Search results for: real time stress detection

Authors: Ivette Gonzalez-Rivera, Diana B. Paz-Trejo, Oscar Galicia-Castillo, David N. Velazquez-Martinez, Hugo Sanchez-Castillo

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Prolonged exposure to stress can cause disorders related with dysfunction in the prefrontal cortex such as generalized anxiety and depression. These disorders involve alterations in neurotransmitter systems; the serotonergic system—a target of the drugs that are commonly used as a treatment to these disorders—is one of them. Recent studies suggest that 5-HT1A receptors play a pivotal role in the serotonergic system regulation and in stress responses. In the same way, there is increasing evidence that astrocytes are involved in the pathophysiology of stress. The aim of this study was to examine the effects of 8-OH-DPAT, a selective agonist of 5-HT1A receptors, in the behavioral signs of anxiety and anhedonia as well as in the number of astrocytes in the medial prefrontal cortex (mPFC) after exposure to chronic stress. They used 50 male Wistar rats of 250-350 grams housed in standard laboratory conditions and treated in accordance with the ethical standards of use and care of laboratory animals. A protocol of chronic unpredictable stress was used for 10 consecutive days during which the presentation of stressors such as motion restriction, water deprivation, wet bed, among others, were used. 40 rats were subjected to the stress protocol and then were divided into 4 groups of 10 rats each, which were administered 8-OH-DPAT (Tocris, USA) intraperitoneally with saline as vehicle in doses 0.0, 0.3, 1.0 and 2.0 mg/kg respectively. Another 10 rats were not subjected to the stress protocol or the drug. Subsequently, all the rats were measured in an open field test, a forced swimming test, sucrose consume, and a cero maze test. At the end of this procedure, the animals were sacrificed, the brain was removed and the tissue of the mPFC (Bregma: 4.20, 3.70, 2.70, 2.20) was processed in immunofluorescence staining for astrocytes (Anti-GFAP antibody - astrocyte maker, ABCAM). Statistically significant differences were found in the behavioral tests of all groups, showing that the stress group with saline administration had more indicators of anxiety and anhedonia than the control group and the groups with administration of 8-OH-DPAT. Also, a dose dependent effect of 8-OH-DPAT was found on the number of astrocytes in the mPFC. The results show that 8-OH-DPAT can modulate the effect of stress in both behavioral and anatomical level. Also they indicate that 5-HT1A receptors and astrocytes play an important role in the stress response and may modulate the therapeutic effect of serotonergic drugs, so they should be explored as a fundamental part in the treatment of symptoms of stress and in the understanding of the mechanisms of stress responses.

Keywords: anxiety, prefrontal cortex, serotonergic system, stress

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Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

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Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD

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Authors: Seyhan Sahan-Firat, Meryem Temiz-Resitoglu, Demet Sinem Guden, Sefika Pinar Kucukkavruk, Bahar Tunctan, Ayse Nihal Sari, Zumrut Kocak

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We hypothesized that mTOR inhibition may prevent the multiple organ failures following severe multiple tissue injury associated with increased NADPH oxidase system activity occur in zymosan-induced systemic inflammation. Therefore, we investigated the role of mTOR in oxidative/nitrosative stress associated with increase in NADPH oxidase activity in zymosan-induced systemic inflammation model in rats. Male Wistar rats received saline (4 ml/kg, i.p.) and zymosan (500 mg/kg, i.p.) at time 0. Saline, or zymosan-treated rats were given rapamycin (1 mg/kg, i.p.) 1 h after saline or zymosan injections. Rats were sacrified 4 h after zymosan challenge and kidney, heart, thoracic aorta, and superior mesenteric artery were collected. NADPH oxidase activity, p22phox, gp91phox, and p47phox protein expression and nitrotyrosine levels were measured in tissue samples. Zymosan administration caused an increase in NADPH oxidase activity, p22phox, gp91phox, and p47phox protein expression and nitrotyrosine levels in kidney, heart, thoracic aorta, and superior mesenteric artery. These changes caused by zymosan reversed by rapamycin, a selective mTOR inhibitor. Rapamycin alone had no effect on the parameters measured. Our results demonstrated that zymosan-induced oxidative/nitrosative stress presumably due to enhanced activity of NADPH oxidase, expression of p22phox, gp91phox, and p47phox and production of peroxynitrite were mediated by mTOR. [This work was financially supported by Research Foundation of Mersin University (2016-2-AP3-1900)].

Keywords: oxidative stress, mTOR, nitrosative stress, zymosan

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Authors: Hannah Gutmann, Rick Richardson, Richard Bryant

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Intrusive memories following a traumatic event are not uncommon. However, in some individuals, these memories become maladaptive and lead to prolonged stress reactions. A seminal model of PTSD explains that aberrant processing during trauma may lead to prolonged stress reactions and intrusive memories. This model explains that elevated arousal at the time of the trauma promotes data driven processing, leading to fragmented and intrusive memories. This study investigated the role of elevated arousal on the development of intrusive memories. We measured salivary markers of arousal and investigated what impact this had on data driven processing, memory fragmentation, and subsequently, the development of intrusive memories. We assessed 100 healthy participants to understand their processing style, arousal, and experience of intrusive memories. Participants were randomised to a control or experimental condition, the latter of which was designed to increase their arousal. Based on current theory, participants in the experimental condition were expected to engage in more data driven processing and experience more intrusive memories than participants in the control condition. This research aims to shed light on the mechanisms underlying the development of intrusive memories to illustrate ways in which therapeutic approaches for PTSD may be augmented for greater efficacy.

Keywords: stress, cortisol, SAA, PTSD, intrusive memories

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Authors: K. S. Vedasingha, K. K. M. T. Perera, K. I. Hathurusinghe, H. W. I. Akalanka, Nelum Chathuranga Amarasena, Nalaka R. Dissanayake

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Railways provide the most convenient and economically beneficial mode of transportation, and it has been the most popular transportation method among all. According to the past analyzed data, it reveals a considerable number of accidents which occurred at railways and caused damages to not only precious lives but also to the economy of the countries. There are some major issues which need to be addressed in railways of South Asian countries since they fall under the developing category. The goal of this research is to minimize the influencing aspect of railway level crossing accidents by developing the “railway process automation system”, as there are high-risk areas that are prone to accidents, and safety at these places is of utmost significance. This paper describes the implementation methodology and the success of the study. The main purpose of the system is to ensure human safety by using the Internet of Things (IoT) and image processing techniques. The system can detect the current location of the train and close the railway gate automatically. And it is possible to do the above-mentioned process through a decision-making system by using past data. The specialty is both processes working parallel. As usual, if the system fails to close the railway gate due to technical or a network failure, the proposed system can identify the current location and close the railway gate through a decision-making system, which is a revolutionary feature. The proposed system introduces further two features to reduce the causes of railway accidents. Railway track crack detection and motion detection are those features which play a significant role in reducing the risk of railway accidents. Moreover, the system is capable of detecting rule violations at a level crossing by using sensors. The proposed system is implemented through a prototype, and it is tested with real-world scenarios to gain the above 90% of accuracy.

Keywords: crack detection, decision-making, image processing, Internet of Things, motion detection, prototype, sensors

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Authors: Nomfundo Ngombane, Topside E. Mathonsi

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Remote sensing and satellite imaging have been widely used to detect wildfires; nevertheless, the technologies present some limitations in terms of early wildfire detection as the technologies are greatly influenced by weather conditions and can miss small fires. The fires need to have spread a few kilometers for the technologies to provide accurate detection. The South African Advanced Fire Information System uses MODIS (Moderate Resolution Imaging Spectroradiometer) as satellite imaging. MODIS has limitations as it can exclude small fires and can fall short in validating fire vulnerability. Thus in the future, a Machine Learning algorithm will be designed and implemented for the early detection of wildfires. A simulator will be used to evaluate the effectiveness of the proposed solution, and the results of the simulation will be presented.

Keywords: moderate resolution imaging spectroradiometer, advanced fire information system, machine learning algorithm, detection of wildfires

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Authors: Abdulrahman S. Alturki, John S. Loomis

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This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.

Keywords: camera calibration, corner detector, edge detector, saddle points

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Authors: Jennifer Loar, Jason Montefalcon, Kissy Mae Alimpangog, Miriam Bongo

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The demanding, professional roles that air traffic controllers (ATC) play in air transport operation provided the main motivation of this paper. As the controllers’ workload stress becomes more complex due to various stressors, the challenge to overcome these in the pursuit of improving the efficiency of controllers and safety level of aircrafts has been relevant. Therefore, in order to determine the main stressors and surface the best alternative, two widely-known multi-criteria decision-making (MCDM) methods, DANP and PROMETHEE II, are applied. The proposed method is demonstrated in a case study at Mactan Civil Aviation Authority of the Philippines (CAAP). The results showed that the main stressors are high air traffic volume, extraneous traffic, unforeseen events, limitations and reliability of equipment, noise/distracter, micro climate, bad posture, relations with supervisors and colleagues, private life conditions/relationships, and emotional conditions. In the outranking of alternatives, compartmentalization is believed to be the most preferred alternative to overcome controllers’ workload stress. This implies that compartmentalization can best be applied to reduce controller workload stress.

Keywords: air traffic controller, DANP, MCDM, PROMETHEE II, workload stress

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Authors: Ririt Aprilin Sumarsono

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Composite member (concrete and steel) has been widely advanced for structural utilization due to its best performance in resisting load, reducing the total weight of the structure, increasing stiffness, and other available advantages. On the other hand, the environment load such as corrosion (e.g. chloride ingress) creates significant time-dependent degradation for steel. Analysis performed in this paper is mainly considered uniform corrosion for evaluating the composite beam without examining the pit corrosion as the initial corrosion formed. Corrosion level in terms of weight loss is modified in yield stress and modulus elasticity of steel. Those two mechanical properties are utilized in this paper for observing the stresses due to corrosion attacked. As corrosion level increases, the effective width of the composite beam in the concrete section will be wider. The position of a neutral axis of composite section will indicate the composite action due to corrosion of composite beam so that numerous shear connectors provided must be reconsidered. Flexure capacity quantification provides stresses, and shear capacity calculation derives connectors needed in overcoming the shear problem for composite beam under corrosion. A model of simply supported composite beam examined in this paper under uniform corrosion where the stresses as the focus of the evaluation. Principal stress at the first stage of composite construction decline as the corrosion level incline, parallel for the second stage stress analysis where the tension region held by the steel undergoes lower capacity due to corrosion. Total stresses of the composite section for steel to be born significantly decreases particularly in the outermost fiber of tension side. Whereas, the available compression side is smaller as the corrosion level increases so that the stress occurs on the compression side shows reduction as well. As a conclusion, the increment of corrosion level will degrade both compression and tension side of stresses.

Keywords: composite beam, modulus of elasticity, stress analysis, yield strength, uniform corrosion

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Authors: Gilberto Goracci, Fabio Curti

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This work presents a robust, light, and inexpensive algorithm to perform autonomous orbit determination using onboard magnetometer data in real-time. Magnetometers are low-cost and reliable sensors typically available on a spacecraft for attitude determination purposes, thus representing an interesting choice to perform real-time orbit determination without the need to add additional sensors to the spacecraft itself. Magnetic field measurements can be exploited by Extended/Unscented Kalman Filters (EKF/UKF) for orbit determination purposes to make up for GPS outages, yielding errors of a few kilometers and tens of meters per second in the position and velocity of a spacecraft, respectively. While this level of accuracy shows that Kalman filtering represents a solid baseline for autonomous orbit determination, it is not enough to provide a reliable state estimation in the absence of GPS signals. This work combines the solidity and reliability of the EKF with the versatility of a Recurrent Neural Network (RNN) architecture to further increase the precision of the state estimation. Deep learning models, in fact, can grasp nonlinear relations between the inputs, in this case, the magnetometer data and the EKF state estimations, and the targets, namely the true position, and velocity of the spacecraft. The model has been pre-trained on Sun-Synchronous orbits (SSO) up to 2126 kilometers of altitude with different initial conditions and levels of noise to cover a wide range of possible real-case scenarios. The orbits have been propagated considering J2-level dynamics, and the geomagnetic field has been modeled using the International Geomagnetic Reference Field (IGRF) coefficients up to the 13th order. The training of the module can be completed offline using the expected orbit of the spacecraft to heavily reduce the onboard computational burden. Once the spacecraft is launched, the model can use the GPS signal, if available, to fine-tune the parameters on the actual orbit onboard in real-time and work autonomously during GPS outages. In this way, the provided module shows versatility, as it can be applied to any mission operating in SSO, but at the same time, the training is completed and eventually fine-tuned, on the specific orbit, increasing performances and reliability. The results provided by this study show an increase of one order of magnitude in the precision of state estimate with respect to the use of the EKF alone. Tests on simulated and real data will be shown.

Keywords: artificial intelligence, extended Kalman filter, orbit determination, magnetic field

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Authors: M. Esmailian, M. Shakouri, A. Mottahedi, S. G. Shabestari

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Heat treatable aluminium alloys such as 7075 and 7055, because of high strength and low density, are used widely in aircraft industry. For best mechanical properties, T6 heat treatment has recommended for this regards, but this temper treatment is sensitive to corrosion induced and Stress Corrosion Cracking (SCC) damage. For improving this property, the over-aging treatment (T7) applies to this alloy, but it decreases the mechanical properties up to 30 percent. Hence, to increase the mechanical properties, without any remarkable decrease in SCC resistant, Retrogression and Re-Aging (RRA) heat treatment is used. This treatment performs in a relatively short time. In this paper, the RRA heat treatment was applied to 7055 aluminum alloy and then effect of RRA time on the mechanical properties of 7055 has been investigated. The results show that the 40 minute time is suitable time for retrogression of 7055 aluminum alloy and ultimate strength increases up to 625MPa.

Keywords: 7055 Aluminum alloy, mechanical properties, SCC resistance, heat Treatment

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Authors: Kashika P. H.

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The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

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Authors: Richard O’Riordan, Saritha Unnikrishnan

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Autonomous Vehicles (AVs) are incorporating an increasing number of ADAS features, including automated lane-keeping systems. In recent years, many research papers into lane detection algorithms have been published, varying from computer vision techniques to deep learning methods. The transition from lower levels of autonomy defined in the SAE framework and the progression to higher autonomy levels requires increasingly complex models and algorithms that must be highly reliable in their operation and functionality capacities. Furthermore, these algorithms have no room for error when operating at high levels of autonomy. Although the current research details existing computer vision and deep learning algorithms and their methodologies and individual results, the research also details challenges faced by the algorithms and the resources needed to operate, along with shortcomings experienced during their detection of lanes in certain weather and lighting conditions. This paper will explore these shortcomings and attempt to implement a lane detection algorithm that could be used to achieve improvements in AV lane detection systems. This paper uses a pre-trained LaneNet model to detect lane or non-lane pixels using binary segmentation as the base detection method using an existing dataset BDD100k followed by a custom dataset generated locally. The selected roads will be modern well-laid roads with up-to-date infrastructure and lane markings, while the second road network will be an older road with infrastructure and lane markings reflecting the road network's age. The performance of the proposed method will be evaluated on the custom dataset to compare its performance to the BDD100k dataset. In summary, this paper will use Transfer Learning to provide a fast and robust lane detection algorithm that can handle various road conditions and provide accurate lane detection.

Keywords: ADAS, autonomous vehicles, deep learning, LaneNet, lane detection

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Authors: H. Jawan

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This review describes the models of environmental-related crack propagation of aluminum alloys (7xxx) during the last few decades. Acknowledge on effects of different factors on the susceptibility to SCC permits to propose valuable mechanisms on crack advancement. The reliable mechanism of cracking give a possibility to propose the optimum chemical composition and thermal treatment conditions resulting in microstructure the most suitable for real environmental condition and stress state.

Keywords: microstructure, environmental, propagation, mechanism

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Authors: Mohammad Motiee

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The present study aims at presenting Samuel Beckett's attempts to pierce the world of knowledge and understanding with a hope to approach it though he knew it is unattainable. To know about Beckett more and to get the idea about the notion of the absurd, we found it necessary to find the real meaning of existence both in the notion of the absurd and in Existentialism. Among many philosophers, as is evident in this paper, who worked on the concept of existence, Beckett reveals a very peculiar path by which some labelled him a mere absurdist. In this study, we tried to show that unlike this label and also unlike many philosophers' premise, Beckett did not assign his contemplation on the boundaries of existence but to find a way to retreat from it. This is the only way for him to find the real meaning of Self. While Existentialism advocates primary existence, Beckett's Absurdity appreciates a reliable being in a realm out of limits of the world. The Absurd person has no tendency to put himself in the barriers of time and language. Time imprisons one in the frame of days and nights, the solid dimensions in which the Self cannot be evidenced. Beckett shows sadly how the boundaries and dimensions blind the being and how the absurd meaning of existence arises from such a limit in the mundane realm.

Keywords: existence, absurdity, existentialism, self, alienation, being

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Authors: Xinghang Lv, Tao Peng, Jia Chen, Junping Liu, Xinrong Hu, Ruhan He, Minghua Jiang, Wenli Cao

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As one of the most dangerous vulnerabilities, effective detection of buffer overflow vulnerabilities is extremely necessary. Traditional detection methods are not accurate enough and consume more resources to meet complex and enormous code environment at present. In order to resolve the above problems, we propose the method for Buffer overflow detection based on Abstract syntax tree, Control flow graph, and Data dependency graph (BodeACD) in C/C++ programs with source code. Firstly, BodeACD constructs the function samples of buffer overflow that are available on Github, then represents them as code representation sequences, which fuse control flow, data dependency, and syntax structure of source code to reduce information loss during code representation. Finally, BodeACD learns vulnerability patterns for vulnerability detection through deep learning. The results of the experiments show that BodeACD has increased the precision and recall by 6.3% and 8.5% respectively compared with the latest methods, which can effectively improve vulnerability detection and reduce False-positive rate and False-negative rate.

Keywords: vulnerability detection, abstract syntax tree, control flow graph, data dependency graph, code representation, deep learning

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Authors: Garreth Kestell, Lukah Dykes, Danielle Zerk, Kyla Trewartha, Rhianon Marshall, Elena Rudnik

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Adolescent mental health is an international priority and the impact of innovative service models must be evaluated. Secondary school-based mental health services (SBMHS) involving private general practitioners and psychologists are a model of care being trialed in South Australia. Measures of depression, anxiety, and stress are routinely collected throughout psychotherapy sessions. This research set out to quantify the impact of psychotherapy for rural adolescents in a school setting and explore the importance of session frequency. Methods: Demographics, session date and DASS21 scores from students (n=65) seen in 2016 by three psychologists working at the SBMHS were recorded. Students were aged 13-18 years (M=15.43, SD= 1.24), mostly female (F=51, M=14), attended between 1 and 23 sessions with a median of 6 sessions (MAD 5.93) in one-year. The treating psychologist collected self-administered DASS21 scores. A mixed model analysis was used with age, sex, treating psychologist, months from first session, and session number as fixed effects, with response variables of DASS depression, anxiety, and stress scores. Results: 71.5% were classified as having extreme or severe anxiety and half had extreme or severe depression and/or stress scores. On average males had a greater increase in DASS scores over time but males attending more sessions benefited most from therapy. Discussion: Psychologists are treating rural adolescents in schools for severe anxiety, depression, and stress. This pilot study indicates that a predictive model combining demographics, session frequency, and DASS scores may help identify who is most likely to benefit from individual psychotherapy. Variations in DAS scores of individuals over time indicate the need for the collection of information such as living situation and exposure to alcohol. A larger sample size and additional data are currently being collected to allow for a more robust analysis.

Keywords: adolescent health, psychotherapy, school based mental health services, DAS21

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Authors: Jui-Hsiu Chang

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As an increasing number of restaurants are growing, the demand for man force in the food service industry is dramatically increasing as well. However, food service workers often complete the heavy workload, infrequent breaks, long hours and shifts. With the overwhelming workload, many workers have experienced high injury rates. As a result, the restaurant industry reports a higher employee turnover rate compare to other service industries in Taiwan. Restaurant managers are seeing ways to retain good employees in order to provide good quality service for daily operation. The purpose of this study was to explore the relationship among exercise participation, job stress and job satisfaction on the food service employees. In addition, to examine how the job stress affected their job satisfaction. A survey using a self-reported questionnaire was conducted to collect data, and 269 questionnaires were collected for data analysis. The obtained materials were analyzed using descriptive statistic, independent t-test, one-way ANOVA, linear regression analysis. The results show that 1. Job stress had a significantly negative influence on employees’ job satisfaction. 2. Exercise participation had significantly positive influence on employees’ job satisfaction. 3. Job stress and job satisfaction varied among the groups of respondent with different level of exercise involvement. Furthermore, the practical implications were proposed for the food service company management when developing daily operational strategies.

Keywords: exercise participation, food service employees, job satisfaction, job stress

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Authors: Maryam Heidari, James H. Jones Jr.

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Millions of online posts about different topics and products are shared on popular social media platforms. One use of this content is to provide crowd-sourced information about a specific topic, event or product. However, this use raises an important question: what percentage of information available through these services is trustworthy? In particular, might some of this information be generated by a machine, i.e., a bot, instead of a human? Bots can be, and often are, purposely designed to generate enough volume to skew an apparent trend or position on a topic, yet the consumer of such content cannot easily distinguish a bot post from a human post. In this paper, we introduce a model for social media bot detection which uses Bidirectional Encoder Representations from Transformers (Google Bert) for sentiment classification of tweets to identify topic-independent features. Our use of a Natural Language Processing approach to derive topic-independent features for our new bot detection model distinguishes this work from previous bot detection models. We achieve 94\% accuracy classifying the contents of data as generated by a bot or a human, where the most accurate prior work achieved accuracy of 92\%.

Keywords: bot detection, natural language processing, neural network, social media

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Authors: Zhang Tao, Si Tang, Zhang Yufeng, Jin Jiahua

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Work pressure is an emerging research of organizational behavior. Many factors associated with this study also attracted the interest of scholars. Macao is surrounding by open micro-capitalist economy which has a high internationalization level and Mature operation system. And there is no doubt that tourism and hotel service industry is the pillar of the Macao economy with the developing of the mainland individual tourist visa. More and more cities are willing to inclusive culture diversity which lead to the amount of inbound tourists present high-speed up trend cause the hotel industry has a strong customer base and development space. At the same time, the hotel staff is an important role in the service. However, affected by some adverse factors, the hotel staff face a variety of pressures. This study combs the concept and theory of pressures relevant influencing factors and puts forward the purpose of this research. The focus of this study will be organizational supported by work efficiency and work pressure, using qualitative and quantitative research methods. Through questionnaires and interviews, 10 hotels in Macao were selected and 500 questionnaires were distributed to the employees. Statistical analysis software SPSS was used for descriptive statistics. By exploratory factor analysis and confirmatory factor analysis, effect. And the relevant practitioners on behalf of the interview content analysis. The innovation of this research lies in the empirical study of the relationship between the working pressure, organizational support and working efficiency of Macau hotel practitioners, and constructs and validates the structural model of the relationship among them. This model will be helpful for people to use more research methods to study hotel practitioners pressure in the future. At the same time, we can draw the following conclusions: 1. There is a significant negative correlation between salary level and job stress; 2. There is a significant negative correlation between job stress and performance; 3. Different organizational support can interfere the relationship between job stress and performance; 4. Put forward the strategy of relevance adjustment, which provides a reference value for the hotel industry in human resource management. It would be helpful to improve their service standard by training their practitioners more scientifically and rationally.

Keywords: Macau, perceived organizational support, work stress, work efficiency

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Authors: Chonlakorn Wiboonsiriruk, Ekachai Phaisangittisagul, Chadchai Srisurangkul, Itsuo Kumazawa

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Public transportation is a crucial aspect of passenger transportation, with buses playing a vital role in the transportation service. Passenger counting is an essential tool for organizing and managing transportation services. However, manual counting is a tedious and time-consuming task, which is why computer vision algorithms are being utilized to make the process more efficient. In this study, different object detection algorithms combined with passenger tracking are investigated to compare passenger counting performance. The system employs the EfficientDet algorithm, which has demonstrated superior performance in terms of speed and accuracy. Our results show that the proposed system can accurately count passengers in varying conditions with an accuracy of 94%.

Keywords: computer vision, object detection, passenger counting, public transportation

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Authors: Vera Jancurova

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The financial theory is dominated by the believe that weekday effect has disappeared from current markets. The purpose of this article is to study anomalies, especially weekday effect, at real markets that disrupt the efficiency of financial markets. The research is based on the analyses of historical daily exchange rates of significant world indices to determine the presence of weekday effects on financial markets. The methodology used for the study is based on the analyzes of daily averages of particular indexes for different time periods. Average daily gains were analyzed for their whole time interval and then for particular five and ten years periods with the aim to detect the presence on current financial markets. The results confirm the presence of weekday effect at the most significant indices - for example: Nasdaq, S & P 500, FTSE 100 and the Hang Seng. It was confirmed that in the last ten years, the weekend effect disappeared from financial markets. However in last year’s the indicators show that weekday effect is coming back. The study shows that weekday effect has to be taken into consideration on financial markets, especially in the past years.

Keywords: indices, anomalies, behavioral finance, weekday effect

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Authors: C. C. Egwuonwu, N. A. A. Okereke, K. O. Chilakpu, S. O. Ohanyere

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In this study, initial soil strength indices (qu) and stress-strain characteristics, namely failure strain (ϵf), area under the stress-strain curve up to failure (Is) and stress-strain modulus between no load and failure (Es) were investigated as potential indicators for characterizing the erosion resistance of two compacted soils, namely sandy clay loam (SCL) and clay loam (CL) in some selected sites in Enugu State, Nigeria. The unconfined compressive strength (used in obtaining strength indices) and stress-strain measurements were obtained as a function of moisture content in percentage (mc %) and dry density (γd). Test were conducted over a range of 8% to 30% moisture content and 1.0 g/cm3 to 2.0 g/cm3 dry density at applied loads of 20, 40, 80, 160 and 320 kPa. Based on the results, it was found out that initial soil strength alone was not a good indicator of erosion resistance. For instance, in the comparison of exponents of mc% and γd for jet index or erosion resistance index (Ji) and the strength measurements, qu and Es agree in signs for mc%, but are opposite in signs for γd. Therefore, there is an inconsistency in exponents making it difficult to develop a relationship between the strength parameters and Ji for this data set. In contrast, the exponents of mc% and γd for Ji and ϵf and Is are opposite in signs, there is potential for an inverse relationship. The measured stress-strain characteristics, however, appeared to have potential in providing useful information on erosion resistance. The models developed for the prediction of the extent or the susceptibility of soils to erosion and subjected to sensitivity test on some selected sites achieved over 90% efficiency in their functions.

Keywords: characterization of erodibility, selected sites in Enugu state, soil strength, stress-strain indices

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Authors: A. Benyahia, M. Zergoug, M. Amir, M. Fodil

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The main objective of this work is to enhance the Pulsed Eddy Current (PEC) response from the aluminum structure using signal processing. Cracks and metal loss in different structures cause changes in PEC response measurements. In this paper, time-frequency analysis is used to represent PEC response, which generates a large quantity of data and reduce the noise due to measurement. Power Spectral Density (PSD) after Wavelet Decomposition (PSD-WD) is proposed for defect detection. The experimental results demonstrate that the cracks in the surface can be extracted satisfactorily by the proposed methods. The validity of the proposed method is discussed.

Keywords: DT, pulsed eddy current, continuous wavelet transform, Mexican hat wavelet mother, defect detection, power spectral density.

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Authors: Amjad Abdullah, Amjad Yahya, Bushra Aljohani, Amani Alghamdi

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Change point detection is an important part of data analysis. The presence of a change point refers to a significant change in the behavior of a time series. In this article, we examine the detection of multiple change points of parameters of the exponential Lomax distribution, which is broad and flexible compared with other distributions while fitting data. We used the Schwarz information criterion and binary segmentation to detect multiple change points in publicly available data on the average temperature in the ozone layer. The change points were successfully located.

Keywords: binary segmentation, change point, exponentialLomax distribution, information criterion

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Authors: P. Saleh, G. Challita, R. Hazimeh, K. Khalil

Abstract:

In this paper 3D FEM analysis was carried out on double lap bonded joint with composite adherents subjected to dynamic shear. The adherents are made of Carbon/Epoxy while the adhesive is epoxy Araldite 2031. The maximum average shear stress and the stress homogeneity in the adhesive layer were examined. Three fibers textures were considered: UD; 2.5D and 3D with same volume fiber then a parametric study based on changing the thickness and the type of fibers texture in 2.5D was accomplished. Moreover, adherents’ dissimilarity was also investigated. It was found that the main parameter influencing the behavior is the longitudinal stiffness of the adherents. An increase in the adherents’ longitudinal stiffness induces an increase in the maximum average shear stress in the adhesive layer and an improvement in the shear stress homogeneity within the joint. No remarkable improvement was observed for dissimilar adherents.

Keywords: adhesive, composite adherents, impact shear, finite element

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Authors: Shitu Sani

Abstract:

The paper is advanced on the historical background of the effects of excess work load on lecturers in higher institutions of learning which will assess the socio-economic and psychological disposition of lecturers in the realm of quality production. The paper further discusses the significant roles played by excess work load in general transformation of higher education, which will give the management and stake holders input for successful development of higher education. Even though all forms of work and organizational procedures are potential source of stress and stressors. In higher institution of leaning, lecturers perform many responsibilities such as lecturing, carrying out research and engaging in community services. If these multiple roles could not be handle property it would have result in stress which may have negative impact on job performance, and it’s relation with instructional technology. A sample 191 lecturers were randomly selected from the higher institutions in the northern west zone in Nigerian using two instruments i.e. work load stress management question and job performance Approval, data were collected on lecturers of socio-economic and physiological stress and job performances. Findings of the study shows that lecture experienced excess work load in academic activities. Lecturer’s job performance was negatively influences by socio-economic and psychological work stress. Among the recommendation made were the need for organizing regular induction courses for lecturers on stress, and enhance interpersonal relations among the lecturers as well as provision of electronic public address system to reduce the stress.

Keywords: effect, excess, lecturers, workload

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Authors: Abdela Bulbula

Abstract:

Background: Marek’s disease virus is a devastating infection, causing high morbidity and mortality in chickens in Ethiopia. Methods: The current study was conducted from March to November, 2021 with the general objective of performing antemortem and postmortem, isolation, and molecular detection of Marek’s disease virus from outbreak cases in southwestern Ethiopia. Accordingly, based on outbreak information reported from the study sites namely, Bedelle, Yayo, and Bonga towns in southwestern Ethiopia, 50 sick chickens were sampled. The backyard and intensive farming systems of chickens were included in the sampling and priorities were given for chickens that showed clinical signs that are characteristics of Marek’s disease. Results: By clinical examinations, paralysis of legs and wings, gray eye, loss of weight, difficulty in breathing, and depression were recorded on all chickens sampled for this study and death of diseased chickens was observed. In addition, enlargement of the spleen and gross lesions of the liver and heart were recorded during postmortem examination. The death of infected chickens was observed in both vaccinated and non-vaccinated flocks. Out of 50 pooled feather follicle samples, Marek’s disease virus was isolated from 14/50 (28%) by cell culture method and out of six tissue samples, the virus was isolated from 5/6(83.30%). By Real time polymerization chain reaction technique, which was targeted to detect the Meq gene, Marek’s disease virus was detected from 18/50 feather follicles which accounts for 36% of sampled chickens. Conclusion: In general, the current study showed that the circulating Marek’s disease virus in southwestern Ethiopia was caused by the oncogenic Gallid herpesvirus-2 (Serotype-1). Further research on molecular characterization of revolving virus in current and other regions is recommended for effective control of the disease through vaccination.

Keywords: Ethioi, Marek's disease, isolation, molecular

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Authors: Nguyen Thi Loan, Phan Ngoc Thanh Tra

Abstract:

Container is one of the techniques used in Eye Movement Desensitization and Reprocessing (EDMR) Therapy. This paper presents the positive results of applying Container technique to “high risk children”. The sample for this research is composed of 60 “high risk children” whose ages range from 11 to 18 years old, housed in Ho Chi Minh City Youth Center. They have been under the program of the Worldwide Orphans Foundation since August 2015 for various reasons such as, loss of parents, anti-social behaviors, homelessness, child labor among others. These “high risk children” are under high levels of stress, anxiety and depression. The subjects were divided into two groups: the control and the experimental with 30 members each. The experimental group was applied Container Technique and the instruments used to measure their levels of stress, anxiety, and depression are DASS-42 and ASEBA. Results show that after applying the Container Technique to the experimental group, there are significant differences between the two groups’ levels of stress, anxiety and depression. The experimental group’s levels of stress, anxiety and depression decreased significantly. The results serve as a basis for the researchers to make an appeal to psychologists to apply Container Technique in doing psychological treatment in a suitable context.

Keywords: anxiety, depression, container technique, EMDR

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Authors: Arunas Burinskas, Aurelija Burinskiene

Abstract:

On average, ten percent of drugs - commercial products are not available in pharmacies due to shortage. The shortage event disbalance sales and requires a recovery period, which is too long. Therefore, one of the critical issues that pharmacies do not record potential sales transactions during shortage and recovery periods. The authors suggest estimating outliers during shortage and recovery periods. To shorten the recovery period, the authors suggest using average sales per sales day prediction, which helps to protect the data from being downwards or upwards. Authors use the outlier’s visualization method across different drugs and apply the Grubbs test for significance evaluation. The researched sample is 100 drugs in a one-month time frame. The authors detected that high demand variability products had outliers. Among analyzed drugs, which are commercial products i) High demand variability drugs have a one-week shortage period, and the probability of facing a shortage is equal to 69.23%. ii) Mid demand variability drugs have three days shortage period, and the likelihood to fall into deficit is equal to 34.62%. To avoid shortage events and minimize the recovery period, real data must be set up. Even though there are some outlier detection methods for drug data cleaning, they have not been used for the minimization of recovery period once a shortage has occurred. The authors use Grubbs’ test real-life data cleaning method for outliers’ adjustment. In the paper, the outliers’ adjustment method is applied with a confidence level of 99%. In practice, the Grubbs’ test was used to detect outliers for cancer drugs and reported positive results. The application of the Grubbs’ test is used to detect outliers which exceed boundaries of normal distribution. The result is a probability that indicates the core data of actual sales. The application of the outliers’ test method helps to represent the difference of the mean of the sample and the most extreme data considering the standard deviation. The test detects one outlier at a time with different probabilities from a data set with an assumed normal distribution. Based on approximation data, the authors constructed a framework for scaling potential sales and estimating outliers with Grubbs’ test method. The suggested framework is applicable during the shortage event and recovery periods. The proposed framework has practical value and could be used for the minimization of the recovery period required after the shortage of event occurrence.

Keywords: drugs, Grubbs' test, outlier, shortage event

Procedia PDF Downloads 120