Search results for: multiple detection

Authors: Naya Masood, Russell Hodgson, Mark Tacey

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Purpose: Patients with acute diverticulitis (AD) have an increased risk of underlying colorectal cancer (CRC); however, those with uncomplicated AD may have the same underlying population risk. This study informs on an Australian AD population who were not routinely offered colonoscopic follow-up. Methods: A 2-year (July 2016 – June 2018) retrospective study of patients admitted with CT-confirmed acute diverticulitis was conducted. CT findings were categorised as ‘complicated’ and ‘uncomplicated’ and were correlated with the detection of cancer in subsequent colonoscopy or follow-up. Results: 67.7% (n=292) of 431 patients were seen to have had complicated AD on an abdominopelvic CT scan. Patients were complicated most commonly due to bowel wall thickening reported on CT (90.4%), perforation (20.2%), or an abscess (12%). Follow-up colonoscopic evaluation was conducted in 52.9% (n=228) of total cases of AD, out of which 156 suffered complicated AD and the rest uncomplicated. None of the uncomplicated AD patients in our cohort were found to have CRC. Of those with complicated AD, six were found to have CRC. Conclusion: The only CRC diagnoses were made in patients with complicated AD. Despite available evidence, a significant proportion of uncomplicated AD patients were still undergoing colonoscopy. There is scope to further safely decrease the number of colonoscopies performed in AD patients.

Keywords: acute diverticulitis, colonoscopy, colorectal cancer, advanced adenoma, complicated diverticulitis

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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Authors: Han Run-Sheng, Li Wen-Yao, Wang Feng, Liu Fei, Qiu Wen-Long, Lei Li

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Accurately positioning detection of concealed deposits or ore-bodies is one of the difficult problems in mineral exploration field. Theory calculation and exploration practices for tunnel gravity indicate that 3D high-precision Tunnel Gravity Exploration Method (TGEM) can find concealed high-density three-dimensional ore-bodies in the depth. The ore-finding breakthroughs at the depth of the Zhaotong Maoping carbonate-hosted Zn–Pb–(Ag–Ge) deposit in Northeastern Yunnan have proved that the exploration method in combination with MEAHFZ method is effective to detect concealed high-density ore-bodies. TGEM may overcome anomalous ambiguity of other geophysical methods for 3D positioning of concealed ore-bodies.

Keywords: 3D tunnel gravity exploration method, concealed high-density Ore-bodies, Zn–Pb–(Ag–Ge) deposit, Zaotong mapping, Northeastern Yunnan

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Authors: Mohamad Reza Khodabakhsh

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Physical activity is important because it affects the stress and mental health of the elderly. The purpose of this research is to examine the relationship between the physical activity of the elderly and stress and mental health. The current research is correlational research, and the studied population includes all the elderly who are engaged in sports in the parks of Mashhad city in 2021. The whole community consists of 200 people. Sampling was done by the headcount method. The tool used in this research is a questionnaire. The physical activity questionnaire is Likert. General GHQ is based on the self-report method. The study method is correlation type to find the relationship between predictor and predicted variables, and the multiple regression method was used for the relationships between the sub-components. And the results showed that physical activity has the effect of reducing the stress of the elderly and improving their mental health. In general, the results of this research indicate the confirmation of the research hypotheses.

Keywords: relationship, physical activity, stress, mental health, elderly

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Authors: Anne-Lena Kampen, Øivind Kure

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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: central machine learning, embedded machine learning, energy consumption, local machine learning, wireless sensor networks, WSN

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Authors: Smita Lakhotia, C. Kew, S. H. M. Siraj, B. Chern

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Up to 50% of those with endometriosis may suffer from infertility due to either distorted pelvic anatomy/impaired oocyte release or inhibit ovum pickup and transport, altered peritoneal function, endocrine and anovulatory disorders, including LUF, impaired implantation, progesterone resistance or decreased levels of cellular immunity. The dilemma continues as to whether the surgery or IVF is the optimal management for such recurrent endometriomas. The core question is whether surgery adds anything of value for infertile women with recurrent endometriosis or not. Complete and detailed information on risks and benefits of treatment alternatives must be offered to patients, giving a realistic estimate of chances of success of repetitive surgery and of multiple IVF cycles in order to allow unbiased choices between different possible optionsAn individualized treatment plan should be developed taking into account patient age, duration of infertility, previous pregnancies and specific clinical conditions and wish.

Keywords: recurrent endometriosis, infertility, oocyte release, pregnancy

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Authors: Abdolreza Esmaeilzadeh, Mehri Mirzaei

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Objective: Rheumatic disease is a chronic disease that causes pain, stiffness, swelling and limited motion and function of many joints. RA is the most common form of autoimmune arthritis, affecting more than 1.3 million Americans. Of these, about 75% are women. Materials and Methods: This study was formed due to the misconception about ANA test, which is frequently performed with methods based upon solid phase as ELISA. This experiment was conducted on 430 patients, with clinical symptoms that are likely affected with rheumatic diseases, simultaneously by means of ANA and FANA. Results: 36 cases (8.37%) of patients, despite positive ANA, have demonstrated negative results via Indirect Immunofluorescence Assay (IIFA), (false positive). 116 cases (27%) have demonstrated negative ANA results, by means of the ELISA technique, although they had positive IIFA results. Conclusion: Other advantages of IIFA are antibody titration and specific pattern detection that have the capability of distinguishing positive dsDNA results. According to the restrictions and false negative cases, in patients, IIFA test is highly recommended for these disease's diagnosis.

Keywords: autoimmune disease, IIFA, EIA, rheumatic disease

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Authors: Andreas Hirseland, Lukas Kerschbaumer

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In Germany, during the past years there constantly are about one million long term unemployed who did not benefit from the prospering labor market while most short term unemployed did. Instead, they are continuously dependent on welfare and sometimes precarious short-term employment, experiencing work poverty. Long term unemployment thus turns into a main obstacle to regular employment, especially if accompanied by other impediments such as low level education (school/vocational), poor health (especially chronical illness), advanced age (older than fifty), immigrant status, motherhood or engagement in care for other relatives. Almost two thirds of all welfare recipients have multiple impediments which hinder a successful transition from welfare back to sustainable and sufficient employment. Hiring them is often considered as an investment too risky for employers. Therefore formal application schemes based on formal qualification certificates and vocational biographies might reduce employers’ risks but at the same time are not helpful for long-term unemployed and welfare recipients. The panel survey ‘Labor market and social security’ (PASS; ~15,000 respondents in ~10,000 households), carried out by the Institute of Employment Research (the research institute of the German Federal Labor Agency), shows that their chance to get back to work tends to fall to nil. Only 66 cases of such unlikely transitions could be observed. In a sequential explanatory mixed-method study, the very scarce ‘success stories’ of unlikely transitions from long term unemployment to work were explored by qualitative inquiry – in-depth interviews with a focus on biography accompanied by qualitative network techniques in order to get a more detailed insight of relevant actors involved in the processes which promote the transition from being a welfare recipient to work. There is strong evidence that sustainable transitions are influenced by biographical resources like habits of network use, a set of informal skills and particularly a resilient way of dealing with obstacles, combined with contextual factors rather than by job-placement procedures promoted by Job-Centers according to activation rules or by following formal paths of application. On the employer’s side small and medium-sized enterprises are often found to give job opportunities to a wider variety of applicants, often based on a slow but steadily increasing relationship leading to employment. According to these results it is possible to show and discuss some limitations of (German) activation policies targeting welfare dependency and long-term unemployment. Based on these findings, indications for more supportive small scale measures in the field of labor-market policies are suggested to help long-term unemployed with multiple impediments to overcome their situation.

Keywords: against-all-odds, economic sociology, long-term unemployment, mixed-methods

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Authors: Juan David Sepulveda

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This article reflects the current stage of progress in the project “Determining technological trends in energy generation”. At first it was oriented towards finding out those trends by employing such tools as the scientometrics community had proved and accepted as effective for getting reliable results. Because a documented methodological guide for this purpose could not be found, the decision was made to reorient the scope and aim of this project, changing the degree of interest in pursuing the objectives. Therefore it was decided to propose and implement a novel guide from the elements and techniques found in the available literature. This article begins by explaining the elements and considerations taken into account when implementing and applying this methodology, and the tools that led to the implementation of a software application for patent revision. Univariate analysis helped recognize the technological leaders in the field of energy, and steered the way for a multivariate analysis of this sample, which allowed for a graphical description of the techniques of mature technologies, as well as the detection of emerging technologies. This article ends with a validation of the methodology as applied to the case of fuel cells.

Keywords: energy, technology mapping, patents, univariate analysis

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Authors: M. D. Haneef, R. B. Randall, Z. Peng

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Journal bearings used in IC engines are prone to premature failures and are likely to fail earlier than the rated life due to highly impulsive and unstable operating conditions and frequent starts/stops. Vibration signature extraction and wear debris analysis techniques are prevalent in the industry for condition monitoring of rotary machinery. However, both techniques involve a great deal of technical expertise, time and cost. Limited literature is available on the application of these techniques for fault detection in reciprocating machinery, due to the complex nature of impact forces that confounds the extraction of fault signals for vibration based analysis and wear prediction. This work is an extension of a previous study, in which an engine simulation model was developed using a MATLAB/SIMULINK program, whereby the engine parameters used in the simulation were obtained experimentally from a Toyota 3SFE 2.0 litre petrol engines. Simulated hydrodynamic bearing forces were used to estimate vibrations signals and envelope analysis was carried out to analyze the effect of speed, load and clearance on the vibration response. Three different loads 50/80/110 N-m, three different speeds 1500/2000/3000 rpm, and three different clearances, i.e., normal, 2 times and 4 times the normal clearance were simulated to examine the effect of wear on bearing forces. The magnitude of the squared envelope of the generated vibration signals though not affected by load, but was observed to rise significantly with increasing speed and clearance indicating the likelihood of augmented wear. In the present study, the simulation model was extended further to investigate the bearing wear behavior, resulting as a consequence of different operating conditions, to complement the vibration analysis. In the current simulation, the dynamics of the engine was established first, based on which the hydrodynamic journal bearing forces were evaluated by numerical solution of the Reynold’s equation. Also, the essential outputs of interest in this study, critical to determine wear rates are the tangential velocity and oil film thickness between the journal and bearing sleeve, which if not maintained appropriately, have a detrimental effect on the bearing performance. Archard’s wear prediction model was used in the simulation to calculate the wear rate of bearings with specific location information as all determinative parameters were obtained with reference to crank rotation. Oil film thickness obtained from the model was used as a criterion to determine if the lubrication is sufficient to prevent contact between the journal and bearing thus causing accelerated wear. A limiting value of 1 µm was used as the minimum oil film thickness needed to prevent contact. The increased wear rate with growing severity of operating conditions is analogous and comparable to the rise in amplitude of the squared envelope of the referenced vibration signals. Thus on one hand, the developed model demonstrated its capability to explain wear behavior and on the other hand it also helps to establish a correlation between wear based and vibration based analysis. Therefore, the model provides a cost-effective and quick approach to predict the impending wear in IC engine bearings under various operating conditions.

Keywords: condition monitoring, IC engine, journal bearings, vibration analysis, wear prediction

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Authors: Yu-Lin Shen, Ming-Kuen Chang

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In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

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Authors: Rana Akyazi, Cal Welbourn, Oscar E. Liburd

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The family Phytoseiidae are the most common plant inhabiting group of predatory mites. They are generally considered to be important biological control agents of pest mites on many crops world-wide. Several species of these mites are commercially available in many countries. This study was carried out to determine phytoseiid mite species on nine different blackberry varieties (Arapaho, Choctaw, Kiowa, Nachez, Navaho, Osage, Ouachita, Von, Watchita). The survey was conducted from June to October 2016. Leaf samples were collected monthly from selected organic and conventional commercial blackberry (Rubus spp.) farms in Florida and Georgia, USA. Nine phytoseiid mite (Acari: Mesostigmata) species were determined during the study. The results also showed that the incidence of Phytoseiidae was greater in organic than in conventional blackberries. Future survey studies can provide detection of new species, which may hold potential for biological control of economically important pests in key fruit crops.

Keywords: biological control, mite, Phytoseiidae, predator, Rubus spp.

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Authors: Saeedeh Barzegar Khalilsaraei, Manoocheher Kelarestaghi, Farshad Eshghi

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The vehicle color, as a prominent and stable feature, helps to identify a vehicle more accurately. As a result, vehicle color recognition is of great importance in intelligent transportation systems. Unlike conventional methods which use only a single Convolutional Neural Network (CNN) for feature extraction or classification, in this paper, four CNNs, with different architectures well-performing in different classes, are trained to extract various features from the input image. To take advantage of the distinct capability of each network, the multiple outputs are combined using a stack generalization algorithm as an ensemble technique. As a result, the final model performs better than each CNN individually in vehicle color identification. The evaluation results in terms of overall average accuracy and accuracy variance show the proposed method’s outperformance compared to the state-of-the-art rivals.

Keywords: Vehicle Color Recognition, Ensemble Algorithm, Stack Generalization, Convolutional Neural Network

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Authors: Yiding Qu, Svetlana V. Komarova

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Chemokines acting through their cognate chemokine receptors guide the directional migration of the cell along the chemokine gradient. Several chemokine receptors were recently identified as non-signaling (decoy), based on their ability to bind the chemokine but produce no measurable signal in the cell. The function of these decoy receptors is not well understood. We examined the expression of a decoy receptor CCRL1 and a signaling receptor that binds to the same ligands, CCR7, in prostate cancer using publically available microarray data (www.oncomine.org). The expression of both CCRL1 and CCR7 increased in an approximately half of prostate carcinoma samples and the majority of metastatic cancer samples compared to normal prostate. Moreover, the expression of CCRL1 positively correlated with the expression of CCR7. These data suggest that CCR7 and CCRL1 can be used as clinical markers for the early detection of transformation from carcinoma to metastatic cancer. In addition, these data support our hypothesis that the non-signaling chemokine receptors actively stimulate cell migration.

Keywords: bioinformatics, cell migration, decoy receptor, meta-analysis, prostate cancer

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Authors: Aron Miranda Burgos, Ergon Cugler de Moraes Silva

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In the present article, it is observed that the constant advancement of issues related to misinformation impacts the guarantee of the public policy cycle. Thus, it is found that the dissemination of false information has a direct influence on each of the component stages of this cycle. Therefore, in order to maintain scientific and theoretical credibility in the qualitative analysis process, it was necessary to logically interpose the concepts of firehosing of falsehood, fake news, public policy cycle, as well as using the epistemological and pragmatic mechanism at the intersection of such academic concepts, such as the scientific method. It was found, through the analysis of official documents and public notes, how the multiple theoretical perspectives evidence the commitment of the provision and elaboration of public policies, verifying the way in which the fake news impact each part of the process in this atmosphere.

Keywords: firehosing of falsehood, governance, misinformation, post-truth

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Authors: Ghazala Hcini, Imen Jdey, Hela Ltifi

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Malaria disease should be considered and handled as a potential restorative catastrophe. One of the most challenging tasks in the field of microscopy image processing is due to differences in test design and vulnerability of cell classifications. In this article, we focused on applying deep learning to classify patients by identifying images of infected and uninfected cells. We performed multiple forms, counting a classification approach using the Hue, Saturation, Value (HSV) color space. HSV is used since of its superior ability to speak to image brightness; at long last, for classification, a convolutional neural network (CNN) architecture is created. Clusters of focus were used to deliver the classification. The highlights got to be forbidden, and a few more clamor sorts are included in the information. The suggested method has a precision of 99.79%, a recall value of 99.55%, and provides 99.96% accuracy.

Keywords: deep learning, convolutional neural network, image classification, color transformation, HSV color, malaria diagnosis, malaria cells images

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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Authors: Khalil Khanafer

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This study emphasizes on analyzing the effect of flow conditions and the geometric variation of the microcantilever’s bluff body on the microcantilever detection capabilities within a fluidic device using a finite element fluid-structure interaction model. Such parameters include inlet velocity, flow direction, and height of the microcantilever’s supporting system within the fluidic cell. The transport equations are solved using a finite element formulation based on the Galerkin method of weighted residuals. For a flexible microcantilever, a fully coupled fluid-structure interaction (FSI) analysis is utilized and the fluid domain is described by an Arbitrary-Lagrangian–Eulerian (ALE) formulation that is fully coupled to the structure domain. The results of this study showed a profound effect on the magnitude and direction of the inlet velocity and the height of the bluff body on the deflection of the microcantilever. The vibration characteristics were also investigated in this study. This work paves the road for researchers to design efficient microcantilevers that display least errors in the measurements.

Keywords: fluidic cell, FSI, microcantilever, flow direction

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Authors: Dae Il Kim, Jungho Moon, Tae Yun Chung

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This paper presents a car parking monitoring system using a wireless sensor network. The presented sensor network has a line-shaped topology and adopts a TDMA-based protocol for allowing multi-hop communications. Sensor nodes are deployed in the ground of an outdoor parking lot in such a way that a sensor node monitors a parking space. Each sensor node detects the availability of the associated parking space and transmits the detection result to a sink node via intermediate sensor nodes existing between the source sensor node and the sink node. We evaluate the feasibility of the presented sensor network and the TDMA-based communication protocol through experiments using 11 sensor nodes deployed in a real parking lot. The result shows that the presented car parking monitoring system is robust to changes in the communication environments and efficient for monitoring parking spaces of outdoor parking lots.

Keywords: multi-hop communication, parking monitoring system, TDMA, wireless sensor network

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Authors: Saima Akbar

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The global financial crisis severely and adversely impacted the Pakistanis’ financial setups with far-reaching consequences for its victims. This study aimed to analyze the various determinants of the banks’ financial performance in Pakistan. The stepwise multiple regression analysis and pre-post analysis were carried out in this regard by using SPSS ver 22. The study found that the assets quality is the most influential determinant of return over assets followed by bank size and solvency. Advances, liquidity, investments, and size have positive while poor assets quality and deposits have a negative impact on the return over assets. The comparison of the pre-crisis and post-crisis coefficient values of the independent variables revealed that the global financial crisis had exerted a significant impact on the relative ability of the financial performance determinants to explain variations in return over assets.

Keywords: pre-crisis, post-crisis, coefficient values, determinants

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Authors: Afy Syahidan ACHMAD, Astin NURDIANA, SURYANTINI

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In volcanic arc environment we can find multiple volcanic deposits which overlapped with another volcanic deposit so it will complicates source and distribution determination. This problem getting more difficult when we can not trace any deposit border evidences in field especially in high vegetation volcanic area, or overlapped deposit with same characteristics. Main purpose of this study is to solve complex volcanostratigraphy mapping problems trough ridge, valley, and river continuity. This method application carried out in Old Sunda Volcanic, West Java, Indonesia. Using 1:100.000 and 1:50.000 topographic map, and regional geology map, old sunda volcanic deposit was differentiated in regional level and detail level. Final product of this method is volcanostratigraphy unit determination in reconnaissance stage to simplify mapping process.

Keywords: volcanostratigraphy, study, method, volcanic deposit

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Authors: Yashas Mattur, Jensen Coonradt

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Muon flux, the rate of muons reaching Earth from the atmosphere, is impacted by various factors such as air pressure, temperature, and humidity. However, the influence of concentrations of PM₂.₅ (particulate matter with diameters 2.5 mm or smaller) on muon detection rates remains unexplored. During the summer of 2023, smoke from Canadian wildfires (containing significant amounts of particulate matter) blew over regions in the Northern US, introducing huge fluctuations in PM₂.₅ concentrations, thus inspiring our experiment to investigate the correlation of PM₂.₅ concentrations and muon rates. To investigate this correlation, muon collision rates were measured and analyzed alongside PM₂.₅ concentration data over the periods of both light and heavy smoke. Other confounding variables, including temperature, humidity, and atmospheric pressure, were also considered. The results reveal a statistically significant inverse correlation between muon flux and PM₂.₅ concentrations, indicating that particulate matter has an impact on the rate of muons reaching the earth’s surface.

Keywords: Muon Flux, atmospheric effects on muons, PM₂.₅, airborne particulate matter

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Authors: Phatthanan Chaiyabut

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This research paper investigates whether the development of environmentally friendly practices by luxury hotel resorts can be used as a strategy for gaining competitive advantage through differentiation, and suggests ways to do it. The focus is on luxury hotel resorts in Samut Songkram Province, Thailand. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. Findings indicate that environmentally friendly development of hotel resorts in Samut Songkram Province has a very limited use as a corporate strategy. Only two luxury hotel resorts had it incorporated in their strategy, it is not much used in marketing indicating environmental issues are not seen as important. This was confirmed through the interviews with the managers that it is not seen as important issue to promote.

Keywords: competitive advantage, competitive strategy, Samut Songkram Province, hotel and resort

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Authors: M. W. Sun, Y. Zhang, L. M. Zhang, Z. H. Wang, Z. Q. Chen

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In the realm of flight control, the Proportional- Derivative (PD) control is still widely used for the attitude control in practice, particularly for the pitch control, and the attitude dynamics using PD controller should be investigated deeply. According to the empirical knowledge about the unstable flight dynamics, the control parameter combination conditions to generate sole or finite number of closed-loop oscillations, which is a quite smooth response and is more preferred by practitioners, are presented in analytical or numerical manners. To analyze the effects of the combination conditions of the control parameters, the roots of several polynomials are sought to obtain feasible solutions. These conditions can also be plotted in a 2-D plane which makes the conditions be more explicit by using multiple interval operations. Finally, numerical examples are used to validate the proposed methods and some comparisons are also performed.

Keywords: attitude control, dynamic performance, numerical solving method, interval, unstable flight dynamics

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Authors: Dongyeob Han, Jungwon Huh, Quang Huy Tran, Choonghyun Kang

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Unmanned Aerial Vehicles (UAVs) have been used for surveillance, monitoring, inspection, and mapping. In this paper, we present a systematic approach for automatic registration of UAV images for monitoring facilities such as building, green house, and civil structures. The two-step process is applied; 1) an image matching technique based on SURF (Speeded up Robust Feature) and RANSAC (Random Sample Consensus), 2) bundle adjustment of multi-temporal images. Image matching to find corresponding points is one of the most important steps for the precise registration of multi-temporal images. We used the SURF algorithm to find a quick and effective matching points. RANSAC algorithm was used in the process of finding matching points between images and in the bundle adjustment process. Experimental results from UAV images showed that our approach has a good accuracy to be applied to the change detection of facility.

Keywords: building, image matching, temperature, unmanned aerial vehicle

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Authors: Aditya Sethi, Vaibhav Sethi, Shenouda Girgis

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We present a case of a 31-year-old female who presented with a three week history of left eye blurry vision following a fever. She was diagnosed with Typhoid fever, confirmed by a positive Widal test report. On examination, her best corrected visual acuity in the right eye was 20/20 and in the left eye was 20/60. Fundus examination of the right eye showed a focal area of retinitis with retinal haemorrhages along the superior arcade within the macula. There was also focal area of retinitis with superficial retinal haemorrhages along the superior arcade vessels. There was also presence of multiple yellowish white exudates within the adjacent retinal artery arranged in a beaded pattern, suggestive of Kyrieleis' vasculitis. Optical Coherence Tomography (OCT) of the left eye demonstrated cystoid macula edema with serous foveal detachment.

Keywords: typhoid retinitis, Kyrieleis’ vasculitis, immune-mediated retinitis, post-fever retinitis, typhoid retinopathy, retinitis

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Authors: Khalid Soussi

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The study at hand has attempted to describe the acquisition of three EFL lexical knowledge aspects - meaning, synonymy and collocation – across three academic levels: Baccalaureate, second year and fourth year university levels in Morocco. The research also compares the development of the three lexical knowledge aspects between knowledge (reception) and use (production) and attempts to trace their order of acquisition. This has led to the use of three main data collection tasks: translation, acceptability judgment and multiple choices. The study has revealed the following findings. First, L1 and EFL mental lexicons are connected at the lexical knowledge depth. Second, such connection is active whether in language reception or use. Third, the connectivity between L1 and EFL mental lexicons tends to relatively decrease as the academic level of the learners increases. Finally, the research has revealed a significant 'order' of acquisition between the three lexical aspects, though not a very strong one.

Keywords: vocabulary acquisition, EFL lexical knowledge, mental lexicon, vocabulary knowledge depth

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Authors: Mubarak Saadu Nabunkari, Abdullahi Abdu Ibrahim, Muhammad Ilyas

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This study looks at how Internet of Things (IoT) devices are used in healthcare to monitor and treat patients better. However, using these devices in healthcare comes with security problems. The research explores using Security Information and Event Management (SIEM) systems with healthcare IoT devices to solve these security challenges. Reviewing existing literature shows the current state of IoT security and emphasizes the need for better protection. The main worry is that healthcare IoT devices can be easily hacked, putting patient data and device functionality at risk. To address this, the research suggests a detailed security framework designed for these devices. This framework, based on literature and best practices, includes important security measures like authentication, data encryption, access controls, and anomaly detection. Adding SIEM systems to this framework helps detect threats in real time and respond quickly to incidents, making healthcare IoT devices more secure. The study highlights the importance of this integration and offers guidance for implementing healthcare IoT securely, efficiently, and effectively.

Keywords: cyber security, threat intelligence, forensics, heath care

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Authors: Thi Thi Zin, Pyke Tin, Ikuo Kobayashi, Yoichiro Horii

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Today dairy farm experts and farmers have well recognized the importance of dairy cow Body Condition Score (BCS) since these scores can be used to optimize milk production, managing feeding system and as an indicator for abnormality in health even can be utilized to manage for having healthy calving times and process. In tradition, BCS measures are done by animal experts or trained technicians based on visual observations focusing on pin bones, pin, thurl and hook area, tail heads shapes, hook angles and short and long ribs. Since the traditional technique is very manual and subjective, the results can lead to different scores as well as not cost effective. Thus this paper proposes an algebraic geometric imaging approach for an automatic dairy cow BCS system. The proposed system consists of three functional modules. In the first module, significant landmarks or anatomical points from the cow image region are automatically extracted by using image processing techniques. To be specific, there are 23 anatomical points in the regions of ribs, hook bones, pin bone, thurl and tail head. These points are extracted by using block region based vertical and horizontal histogram methods. According to animal experts, the body condition scores depend mainly on the shape structure these regions. Therefore the second module will investigate some algebraic and geometric properties of the extracted anatomical points. Specifically, the second order polynomial regression is employed to a subset of anatomical points to produce the regression coefficients which are to be utilized as a part of feature vector in scoring process. In addition, the angles at thurl, pin, tail head and hook bone area are computed to extend the feature vector. Finally, in the third module, the extracted feature vectors are trained by using Markov Classification process to assign BCS for individual cows. Then the assigned BCS are revised by using multiple regression method to produce the final BCS score for dairy cows. In order to confirm the validity of proposed method, a monitoring video camera is set up at the milk rotary parlor to take top view images of cows. The proposed method extracts the key anatomical points and the corresponding feature vectors for each individual cows. Then the multiple regression calculator and Markov Chain Classification process are utilized to produce the estimated body condition score for each cow. The experimental results tested on 100 dairy cows from self-collected dataset and public bench mark dataset show very promising with accuracy of 98%.

Keywords: algebraic geometric imaging approach, body condition score, Markov classification, polynomial regression

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Authors: Arafat A. A. Shabaneh

Abstract:

Harsh environments demand a developed detection of an optical communication system to ensure a high level of security and safety. Fiber Bragg gratings (FBG) are emerging sensing instruments that respond to variations in strain and temperature via varying wavelengths. In this paper, cascaded uniform FBG as a strain sensor for 6 km length at 1550 nm wavelength with 30 oC is designed with analyzing of dynamic strain and wavelength shifts. FBG is placed in a small segment of optical fiber, which reflects light of a specific wavelength and passes the remaining wavelengths. This makes a periodic alteration in the refractive index within the fiber core. The alteration in the modal index of fiber produced due to strain consequences in a Bragg wavelength. When the developed sensor exposure to a strain of cascaded uniform FBG by 0.01, the wavelength is shifted to 0.0000144383 μm. The sensing accuracy of the developed sensor is 0.0012. Simulation results show reliable and effective strain monitoring sensors for remote sensing applications.

Keywords: Cascaded fiber Bragg gratings, Strain sensor, Remote sensing, Wavelength shift

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