Search results for: Network Time Protocol

Authors: M. Marsadek, A. Mohamed

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Power system security analysis is the most time demanding process due to large number of possible contingencies that need to be analyzed.  In a power system, any contingency resulting in security violation such as line overload or low voltage may occur for a number of reasons at any time.  To efficiently rank a contingency, both probability and the extent of security violation must be considered so as not to underestimate the risk associated with the contingency. This paper proposed a contingency ranking method that take into account the probabilistic nature of power system and the severity of contingency by using a newly developed method based on risk factor.  The proposed technique is implemented on IEEE 24-bus system.

Keywords: line overload, low voltage, probability, risk factor, severity

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Authors: Ilknur Çevik Tekin, Serdar Öge

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As a result of globalization and changing consumer preferences, the number of shopping malls has increased significantly in recent years. Consumers prefer shopping malls to both do comfortable shopping in a short time and benefit from the social facilities there. Employees, who are obliged to behave to the consumers in the way the company wants them to do, often spend intensive emotional effort because companies buy the emotions the employees must display to customers in order to ensure customer satisfaction. The emotions the employees constantly try to contain may lead to the phenomenon of burn-out in time. This study was conducted to reveal the relationship between the emotional labor and burn-out levels of shopping mall employees, who work in shopping malls and are supposed to reflect the corporate culture.

Keywords: emotional labor, burnout, shopping mall employees

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Authors: Samar Mousa, Rebecca Shirley

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Injuries to the hand account for 20% of all emergency department attendances, with an estimated annual treatment cost of over £100 million in the UK. Functional impairments as a result of hand injuries often necessitate absence from employment, resulting in reduced productivity estimated to incur an additional £600m loss to the UK economy. Appropriate and early management is vital to preserve anatomy, prevent stiffness and allow function. The initial assessment and management of hand injuries are usually undertaken by junior staff, many of whom have little or no training or experience in splinting hand fractures. In our plastic surgery department at Stoke Mandeville hospital Buckinghamshire trust, we carried out an audit project to detect errors in hand splinting in the period between April 2022 and July 2022 and find out measures to support junior doctors, nurses and hand therapists in providing the best possible care for hand trauma patients. Our standards were The British Society for Surgery of the Hand (BSSH) standard of care in hand trauma, AO surgery reference and Stoke Mandeville hospital hand therapy mini protocol Feb 2022 During the period of 4 months, 5 cases were identified. Two cases of wrong splint choice, two cases of early removal of the splint and one tight splint that required change. In order to avoid those mistakes, a training program was given to junior doctors and nurses in collaboration with the hand therapy team regarding ways of splinting the hand in different injuries like fractures, tendons injuries, muscle injuries and ligamentous injuries. In addition to, a poster hung in the examination rooms and theatres to help junior doctors reach the correct decision.

Keywords: splinting, hand trauma, plastic surgery, tendon injury, hand fracrture

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Authors: Mohamed Mounir Tellache, Hiroyuki Kambara, Yasuharu Koike, Makoto Miyakoshi, Natsue Yoshimura

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This study explores the practicality of using electroencephalographic (EEG) independent components to predict eight-direction finger movements in pseudo-real-time. Six healthy participants with individual-head MRI images performed finger movements in eight directions with two different arm configurations. The analysis was performed in two stages. The first stage consisted of using independent component analysis (ICA) to separate the signals representing brain activity from non-brain activity signals and to obtain the unmixing matrix. The resulting independent components (ICs) were checked, and those reflecting brain-activity were selected. Finally, the time series of the selected ICs were used to predict eight finger-movement directions using Sparse Logistic Regression (SLR). The second stage consisted of using the previously obtained unmixing matrix, the selected ICs, and the model obtained by applying SLR to classify a different EEG dataset. This method was applied to two different settings, namely the single-participant level and the group-level. For the single-participant level, the EEG dataset used in the first stage and the EEG dataset used in the second stage originated from the same participant. For the group-level, the EEG datasets used in the first stage were constructed by temporally concatenating each combination without repetition of the EEG datasets of five participants out of six, whereas the EEG dataset used in the second stage originated from the remaining participants. The average test classification results across datasets (mean ± S.D.) were 38.62 ± 8.36% for the single-participant, which was significantly higher than the chance level (12.50 ± 0.01%), and 27.26 ± 4.39% for the group-level which was also significantly higher than the chance level (12.49% ± 0.01%). The classification accuracy within [–45°, 45°] of the true direction is 70.03 ± 8.14% for single-participant and 62.63 ± 6.07% for group-level which may be promising for some real-life applications. Clustering and contribution analyses further revealed the brain regions involved in finger movement and the temporal aspect of their contribution to the classification. These results showed the possibility of using the ICA-based method in combination with other methods to build a real-time system to control prostheses.

Keywords: brain-computer interface, electroencephalography, finger motion decoding, independent component analysis, pseudo real-time motion decoding

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Authors: Mohammed Farag, Mina Attari, S. Andrew Gadsden, Saeid R. Habibi

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Battery state of charge (SOC) estimation is an important parameter as it measures the total amount of electrical energy stored at a current time. The SOC percentage acts as a fuel gauge if it is compared with a conventional vehicle. Estimating the SOC is, therefore, essential for monitoring the amount of useful life remaining in the battery system. This paper looks at the implementation of three nonlinear estimation strategies for Li-Ion battery SOC estimation. One of the most common behavioral battery models is the one state hysteresis (OSH) model. The extended Kalman filter (EKF), the smooth variable structure filter (SVSF), and the time-varying smoothing boundary layer SVSF are applied on this model, and the results are compared.

Keywords: state of charge estimation, battery modeling, one-state hysteresis, filtering and estimation

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Authors: Ibrahim Umar, Ashiru Rajab, Sumayya Chindo, Emmanuel Olashore

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INTRODUCTION: Kano is the most populous state in Nigeria and one of the two states with the highest TB burden in the country. The state notifies an average of 8,000+ TB cases quarterly and has the highest yearly notification of all the states in Nigeria from 2020 to 2022. The contribution of the state TB program to the National TB notification varies from 9% to 10% quarterly between the first quarter of 2022 and second quarter of 2023. The Kano State TB Situation Room is an innovative platform for timely data collection, collation and analysis for informed decision in health system. During the 2023 second National TB Testing week (NTBTW) Kano TB program aimed at early TB detection, prevention and treatment. The state TB Situation room provided avenue to the state for coordination and surveillance through real time data reporting, review, analysis and use during the NTBTW. OBJECTIVES: To assess the role of innovative information and communication technology platform for real-time TB reporting during second National TB Testing week in Nigeria 2023. To showcase the NTBTW data cascade analysis using TSR as innovative ICT platform. METHODOLOGY: The State TB deployed a real-time virtual dashboard for NTBTW reporting, analysis and feedback. A data room team was set up who received realtime data using google link. Data received was analyzed using power BI analytic tool with statistical alpha level of significance of <0.05. RESULTS: At the end of the week-long activity and using the real-time dashboard with onsite mentorship of the field workers, the state TB program was able to screen a total of 52,054 people were screened for TB from 72,112 individuals eligible for screening (72% screening rate). A total of 9,910 presumptive TB clients were identified and evaluated for TB leading to diagnosis of 445 TB patients with TB (5% yield from presumptives) and placement of 435 TB patients on treatment (98% percentage enrolment). CONCLUSION: The TB Situation Room (TBSR) has been a great asset to Kano State TB Control Program in meeting up with the growing demand for timely data reporting in TB and other global health responses. The use of real time surveillance data during the 2023 NTBTW has in no small measure improved the TB response and feedback in Kano State. Scaling up this intervention to other disease areas, states and nations is a positive step in the right direction towards global TB eradication.

Keywords: tuberculosis (tb), national tb testing week (ntbtw), tb situation rom (tsr), information communication technology (ict)

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Authors: Marco Frieslaar, Bing Chu, Eric Rogers

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Stroke is a devastating illness that is the second biggest cause of death in the world (after heart disease). Where it does not kill, it leaves survivors with debilitating sensory and physical impairments that not only seriously harm their quality of life, but also cause a high incidence of severe depression. It is widely accepted that early intervention is essential for recovery, but current rehabilitation techniques largely favor hospital-based therapies which have restricted access, expensive and specialist equipment and tend to side-step the emotional challenges. In addition, there is insufficient funding available to provide the long-term assistance that is required. As a consequence, recovery rates are poor. The relatively unexplored solution is to develop therapies that can be harnessed in the home and are formulated from technologies that already exist in everyday life. This would empower individuals to take control of their own improvement and provide choice in terms of when and where they feel best able to undertake their own healing. This research seeks to identify how effective post-stroke, rehabilitation therapy can be applied to upper limb mobility, within the physical context of a home rather than a hospital. This is being achieved through the design and construction of an automation scheme, based on iterative learning control and the Riener muscle model, that has the ability to adapt to the user and react to their level of fatigue and provide tangible physical recovery. It utilizes a SMART Phone and laptop to construct an iterative learning control (ILC) system, that monitors upper arm movement in three dimensions, as a series of exercises are undertaken. The equipment generates functional electrical stimulation to assist in muscle activation and thus improve directional accuracy. In addition, it monitors speed, accuracy, areas of motion weakness and similar parameters to create a performance index that can be compared over time and extrapolated to establish an independent and objective assessment scheme, plus an approximate estimation of predicted final outcome. To further extend its assessment capabilities, nerve conduction velocity readings are taken by the software, between the shoulder and hand muscles. This is utilized to measure the speed of response of neuron signal transfer along the arm and over time, an online indication of regeneration levels can be obtained. This will prove whether or not sufficient training intensity is being achieved even before perceivable movement dexterity is observed. The device also provides the option to connect to other users, via the internet, so that the patient can avoid feelings of isolation and can undertake movement exercises together with others in a similar position. This should create benefits not only for the encouragement of rehabilitation participation, but also an emotional support network potential. It is intended that this approach will extend the availability of stroke recovery options, enable ease of access at a low cost, reduce susceptibility to depression and through these endeavors, enhance the overall recovery success rate.

Keywords: home-based therapy, iterative learning control, Riener muscle model, SMART phone, stroke rehabilitation

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Authors: Rowanda Daoud Ahmed, Mansoor Abdulhak, Muhammad Azeem Afzal, Sezer Filiz, Usama Ahmad Mughal

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This paper discusses important aspects of AI in the healthcare domain. The increase of data in healthcare both in size and complexity, opens more room for artificial intelligence applications. Our focus is to review the main AI methods within the scope of the health care domain. The results of the review show that recommendations for diagnosis and recommendations for treatment, patent engagement, and administrative tasks are the key applications of AI in healthcare. Understanding the potential of AI methods in the domain of healthcare would benefit healthcare practitioners and will improve patient outcomes.

Keywords: AI in healthcare, technologies of AI, neural network, future of AI in healthcare

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Authors: Cahit Perkgöz

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Artificial intelligence has brought new approaches to solving problems in almost every research field in recent years. One of these topics is shape design and optimization, which has the possibility of applications in many fields, such as nanotechnology and electronics. A properly constructed cost function can eliminate the need for labeled data required in deep learning and create desired shapes. In this work, the network parameters are optimized differentially, which differs from traditional approaches. The methods are tested for physics-related structures and successful results are obtained. This work is supported by Eskişehir Technical University scientific research project (Project No: 20ADP090)

Keywords: deep learning, shape design, optimization, artificial intelligence

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Authors: Chaiyaporn Yuksen, Tapanawat Chaiwan

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Introduction: Emergency medical service (EMS) care for trauma patients must be provided on-scene assessment and essential treatment and have appropriate transporting to the trauma center. The shock index (SI), reverse shock index Glasgow Coma Scale (rSIG), and National Early Warning Score (NEWS) triage tools are easy to use in a prehospital setting. There is no standardized on-scene triage protocol in prehospital care. The primary objective was to determine the accuracy of SI, rSIG, and NEWS to predict the severity of trauma patients in the emergency department (ED). Methods: This was a retrospective cross-sectional and diagnostic research conducted on trauma patients transported by EMS to the ED of Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand, from January 2015 to September 2022. We included the injured patients receiving prehospital care and transport to the ED of Ramathibodi Hospital by the EMS team from January 2015 to September 2022. We compared the on-scene parameter (SI, rSIG, and NEWS) and ED (Emergency Severity Index) with the area under ROC. Results: 218 patients were traumatic patients transported by EMS to the ED. 161 was ESI level 1-2, and 57 was level 3-5. NEWS was a more accurate triage tool to discriminate the severity of trauma patients than rSIG and SI. The area under the ROC was 0.743 (95%CI 0.70-0.79), 0.649 (95%CI 0.59-0.70), and 0.582 (95%CI 0.52-0.65), respectively (P-value <0.001). The cut point of NEWS to discriminate was 6 points. Conclusions: The NEWs was the most accurate triage tool in prehospital seeing in trauma patients.

Keywords: on-scene triage, trauma patient, ED triage, accuracy, NEWS

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Authors: Kidane workelul, Li xu, Xiaoyang Pang, Jiaping Lv

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Dairy products are exceptionally ideal media for the growth of microorganisms because of their high nutritional content. There are several ways that milk might get contaminated throughout the milking process, including how the raw milk is transported and stored, as well as how long it is kept before being processed. Psychrotrophic bacteria are among the one which can deteriorate the quality of milk mainly their heat resistance proteas and lipase enzyme. For this research purpose 8 selected strains of Psychrotrophic bacteria (Entrococcus hirae, Pseudomonas fluorescens, Pseudomonas azotoformans, Pseudomonas putida, Exiguobacterium indicum, Pseudomonas paralactice, Acinetobacter indicum, Serratia liquefacients)are chosen and try to determine their characteristics based on the research methodology protocol. Thus, the 8 selected strains are cultured, plated incubate, extracted their genomic DNA and genome DNA was amplified, the purpose of the study was to identify their Psychrotrophic properties, lipase hydrolysis positive test, their optimal incubation temperature, designed primer using the noble strain P,flourescens conserved region area in target with lipA gene, optimized primer specificity as well as sensitivity and PCR detection for lipase positive strains using the design primers. Based on the findings both the selected 8 strains isolated from stored raw milk are Psychrotrophic bacteria, 6 of the selected strains except the 2 strains are positive for lipase hydrolysis, their optimal temperature is 20 to 30 OC, the designed primer specificity is very accurate and amplifies for those strains only with lipase positive but could not amplify for the others. Thus, the result is promising and could help in detecting the Psychrotrophic bacteria producing heat resistance enzymes (lipase) at early stage before the milk is processed and this will safe production loss for the dairy industry.

Keywords: dairy industry, heat-resistant, lipA, milk, primer and psychrotrophic

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Authors: Atena Naeimi, Mehri-Sadat Ekrami-Kakhki

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Fe3O4 is one of the important magnetic oxides with spinel structure; it has exhibited unique electric and magnetic properties based on the electron transfer between Fe2+ and Fe3+ in the octahedral sites. Fe3O4 have received considerable attention in various areas such as cancer therapy, drug targeting, enzyme immobilization catalysis, magnetic cell separation, magnetic refrigeration systems and super-paramagnetic materials. Fe3O4–ZnO nanostructures were synthesized via a surfactant-free ultrasonic reaction at room temperatures. The effect of various parameters such as temperature, time, and power on the size and morphology of the product was investigated. Alternating gradient force magnetometer shows that Fe3O4 nanoparticles exhibit super-paramagnetic behaviour at room temperature. For preparation of nanocomposite 1 g of Fe3O4 nanostructures were dispersed in 100 mL of distilled water. 0.25 g of Zn (NO3)2 and 20 mL of NH3 solution 1 M were then slowly added to the solution under ultrasonic irradiation. The product was centrifuged, washed with distilled water and dried in the air. The photocatalytic behaviour of Fe3O4–ZnO nanoparticles was evaluated using the degradation of a methyl orange aqueous solution under ultraviolet light irradiation. As time increased, more and more methyl orange was adsorbed on the nanoparticles catalyst, until the absorption peak vanish. The methyl orange concentration decreased rapidly with increasing UV-irradiation time.

Keywords: nanocomposite, ultrasonic, paramagnetic, photocatalytic

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Authors: Amit R. Bhende, G. K. Awari

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Remaining useful life (RUL) prediction is one of key technologies to realize prognostics and health management that is being widely applied in many industrial systems to ensure high system availability over their life cycles. The present work proposes a data-driven method of RUL prediction based on multiple health state assessment for rolling element bearings. Bearing degradation data at three different conditions from run to failure is used. A RUL prediction model is separately built in each condition. Feed forward back propagation neural network models are developed for prediction modeling.

Keywords: bearing degradation data, remaining useful life (RUL), back propagation, prognosis

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Authors: Luisa Mesquita Oliveira Ribeiro, Alexei Manso Correa Machado

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Handwritten signature is a unique form for recognizing an individual, used to discern documents, carry out investigations in the criminal, legal, banking areas and other applications. Signature verification is based on large amounts of biometric data, as they are simple and easy to acquire, among other characteristics. Given this scenario, signature forgery is a worldwide recurring problem and fast and precise techniques are needed to prevent crimes of this nature from occurring. This article carried out a study on the efficiency of the Capsule Network in analyzing and recognizing signatures. The chosen architecture achieved an accuracy of 98.11% and 80.15% for the CEDAR and GPDS databases, respectively.

Keywords: biometrics, deep learning, handwriting, signature forgery

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Authors: Mahdieh Jajroudi

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Developing a pharmacokinetic model for the neuroendocrine tumors therapy agent 177Lu-DOTATATE in nude mice bearing AR42J rat pancreatic tumor to investigate and evaluate the behavior of the complex was the main purpose of this study. The utilization of compartmental analysis permits the mathematical differencing of tissues and organs to become acquainted with the concentration of activity in each fraction of interest. Biodistribution studies are onerous and troublesome to perform in humans, but such data can be obtained facilely in rodents. A physiologically based pharmacokinetic model for scaling up activity concentration in particular organs versus time was developed. The mathematical model exerts physiological parameters including organ volumes, blood flow rates, and vascular permabilities; the compartments (organs) are connected anatomically. This allows the use of scale-up techniques to forecast new complex distribution in humans' each organ. The concentration of the radiopharmaceutical in various organs was measured at different times. The temporal behavior of biodistribution of 177Lu labeled somatostatin analogues was modeled and drawn as function of time. Conclusion: The variation of pharmaceutical concentration in all organs is characterized with summation of six to nine exponential terms and it approximates our experimental data with precision better than 1%.

Keywords: biodistribution modeling, compartmental analysis, 177Lu labeled somatostatin analogues, neuroendocrine tumors

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Authors: Nadia Yaghoobi, Seyed Majid Esmaeilzadeh

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Due to advancements in wireless communication, new sensor capabilities have been created. In addition to the automation industry, the Internet of Things (IoT) has been used in environmental issues and has provided the possibility of communication between different devices for data collection and exchange. Water quality depends on many factors which are essential for maintaining the minimum sustainability of water. Regarding the great dependence of fishes on the quality of the aquatic environment, water quality can directly affect their activity. Therefore, monitoring water quality is an important issue to consider, especially in the fish farming industry. The conventional method of water quality testing is to collect water samples manually and send them to a laboratory for testing and analysis. This time-consuming method is a waste of manpower and is not cost-effective. The water quality measurement system implemented in this project monitors water quality in real-time through various sensors (parameters: water temperature, water level, dissolved oxygen, humidity and ambient temperature, water turbidity, PH). The Wi-Fi module, ESP8266, transmits data collected by sensors wirelessly to ThingSpeak and the smartphone app. Also, with the help of these instantaneous data, water temperature and water level can be controlled by using a heater and a water pump, respectively. This system can have a detailed study of the pollution and condition of water resources and can provide an environment for safe fish farming.

Keywords: dissolved oxygen, IoT, monitoring, ThingSpeak, water level, water quality, WiFi module

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Authors: Jose Neri, Fabrice Canto, Alastair Magnaldo, Laurent Guillerme, Vincent Dugas

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A miniaturized and automated approach for the volumetric titration of free nitric acid in U(VI) solutions is presented. Free acidity measurement refers to the acidity quantification in solutions containing hydrolysable heavy metal ions such as U(VI), U(IV) or Pu(IV) without taking into account the acidity contribution from the hydrolysis of such metal ions. It is, in fact, an operation having an essential role for the control of the nuclear fuel recycling process. The main objective behind the technical optimization of the actual ‘beaker’ method was to reduce the amount of radioactive substance to be handled by the laboratory personnel, to ease the instrumentation adjustability within a glove-box environment and to allow a high-throughput analysis for conducting more cost-effective operations. The measurement technique is based on the concept of the Taylor-Aris dispersion in order to create inside of a 200 μm x 5cm circular cylindrical micro-channel a linear concentration gradient in less than a second. The proposed analytical methodology relies on the actinide complexation using pH 5.6 sodium oxalate solution and subsequent alkalimetric titration of nitric acid with sodium hydroxide. The titration process is followed with a CCD camera for fluorescence detection; the neutralization boundary can be visualized in a detection range of 500nm- 600nm thanks to the addition of a pH sensitive fluorophore. The operating principle of the developed device allows the active generation of linear concentration gradients using a single cylindrical micro channel. This feature simplifies the fabrication and ease of use of the micro device, as it does not need a complex micro channel network or passive mixers to generate the chemical gradient. Moreover, since the linear gradient is determined by the liquid reagents input pressure, its generation can be fully achieved in faster intervals than one second, being a more timely-efficient gradient generation process compared to other source-sink passive diffusion devices. The resulting linear gradient generator device was therefore adapted to perform for the first time, a volumetric titration on a chip where the amount of reagents used is fixed to the total volume of the micro channel, avoiding an important waste generation like in other flow-based titration techniques. The associated analytical method is automated and its linearity has been proven for the free acidity determination of U(VI) samples containing up to 0.5M of actinide ion and nitric acid in a concentration range of 0.5M to 3M. In addition to automation, the developed analytical methodology and technique greatly improves the standard off-line oxalate complexation and alkalimetric titration method by reducing a thousand fold the required sample volume, forty times the nuclear waste per analysis as well as the analysis time by eight-fold. The developed device represents, therefore, a great step towards an easy-to-handle nuclear-related application, which in the short term could be used to improve laboratory safety as much as to reduce the environmental impact of the radioanalytical chain.

Keywords: free acidity, lab-on-a-chip, linear concentration gradient, Taylor-Aris dispersion, volumetric titration

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Authors: Hammad Khalid

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In this paper, a strategy for computerized arranging of Fiber to the Home (FTTH) get to systems is proposed. We presented an efficient methodology for arranging access organize framework. The GIS information and a lot of calculations were utilized to make the arranging procedure increasingly programmed. The technique clarifies various strides of the arranging process. Considering various situations, various designs can be produced by utilizing the technique. It was likewise conceivable to produce the designs in an extremely brief temporal contrast with the conventional arranging. A contextual investigation is considered to delineate the utilization and abilities of the arranging technique. The technique, be that as it may, doesn't completely robotize the arranging however, make the arranging procedure fundamentally quick. The outcomes and dialog are displayed and end is given at last.

Keywords: FTTH, GIS, robotize, plan

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Authors: Seung-Seok Bak, Chang-Mu Jung

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An enough amount supply of industrial complexes is an important national policy in South Korea, which is highly dependent on foreign trade. A development process of the industrial complex can distinguish between the planning stage and the construction stage. The planning stage consists of the process of consulting with many stakeholders on the contents of the development of industrial complex, feasibility study, compliance with the Regional policies, and so on. The industrial complex planning stage, including licensing procedure, usually takes about three years in South Korea. The government determined that the appropriate supply of industrial complexes have been delayed, due to the long licensing period and drafted a law to shorten the license period in 2008. The law was expected to shorten the period of licensing, which was about three years, to six months. This paper attempts to show that the shortening of the licensing period does not positively affect the appropriate supply of industrial complexes. To do this, we used Interrupted Time Series Designs. As a result, it was found that the supply of industrial complexes was influenced more by other factors such as actual industrial complex demand of private sector and macro-level economic variables. In addition, the specific provisions of the law conflict with local policy and cause some problems such as damage to nature and agricultural land, traffic congestion.

Keywords: development of industrial complexes, industrial complexes, interrupted time series designs, simplification of licensing procedures for industrial complexes, time series regression

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Authors: Nhleko Monique Chiloane

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The gold mining industry has predominantly used ammonium nitrate fuel oil (ANFO) explosives for decades, although these are known to be “gassier” and their detonation results in toxic fumes, for example, carbon monoxide (CO), nitrogen oxides (NOx) and ammonia. Re-entry into underground workings too soon after blasting can lead to fatal exposure to toxic fumes. It is, therefore, required that the polluted air be removed from the affected areas within a reasonable period before employees' re-entry into the working area. Post-blast re-entry times have therefore been described as a productivity bottleneck. The known causes of post-blast fumes are water ingress, incorrect fuel to oxygen ratio, confinement, explosive additives etc. To prevent or minimize post-blast fumes, some researchers have used neutralization, re-burning technique and non-explosive products or different oxidizing agents. The use of commercial explosives without nitrate oxidizing agents can also minimize the production of blasting fumes and thereby reduce the time needed for the clearance of these fumes to allow workers to re-enter the underground workings safely. The reduction in non-production time directly contributes to an increase in the available time per shift for productive work, thus leading to continuous mining. However, owing to its low cost and ease of use, ANFO is still widely used in South African underground blasting operations.

Keywords: post-blast fumes, continuous mining, ammonium nitrate explosive, non-explosive blasting, re-entry period

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Authors: Rania Hanafi Said, Rasha Mohamed Taha

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Background: By using nanoparticles as drug delivery, it may be possible to avoid the drawbacks of systemic antibiotic dosing, including bacterial antibiotic resistance. The goal of this study was to see how well tetracycline loaded on nanochitosan worked to treat gingival inflammation in albino rats caused by Porphyromonas gingivalis. The study analyzed immunohistochemically the localization of the pro-inflammatory cytokine Interleukin-1beta (IL-1β). Material and methods: In this study, fifty mature male albino rats weighing 150 to 180 grams each were used. They were randomly divided into five groups. We checked for weight changes in rats. Ten male albino rats were included in Group I, which served as a negative control group. Ten rats were included in Group II, where they were exposed once to Porphyromonas. Group III contained ten rats, which were treated the same as Group II plus daily injections of diluted tetracycline powder at the infection sites. Ten rats in Group IV received the same procedure as those in Group II before receiving daily injections of nanochitosan at the injection sites. Finally, Group V, which had ten rats. Following the same protocol as Group II, they received localized injections of tetracycline loaded on nanochitosan once daily. Rats' gingivae were extracted and prepared after they were anesthetized. The biopsies were examined histologically and immunohistochemically by light microscopy. Results: Groups I and V had a nearly normal histological appearance of gingival tissue. In Groups II, III, and IV, degeneration was seen because the epithelial cells were bigger, collagen fibers were pulling away from the lamina propria connective tissue, and the basement membranes had come to an end. There was no discernible difference between groups V and I when they were examined immunohistochemically. Conclusion: The use of nano chitosan as a tetracycline carrier is a novel technique to overcome the drug's rising level of resistance.

Keywords: Immunohistochemistry, Nanochitosan, porphyromonas gingivitis, Tetracycline

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Authors: Ivanka Valova

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This paper is aimed at using a multi-agent approach to monitor and diagnose a biotechnological system in order to validate certain control actions depending on the process development and the operating conditions. A multi-agent system is defined as a network of interacting software modules that collectively solve complex tasks. Remote monitoring and control of biotechnological processes is a necessity when automated and reliable systems operating with no interruption of certain activities are required. The advantage of our approach is in its flexibility, modularity and the possibility of improving by acquiring functionalities through the integration of artificial intelligence.

Keywords: multi-agent approach, artificial intelligence, biotechnological processes, anaerobic biodegradation

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Authors: Guillaume Craveur

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The evaluation of the passenger exchange time is necessary for railway operators in order to optimize and dimension rail traffic. Several influential parameters are identified and studied. Each parameter leads to a modeling completed with the buildingEXODUS software. The objective is the modelling of passenger exchanges measured by passenger counting. Population size is dimensioned using passenger counting files which are a report of the train service and contain following useful informations: number of passengers who get on and leave the train, exchange time. These information are collected by sensors placed at the top of each train door. With passenger counting files it is possible to know how many people are engaged in the exchange and how long is the exchange, but it is not possible to know passenger flow of the door. All the information about observed exchanges are thus not available. For this reason and in order to minimize inaccuracies, only short exchanges (less than 30 seconds) with a maximum of people are performed.

Keywords: passengers exchange, numerical tools, rolling stock, platforms

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Authors: Anders S. Kristensen, Dewan Ahsan, Saqib Mehmood, Shakeel Ahmed

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Traffic accidents are a result of the convergence of hazards, malfunctioning of vehicles and human negligence that have adverse economic and health impacts and effects. Unfortunately, avoiding them completely is very difficult, but with quick response to rescue and first aid, the mortality rate of inflicted persons can be reduced significantly. Smart and innovative technologies can play a pivotal role to respond faster to traffic crash emergencies comparing conventional means of transportation. For instance, Rescue Emergency Drone (RED) can provide faster and real-time crash site risk assessment to emergency medical services, thereby helping them to quickly and accurately assess a situation, dispatch the right equipment and assist bystanders to treat inflicted person properly. To conduct a research in this regard, the case of a traffic roundabout that is prone to frequent traffic accidents on the outskirts of Esbjerg, a town located on western coast of Denmark is hypothetically considered. Along with manual calculations, Emergency Disaster Management Simulation (EDMSIM) has been used to verify the response time of RED from a fire station of the town to the presumed crash site. The results of the study demonstrate the robustness of RED into emergency services to help save lives. 

Keywords: automated external defibrillator, medical emergency, response time, unmanned aerial system

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Authors: Ya Lv

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This article presents the application of the semi-analytic method (SAM) in the thermal management solution (TMS) of the energy storage system (ESS). The TMS studied in this work is fluid cooling. In fluid cooling, both effective heat conduction and heat convection are indispensable due to the heat transfer from solid to fluid. Correspondingly, an efficient TMS requires a design investigation of the following parameters: fluid inlet temperature, ESS initial temperature, fluid flow rate, working c rate, continuous working time, and materials properties. Their variation induces a change of thermal performance in the battery module, which is usually evaluated by numerical simulation. Compared to complicated computation resources and long computation time in simulation, the SAM is developed in this article to predict the thermal influence within a few seconds. In SAM, a fast prediction model is reckoned by combining numerical simulation with theoretical/empirical equations. The SAM can explore the thermal effect of boundary parameters in both steady-state and transient heat transfer scenarios within a short time. Therefore, the SAM developed in this work can simplify the design cycle of TMS and inspire more possibilities in TMS design.

Keywords: semi-analytic method, fast prediction model, thermal influence of boundary parameters, energy storage system

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Authors: Shuenn-Yih Chang, Chiu-LI Huang, Ngoc-Cuong Tran

Abstract:

A new family of structure-dependent integration methods, whose coefficients of the difference equation for displacement increment are functions of the initial structural properties and the step size for time integration, is proposed in this work. This family method can simultaneously integrate the controllable numerical dissipation, explicit formulation and unconditional stability together. In general, its numerical dissipation can be continuously controlled by a parameter and it is possible to achieve zero damping. In addition, it can have high-frequency damping to suppress or even remove the spurious oscillations high frequency modes. Whereas, the low frequency modes can be very accurately integrated due to the almost zero damping for these low frequency modes. It is shown herein that the proposed family method can have exactly the same numerical properties as those of HHT-α method for linear elastic systems. In addition, it still preserves the most important property of a structure-dependent integration method, which is an explicit formulation for each time step. Consequently, it can save a huge computational efforts in solving inertial problems when compared to the HHT-α method. In fact, it is revealed by numerical experiments that the CPU time consumed by the proposed family method is only about 1.6% of that consumed by the HHT-α method for the 125-DOF system while it reduces to be 0.16% for the 1000-DOF system. Apparently, the saving of computational efforts is very significant.

Keywords: structure-dependent integration method, nonlinear dynamic analysis, unconditional stability, numerical dissipation, accuracy

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Authors: Larasati Zuhro, Ida F Priyanto

Abstract:

Background: In March 2020, Indonesia started to be affected by Covid-19, and the number of victims increased slowly but surely until finally, the highest number of victims reached the highest—about 50,000 persons—for the daily cases in the middle of 2021. Like other institutions, schools and universities were suddenly closed in March 2020, and students had to change their ways of studying from face-to-face to online. This sudden changed affected students and faculty, including LIS students and faculty because they never experienced online classes in Indonesia due to the previous regulation that academic and school activities were all conducted onsite. For almost two years, school and academic activities were held online. This indeed has affected the way students learned and faculty delivered their courses. This raises the question of whether students are now ready for their new learning activities due to the covid-19 disruption. Objectives: this study was conducted to find out the impact of covid-19 pandemic on the LIS learning process and the effectiveness of online classes for students of LIS in Indonesia. Methodology: This was qualitative research conducted among LIS students at UIN Sunan Kalijaga, Yogyakarta, Indonesia. The population are students who were studying for masters’program during covid-19 pandemic. Results: The study showed that students were ready with the online classes because they are familiar with the technology. However, the Internet and technology infrastructure do not always support the process of learning. Students mention slow WIFI is one factor that causes them not being able to study optimally. They usually compensate themselves by visiting a public library, a café, or any other places to get WIFI network. Noises come from the people surrounding them while they are studying online.Some students could not concentrate well when attending the online classes as they studied at home, and their families sometimes talk to other family members, or they asked the students while they are attending the online classes. The noise also came when they studied in a café. Another issue is that the classes were held in shorter time than that in the face-to-face. Students said they still enjoyed the onsite classes instead of online, although they do not mind to have hybrid model of learning. Conclusion: Pandemic of Covid-19 has changed the way students of LIS in Indonesia learn. They have experienced a process of migrating the way they learn from onsite to online. They also adapted their learning with the condition of internet access speed, infrastructure, and the environment. They expect to have hybrid classes in the future.

Keywords: learning, LIS students, pandemic, covid-19

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Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

Abstract:

Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: clustering, data mining, DBSCAN, k-means, k-medoids, sensor data

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Authors: Khaled Mohammed

Abstract:

This paper presents novel face recognition and identification approaches for the real-time attendance management problem in large companies/factories and government institutions. The proposed uses the Minimum Ratio (MR) approach for employee identification. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features. Experimental results indicated an improvement in the performance of the proposed system compared to the Previous approaches at a rate between 2% to 5%. In addition, it decreased the time two times if compared with the Previous techniques, such as Extreme Learning Machine (ELM) & Multi-Scale Structural Similarity index (MS-SSIM). Finally, it achieved an accuracy of 99%.

Keywords: attendance management system, face detection and recognition, live face recognition, minimum ratio

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Authors: Zheng Sun, Weiwei Cui, Xiaodong Ma, Hongxin Jin, Dongpao Hong, Jinsong Yang, Jingyi Sun

Abstract:

With the improvement of the performance and complexity of modern equipment, automatic test system (ATS) becomes widely used for condition monitoring and fault diagnosis. However, the conventional ATS mainly works in a serial mode, and lacks the ability of testing several equipments at the same time. That leads to low test efficiency and ATS redundancy. Especially for a large majority of equipment under test, the conventional ATS cannot meet the requirement of efficient testing. To reduce the support resource and increase test efficiency, we propose a method of design for the parallel test based on the embedded system in this paper. Firstly, we put forward the general framework of the parallel test system, and the system contains a central management system (CMS) and several distributed test subsystems (DTS). Then we give a detailed design of the system. For the hardware of the system, we use embedded architecture to design DTS. For the software of the system, we use test program set to improve the test adaption. By deploying the parallel test system, the time to test five devices is now equal to the time to test one device in the past. Compared with the conventional test system, the proposed test system reduces the size and improves testing efficiency. This is of great significance for equipment to be put into operation swiftly. Finally, we take an industrial control system as an example to verify the effectiveness of the proposed method. The result shows that the method is reasonable, and the efficiency is improved up to 500%.

Keywords: parallel test, embedded system, automatic test system, automatic test system (ATS), central management system, central management system (CMS), distributed test subsystems, distributed test subsystems (DTS)

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