Search results for: detecting face

Authors: Priyadharshini Ahrumugam

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Cooperative groups through much research have been recognized to churn remarkable achievements instead of solitary or individualistic efforts. Based on Johnson and Johnson’s model of cooperative learning, the five key components of cooperation are positive interdependence, face-to-face promotive interaction, individual accountability, social skills and group processing. In 2011, the Malaysian Ministry of Higher Education (MOHE) introduced the Holistic Student Development policy with the aim to develop morally sound individuals equipped with lifelong learning skills. The Community Service project was included in the improvement initiative. The purpose of this study is to assess the relationship of team-based learning in facilitating particularly students’ positive interdependence and face-to-face promotive interaction. The research methods involve in-depth interviews with the team leaders and selected team members, and a content analysis of the undergraduate students’ reflective journals. A significant positive relationship was found between students’ progressive outlook towards teamwork and the highlighted two components. The key findings show that students have gained in their individual learning and work results through teamwork and interaction with other students. The inclusion of Community Service as a MOHE subject resonates with cooperative learning methods that enhances supportive relationships and develops students’ social skills together with their professional skills.

Keywords: community service, cooperative learning, positive interdependence, teamwork

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Authors: Mei-Hui Liu

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This study examines the effectiveness of a blended professional development program on preservice EFL (English as a foreign language) teachers’ learning to teach speech acts with the advent of Information and Communication Technology, researchers and scholars underscore the significance of integrating online and face-to-face learning opportunities in the teacher education field. Yet, a paucity of evidence has been documented to investigate the extent to which such a blended professional learning model may impact real classroom practice and student learning outcome. This yearlong project involves various stakeholders, including 25 preservice teachers, 5 English professionals, and 45 secondary school students. Multiple data sources collected are surveys, interviews, reflection journals, online discussion messages, artifacts, and discourse completion tests. Relying on the theoretical lenses of Community of Inquiry, data analysis depicts the nature and process of preservice teachers’ professional development in this blended learning community, which triggers and fosters both face-to-face and synchronous/asynchronous online interactions among preservice teachers and English professionals (i.e., university faculty and in-service teachers). Also included is the student learning outcome after preservice teachers put what they learn from the support community into instructional practice. Pedagogical implications and research suggestions are further provided based on the research findings and limitations.

Keywords: blended professional development, preservice EFL teachers, speech act instruction, student learning outcome

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Authors: Niddal Imam, Vassilios G. Vassilakis

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After analysing messages posted by health-related spam campaigns in Twitter Arabic hashtags, we found that these campaigns use unique hijacked accounts (we call them adversarial hijacked accounts) as adversarial examples to fool deployed ML-based spam detectors. Existing ML-based models build a behaviour profile for each user to detect hijacked accounts. This approach is not applicable for detecting spam in Twitter hashtags since they are computationally expensive. Hence, we propose an adversary-aware ML-based detector, which includes a newly designed feature (avg posts) to improve the detection of spam tweets posted by the adversarial hijacked accounts at a tweet-level in trending hashtags. The proposed detector was designed considering three key points: robustness, adaptability, and interpretability. The new feature leverages the account’s temporal patterns (i.e., account age and number of posts). It is faster to compute compared to features discussed in the literature and improves the accuracy of detecting the identified hijacked accounts by 73%.

Keywords: Twitter spam detection, adversarial examples, evasion attack, adversarial concept drift, account hijacking, trending hashtag

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Authors: Yi-Ju Lee

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This study identified the hypothesized relationships among tourist emotion, creative experience, and behavioral intention of handmade ancient candy in Tainan, Taiwan. A face-to-face questionnaire survey was administered in Anping, Tainan. The result also revealed significant positive relationships between emotion, creative experience and behavioral intention in handmade activities. This paper provides additional suggestions for enhancing behavioral intention and guidance regarding creative tourism.

Keywords: creative tourism, sense of achievement, unique learning, interaction with instructors

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Authors: Mohieddine Benghersallah, Mohamed Zakaria Zahaf, Ali Medjber, Idriss Tibakh

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The objective of this study is to analyse the effects of cutting parameters on surface roughness in dry face milling using statistical techniques. We studied the effect of the microstructure of AISI 52100 steel on machinability before and after hardening. The machining tests were carried out on a high rigidity vertical milling machine with a 25 mm diameter face milling cutter equipped with micro-grain bicarbide inserts with PVD (Ti, AlN) coating in GC1030 grade. A Taguchi L9 experiment plan is adopted. Analysis of variance (ANOVA) was used to determine the effects of cutting parameters (Vc, fz, ap) on the roughness (Ra) of the machined surface. Regression analysis to assess the machinability of steel presented mathematical models of roughness and the combination of parameters to minimize it. The recorded results show that feed per tooth has the most significant effect on the surface condition for both steel treatment conditions. The best roughnesses were obtained for the hardened AISI 52100 steel.

Keywords: machinability, heat treatment, microstructure, surface roughness, Taguchi method

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Authors: Jaqueline Maria Ribeiro Vieira

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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). Previously we developed and proposed a novel strategy capable of detecting patterns at borehole images that may point to regions that have tension and breakout characteristics, based on segmented images. In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge data set configurations.

Keywords: image segmentation, oil well visualization, classifiers, data-mining, visual computer

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Authors: Farshid Hajati, Soheila Gheisari, Ali Cheraghian, Yongsheng Gao

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This paper presents a new Surface Geodesic Derivative Pattern (SGDP) for matching textured deformable 3D surfaces. SGDP encodes micro-pattern features based on local surface higher-order derivative variation. It extracts local information by encoding various distinctive textural relationships contained in a geodesic neighborhood, hence fusing texture and range information of a surface at the data level. Geodesic texture rings are encoded into local patterns for similarity measurement between non-rigid 3D surfaces. The performance of the proposed method is evaluated extensively on the Bosphorus and FRGC v2 face databases. Compared to existing benchmarks, experimental results show the effectiveness and superiority of combining the texture and 3D shape data at the earliest level in recognizing typical deformable faces under expression, illumination, and pose variations.

Keywords: 3D face recognition, pose, expression, surface matching, texture

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Authors: Kriddikorn Kaewwongsri, Nikom Suvonvorn

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In the deep south of Thailand, checkpoints for people verification are necessary for the security management of risk zones, such as official buildings in the conflict area. In this paper, we propose an automatic checkpoint system that verifies persons using information from ID cards and facial features. The methods for a person’s information abstraction and verification are introduced based on useful information such as ID number and name, extracted from official cards, and facial images from videos. The proposed system shows promising results and has a real impact on the local society.

Keywords: face comparison, card recognition, OCR, checkpoint system, authentication

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Authors: M. Moslehpour, S. Khorsandi

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As transition to widespread use of IPv6 addresses has gained momentum, it has been shown to be vulnerable to certain security attacks such as those targeting Neighbor Discovery Protocol (NDP) which provides the address resolution functionality in IPv6. To protect this protocol, Secure Neighbor Discovery (SEND) is introduced. This protocol uses Cryptographically Generated Address (CGA) and asymmetric cryptography as a defense against threats on integrity and identity of NDP. Although SEND protects NDP against attacks, it is computationally intensive due to Hash2 condition in CGA. To improve the CGA computation speed, we parallelized CGA generation process and used the available resources in a trusted network. Furthermore, we focused on the influence of the existence of malicious nodes on the overall load of un-malicious ones in the network. According to the evaluation results, malicious nodes have adverse impacts on the average CGA generation time and on the average number of tries. We utilized a Trust Management that is capable of detecting and isolating the malicious node to remove possible incentives for malicious behavior. We have demonstrated the effectiveness of the Trust Management System in detecting the malicious nodes and hence improving the overall system performance.

Keywords: CGA, ICMPv6, IPv6, malicious node, modifier, NDP, overall load, SEND, trust management

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Authors: Aysun Sezer

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Magnetic Resonance Imaging (MRI) is one of the advanced diagnostic tools for evaluating shoulder pathologies. Proton Density (PD)-weighted MRI sequences prove highly effective in detecting edema. However, they are deficient in the anatomical identification of bones due to a trauma-induced decrease in signal-to-noise ratio and blur in the traumatized cortices. Computer-based diagnostic systems require precise segmentation, identification, and localization of anatomical regions in medical imagery. Deep learning-based object detection algorithms exhibit remarkable proficiency in real-time object identification and localization. In this study, the YOLOv8 model was employed to detect humeral head and scapular regions in 665 axial PD-weighted MR images. The YOLOv8 configuration achieved an overall success rate of 99.60% and 89.90% for detecting the humeral head and scapula, respectively, with an intersection over union (IoU) of 0.5. Our findings indicate a significant promise of employing YOLOv8-based detection for the humerus and scapula regions, particularly in the context of PD-weighted images affected by both noise and intensity inhomogeneity.

Keywords: YOLOv8, object detection, humerus, scapula, IRM

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Authors: Abdullah Karaman, Kursad Sayin

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In this research, which information technologies are used in small hotel businesses, and the information technologies-performance perception of the managers are pointed out. During the research, the questionnaire was prepared and the small scale hotel managers were interviewed face to face and they filled out the questionnaire and the answers acquired were evaluated. As the result of the research, it was obtained that the managers do not care much about the information technologies usage in practice even though they accepted that the information technologies are important in terms of performance.

Keywords: information technologies, managers, performance, small hotels

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Authors: R. L. Ujjwal, Abhishek Jain

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In the field of computer vision, most facial variations such as identity, expression, emotions and gender have been extensively studied. Automatic age estimation has been rarely explored. With age progression of a human, the features of the face changes. This paper is providing a new comparable study of different type of algorithm to feature extraction [Hybrid features using HAAR cascade & HOG features] & classification [KNN & SVM] training dataset. By using these algorithms we are trying to find out one of the best classification algorithms. Same thing we have done on the feature selection part, we extract the feature by using HAAR cascade and HOG. This work will be done in context of age group classification model.

Keywords: computer vision, age group, face detection

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Authors: Amjed Sid Ahmed, Rosilah Hassan, Nor Effendy Othman

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Limited functioning of the Internet Protocol version 4 (IPv4) has necessitated the development of the Internetworking Protocol next generation (IPng) to curb the challenges. Indeed, the IPng is also referred to as the Internet Protocol version 6 (IPv6) and includes the Neighbor Discovery Protocol (NDP). The latter performs the role of Address Auto-configuration, Router Discovery (RD), and Neighbor Discovery (ND). Furthermore, the role of the NDP entails redirecting the service, detecting the duplicate address, and detecting the unreachable services. Despite the fact that there is an NDP’s assumption regarding the existence of trust the links’ nodes, several crucial attacks may affect the Protocol. Internet Engineering Task Force (IETF) therefore has recommended implementation of Secure Neighbor Discovery Protocol (SEND) to tackle safety issues in NDP. The SEND protocol is mainly used for validation of address rights, malicious response inhibiting techniques and finally router certification procedures. For routine running of these tasks, SEND utilizes on the following options, Cryptographically Generated Address (CGA), RSA Signature, Nonce and Timestamp option. CGA is produced at extra high costs making it the most notable disadvantage of SEND. In this paper a clear description of the constituents of CGA, its operation and also recommendations for improvements in its generation are given.

Keywords: CGA, IPv6, NDP, SEND

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Authors: Anne Mastamet-Mason, Oluwatosin Onakoya, Karla Tissiman

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The COVID-19 pandemic that ravaged the world in 2020 brought about the need for handmade fabric face masks in South Africa and beyond. These masks showcased individuality and environmental responsibility and effectively aided our battle against the virus. These practical masks held significant meaning, representing human creativity, resilience, and commitment to sustainability in adversity. This paper examines how aesthetics, sustainability, and safety were achieved in the Handmade Fabric Face Masks. It analyses how their integration signified human agility and resilience to the pandemic while promoting dignity and environmental welfare. The research conducted a qualitative analysis to choose handmade fabric face masks and assess their aesthetic, sustainable, and safety features. The study involved interviewing a group of mask designers and users who evaluated the masks' efficacy in providing protection, aesthetics, and environmental sustainability. Although the designers demonstrated a high level of knowledge in the design aspects, the results indicated a need for more information regarding the functional safety measures and some environmental factors in mask selection and production. The mask analysis also revealed that the masks available in the market combined aesthetics and environmental protection but had limited safety measures. Despite the lack of balance of aesthetics, sustainability, and safety among the designers and the users of hand-fabric masks, functional aspects of fabrics and sustainability literacy are essential

Keywords: sustainable fashion, fabric mask, aesthetics, safety measures

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Authors: Lilis Kistriyani, Dine Olisvia, Lutfa Rahmawati

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Facial mask is an important part of every beauty treatment because it will give a smooth and gentle effect on the face. This research is done to make edible film that will be applied for face mask. The main ingredient in making this edible film is purple sweet potato powder with the addition of glycerol as plasticizer. One of the ingredients in purple sweet potato is a flavonoid compound. The purpose of this study was to determine the effect of increasing the amount of glycerol to flavonoids release and the effect on the physical properties and biological properties of edible film produced. The stages of this research are the making of edible film, then perform some analysis, among others, spectrophotometer UV-vis analysis to find out how many flavonoids can be released into facial skin, tensile strength and elongation of break analysis, biodegradability analysis, and microbiological analysis. The variation of edible film is the volume of glycerol that is 1 ml, 2 ml, 3 ml. The results of spectrophotometer UV-vis analysis showed that the most flavonoid release concentration is 20.33 ppm in the 2 ml glycerol variation. The best tensile strength value is 8,502 N, and the greatest elongation of break value is 14% in 1 ml glycerol variation. In the biodegradability test, the more volume of glycerol added the faster the edible film is degraded. The results of microbiological analysis showed that purple sweet potato extract has the ability to inhibit the growth of Propionibacterium acnes seen in the presence of inhibiting zone which is 18.9 mm.

Keywords: face mask, edible film, plasticizer, flavonoid

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Authors: Bernadette F. De La Cruz, Susan Marie R. Dela Cruz, Georgia D. Demavibas

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The Expanded Student Grant-in-Aid Program for Poverty Alleviation (ESGP-PA) is a government program that aims to contribute to the National Government’s thrusts in effectively addressing poverty alleviation by increasing the number of graduates in higher education among indigent households and to get these graduates employed in in-demand occupations in order to lift their families out of poverty. Higher education continues to see an influx of these students from poor families that have never previously sent anyone to college. There are many challenges that face college students at all levels, but these are special challenges for first-generation students. Challenges that face these students can include lack of interest in attending school, low aptitude, being not single anymore, factors such as unfamiliarity with college expectations, lack of preparations while in secondary school, and limited support from family members. This research looks at some of the challenges first-generation college students face and examines the impact of these challenges on student’s aspirations for the attainment of a college degree and ultimately a high-paying career.

Keywords: ESGP-PA, first-generation college students, low aptitude, poverty alleviation

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Authors: Omar Dib, Rita Yaacoub, Luc Eveleigh, Nathalie Locquet, Hussein Dib, Ali Bassal, Christophe B. Y. Cordella

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The potential of front-face fluorescence coupled with chemometric techniques, namely parallel factor analysis (PARAFAC) and multiple linear regression (MLR) as a rapid analysis tool to characterize Lebanese virgin olive oils was investigated. Fluorescence fingerprints were acquired directly on 102 Lebanese virgin olive oil samples in the range of 280-540 nm in excitation and 280-700 nm in emission. A PARAFAC model with seven components was considered optimal with a residual of 99.64% and core consistency value of 78.65. The model revealed seven main fluorescence profiles in olive oil and was mainly associated with tocopherols, polyphenols, chlorophyllic compounds and oxidation/hydrolysis products. 23 MLR regression models based on PARAFAC scores were generated, the majority of which showed a good correlation coefficient (R > 0.7 for 12 predicted variables), thus satisfactory prediction performances. Acid values, peroxide values, and Delta K had the models with the highest predictions, with R values of 0.89, 0.84 and 0.81 respectively. Among fatty acids, linoleic and oleic acids were also highly predicted with R values of 0.8 and 0.76, respectively. Factors contributing to the model's construction were related to common fluorophores found in olive oil, mainly chlorophyll, polyphenols, and oxidation products. This study demonstrates the interest of front-face fluorescence as a promising tool for quality control of Lebanese virgin olive oils.

Keywords: front-face fluorescence, Lebanese virgin olive oils, multiple Linear regressions, PARAFAC analysis

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Authors: Ambuj Kumar Gautam, V. Vasu

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This paper introduces a head movement based Human Machine Interface (HMI) that uses the right and left movements of head to control a robot motion. Here we present an approach for making an effective technique for real-time face orientation information system, to control a robot which can be efficiently used for Electrical Powered Wheelchair (EPW). Basically this project aims at application related to HMI. The system (machine) identifies the orientation of the face movement with respect to the pixel values of image in a certain areas. Initially we take an image and divide that whole image into three parts on the basis of its number of columns. On the basis of orientation of face, maximum pixel value of approximate same range of (R, G, and B value of a pixel) lie in one of divided parts of image. This information we transfer to the microcontroller through serial communication port and control the motion of robot like forward motion, left and right turn and stop in real time by using head movements.

Keywords: electrical powered wheelchair (EPW), human machine interface (HMI), robotics, microcontroller

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Authors: Ashwag O. Maghraby, Nida N. Khan, Hosnia A. Ahmed, Ghufran N. Brohi, Hind F. Assouli, Jawaher S. Melibari

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The Arabic language is one of the most important languages. Learning it is so important for many people around the world because of its religious and economic importance and the real challenge lies in practicing it without grammatical or syntactical mistakes. This research focused on detecting and correcting the syntactic mistakes of Arabic syntax according to their position in the sentence and focused on two of the main syntactical rules in Arabic: Dual and Plural. It analyzes each sentence in the text, using Stanford CoreNLP morphological analyzer and machine-learning approach in order to detect the syntactical mistakes and then correct it. A prototype of the proposed system was implemented and evaluated. It uses support vector machine (SVM) algorithm to detect Arabic grammatical errors and correct them using the rule-based approach. The prototype system has a far accuracy 81%. In general, it shows a set of useful grammatical suggestions that the user may forget about while writing due to lack of familiarity with grammar or as a result of the speed of writing such as alerting the user when using a plural term to indicate one person.

Keywords: Arabic language acquisition and learning, natural language processing, morphological analyzer, part-of-speech

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Authors: Ahmed Ashit

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Image fusion is a significant and efficient image processing method used for detecting different types of tumors. This method has been used as an effective combination technique for obtaining high quality images that combine anatomy and physiology of an organ. It is the main key in the huge biomedical machines for diagnosing cancer such as PET-CT machine. This thesis aims to develop an image analysis system for the detection of the eye tumor. Different image processing methods are used to extract the tumor and then mark it on the original image. The images are first smoothed using median filtering. The background of the image is subtracted, to be then added to the original, results in a brighter area of interest or tumor area. The images are adjusted in order to increase the intensity of their pixels which lead to clearer and brighter images. once the images are enhanced, the edges of the images are detected using canny operators results in a segmented image comprises only of the pupil and the tumor for the abnormal images, and the pupil only for the normal images that have no tumor. The images of normal and abnormal images are collected from two sources: “Miles Research” and “Eye Cancer”. The computerized experimental results show that the developed image fusion based eye tumor detection system is capable of detecting the eye tumor and segment it to be superimposed on the original image.

Keywords: image fusion, eye tumor, canny operators, superimposed

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Authors: Andreas Livera, Spyros Theocharides, Michalis Florides, Charalambos Anastassiou

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A main challenge in the quest for ensuring quality of operation, especially for photovoltaic (PV) systems, is to safeguard the reliability and optimal performance by detecting and diagnosing potential failures and performance losses at early stages or before the occurrence through real-time monitoring, supervision, fault detection, and predictive maintenance. The purpose of this work is to present the functionalities and results related to the development and validation of a software platform for PV assets diagnosis and maintenance. The platform brings together proprietary hardware sensors and software algorithms to enable the early detection and prediction of the most common and critical faults in PV systems. It was validated using field measurements from operating PV systems. The results showed the effectiveness of the platform for detecting faults and losses (e.g., inverter failures, string disconnections, and potential induced degradation) at early stages, forecasting PV power production while also providing recommendations for maintenance actions. Increased PV energy yield production and revenue can be thus achieved while also minimizing operation and maintenance (O&M) costs.

Keywords: failure detection and prediction, operation and maintenance, performance monitoring, photovoltaic, platform, recommendations, predictive maintenance

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Authors: Ayşen Melda Çolak, Volkan Okatan, Ercan Yıldız

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In our country, fruit production was determined as 17.2 million tons in 2011 according to official data. Turkey fig, apricot, cherry and quince production ranks first in the world. Almost all the regions of our country, despite the growing of fruit 54% of the total fruit production occur in the Mediterranean and the Aegean Region. However, fruit production in the country is consumed in the domestic market and export rates are often very low. In this study, a questionnaire to 100 farmers face-to-face interview. According to the survey, 40% of those in fruit and 7 da of 7 hectares land are small. 30% of soil testing for manufacturers, testing for 20% of the water. Manufacturers who deliberately fertilization rate of only 10%.

Keywords: fruit, generation, potential, Sivasli survey

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Authors: M. Okeke, A. Blyth

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Industrial Control Systems (ICS) such as Supervisory Control And Data Acquisition (SCADA) can be seen in many different critical infrastructures, from nuclear management to utility, medical equipment, power, waste and engine management on ships and planes. The role SCADA plays in critical infrastructure has resulted in a call to secure them. Many lives depend on it for daily activities and the attack vectors are becoming more sophisticated. Hence, the security of ICS is vital as malfunction of it might result in huge risk. This paper describes how the application of Prey Predator (PP) approach in flocks of birds could enhance the detection of malicious activities on ICS. The PP approach explains how these animals in groups or flocks detect predators by following some simple rules. They are not necessarily very intelligent animals but their approach in solving complex issues such as detection through corporation, coordination and communication worth emulating. This paper will emulate flocking behavior seen in birds in detecting predators. The PP approach will adopt six nearest bird approach in detecting any predator. Their local and global bests are based on the individual detection as well as group detection. The PP algorithm was designed following MapReduce methodology that follows a Split Detection Convergence (SDC) approach.

Keywords: artificial life, industrial control system (ICS), IDS, prey predator (PP), SCADA, SDC

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Authors: Opeyemi Fadipe, Masud Salimian

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The COVID-19 pandemic has introduced a new normal into the world; online teaching is now the most used method of teaching over the face to face meeting. With the emergency of these teaching, online-teaching has been improved over time and with more technological advancement tools introduced. Practical courses are more demanding to teach because it requires the physical presence of the student as well as a demonstration of the equipment. In this study, a case of Lagos State University thermofluid practical was the understudy. A survey was done and give to a sample of students to fill. The result showed that the blend-approach is better for practical course teaching. Software simulation of the equipment used to conduct practical should be encouraged in the future.

Keywords: COVID-19, online teaching, t-distribution, thermofluid

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Authors: Mohammad Alhajeri

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This paper reports a computational fluid dynamics (CFD) investigation of cylindrical filter. Silicon carbide cylindrical filter elements have proven to be an effective mean of removing particulates to levels exceeding the new source performance standard. The CFD code is used here to understand the deposition process and the factors that affect the particles distribution over the filter element surface. Different approach cross flow velocity to filter face velocity ratios and different face velocities (ranging from 2 to 5 cm/s) are used in this study. Particles in the diameter range 1 to 100 microns are tracked through the domain. The radius of convergence (or the critical trajectory) is compared and plotted as a function of many parameters.

Keywords: filtration, CFD, CCF, hot gas filtration

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Authors: Priya Saha, Sourav Dey Roy Jr., Debotosh Bhattacharjee, Mita Nasipuri, Barin Kumar De, Mrinal Kanti Bhowmik

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Biometric face recognition technology (FRT) has gained a lot of attention due to its extensive variety of applications in both security and non-security perspectives. It has come into view to provide a secure solution in identification and verification of person identity. Although other biometric based methods like fingerprint scans, iris scans are available, FRT is verified as an efficient technology for its user-friendliness and contact freeness. Accurate facial feature localization plays an important role for many facial analysis applications including biometrics and emotion recognition. But, there are certain factors, which make facial feature localization a challenging task. On human face, expressions can be seen from the subtle movements of facial muscles and influenced by internal emotional states. These non-rigid facial movements cause noticeable alterations in locations of facial landmarks, their usual shapes, which sometimes create occlusions in facial feature areas making face recognition as a difficult problem. The paper proposes a new hybrid based technique for automatic landmark detection in both neutral and expressive frontal and near frontal face images. The method uses the concept of thresholding, sequential searching and other image processing techniques for locating the landmark points on the face. Also, a Graphical User Interface (GUI) based software is designed that could automatically detect 16 landmark points around eyes, nose and mouth that are mostly affected by the changes in facial muscles. The proposed system has been tested on widely used JAFFE and Cohn Kanade database. Also, the system is tested on DeitY-TU face database which is created in the Biometrics Laboratory of Tripura University under the research project funded by Department of Electronics & Information Technology, Govt. of India. The performance of the proposed method has been done in terms of error measure and accuracy. The method has detection rate of 98.82% on JAFFE database, 91.27% on Cohn Kanade database and 93.05% on DeitY-TU database. Also, we have done comparative study of our proposed method with other techniques developed by other researchers. This paper will put into focus emotion-oriented systems through AU detection in future based on the located features.

Keywords: biometrics, face recognition, facial landmarks, image processing

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Authors: Victor Milanes, Martha Hubertz

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In the wake of COVID-19, all aspects of life have been estranged, and humanity has been forced to shift toward a more technologically integrated mode of operation. Essential work such as Healthcare, business, and public policy are a few notable industries that were initially dependent upon face-to-face modality but have completely reimagined their operation style. Unique to these fields, education was particularly strained because academics, teachers, and professors alike were obligated to shift their curriculums online over the course of a few weeks while also maintaining the expectation that they were educating their students to a similar level accomplished pre-pandemic. This was notable as research indicates two key concepts: Students prefer face-to-face modality, and due to the disruption in academic continuity/style, there was a negative impact on student's overall education and performance. With these two principles in mind, this study aims to inquire what online strategies could be best employed by teachers to educate their students, as well as what strategies could be adopted in a multimodal setting if deemed necessary by the instructor or outside convoluting factors (Such as the case of COVID-19, or a personal matter that demands the teacher's attention away from the classroom). Strategies and methods will be cross-analyzed via a ranking system derived from various recognized teaching assessments, in which engagement, retention, flexibility, interest, and performance are specifically accounted for. We expect to see an emphasis on positive social pressure as a dominant factor in the improved propensity for education, as well as a preference for visual aids across platforms, as research indicates most individuals are visual learners.

Keywords: technological integration, multimodal teaching, education, student engagement

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Authors: Rachel Byrne

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Background: Due to patient and student safety concerns, combined with clinical teachers being redeployed to clinical practice, COVID-19 has resulted in a reduction in face-to-face teaching sessions for medical students. Traditionally such sessions are particularly important for final year medical students, especially in preparing for their final practical exams. A reduced student presence on the wards has also resulted in fewer opportunities for junior doctors to provide teaching sessions. This has implications for junior doctors achieving their own curriculum outcomes for teaching, as well as potentially hindering the development of a future interest in medical education. Aims: The aims of the study are 1) To create a safe face-to-face teaching environment during COVID-19 which focussed on exam preparation for final year medical students, 2) To provide a platform for doctors to gain teaching experience, 3 ) to enable doctors to gain feedback or assessments on their teaching, 4) To create beginners guide to designing a new teaching program for future junior doctors. Methods: We created a program of timed clinical stations consisting of four sessions every five weeks during the student’s medicine attachment. Each session could be attended by 6 students and consisted of 6 stations ran by junior doctors, with each station following social distancing and personal protective equipment requirements. Junior doctors were asked to design their own stations. The sessions ran out-of-hours on weekday evenings and were optional for the students. Results: 95/95 students and 20/40 doctors involved in the programme completed feedback. 100% (n=95) of students strongly agreed/agreed that sessions were aimed at an appropriate level and provided constructive feedback. 100% (n=95) of students stated they felt more confident in their abilities and would recommend the session to peers. 90% (n=18) of the teachers strongly agreed/agreed that they felt more confident in their teaching abilities and that the sessions had improved their own medical knowledge. 85% (n=17) of doctors had a teaching assessment completed, and 83% (n=16) said the program had made them consider a career in medical education. The difficulties of creating such a program were highlighted throughout, and a beginner’s guide was created with the hopes of helping future doctors who are interested in teaching address the common obstacles.

Keywords: COVID-19, education, safety, medical

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Authors: Sekkal Nawel, Mahammed Nadir

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The proliferation of online activities on Online Social Networks (OSNs) has captured significant user attention. However, this growth has been hindered by the emergence of fraudulent accounts that do not represent real individuals and violate privacy regulations within social network communities. Consequently, it is imperative to identify and remove these profiles to enhance the security of OSN users. In recent years, researchers have turned to machine learning (ML) to develop strategies and methods to tackle this issue. Numerous studies have been conducted in this field to compare various ML-based techniques. However, the existing literature still lacks a comprehensive examination, especially considering different OSN platforms. Additionally, the utilization of bio-inspired algorithms has been largely overlooked. Our study conducts an extensive comparison analysis of various fake profile detection techniques in online social networks. The results of our study indicate that supervised models, along with other machine learning techniques, as well as unsupervised models, are effective for detecting false profiles in social media. To achieve optimal results, we have incorporated six bio-inspired algorithms to enhance the performance of fake profile identification results.

Keywords: machine learning, bio-inspired algorithm, detection, fake profile, system, social network

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Authors: Birgit Rasmussen, Thomas Maribo, Bente S. Toft

Abstract:

BACKGROUND: Cardiac rehabilitation is the standard treatment for ischemic heart disease. Cardiac rehabilitation improves quality of life, reduces mortality and the risk of readmission, and provides patients with valuable knowledge and encouragement from peers and staff. Still, less than half of eligible patients enroll. Face-to-face interventions have the potential to support patients' decision-making and increase enrolment in cardiac rehabilitation. However, we lack knowledge of the content and characteristics of interventions. AIM: The aim was to outline and evaluate the content and characteristics of studies that have reported on face-to-face interventions to encourage enrolment in cardiac rehabilitation in patients with ischemic heart disease. METHOD: This scoping review followed the Joanne Briggs Institute methodology. Based on an a-priori protocol that defined the systematic search criteria, six databases were searched for studies published between 2001 and 2023. Two reviewers independently screened and selected studies. All authors discussed the summarized data prior to the narrative presentation. RESULTS: After screening and full text review of 5583 records, 20 studies of heterogeneous design and content were included. Four studies described the key contents in face-to-face interventions to be education, support of autonomy, addressing reasons for change, and emotional and cognitive support while showing understanding. Two studies used motivational interviewing to target patients' experiences and address worries and anticipated difficulties. Four quantitative studies found associations between enrolment and intention to attend, cardiac rehabilitation barriers, exercise self-efficacy, and perceived control. When patients asked questions, enrolment rates were higher, while providing reassurance and optimism could lead to non-attendance if patients had a high degree of worry. In qualitative studies, support to overcome barriers and knowledge about health benefits from participation in cardiac rehabilitation facilitated enrolment. Feeling reassured that the cardiac condition was good could lead to non-attendance. DISCUSSION AND CONCLUSION: To support patients' enrolment in cardiac rehabilitation, it is recommended that interventions integrate a person-centered dialogue. Individual worries and barriers to cardiac rehabilitation should be jointly explored. When talking with patients for whom worries predominate, the recommendation is to focus on the patients' perspectives and avoid too much focus on reassurance and problem-solving. The patients' perspectives, the mechanisms of change, and the process evaluation of the intervention including person-centeredness are relevant to include in future studies.

Keywords: ischemic heart disease, cardiac rehabilitation, enrolment, person-centered, in-hospital interventions

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