Search results for: person identification

Authors: Ahmed Abdrabou, Medhat Abdalla

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The studied stele dates back to Third Intermediate Period (1075-664) B.C in an ancient Egypt. It is made of wood and covered with painted gesso layers. This study aims to use a combination of multi spectral imaging {visible, infrared (IR), Visible-induced infrared luminescence (VIL), Visible-induced ultraviolet luminescence (UVL) and ultraviolet reflected (UVR)}, along with portable x-ray fluorescence in order to map and identify the pigments as well as to provide a deeper understanding of the painting techniques. Moreover; the authors were significantly interested in the identification of wood species. Multispectral imaging acquired in 3 spectral bands, ultraviolet (360-400 nm), visible (400-780 nm) and infrared (780-1100 nm) using (UV Ultraviolet-induced luminescence (UVL), UV Reflected (UVR), Visible (VIS), Visible-induced infrared luminescence (VIL) and Infrared photography. False color images are made by digitally editing the VIS with IR or UV images using Adobe Photoshop. Optical Microscopy (OM), potable X-ray fluorescence spectroscopy (p-XRF) and Fourier Transform Infrared Spectroscopy (FTIR) were used in this study. Mapping and imaging techniques provided useful information about the spatial distribution of pigments, in particular visible-induced luminescence (VIL) which allowed the spatial distribution of Egyptian blue pigment to be mapped and every region containing Egyptian blue, even down to single crystals in some instances, is clearly visible as a bright white area; however complete characterization of the pigments requires the use of p. XRF spectroscopy. Based on the elemental analysis found by P.XRF, we conclude that the artists used mixtures of the basic mineral pigments to achieve a wider palette of hues. Identification of wood species Microscopic identification indicated that the wood used was Sycamore Fig (Ficus sycomorus L.) which is recorded as being native to Egypt and was used to make wooden artifacts since at least the Fifth Dynasty.

Keywords: polychrome wooden stele, multispectral imaging, IR luminescence, Wood identification, Sycamore Fig, p-XRF

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Authors: Patthida Bunchavalit, Saharot Kittimahacharoen

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The objective of this article is to compare rice blessing ceremony between Thailand and Vietnam. Both countries are located in Southeast Asia where agriculture is the main occupation. As a result of the study, it is found that the rice blessing ceremony of Thai and Vietnamese societies have differences and similarities. A person leading the ceremony is a person who has the highest position in the country. For Thailand, it is the king or royal family member while for Vietnam, it is the president. In Thailand, the ceremony began in Ayutthaya period which derived from Buddhism and Brahmanism ideology. It is annually organized in the beginning of raining season. In Vietnam, it is annually organized in the beginning of spring. The first time it occurred was in Tien Le Monarchy period of Thien Phuc era deriving from Chinese ideology. The differences are ideas, believes, objectives and details of the ceremony. It is, in Thailand, to boost farmer’s morale and to predict the fertility of crops in each year. Additionally, there is a prediction using royal cows. Meanwhile, in Vietnam the purpose is to worship god of weather for seasonal rain and productive harvesting. Therefore, it is presumed that the rice blessing ceremony of Thailand and Vietnam somewhat have similarities in spite of having different origin but are on the same basis of belief.

Keywords: agriculture, ceremony, culture, Thailand, Vietnam

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Authors: Svetlana L. Mishlanova, Evgeniia V. Ermakova, Mariia E. Timirkina

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The paper is concerned with the study of metaphor production in essays written by Russian and English native speakers in the framework of cognitive metaphor theory. It considers metaphorical competence as individual’s ability to recognize, understand and use metaphors in speech. The work analyzes the influence of visual metaphor on production and density of conventional and novel verbal metaphors. The main methods of research include experiment connected with image interpretation, metaphor identification procedure (MIPVU) and visual conventional metaphors identification procedure proposed by VisMet group. The research findings will be used in the project aimed at comparing metaphorical competence of native and non-native English speakers.

Keywords: metaphor, metaphorical competence, conventional, novel

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Authors: Pathinathan Theresanathan, Ajay Minj

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Ignatian Discernment Process (IDP) is an intense decision-making tool to decide on life-issues. Decisions are influenced by various factors outside of the decision maker and inclination within. This paper develops IDP in the context of Fuzzy Multi-criteria Decision Making (FMCDM) process. Extended VIKOR method is a decision-making method which encompasses even conflict situations and accommodates weightage to various issues. Various aspects of IDP, namely three ways of decision making and tactics of inner desires, are observed, analyzed and articulated within the frame work of fuzzy rules. The decision-making situations are broadly categorized into two types. The issues outside of the decision maker influence the person. The inner feeling also plays vital role in coming to a conclusion. IDP integrates both the categories using Extended VIKOR method. Case studies are carried out and analyzed with FMCDM process. Finally, IDP is verified with an illustrative case study and results are interpreted. A confused person who could not come to a conclusion is able to take decision on a concrete way of life through IDP. The proposed IDP model recommends an integrated and committed approach to value-based decision making.

Keywords: AHP, FMCDM, IDP, ignatian discernment, MCDM, VIKOR

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Authors: Roihatul Mutiah, Sukardiman, Aty Widyawaruyanti

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Calotropis gigantiea (L.) R. Br (Apocynaceae) commonly called as “Biduri” or “giant milk weed” is a well-known weed to many cultures for treating various disorders. Several studies reported that C.gigantea roots has anticancer activity. The main aim of this research was to isolate and identify an active marker compound of C.gigantea roots for quality control purpose of its extract in the development as anticancer natural product. The isolation methods was bioactivity guided column chromatography, TLC, and HPLC. Evaluated anticancer activity of there substances using MTT assay methods. Identification structure active compound by UV, 1HNMR, 13CNMR, HMBC, HMQC spectral and other references. The result showed that the marker active compound was identical as Calotropin.

Keywords: calotropin, Calotropis gigantea, anticancer, marker active

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Authors: Luci V. Hyett

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The criminal law of England and Wales currently deems that a person cannot consent to the infliction of injury upon their own body, where the level of harm is considered to be Actual or Grevious. This renders the defence of consent of the victim as being unavailable to those persons carrying out an Alternative Body Modification procedure. However, the criminalization of consensual injury is more appropriately deemed as being categorized as an offense against public morality and not one against the person, which renders the State’s involvement in the autonomous choices of a consenting adult, when determining what can be done to one’s own body, an arbitrary one. Furthermore, to recognise in law that a person is capable of giving a valid consent to socially acceptable cosmetic interventions that largely consist of procedures designed to aesthetically please men and, not those of people who want to modify their bodies for other reasons means that patriarchal attitudes are continuing to underpin public repulsion and inhibit social acceptance of such practices. Theoretical analysis will begin with a juridical examination of R v M(B) [2019] QB 1 where the High Court determined that Alternative Body Modification was not a special category exempting a person so performing from liability for Grevious Bodily Harm using the defence of consent. It will draw from its reasoning which considered that ‘the removal of body parts were medical procedures being carried out for no medical reason by someone not qualified to carry them out’ which will form the basis of this enquiry. It will consider the philosophical work of Georgio Agamben when analysing whether the biopolitical climate in the UK, which places the optimization of the perfect, healthy body at the centre of political concern can explain why those persons who wish to engage in Alternative Body Modification are treated as the ‘Exception’ to that which is normal using the ‘no medical reason’ canon to justify criminalisation, rather than legitimising the industry through regulation. It will consider, through a feminist lens, the current conflict in law between traditional cosmetic interventions which alter one’s physical appearance for socially accepted aesthetic purposes such as those to the breast, lip and buttock and, modifications described as more outlandish such as earlobe stretching, tooth filing and transdermal implants to create horns and spikes under the skin. It will assert that ethical principles relating to the psychological impact of body modification described as ‘alternative’ is used as a means to exclude person’s seeking such a procedure from receiving safe and competent treatment via a registered cosmetic surgeon which leads to these increasingly popular surgery’s being performed in Tattoo parlours throughout the UK as an extension to other socially acceptable forms of self-modification such as piercings. It will contend that only by ‘inclusive exclusion’ will those ‘othered’ through ostracisation be welcomed into the fold of normality and this can only be achieved through recognition of alternative body modification as a legitimate cosmetic intervention, subject to the same regulatory framework as existing practice. This would assist in refocusing the political landscape by erring on the side of liberty rather than that of biology.

Keywords: biopolitics, body modification, consent, criminal law

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Authors: Khaled M. El Naggar

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This paper introduces a digital method for fault section identification in transmission lines. The method uses digital set of the measured short circuit current to locate faults in electrical power systems. The digitized current is used to construct a set of overdetermined system of equations. The problem is then constructed and solved using the proposed digital optimization technique to find the fault distance. The proposed optimization methodology is an application of simulated annealing optimization technique. The method is tested using practical case study to evaluate the proposed method. The accurate results obtained show that the algorithm can be used as a powerful tool in the area of power system protection.

Keywords: optimization, estimation, faults, measurement, high voltage, simulated annealing

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Authors: Nazih Ramadan, Ghada Hassabo

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Background and Aims: Domestic violence and other forms of violence against women and other family members are known to be substantial and widespread, with women more likely than men to be abused mostly by their partner, which is known as gender-based violence. Domestic violence is a major precipitating factor for suicide in many communities especially in our Middle East area. The aim of the study is to show the real relation between suicidal attempts and domestic violence especially in female victims. We tried also through this study to know the most common age at which the abused person attempt suicide, the perpetrator, the educational level of the abused person, and the social level of them. Materials and Methods: In this study, we collect data from 150 victims of suicidal attempts who came to seek medical help at National Poisoning Center. They were asked to answer a preformed questionnaire after giving consent. Results: The study shows that women are at higher risk for suicidal behavior and that suicidal attempt is directly proportionate to low level of education and low social class situation. Conclusion: the study shows the strong relation between attempting suicide and exposure to domestic violence. At the end of this work, we recommend understanding the broad scope and tragic impact of domestic violence; further research is needed concerning domestic violence-related suicide.

Keywords: Cairo, domestic violence, domestic violence-related suicide, violence against women

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Authors: Ankit Kamboj, Shikha Talwar, Nilesh Powar

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To successfully deliver our products in the market, the employees need to be in a safe environment, especially in an industrial and manufacturing environment. The consequences of delinquency in wearing safety glasses while working in industrial plants could be high risk to employees, hence the need to develop a real-time automatic detection system which detects the persons (violators) not wearing safety glasses. In this study a convolutional neural network (CNN) algorithm called faster region based CNN (Faster RCNN) with rotated bounding box has been used for detecting safety glasses on persons; the algorithm has an advantage of detecting safety glasses with different orientation angles on the persons. The proposed method of rotational bounding boxes with a convolutional neural network first detects a person from the images, and then the method detects whether the person is wearing safety glasses or not. The video data is captured at the entrance of restricted zones of the industrial environment (manufacturing plant), which is further converted into images at 2 frames per second. In the first step, the CNN with pre-trained weights on COCO dataset is used for person detection where the detections are cropped as images. Then the safety goggles are labelled on the cropped images using the image labelling tool called roLabelImg, which is used to annotate the ground truth values of rotated objects more accurately, and the annotations obtained are further modified to depict four coordinates of the rectangular bounding box. Next, the faster RCNN with rotated bounding box is used to detect safety goggles, which is then compared with traditional bounding box faster RCNN in terms of detection accuracy (average precision), which shows the effectiveness of the proposed method for detection of rotatory objects. The deep learning benchmarking is done on a Dell workstation with a 16GB Nvidia GPU.

Keywords: CNN, deep learning, faster RCNN, roLabelImg rotated bounding box, safety goggle detection

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Authors: Vikram Saini, Lillie Dewan

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This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

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Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

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One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

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Authors: Fatma Susilawati Mohamad, Azizah Abdul Manaf, Fadhillah Ahmad, Zarina Mohamad, Wan Suryani Wan Awang

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A simple and robust multi-class linear classifier is proposed and implemented. For a pair of classes of the linear boundary, a collection of segments of hyper planes created as perpendicular bisectors of line segments linking centroids of the classes or part of classes. Nearest Neighbor and Linear Discriminant Analysis are compared in the experiments to see the performances of each classifier in discriminating ripeness of oil palm. This paper proposes a multi-class linear classifier using Linear Discriminant Analysis (LDA) for image identification. Result proves that LDA is well capable in separating multi-class features for ripeness identification.

Keywords: multi-class, linear classifier, nearest neighbor, linear discriminant analysis

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Authors: Florian Pfeffel, Valentin Nickolai, Christian Louis Kühner

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Digitalization has disrupted the traditional workplace environment by allowing many employees to work from anywhere at any time. This trend of working from home was further accelerated due to the COVID-19 crisis, which forced companies to rethink their workplace models. While in many companies, this shift happened out of pure necessity; many employees were left more satisfied with their job due to the opportunity to work from home. This study focuses on employees’ job satisfaction in the service sector in dependence on the different work models, which are defined as a “work from home” model, the traditional “work in office” model, and a hybrid model. Using structural equation modeling (SEM), these three work models have been analyzed based on 13 influencing factors on job satisfaction that have been further summarized in the three groups “classic influencing factors”, “influencing factors changed by remote working”, and “new remote working influencing factors”. Based on the influencing factors on job satisfaction, a survey has been conducted with n = 684 employees in the service sector. Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. Additionally, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). The SEM-analysis has shown that the most significant influencing factor on job satisfaction is “identification with the work” with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis shows that the identification with the work is the most significant factor in all three work models and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that employees who work entirely remotely or have a hybrid work model are significantly more satisfied with their job, with a job satisfaction score of 5.0 respectively on a scale from 1 (very dissatisfied) to 7 (very satisfied), than employees do not have the option to work from home with a score of 4.6. This comes as a result of the lower identification with the work in the model without any remote working. Furthermore, the responses indicate that it is important to consider the individual preferences of each employee when it comes to the work model to achieve overall higher job satisfaction. Thus, it can be argued that companies can profit off of more motivation and higher productivity by considering the individual work model preferences, therefore, increasing the identification with the respective work.

Keywords: home-office, identification with work, job satisfaction, new work, remote work, structural equation modeling

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Authors: Slimane Ouhmad, Abdellah Halimi

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In this work, we have applied neural networks method MLP type to a database from an array of six sensors for the detection of three toxic gases. As the choice of the number of hidden layers and the weight values has a great influence on the convergence of the learning algorithm, we proposed, in this article, a mathematical formulation to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases on the one hand, and optimize the computation time on the other hand, the comparison to other results achieved in this case.

Keywords: MLP Neural Network, back-propagation, number of neurons in the hidden layer, identification, computing time

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Authors: Sung-Jun Yoo, Kazuhide Ito

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In this study, a comprehensive computer simulated person (CSP) that integrates computational human model (virtual manikin) and respiratory tract model (virtual airway), was applied for estimation of indoor environmental quality. Moreover, an inclusive prediction method was established by integrating computational fluid dynamics (CFD) analysis with advanced CSP which is combined with physiologically-based pharmacokinetic (PBPK) model, unsteady thermoregulation model for analysis targeting micro-climate around human body and respiratory area with high accuracy. This comprehensive method can estimate not only the contaminant inhalation but also constant interaction in the contaminant transfer between indoor spaces, i.e., a target area for indoor air quality (IAQ) assessment, and respiratory zone for health risk assessment. This study focused on the usage of the CSP as an air/thermal quality sensor in indoors, which means the application of comprehensive model for assessment of IAQ and thermal environmental quality. Demonstrative analysis was performed in order to examine the applicability of the comprehensive model to the heating, ventilation, air conditioning (HVAC) control scheme. CSP was located at the center of the simple model room which has dimension of 3m×3m×3m. Formaldehyde which is generated from floor material was assumed as a target contaminant, and flow field, sensible/latent heat and contaminant transfer analysis in indoor space were conducted by using CFD simulation coupled with CSP. In this analysis, thermal comfort was evaluated by thermoregulatory analysis, and respiratory exposure risks represented by adsorption flux/concentration at airway wall surface were estimated by PBPK-CFD hybrid analysis. These Analysis results concerning IAQ and thermal comfort will be fed back to the HVAC control and could be used to find a suitable ventilation rate and energy requirement for air conditioning system.

Keywords: CFD simulation, computer simulated person, HVAC control, indoor environmental quality

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Authors: Mawa Abdelbagi Mohamed Mohamed, Eslam Alaa Elbahlawan

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This study examines the complex social fabric woven within the Abu-Shouk internally displaced persons camp, shaped by the chaotic waves of armed conflict and displacement in the early 2000s. The impact of war, economic constraints, and altered living conditions have fundamentally reshaped families and traditions, presenting both challenges and opportunities. In this exploration, we navigate the resilience of a community thrust into adversity, spotlighting how it emerged as essential in rebuilding social bonds. Exchanges of culture, intertribal marriages, and communal gathering spots have become essential tools in fostering cohesion and understanding amidst diversity. However, this resilience has been tested by the intrusion of politics, leading to shifts in governance structures and community dynamics. As we conclude, it is evident that while the scars of displacement and political disruptions are present, the community's enduring spirit and adaptability shine through. Empowering the community to rebuild their social tapestry, bridging the gaps, and restoring unity amid evolving political realities remain the beacon guiding their journey toward a shared, purposeful future.

Keywords: darfur, internally displaced person, social fabric, conflict

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Authors: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

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This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

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Authors: Khaled Mohammed

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

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

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Authors: Adèle Hotte-Meunier, Lisa Sarraf, Alan Bougeard, Félicia Bernier, Chloé Voyer, Jiaxuan Deng, Stéphanie El Asmar, Alina Stamate, Marc Corbière, Patrizia Villotti, Geneviève Sauvé

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Background: Attention-Deficit/Hyperactivity Disorder (ADHD) is characterized by a persistent pattern of inattention and/or hyperactivity-impulsivity that interferes with psychosocial, educational and occupational functioning. Although often conceptualized as a developmental disorder of childhood, 65% of children with ADHD continue to meet full or partial diagnostic criteria for ADHD in adulthood and an estimated 4% of the workforce has a diagnosis of ADHD. Methods: A systematic review was conducted to understand the experiences of people living with ADHD in the workplace. Articles reporting employment outcomes for people living with were identified by a search in eight databases on four separate occasions from June 27, 2022, to June 21, 2023. A risk of bias assessment for each study was performed using the Mixed Methods Appraisal Tool (MMAT). Results: A total of 79 studies were included in this systematic review (nADHD: 68, 216). Results were synthesized into three broad overarching categories: challenges, strengths and adaptations at work. Further, nine themes were included: ADHD symptoms at work, workplace performance, job satisfaction, interpersonal relationships at work, maladaptive work thoughts and behaviors, personal strengths, embracing ADHD, person-environment fit and accommodations and support. Sex differences were highlighted as a tenth subtheme. ADHD confers both strengths and limitations related to employment. Discussion: Workers with ADHD can not only adapt but thrive in employment with the right person-environment fit, accommodations and support. Many challenges related to ADHD can be managed or remodeled as assets in a workplace environment that fosters acceptance, flexible working practices and openness to neurodiversity.

Keywords: neurodivergence, occupation, workplace, person-environment fit

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Authors: Thanh Nga Thai

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A major issue in air transportation is in flight safety. Recent developments in control engineering have an attractive potential for resolving new issues related to guidance, navigation, and control of flying vehicles. Many future atmospheric missions will require increased on board autonomy including fault diagnosis and the subsequent control and guidance recovery actions. To improve designing system diagnostic, an efficient FDI- fault detection and identification- methodology is necessary to achieve. Contribute to characteristic of different faults in sensor and actuator in the view of mathematics brings a lot of profit in some condition changes in the system. This research finds some profit to reduce a trade-off to achieve between fault detection and performance of the closed loop system and cost and calculated in simulation.

Keywords: fault detection and identification, sensor faults, actuator faults, flight control system

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Authors: Besma Khalfoun

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In many current Human Activity Recognition (HAR) applications, users' data is frequently shared and centrally stored by third parties, posing a significant privacy risk. This practice makes these entities attractive targets for extracting sensitive information about users, including their identity, health status, and location, thereby directly violating users' privacy. To tackle the issue of centralized data storage, a relatively recent paradigm known as federated learning has emerged. In this approach, users' raw data remains on their smartphones, where they train the HAR model locally. However, users still share updates of their local models originating from raw data. These updates are vulnerable to several attacks designed to extract sensitive information, such as determining whether a data sample is used in the training process, recovering the training data with inversion attacks, or inferring a specific attribute or property from the training data. In this paper, we first introduce PUR-Attack, a parameter-based user re-identification attack developed for HAR applications within a federated learning setting. It involves associating anonymous model updates (i.e., local models' weights or parameters) with the originating user's identity using background knowledge. PUR-Attack relies on a simple yet effective machine learning classifier and produces promising results. Specifically, we have found that by considering the weights of a given layer in a HAR model, we can uniquely re-identify users with an attack success rate of almost 100%. This result holds when considering a small attack training set and various data splitting strategies in the HAR model training. Thus, it is crucial to investigate protection methods to mitigate this privacy threat. Along this path, we propose SAFER, a privacy-preserving mechanism based on adaptive local differential privacy. Before sharing the model updates with the FL server, SAFER adds the optimal noise based on the re-identification risk assessment. Our approach can achieve a promising tradeoff between privacy, in terms of reducing re-identification risk, and utility, in terms of maintaining acceptable accuracy for the HAR model.

Keywords: federated learning, privacy risk assessment, re-identification risk, privacy preserving mechanisms, local differential privacy, human activity recognition

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Authors: H. Gholami, M. Jalali Azizpour

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Stress Corrosion Crack (SCC) in pipeline is a type of environmentally assisted cracking (EAC), since its discovery in 1965 as a possible cause of failure in pipeline, SCC has caused, on average, one of two failures per year in the U.S, According to the NACE SCC DA a pipe line segment is considered susceptible to SCC if all of the following factors are met: The operating stress exceeds 60% of specified minimum yield strength (SMYS), the operating temperature exceeds 38°C, the segment is less than 32 km downstream from a compressor station, the age of the pipeline is greater than 10 years and the coating type is other than Fusion Bonded Epoxy(FBE). In this paper as a practical experience in NISOC, Direct Assessment (DA) Method is used for identification SCC defect in unpiggable pipeline located downstream of compressor station.

Keywords: stress corrosion crack, direct assessment, disbondment, transgranular SCC, compressor station

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Authors: Miriam Colleran, Barbara Sheehy-Skeffington

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Background: To explore if there are unique features in the palliative care needs of patients with intellectual disability that may impact on planning for resource and service provision for them. Aim: The purpose of this practice review is to assess the indications for, numbers of and outcomes of care for adults with intellectual disabilities referred to a specialist palliative care service over a twoyear period. Service utilization aspects considered included the frequency of home visits by a specialist palliative care doctor or clinical nurse specialist and the number of hospice admissions that occurred for the patients. Method: A retrospective review was carried out of persons 18 years and older with intellectual disabilities referred to a specialist palliative care service over a 5-year period from 30.11.3018 to 29.11.2023. A manual review was carried out of the register using key terms, namely, known residential care and community dwelling places of service providers for persons with intellectual disabilities in the area and registered diagnoses in addition to the patients known to the clinicians who had intellectual disabilities. Results: 25 referrals were made to the specialist palliative care service of 23 persons with intellectual disabilities during that time. However, this may be an underestimate. 15 women and 8 men were referred with an age range of 19 to 86 years of age. The majority had a diagnosis of Down’s syndrome or Trisomy 21. 5 patients referred did not have home visits from the specialist palliative care team. A range of 2 to 48 phone calls per person occurred by the specialist palliative care team regarding this cohort of patients. The outcomes for the patients included discharge and death. The majority of patients that died, did so in the community. One person however died in hospital. Another person died in a hospice out of area. Conclusion: Providing specialist palliative care for adults with intellectual disabilities is an important element of palliative care. The dominance of the community as the place of death for these patients and the limited number of patients dying in either hospice or hospital are noteworthy. Further research is necessary and education to inform, support, and empower specialist palliative care professionals in optimizing palliative and end-of-life care for persons with intellectual disabilities and to inform service development and provision.

Keywords: about intellectual disability, palliative care

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Authors: Shanika Y. Koreshi

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Sri Lanka housed the lingerie product development and manufacturing subsidiary to renowned brands such as La Senza, Marks & Spencer, H&M, Etam, Lane Bryant, and George. Over the last few years, they have produced local brands such as Amante to cater to the local and regional customers. Past research has identified factors such as quality, price, and design to be vital when marketing lingerie to consumers. However, there has been minimum research that looks into the ethnically targeted market and skin colour within the Asian population. Therefore, the main aim of the research was to identify whether consumer preference for lingerie is influenced by the skin tone of the model wearing it. Moreover, the secondary aim was to investigate if the consumer preference for lingerie is influenced by the consumer’s ethnic identification with the skin tone of the model. An experimental design was used to explore the above aims. The participants constituted of 66 females residing in the western province of Sri Lanka and were gathered via convenience sampling. Six computerized images of a real model were used in the study, and her skin tone was digitally manipulated to express three different skin tones (light, tan and dark). Consumer preferences were measured through a ranking order scale that was constructed via a focus group discussion and ethnic identity was measured by the Multigroup Ethnic Identity Measure-Revised. Wilcoxon signed-rank test, Friedman test, and chi square test of independence were carried out using SPSS version 20. The results indicated that majority of the consumers ethnically identified and preferred the tan skin over the light and dark skin tones. The findings support the existing literature that states there is a preference among consumers when models have a medium skin tone over a lighter skin tone. The preference for a tan skin tone in a model is consistent with the ethnic identification of the Sri Lankan sample. The study implies that lingerie brands should consider the model's skin tones when marketing the brand to different ethnic backgrounds.

Keywords: consumer preference, ethnic identification, lingerie, skin tone

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Authors: A. Medjnoun, R. Bahar

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The disorders caused by the shrinking-swelling phenomenon are prevalent in arid and semi-arid in the presence of swelling clay. This soil has the characteristic of changing state under the effect of water solicitation (wetting and drying). A set of geotechnical parameters is necessary for the characterization of this soil type, such as state parameters, physical and chemical parameters and mechanical parameters. Some of these tests are very long and some are very expensive, hence the use or methods of predictions. The complexity of this phenomenon and the difficulty of its characterization have prompted researchers to use several identification parameters in the prediction of swelling potential. This document is an analytical and statistical study of geotechnical parameters affecting the potential of swelling clays. This work is performing on a database obtained from investigations swelling Algerian soil. The obtained observations have helped us to understand the soil swelling structure and its behavior.

Keywords: analysis, estimated model, parameter identification, swelling of clay

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Authors: Y. Galerkin, K. Soldatova, A. Drozdov

Abstract:

The 6th version of Universal modeling method for centrifugal compressor stage calculation is described. Identification of the new mathematical model was made. As a result of identification the uniform set of empirical coefficients is received. The efficiency definition error is 0,86 % at a design point. The efficiency definition error at five flow rate points (except a point of the maximum flow rate) is 1,22 %. Several variants of the stage with 3D impellers designed by 6th version program and quasi three-dimensional calculation programs were compared by their gas dynamic performances CFD (NUMECA FINE TURBO). Performance comparison demonstrated general principles of design validity and leads to some design recommendations.

Keywords: compressor design, loss model, performance prediction, test data, model stages, flow rate coefficient, work coefficient

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Authors: Heiko Weiß, Andreas Meister, Christoph Ament, Nils Dreifke

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Linear actuators are deployed in a wide range of applications. This paper presents the modeling and system identification of a variable excited linear direct drive (LDD). The LDD is designed based on linear hybrid stepper technology exhibiting the characteristic tooth structure of mover and stator. A three-phase topology provides the thrust force caused by alternating strengthening and weakening of the flux of the legs. To achieve best possible synchronous operation, the phases are commutated sinusoidal. Despite the fact that these LDDs provide high dynamics and drive forces, noise emission limits their operation in calm workspaces. To overcome this drawback an additional excitation of the magnetic circuit is introduced to LDD using additional enabling coils instead of permanent magnets. The new degree of freedom can be used to reduce force variations and related noise by varying the excitation flux that is usually generated by permanent magnets. Hence, an identified simulation model is necessary to analyze the effects of this modification. Especially the force variations must be modeled well in order to reduce them sufficiently. The model can be divided into three parts: the current dynamics, the mechanics and the force functions. These subsystems are described with differential equations or nonlinear analytic functions, respectively. Ordinary nonlinear differential equations are derived and transformed into state space representation. Experiments have been carried out on a test rig to identify the system parameters of the complete model. Static and dynamic simulation based optimizations are utilized for identification. The results are verified in time and frequency domain. Finally, the identified model provides a basis for later design of control strategies to reduce existing force variations.

Keywords: force variations, linear direct drive, modeling and system identification, variable excitation flux

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Authors: Victor Toom

Abstract:

Albeit it is never possible to anticipate the full range of difficulties after a catastrophe, efforts to identify victims of mass casualty events have become institutionalized and standardized with the aim of effectively and efficiently addressing the many challenges and contingencies. Such ‘disaster victim identification’ (DVI) practices are dependent on the forensic sciences, are subject of national legislation, and are reliant on technical and organizational protocols to mitigate the many complexities in the wake of catastrophe. Apart from such technological, legal and bureaucratic elements constituting a DVI operation, victims’ families and their emotions are also part and parcel of any effort to identify casualties of mass human fatality incidents. Take for example the fact that forensic experts require (antemortem) information from the group of relatives to make identification possible. An identified body or body part is also repatriated to kin. Relatives are thus main stakeholders in DVI operations. Much has been achieved in years past regarding facilitating victims’ families’ issues and their emotions. Yet, how families are dealt with by experts and authorities is still considered a difficult topic. Due to sensitivities and required emphatic interaction with families on the one hand, and the rationalized DVI efforts, on the other hand, there is still scope for improving communication, providing information and meaningful inclusion of relatives in the DVI effort. This paper aims to bridge the standardized world of DVI efforts and families’ experienced realities and makes suggestions to further improve DVI efforts through inclusion of victims’ families. Based on qualitative interviews, the paper narrates involvement and experiences of inter alia DVI practitioners, victims’ families, advocates and clergy in the wake of the 1995 Srebrenica genocide which killed approximately 8,000 men, and the 9/11 in New York City with 2,750 victims. The paper shows that there are several models of including victims’ families into a DVI operation, and it argues for a model of where victims’ families become a partner in DVI operations.

Keywords: disaster victim identification (DVI), victims’ families, social science (qualitative), 9/11 attacks, Srebrenica genocide

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Authors: Nestor A. Garcia Fragoso, Tetyana Baydyk, Ernst Kussul

Abstract:

This article contains information from our investigation in the field of voice recognition. For this purpose, we created a voice database that contains different phrases in two languages, English and Spanish, for men and women. As a classifier, the LIRA (Limited Receptive Area) grayscale neural classifier was selected. The LIRA grayscale neural classifier was developed for image recognition tasks and demonstrated good results. Therefore, we decided to develop a recognition system using this classifier for voice recognition. From a specific set of speakers, we can recognize the speaker’s voice. For this purpose, the system uses spectrograms of the voice signals as input to the system, extracts the characteristics and identifies the speaker. The results are described and analyzed in this article. The classifier can be used for speaker identification in security system or smart buildings for different types of intelligent devices.

Keywords: extreme learning, LIRA neural classifier, speaker identification, voice recognition

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Authors: Marjan Heidarzadeh

Abstract:

High quality and purity of DNA isolated from canned tuna is essential for species identification. In this study, the efficiency of five different methods for DNA extraction was compared. Method of national standard in Iran, the CTAB precipitation method, Wizard DNA Clean Up system, Nucleospin and GenomicPrep were employed. DNA was extracted from two different canned tuna in brine and oil of the same tuna species. Three samples of each type of product were analyzed with the different methods. The quantity and quality of DNA extracted was evaluated using the 260 nm absorbance and ratio A260/A280 by spectrophotometer picodrop. Results showed that the DNA extraction from canned tuna preserved in different liquid media could be optimized by employing a specific DNA extraction method in each case. Best results were obtained with CTAB method for canned tuna in oil and with Wizard method for canned tuna in brine.

Keywords: canned tuna PCR, DNA, DNA extraction methods, species identification

Procedia PDF Downloads 657