mainly working-class people, it can be argued that lack of education and knowledge are the main barriers acting against the adoption of innovations. Consequently, it was revealed that most participants eventually decided to "set and forget" the systems in automatic working mode, indicating that the immediate effect of introducing people to assisting technologies also introduced some unintended consequences into their lifestyle. It is argued that this occurrence also indicates the fact that people initially "read" newer technologies and only adopt those features that they find useful and less intrusive in regards to their current lifestyle.

Keywords: automation, communication, greenhouse, sustainable

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Authors: Saleh Gareh, B. C. Kok, H. H. Goh

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Piezoelectric energy harvesting has advantages over other alternative sources due to its large power density, ease of applications, and capability to be fabricated at different scales: macro, micro, and nano. This paper presents an electromechanical-traffic model for roadway compression-based piezoelectric energy harvesting system. A two-degree-of-freedom (2-DOF) electromechanical model has been developed for the piezoelectric energy harvesting unit to define its performance in power generation under a number of external excitations on road surface. Lead Zirconate Titanate (PZT-5H) is selected as the piezoelectric material to be used in this paper due to its high Piezoelectric Charge Constant (d) and Piezoelectric Voltage Constant (g) values. The main source of vibration energy that has been considered in this paper is the moving vehicle on the road. The effect of various frequencies on possible generated power caused by different vibration characteristics of moving vehicle has been studied. A single unit of circle-shape Piezoelectric Cymbal Transducer (PCT) with diameter of 32 mm and thickness of 0.3 mm be able to generate about 0.8 mW and 3 mW of electric power under 4 Hz and 20 Hz of excitation, respectively. The estimated power to be generated for multiple arrays of PCT is approximately 150 kW/ km. Thus, the developed electromechanical-traffic model has enormous potential to be used in estimating the macro scale of roadway power generation system.

Keywords: piezoelectric energy harvesting, cymbal transducer, PZT (lead zirconate titanate), 2-DOF

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Authors: Hanish Mohammed, C. H. Muthukumar Muthuchamy

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The advancement in the science and technology has made it possible to convert electrical energy into any desired form. It has given electrical energy a place of pride in the modern world. The survival of industrial undertakings and our social structure depends primarily upon low cost and uninterrupted supply of electrical energy. Microbial fuel cell (MFC) is a promising and emerging technique for sustainable bioelectricity generation and wastewater treatment. MFCs are devices which are capable of converting organic matter to electricity/hydrogen with help of microorganisms. Different kinds of wastewater could be used in this technique, distillery effluent is one of the most troublesome and complex and strong organic effluent with high chemical oxygen demand of 1,53,846 mg/L. A single cell MFC unit was designed and fabricated for the distillery effluent treatment and to generate electricity. Due to the high COD value of the distillery effluent helped in the production of energy for 74 days. The highest voltage got from the fuel cell is 206 mV on the 30th day. A maximum power density obtained from the MFC was 9.8 mW, treatment efficiency was evaluated in terms of COD removal and other parameters. COD removal efficiencies were around 68.5 % and other parameters such as Total Hardness (81.5%), turbidity (70 %), chloride (66%), phosphate (79.5%), Nitrate (77%) and sulphate (71%). MFC using distillery effluent is a promising new unexplored substrate for the power generation and sustainable treatment technique through harnessing of bioelectricity.

Keywords: microbial fuel cell (MFC), bioelectricity, distillery effluent, wastewater treatment

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Authors: Andrew Cummings, Rhianne Boag, Sarah Bryson, Gordon Turner

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Packages designed for transport of radioactive material must satisfy rigorous safety regulations specified by the International Atomic Energy Agency (IAEA). Higher Activity Waste (HAW) transport packages have to maintain containment of their contents during normal and accident conditions of transport (NCT and ACT). To ensure containment criteria is satisfied these packages are required to be leak-tight in all transport conditions to meet allowable activity release rates. Package design safety reports are the safety cases that provide the claims, evidence and arguments to demonstrate that packages meet the regulations and once approved by the competent authority (in the UK this is the Office for Nuclear Regulation) a licence to transport radioactive material is issued for the package(s). The standard approach to demonstrating containment in the RWM transport safety case is set out in BS EN ISO 12807. In this document a method for measuring a leak rate from the package is explained by way of a small interspace test volume situated between two O-ring seals on the underside of the package lid. The interspace volume is pressurised and a pressure drop measured. A small interspace test volume makes the method more sensitive enabling the measurement of smaller leak rates. By ascertaining the activity of the contents, identifying a releasable fraction of material and by treating that fraction of material as a gas, allowable leak rates for NCT and ACT are calculated. The adherence to basic safety principles in ISO12807 is very pessimistic and current practice in the demonstration of transport safety, which is accepted by the UK regulator. It is UK government policy that management of HAW will be through geological disposal. It is proposed that the intermediate level waste be transported to the geological disposal facility (GDF) in large cuboid packages. This poses a challenge for containment demonstration because such packages will have long seals and therefore large interspace test volumes. There is also uncertainty on the releasable fraction of material within the package ullage space. This is because the waste may be in many different forms which makes it difficult to define the fraction of material released by the waste package. Additionally because of the large interspace test volume, measuring the calculated leak rates may not be achievable. For this reason a justification for a lower releasable fraction of material is sought. This paper considers the use of aerosol processes to reduce the releasable fraction for both NCT and ACT. It reviews the basic coagulation and removal processes and applies the dynamic aerosol balance equation. The proposed solution includes only the most well understood physical processes namely; Brownian coagulation and gravitational settling. Other processes have been eliminated either on the basis that they would serve to reduce the release to the environment further (pessimistically in keeping with the essence of nuclear transport safety cases) or that they are not credible in the conditions of transport considered.

Keywords: aerosol processes, Brownian coagulation, gravitational settling, transport regulations

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Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit

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In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.

Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety

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Authors: Imen Amari, Kaouther Gasmi, Asma Rebaya, Salem Hasnaoui

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The problem of scheduling and mapping data flow applications on multi-core architectures is notoriously difficult. This difficulty is related to the rapid evaluation of Telecommunication and multimedia systems accompanied by a rapid increase of user requirements in terms of latency, execution time, consumption, energy, etc. Having an optimal scheduling on multi-cores DSP (Digital signal Processors) platforms is a challenging task. In this context, we present a novel technic and algorithm in order to find a valid schedule that optimizes the key performance metrics particularly the Latency. Our contribution is based on Satisfiability Modulo Theories (SMT) solving technologies which is strongly driven by the industrial applications and needs. This paper, describe a scheduling module integrated in our proposed Workflow which is advised to be a successful approach for programming the applications based on NoC-DSP platforms. This workflow transform automatically a Simulink model to a synchronous dataflow (SDF) model. The automatic transformation followed by SMT solver scheduling aim to minimize the final latency and other software/hardware metrics in terms of an optimal schedule. Also, finding the optimal numbers of cores to be used. In fact, our proposed workflow taking as entry point a Simulink file (.mdl or .slx) derived from embedded Matlab functions. We use an approach which is based on the synchronous and hierarchical behavior of both Simulink and SDF. Whence, results of running the scheduler which exist in the Workflow mentioned above using our proposed SMT solver algorithm refinements produce the best possible scheduling in terms of latency and numbers of cores.

Keywords: multi-cores DSP, scheduling, SMT solver, workflow

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Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Magnolia G. Martinez-Rivera, Pablo de J. Angeles-Salto, Carlos Herrera-Ventosa

Abstract:

In order to diminish health risks, it is of major importance to monitor air quality. However, this process is accompanied by the high costs of physical and human resources. In this context, this research is carried out with the main objective of developing a predictive model for concentrations of inhalable particles (PM10-2.5) using remote sensing. To develop the model, satellite images, mainly from Landsat 8, of the Mexico City’s Metropolitan Area were used. Using historical PM10 and PM2.5 measurements of the RAMA (Automatic Environmental Monitoring Network of Mexico City) and through the processing of the available satellite images, a preliminary model was generated in which it was possible to observe critical opportunity areas that will allow the generation of a robust model. Through the preliminary model applied to the scenes of Mexico City, three areas were identified that cause great interest due to the presumed high concentration of PM; the zones are those that present high plant density, bodies of water and soil without constructions or vegetation. To date, work continues on this line to improve the preliminary model that has been proposed. In addition, a brief analysis was made of six models, presented in articles developed in different parts of the world, this in order to visualize the optimal bands for the generation of a suitable model for Mexico City. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air quality, modeling pollution, particulate matter, remote sensing

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Authors: Zerzouri Nora, Benalia Nadia, Bensiali Nadia

Abstract:

This paper presents a grid-connected wind power generation scheme using Doubly Fed Induction Generator (DFIG). This can supply power at constant voltage and constant frequency with the rotor speed varying. This makes it suitable for variable speed wind energy application. The DFIG system consists of wind turbine, asynchronous wound rotor induction generator, and inverter with Space Vector Modulation (SVM) controller. In which the stator is connected directly to the grid and the rotor winding is in interface with rotor converter and grid converter. The use of back-to-back SVM converter in the rotor circuit results in low distortion current, reactive power control and operate at variable speed. Mathematical modeling of the DFIG is done in order to analyze the performance of the systems and they are simulated using MATLAB. The simulation results for the system are obtained and hence it shows that the system can operate at variable speed with low harmonic current distortion. The objective is to track and extract maximum power from the wind energy system and transfer it to the grid for useful work.

Keywords: Doubly Fed Induction Generator, Wind Energy Conversion Systems, Space Vector Modulation, distortion harmonics

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Authors: Luc Conti, Dimitry Dumont-Fillon, Harald van Lintel, Eric Chappel

Abstract:

Flow control valves comprise a silicon flexible membrane that deflects against a substrate, usually made of glass, containing pillars, an outlet hole, and anti-stiction features. However, there is a strong interest in using silicon instead of glass as substrate material, as it would simplify the process flow by allowing the use of well controlled anisotropic etching. Moreover, specific devices demanding a bending of the substrate would also benefit from the inherent outstanding mechanical strength of monocrystalline silicon. Unfortunately, direct Si-Si bonding is not easily achieved with highly structured wafers since residual stress may prevent the good adhesion between wafers. Using a thermoplastic polymer, such as parylene, as intermediate layer is not well adapted to this design as the wafer-to-wafer alignment is critical. An alternative anodic bonding method using an intermediate borosilicate layer has been successfully tested. This layer has been deposited onto the silicon substrate. The bonding recipe has been adapted to account for the presence of the SOI buried oxide and intermediate glass layer in order not to exceed the breakdown voltage. Flow control valves dedicated to infusion of viscous fluids at very high pressure have been made and characterized. The results are compared to previous data obtained using the standard anodic bonding method.

Keywords: anodic bonding, evaporated glass, flow control valve, drug delivery

Procedia PDF Downloads 188

Authors: Sanjida Akter, Ambali Alade Odebowale, Andrey E. Miroshnichenko, Haroldo T. Hattori

Abstract:

Photodetectors (PDs) play a pivotal role in optoelectronics and optical devices, serving as fundamental components that convert light signals into electrical signals. As the field progresses, the integration of advanced materials with unique optical properties has become a focal point, paving the way for the innovation of novel PDs. This study delves into the exploration of a cutting-edge photodetector designed for deep and near ultraviolet (UV) applications. The photodetector is constructed with a composite of Zirconium Boride (ZrB2) and Chromium (Cr) alloy, deposited onto a 6H nitrogen-doped silicon carbide substrate. The determination of the optimal alloy thickness is achieved through Finite-Difference Time-Domain (FDTD) simulation, and the synthesis of the alloy is accomplished using radio frequency (RF) sputtering. Remarkably, the resulting photodetector exhibits an exceptional responsivity of 3.5 A/W under an applied voltage of -2 V, at wavelengths of 405 nm and 280 nm. This heterostructure not only exemplifies high performance but also provides a versatile platform for the development of near UV photodetectors capable of operating effectively in challenging conditions, such as environments characterized by high power and elevated temperatures. This study contributes to the expanding landscape of photodetector technology, offering a promising avenue for the advancement of optoelectronic devices in demanding applications.

Keywords: responsivity, silicon carbide, ultraviolet photodetector, zirconium boride

Procedia PDF Downloads 43

Authors: Parisa Mansour

Abstract:

Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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Authors: Ross Lee, Pritpal Singh, Andrew Jester

Abstract:

As the world transitions to a more sustainable energy economy, the deployment of energy storage technologies is expected to increase to develop a more resilient grid system. However, current technologies are associated with various environmental and safety issues throughout their entire lifecycle; therefore, new battery technology is necessary for grid applications to curtail these risks. Biological cells, such as human neurons and electrolytes in the electric eel, can serve as a more sustainable design template for a new bio-inspired (i.e., biomimetic) battery. Within biological cells, an electrochemical gradient across the cell membrane forms the membrane potential, which serves as the driving force for ion transport into/out of the cell, akin to the charging/discharging of a battery cell. This work serves as the first step to developing such a biomimetic battery cell, starting with the fabrication and characterization of ion-selective membranes to facilitate ion transport through the cell. Performance characteristics (e.g., cell voltage, power density, specific energy, roundtrip efficiency) for the cell under investigation are compared to incumbent battery technologies and biological cells to assess the readiness level for this emerging technology. Using a Na⁺-Form Nafion-117 membrane, the cell in this work successfully demonstrated behavior similar to human neurons; these findings will inform how cell components can be re-engineered to enhance device performance.

Keywords: battery, biomimetic, electrolytes, human neurons, ion-selective membranes, membrane potential

Procedia PDF Downloads 98

Authors: MeiBo, ZhaoXing, LuoLei, YuQingkui, TangMin, HanZhengsheng

Abstract:

The Single Event Transients (SETs) were investigated on 0.18μm PDSOI transistors and 100 series CMOS inverter chain using pulse laser. The effect of different laser energy and device bias for waveform on SET was characterized experimentally, as well as the generation and propagation of SET in inverter chain. In this paper, the effects of struck transistors type and struck locations on SETs were investigated. The results showed that when irradiate NMOSFETs from 100th to 2nd stages, the SET pulse width measured at the output terminal increased from 287.4 ps to 472.9 ps; and when irradiate PMOSFETs from 99th to 1st stages, the SET pulse width increased from 287.4 ps to 472.9 ps. When struck locations were close to the output of the chain, the SET pulse was narrow; however, when struck nodes were close to the input, the SET pulse was broadening. SET pulses were progressively broadened up when propagating along inverter chains. The SET pulse broadening is independent of the type of struck transistors. Through analysis, history effect induced threshold voltage hysteresis in PDSOI is the reason of pulse broadening. The positive pulse observed by oscilloscope, contrary to the expected results, is because of charging and discharging of capacitor.

Keywords: single event transients, pulse laser, partially-depleted silicon-on-insulator, propagation-induced pulse broadening effect

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Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

Abstract:

Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

Procedia PDF Downloads 118