Search results for: explainable machine learning

Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay

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Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Keywords: machining, milling operation, tool condition monitoring, tool wear prediction

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Authors: Diogo Santos, Nelson Zagalo, Carla Morais

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No Man’s Sky (NMS) is a sci-fi video game about survival and exploration where players fly spaceships, search for elements, and use them to survive. NMS isn’t a serious game, and not all the science in the game is presented with scientific evidence. To find how players felt about the scientific content in the game and how they perceive the chemistry in it, a survey was sent to NMS’s players, from which were collected answers from 124 respondents from 23 countries. Chemophobia is still a phenomenon when chemistry or chemicals are a subject of discussion, but 68,9% of our respondents showed a positive attitude towards the presence of chemistry in NMS, with 57% stating that playing the video game motivated them to know more about science. 8% of the players stated that NMS often prompted conversations about the science in the video game between them and teachers, parents, or friends. These results give us ideas on how an entertainment game can potentially help scientists, educators, and science communicators reach a growing, evolving, vibrant, diverse, and demanding audience.

Keywords: digital games, science communication, chemistry, informal learning, No Man’s Sky

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Authors: Lisa Gray, Henry Kronner, Tameca Harris-Jackson, Mimi Sodhi, Ruth Gerritsen-McKane, Donette Considine

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The MSW Peer Mentorship Program (PMP) was developed as one of several approaches to foster student success. The key purposes of the PMP are to help new graduate students transition to a graduate program, facilitate relationship building between students, grow and sustain student satisfaction, and build a strong connection to the MSW program. This pilot program also serves as an additional source of support for students during the era of the Covid-19 pandemic. Further, the long-term goals of the program are to assist in student retention. Preliminary findings suggest that both mentors and mentees enrolled in PMP find the peer mentoring relationship to have a positive impact on their graduate learning experience.

Keywords: covid-19, mentorship, peer support, student success

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Authors: Chaiyawat Musikapan, Ratchatin Chancharoen, Saknan Bongsebandhu-Phubhakdi

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For many recent years, soft robotic fingers were used for supporting the patients who had survived the neurological diseases that resulted in muscular disorders and neural network damages, such as stroke and Parkinson’s disease, and inflammatory symptoms such as De Quervain and trigger finger. Generally, the major hand function is significant to manipulate objects in activities of daily living (ADL). In this work, we proposed the model of soft actuator that manufactured by full 3D printing without the molding process and one material for use. Furthermore, we designed the model with a technique of multi cavitation cells (MC-Cells). Then, we demonstrated the curvature bending, fluidic pressure and force that generated to the model for assistive finger flexor and hand grasping. Also, the soft actuators were characterized in mathematics solving by the length of chord and arc length. In addition, we used an adaptive push-button switch machine to measure the force in our experiment. Consequently, we evaluated biomechanics efficiency by the range of motion (ROM) that affected to metacarpophalangeal joint (MCP), proximal interphalangeal joint (PIP) and distal interphalangeal joint (DIP). Finally, the model achieved to exhibit the corresponding fluidic pressure with force and ROM to assist the finger flexor and hand grasping.

Keywords: biomechanics efficiency, curvature bending, hand functional assistance, multi cavitation cells (MC-Cells), range of motion (ROM)

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Authors: Michel Han, Christophe Besson, Alain Savary, Yvan Becher

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The variable flux permanent magnet synchronous motor (VF-PMSM), also called "Memory Motor", is a new generation of motor capable of modifying the magnetization state with short pulses of current during operation or standstill. The impact of such operation is the expansion of the operating range in the torque-speed characteristic and an improvement in energy efficiency at high-speed in comparison to conventional permanent magnet synchronous machines (PMSMs). This paper reviews the operating principle and the unique features of the proposed memory motor. The benefits of this concept are highlighted by comparing the performance of the rotor of the VF-PMSM to that of two PM rotors that are typically found in the industry. The investigation emphasizes the properties of the variable magnetization and presents the comparison of the torque-speed characteristic with the capability of loss reduction in a VF-PMSM by means of experimental results, especially when tests are conducted under identical conditions for each rotor (same stator, same inverter and same experimental setup). The experimental results demonstrated that the VF-PMSM gives an additional degree of freedom to optimize the efficiency over a wide speed range. Thus, with a design easy to manufacture and with the possibility of controlling the magnetization and the demagnetization of the magnets during operations, the VF-PMSM can be interesting for various applications.

Keywords: efficiency, magnetization state, memory motors, performances, permanent-magnet, synchronous machine, variable-flux, variable magnetization, wide speed application

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Authors: Stephanie Remedios, Linda Veronica Rios

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Background. Pediatric obesity is a serious health problem linked to multiple physical diseases and ailments, including diabetes, heart disease, and joint issues. While research has shown pediatric obesity can bring about an array of physical illnesses, it is less known how such a condition can affect children’s cognitive development. With childhood overweight and obesity prevalence rates on the rise, it is essential to understand the scope of their cognitive consequences. The present review of the literature tested the hypothesis that poor physical health, such as childhood obesity or malnutrition, negatively impacts a child’s cognitive development. Methodology. A systematic review was conducted to determine the relationship between poor physical health and lower cognitive functioning in children ages 4-16. Electronic databases were searched for studies dating back to ten years. The following databases were used: Science Direct, FIU Libraries, and Google Scholar. Inclusion criteria consisted of peer-reviewed academic articles written in English from 2012 to 2022 that analyzed the relationship between childhood malnutrition and obesity on cognitive development. A total of 17,000 articles were obtained, of which 16,987 were excluded for not addressing the cognitive implications exclusively. Of the acquired articles, 13 were retained. Results. Research suggested a significant connection between diet and cognitive development. Both diet and physical activity are strongly correlated with higher cognitive functioning. Cognitive domains explored in this work included learning, memory, attention, inhibition, and impulsivity. IQ scores were also considered objective representations of overall cognitive performance. Studies showed physical activity benefits cognitive development, primarily for executive functioning and language development. Additionally, children suffering from pediatric obesity or malnutrition were found to score 3-10 points lower in IQ scores when compared to healthy, same-aged children. Conclusion. This review provides evidence that the presence of physical activity and overall physical health, including appropriate diet and nutritional intake, has beneficial effects on cognitive outcomes. The primary conclusion from this research is that childhood obesity and malnutrition show detrimental effects on cognitive development in children, primarily with learning outcomes. Assuming childhood obesity and malnutrition rates continue their current trade, it is essential to understand the complete physical and psychological implications of obesity and malnutrition in pediatric populations. Given the limitations encountered through our research, further studies are needed to evaluate the areas of cognition affected during childhood.

Keywords: childhood malnutrition, childhood obesity, cognitive development, cognitive functioning

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Authors: Shan-Ken Chien

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This research aims to a one-year course run of String Music Appreciation, an international online course launched on the British open education platform. It explains how to present music teaching videos with three main features. They are music lesson explanations, instrumental playing demonstrations, and live music performances. The plan of this course is with four major themes and a total of 97 steps. In addition, the paper also uses the testing data provided by the education platform to analyze the performance of learners and to understand the operation of the course. It contains three test data in the statistics dashboard. They are course-run measures, total statistics, and statistics by week. The paper ends with a review of the course's star rating in this one-year run. The result of this course run will be adjusted when it starts again in the future.

Keywords: music online courses, MOOCs, ubiquitous learning, string music, general music education

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Authors: Chuang-Chun Chiou

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In this study, a systematic framework of graceful ageing has been used to explore the possible human resource utilization models for graceful ageing purpose. This framework is based on the Chinese culture. We call ‘Nine-old’ target. They are ageing gracefully with feeding, accomplishment, usefulness, learning, entertainment, care, protection, dignity, and termination. This study is focused on two areas: accomplishment and usefulness. We exam the current practices of initiatives and laws of promoting labor participation. That is to focus on how to increase Labor Force Participation Rate of the middle aged as well as the elderly and try to promote the elderly to achieve graceful ageing. Then we present the possible models that support graceful ageing.

Keywords: human resource utilization model, labor participation, graceful ageing, employment

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Authors: Ghorab Sara, Meziani Lila, Rubin Harvey Stuart

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The rapid growth of deep learning has led to intricate and resource-intensive deep neural networks widely used in computer vision tasks. However, their complexity results in high computational demands and memory usage, hindering real-time application. To address this, research focuses on model compression techniques. The paper provides an overview of recent advancements in compressing neural networks and categorizes the various methods into four main approaches: network pruning, quantization, network decomposition, and knowledge distillation. This paper aims to provide a comprehensive outline of both the advantages and limitations of each method.

Keywords: model compression, deep neural network, pruning, knowledge distillation, quantization, low-rank decomposition

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Authors: Kerryn Burgoyne

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Statement of the Problem: Women who suffer mental health issues, because of Autism Spectrum Disorder has a significant impact on their lives, especially if they’ve been bullied or discriminated against for the majority of their lives. Autism can impact one's mental health in many ways (child like behaviour), social anxieties or overload. The impact of mental health can also be experienced when the person does not have a good quality of life for themselves (eg employment, independent living skills), or have support from family/friends/society). Mental health issues were also suffered during COVID 19 Lockdown here in Melbourne Australia. It was stated by the Government at the time that people weren’t allowed to travel more than 5 km outside of their residential areas to prevent the spread of COVID to others. Medical appointments were an exception. Kerryn/KTalk will be doing a paper on this topic for the conference if accepted by the committee.

Keywords: Autism, mental health, living & learning, KTalk

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Authors: Manish Jain, Dinesh Gopalani

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Growing dependency of mankind on software technology increases the need for thorough testing of the software applications and automated testing techniques that support testing activities. We have outlined our testing strategy for performing various types of automated testing of Java applications using AspectJ which has become the de-facto standard for Aspect Oriented Programming (AOP). Likewise JUnit, a unit testing framework is the most popular Java testing tool. In this paper, we have evaluated our proposed AOP approach for automated testing and JUnit on various parameters. First we have provided the similarity between the two approaches and then we have done a detailed comparison of the two testing techniques on factors like lines of testing code, learning curve, testing of private members etc. We established that our AOP testing approach using AspectJ has got several advantages and is thus particularly more effective than JUnit.

Keywords: aspect oriented programming, AspectJ, aspects, JU-nit, software testing

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Authors: Jigg Pelayo, Ricardo Villar

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Leaning on the development of aerial laser scanning in the Philippine geospatial industry, researches about remote sensing and machine vision technology became a trend. Object detection via template matching is one of its application which characterized to be fast and in real time. The paper purposely attempts to provide application for robust pattern matching algorithm based on the normalized cross correlation (NCC) criterion function subjected in Object-based image analysis (OBIA) utilizing high-resolution aerial imagery and low density LiDAR data. The height information from laser scanning provides effective partitioning order, thus improving the hierarchal class feature pattern which allows to skip unnecessary calculation. Since detection is executed in the object-oriented platform, mathematical morphology and multi-level filter algorithms were established to effectively avoid the influence of noise, small distortion and fluctuating image saturation that affect the rate of recognition of features. Furthermore, the scheme is evaluated to recognized the performance in different situations and inspect the computational complexities of the algorithms. Its effectiveness is demonstrated in areas of Misamis Oriental province, achieving an overall accuracy of 91% above. Also, the garnered results portray the potential and efficiency of the implemented algorithm under different lighting conditions.

Keywords: algorithm, LiDAR, object recognition, OBIA

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Authors: Chien-Hung Liu, Yu-Fen Chen

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This study used triangular laser probe and three-axial direction mobile platform for surface measurement, programmed it and applied it to real-time analytic statistics of different measured data. This structure was used to design a system integration program: using triangular laser probe for scattering or reflection non-contact measurement, transferring the captured signals to the computer through RS-232, and using RS-485 to control the three-axis platform for a wide range of measurement. The data captured by the laser probe are formed into a 3D surface. This study constructed an optical measurement application program in the concept of visual programming language. First, the signals are transmitted to the computer through RS-232/RS-485, and then the signals are stored and recorded in graphic interface timely. This programming concept analyzes various messages, and makes proper presentation graphs and data processing to provide the users with friendly graphic interfaces and data processing state monitoring, and identifies whether the present data are normal in graphic concept. The major functions of the measurement system developed by this study are thickness measurement, SPC, surface smoothness analysis, and analytical calculation of trend line. A result report can be made and printed promptly. This study measured different heights and surfaces successfully, performed on-line data analysis and processing effectively, and developed a man-machine interface for users to operate.

Keywords: laser probe, non-contact measurement, triangulation measurement principle, statistical process control, labVIEW

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Authors: Jezza Mae T. Francisco, Marianet R. Delos Santos, Crisjame C. Toribio

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This study aims to determine the reading preference for English enrichment and reading comprehension among primary students and the difference in the reading preference and comprehension for English enrichment among primary students. This study employed a Descriptive-Quantitative Correlational Research Design. This study yielded the following findings: (1) It reveals that primary students got fair on their reading comprehension, and (2) It shows that there is no significant relationship between the reading preference for English enrichment and reading comprehension of the students. It is safe to conclude that the students’ reading preference is growing evidently in various milieus. This can inform the English department curriculum planners to consider their students’ text preferences that interest them to maximize engagement within a dynamic interactive learning process.

Keywords: reading preferences, reading comprehension, primary student, English enrichment

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Authors: Fadzilah Abdul Rahman

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Emotional development is developed between the parents and their child. Behavioural development is also developed between the parents and their child. Social Development is how parents can help their special needs child to adapt to society and to face challenges. In promoting a lifelong learning mindset, enhancing skill sets and readiness to face challenges, parents would be able to counter balance these challenges during their care giving process and better manage their expectations through understanding the hierarchy of needs modality towards a positive attitude, and in turn, improve their quality of life and participation in society. This paper aims to demonstrate how the hierarchy of needs can be applied in various situations of caregiving for parents with a special needs child.

Keywords: hierarchy of needs, parents, special needs, care-giving

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Authors: Alexis Aldo Mendoza Villarroel, Ademir Clemente Villena Zevallos, Cristian Jose Lopez Del Alamo

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With the advancement of technology it is now possible to scan entire objects and obtain their digital representation by using point clouds or polygon meshes. However, some objects may be broken or have missing parts; thus, several methods focused on this problem have been proposed based on Geometric Deep Learning, such as GCNN, ACNN, PointNet, among others. In this article an approach from a different paradigm is proposed, using metric data structures to index global descriptors in the spectral domain and allow the recovery of a set of similar models in polynomial time; to later use the Iterative Close Point algorithm and recover the parts of the incomplete model using the geometry and topology of the model with less Hausdorff distance.

Keywords: 3D reconstruction method, point cloud completion, shape completion, similarity search

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Authors: ShuPei Wang, Yina Patterson

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This article outlines strategies for improving oral expression to advance proficiency in speaking and listening skills through structured argumentation. The objective is to empower students to effectively use the target language to express opinions and construct compelling arguments. This empowerment is achieved by honing learners' debating and questioning skills, which involves increasing their familiarity with vocabulary and phrases relevant to debates and deepening their understanding of the cultural context surrounding pertinent issues. Through this approach, students can enhance their ability to articulate complex concepts and discern critical points, surpassing superficial comprehension and enabling them to engage in the target language actively and competently.

Keywords: debate, teaching and materials design, spoken expression, listening proficiency, critical thinking

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Authors: K. S. Parlak, E. Turan

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The separation of marbles according to the pattern quality is a process made according to expert decision. The classification phase is the most critical part in terms of economic value. In this study, a self-learning system is proposed which performs the classification of marbles quickly and with high success. This system performs ten feature extraction by taking ten marble images from the camera. The marbles are classified by decision tree method using the obtained properties. The user forms the training set by training the system at the marble classification stage. The system evolves itself in every marble image that is classified. The aim of the proposed system is to minimize the error caused by the person performing the classification and achieve it quickly.

Keywords: decision tree, feature extraction, k-means clustering, marble classification

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Authors: S. Bouhouche, R. Drai, J. Bast

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This paper is concerned with a method for uncertainty evaluation of steel sample content using X-Ray Fluorescence method. The considered method of analysis is a comparative technique based on the X-Ray Fluorescence; the calibration step assumes the adequate chemical composition of metallic analyzed sample. It is proposed in this work a new combined approach using the Kalman Filter and Markov Chain Monte Carlo (MCMC) for uncertainty estimation of steel content analysis. The Kalman filter algorithm is extended to the model identification of the chemical analysis process using the main factors affecting the analysis results; in this case, the estimated states are reduced to the model parameters. The MCMC is a stochastic method that computes the statistical properties of the considered states such as the probability distribution function (PDF) according to the initial state and the target distribution using Monte Carlo simulation algorithm. Conventional approach is based on the linear correlation, the uncertainty budget is established for steel Mn(wt%), Cr(wt%), Ni(wt%) and Mo(wt%) content respectively. A comparative study between the conventional procedure and the proposed method is given. This kind of approaches is applied for constructing an accurate computing procedure of uncertainty measurement.

Keywords: Kalman filter, Markov chain Monte Carlo, x-ray fluorescence calibration and testing, steel content measurement, uncertainty measurement

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Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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Borosilicate-crown (BK7) glass has found broad application in the optic and automotive industries and the growing demands for nanometric surface finishes is becoming a necessity in such applications. Thus, it has become paramount to optimize the parameters influencing the surface roughness of this precision lens. The research was carried out on a 4-axes Nanoform 250 precision lathe machine with an ultra-high precision grinding spindle. The experiment varied the machining parameters of feed rate, wheel speed and depth of cut at three levels for different combinations using Box Behnken design of experiment and the resulting surface roughness values were measured using a Taylor Hobson Dimension XL optical profiler. Acoustic emission monitoring technique was applied at a high sampling rate to monitor the machining process while further signal processing and feature extraction methods were implemented to generate the input to a neural network algorithm. This paper highlights the training and development of a back propagation neural network prediction algorithm through careful selection of parameters and the result show a better classification accuracy when compared to a previously developed response surface model with very similar machining parameters. Hence artificial neural network algorithms provide better surface roughness prediction accuracy in the ultra-high precision grinding of BK7 glass.

Keywords: acoustic emission technique, artificial neural network, surface roughness, ultra-high precision grinding

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Authors: Somruay Apichatibutarapong, Chookiat Pudprommart

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The purpose of this study was to develop of statistical analysis by using R programming via internet applied for agriculture experimental design. Data were collected from 65 items in completely randomized design, randomized block design, Latin square design, split plot design, factorial design and nested design. The quantitative approach was used to investigate the quality of learning media on statistical analysis by using R programming via Internet by six experts and the opinions of 100 students who interested in experimental design and applied statistics. It was revealed that the experts’ opinions were good in all contents except a usage of web board and the students’ opinions were good in overall and all items.

Keywords: experimental design, r programming, applied statistics, statistical analysis

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Authors: Vladyslav Povoroznyuk, Anna Musiienko, Nataliia Dzerovych, Roksolana Povoroznyuk

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Osteoporosis and obesity are widespread diseases in people over 50 years associated with changes in structure and body composition. Нigher body mass index (BMI) values are associated with greater bone mineral density (BMD). However, trabecular bone score (TBS) indirectly explores bone quality, independently of BMD. The aim of our study was to evaluate the relationship between the BMD and TBS parameters in Ukrainian men suffering from obesity. We examined 396 men aged 40-89 years. Depending on their BMI all the subjects were divided into two groups: Group I – patients with obesity whose BMI was ≥ 30 kg/m² (n=129) and Group II – patients without obesity and BMI of < 30 kg/m² (n=267). The BMD of total body, lumbar spine L₁-L₄, femoral neck and forearm were measured by DXA (Prodigy, GEHC Lunar, Madison, WI, USA). The TBS of L₁- L₄ was assessed by means of TBS iNsight® software installed on DXA machine (product of Med-Imaps, Pessac, France). In general, obese men had a significantly higher BMD of lumbar spine L₁-L₄, femoral neck, total body and ultradistal forearm (p < 0.001) in comparison with men without obesity. The TBS of L₁-L₄ was significantly lower in obese men compared to non-obese ones (p < 0.001). BMD of lumbar spine L₁-L₄, femoral neck and total body significantly differ in men aged 40-49, 50-59, 60-69, and 80-89 years (p < 0.05). At the same time, in men aged 70-79 years, BMD of lumbar spine L₁-L₄ (p=0.46), femoral neck (p=0.18), total body (p=0.21), ultra-distal forearm (p=0.13), and TBS (p=0.07) did not significantly differ. A significant positive correlation between the fat mass and the BMD at different sites was observed. However, the correlation between the fat mass and TBS of L₁-L₄ was also significant, though negative.

Keywords: bone mineral density, trabecular bone score, obesity, men

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Authors: Keith Schofield, Leigh Morland

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Storytelling is an established means of leadership and management development and is also considered a form of leadership of self and others in its own right. This study focuses on the utility of storytelling in the development of management narratives in an MBA programme; sources include programme participants as well as international recruiters, whose voices are often only heard in terms of economic contribution and globalisation. For many MBA candidates, the return to study requires the development of a new identity which complements their professional identity; each candidate has their own journey and expectations, the use of story can enable candidates to explore their aspirations and assumptions and give voice to previously unspoken ideas. For international recruitment, the story of market development and change must be captured if MBAs are to remain fit for purpose. If used effectively, story acts as a form of critical reflection that can inform the learning journeys of individuals, emerging identities as well as the ongoing design and development of programmes. The landscape of management education is shifting; the MBA begins to attract a different kind of candidate, some are younger than before, others are seeking validation for their existing work practices, yet more are entrepreneurial and wish to capitalise on an institutional experience to further their career. There is a shift in context, creating uncertainty and ambiguity for programme managers and recruiters, thus requiring institutions to create a new MBA narrative. This study utilises Lego SeriousPlay as the means to engaging programme participants and international agents in telling the story of their MBA. We asked MBA participants to tell the story of their leadership and management aspirations and compare these to stories of their development journeys, allowing for critical reflection of their respective development gaps. We asked international recruiters, who act as university agents and promote courses in the student’s country of origin, to explore their mental models of MBA candidates and their learning agenda. The purpose of this process was to explore the agent’s perception of the MBA programme and to articulate the student journey from a recruitment perspective. The paper’s unique contribution is in combining these stories in order to explore the assumptions that determine programme design. Data drawn from reflective statements together with images of Lego ‘builds’ created the opportunity for reflection between the mental models of these groups. Findings will inform the design of the MBA journey and experience; we review the extent to which the changing identities of learners are congruent with programme design. Data from international recruiters also determines the extent to which marketing and recruitment strategies identify with would be candidates.

Keywords: critical reflection, programme management, recruitment, storytelling

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Authors: Wen-Jye Shyr, Chun-Yuan Chang, Bo-Lin Wei, Chia-Ming Lin

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The task of creating an augmented reality technology was described in this study to give operators a user interface that might be a part of an automated storage and retrieval system. Its objective was to give graduate engineering and technology students a system of tools with which to experiment with the creation of augmented reality technologies. To collect and analyze data for maintenance applications, the students used augmented reality technology. Our findings support the evolution of artificial intelligence towards Industry 4.0 practices and the planned Industry 4.0 research stream. Important first insights into the study's effects on student learning were presented.

Keywords: augmented reality, storage and retrieval system, user interface, programmable logic controller

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Authors: S. Shankar Bharathi

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Inspection of surface defects on metallic components has always been challenging due to its specular property. Occurrences of defects such as scratches, rust, pitting are very common in metallic surfaces during the manufacturing process. These defects if unchecked can hamper the performance and reduce the life time of such component. Many of the conventional image processing algorithms in detecting the surface defects generally involve segmentation techniques, based on thresholding, edge detection, watershed segmentation and textural segmentation. They later employ other suitable algorithms based on morphology, region growing, shape analysis, neural networks for classification purpose. In this paper the work has been focused only towards detecting scratches. Global and other thresholding techniques were used to extract the defects, but it proved to be inaccurate in extracting the defects alone. However, this paper does not focus on comparison of different segmentation techniques, but rather describes a novel approach towards segmentation combined with hausdorff dilation distance. The proposed algorithm is based on the distribution of the intensity levels, that is, whether a certain gray level is concentrated or evenly distributed. The algorithm is based on extraction of such concentrated pixels. Defective images showed higher level of concentration of some gray level, whereas in non-defective image, there seemed to be no concentration, but were evenly distributed. This formed the basis in detecting the defects in the proposed algorithm. Hausdorff dilation distance based on mathematical morphology was used to strengthen the segmentation of the defects.

Keywords: metallic surface, scratches, segmentation, hausdorff dilation distance, machine vision

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Authors: Hamid Gholami

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During the years, the language teaching methods have been the offshoots of schools of thought in psychology. The methods were mainly influenced by their contemporary psychological approaches, as Audiolingualism was based on behaviorism and Communicative Language Teaching on constructivism. In 1950s, the text books were full of repetition exercises which were encouraged by Behaviorism. In 1980s they got filled with communicative exercises as suggested by constructivism. The trend went on to nowadays that sees no specific method as prevalent since none of the schools of thought seem to be illustrative of the complexity in human being learning. But some changes can be notable; some textbooks are giving more and more space to repetition exercises at least to enhance some aspects of language proficiency, namely collocations, rhythm and intonation, and conversation models. These changes may mark the reemergence of one of the once widely accepted schools of thought in psychology; behaviorism.

Keywords: language teaching methods, psychology, schools of thought, Behaviorism

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Authors: Muhammad Abdul Basit Memon

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The importance of organizational knowledge sharing and knowledge management has been documented in numerous research studies in available literature, since knowledge sharing has been recognized as a founding pillar for superior organizational performance and a source of gaining competitive advantage. Built on this, most of the successful organizations perceive knowledge management and knowledge sharing as a concern of high strategic importance and spend huge amounts on the effective management and sharing of organizational knowledge. However, despite some very serious endeavors, many firms fail to capitalize on the benefits of knowledge sharing because of being unaware of the individual characteristics, interpersonal, organizational and contextual factors that influence knowledge sharing; simply the antecedent to knowledge sharing. The extant literature on antecedents to knowledge sharing, offers a range of antecedents mentioned in a number of research articles and research studies. Some of the previous studies about antecedents to knowledge sharing, studied antecedents to knowledge sharing regarding inter-organizational knowledge transfer; others focused on inter and intra organizational knowledge sharing and still others investigated organizational factors. Some of the organizational antecedents to KS can relate to the characteristics and underlying aspects of knowledge being shared e.g., specificity and complexity of the underlying knowledge to be transferred; others relate to specific organizational characteristics e.g., age and size of the organization, decentralization and absorptive capacity of the firm and still others relate to the social relations and networks of organizations such as social ties, trusting relationships, and value systems. In the same way some researchers have highlighted on only one aspect like organizational commitment, transformational leadership, knowledge-centred culture, learning and performance orientation and social network-based relationships in the organizations. A bulk of the existing research articles on antecedents to knowledge sharing has mainly discussed organizational or environmental factors affecting knowledge sharing. However, the focus, later on, shifted towards the analysis of individuals or personal determinants as antecedents for the individual’s engagement in knowledge sharing activities, like personality traits, attitude and self efficacy etc. For example, employees’ goal orientations (i.e. learning orientation or performance orientation is an important individual antecedent of knowledge sharing behaviour. While being consistent with the existing literature therefore, the antecedents to knowledge sharing can be classified as being individual and organizational. This paper is an endeavor to discuss a conceptual framework of the individual and organizational antecedents to knowledge sharing in the light of the available literature and empirical evidence. This model not only can help in getting familiarity and comprehension on the subject matter by presenting a holistic view of the antecedents to knowledge sharing as discussed in the literature, but can also help the business managers and especially human resource managers to find insights about the salient features of organizational knowledge sharing. Moreover, this paper can help provide a ground for research students and academicians to conduct both qualitative as well and quantitative research and design an instrument for conducting survey on the topic of individual and organizational antecedents to knowledge sharing.

Keywords: antecedents to knowledge sharing, knowledge management, individual and organizational, organizational knowledge sharing

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Authors: Mariza Kaskara, Stella Girtsou, Maria Prodromou, Alexia Tsouni, Christodoulos Mettas, Stavroula Alatza, Kyriaki Fotiou, Marios Tzouvaras, Charalampos Kontoes, Diofantos Hadjimitsis

Abstract:

Natural hazard assessment and monitoring are crucial in managing the risks associated with fires, floods, and geohazards, particularly in regions prone to these natural disasters, such as Greece and Cyprus. Recent advancements in technology, developed by the BEYOND Center of Excellence of the National Observatory of Athens, have been successfully applied in Greece and are now set to be transferred to Cyprus. The implementation of these advanced technologies in Greece has significantly improved the country's ability to respond to these natural hazards. For wildfire risk assessment, a scalar wildfire occurrence risk index is created based on the predictions of machine learning models. Predicting fire danger is crucial for the sustainable management of forest fires as it provides essential information for designing effective prevention measures and facilitating response planning for potential fire incidents. A reliable forecast of fire danger is a key component of integrated forest fire management and is heavily influenced by various factors that affect fire ignition and spread. The fire risk model is validated by the sensitivity and specificity metric. For flood risk assessment, a multi-faceted approach is employed, including the application of remote sensing techniques, the collection and processing of data from the most recent population and building census, technical studies and field visits, as well as hydrological and hydraulic simulations. All input data are used to create precise flood hazard maps according to various flooding scenarios, detailed flood vulnerability and flood exposure maps, which will finally produce the flood risk map. Critical points are identified, and mitigation measures are proposed for the worst-case scenario, namely, refuge areas are defined, and escape routes are designed. Flood risk maps can assist in raising awareness and save lives. Validation is carried out through historical flood events using remote sensing data and records from the civil protection authorities. For geohazards monitoring (e.g., landslides, subsidence), Synthetic Aperture Radar (SAR) and optical satellite imagery are combined with geomorphological and meteorological data and other landslide/ground deformation contributing factors. To monitor critical infrastructures, including dams, advanced InSAR methodologies are used for identifying surface movements through time. Monitoring these hazards provides valuable information for understanding processes and could lead to early warning systems to protect people and infrastructure. Validation is carried out through both geotechnical expert evaluations and visual inspections. The success of these systems in Greece has paved the way for their transfer to Cyprus to enhance Cyprus's capabilities in natural hazard assessment and monitoring. This transfer is being made through capacity building activities, fostering continuous collaboration between Greek and Cypriot experts. Apart from the knowledge transfer, small demonstration actions are implemented to showcase the effectiveness of these technologies in real-world scenarios. In conclusion, the transfer of advanced natural hazard assessment technologies from Greece to Cyprus represents a significant step forward in enhancing the region's resilience to disasters. EXCELSIOR project funds knowledge exchange, demonstration actions and capacity-building activities and is committed to empower Cyprus with the tools and expertise to effectively manage and mitigate the risks associated with these natural hazards. Acknowledgement:Authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project.

Keywords: earth observation, monitoring, natural hazards, remote sensing

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Authors: Danilo López, Nelson Vera, Luis Pedraza

Abstract:

This paper analyzes fundamental ideas and concepts related to neural networks, which provide the reader a theoretical explanation of Long Short-Term Memory (LSTM) networks operation classified as Deep Learning Systems, and to explicitly present the mathematical development of Backward Pass equations of the LSTM network model. This mathematical modeling associated with software development will provide the necessary tools to develop an intelligent system capable of predicting the behavior of licensed users in wireless cognitive radio networks.

Keywords: neural networks, multilayer perceptron, long short-term memory, recurrent neuronal network, mathematical analysis

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Authors: Robert S. Giachetti, Emanuele Grossi

Abstract:

Loosening of bolted joints in rotating machines can adversely affect their performance, cause mechanical damage, and lead to injuries. In this paper, two potential loosening phenomena in rotating applications are discussed. First, ‘precession,’ is governed by thread/nut contact forces, while the second is based on inertial effects of the fastened assembly. These mechanisms are reviewed within the context of historical usage of left-handed fasteners in rotating machines which appears absent in the literature and common machine design texts. Historically, to prevent loosening of wheel nuts, vehicle manufacturers have used right-handed and left-handed threads on different sides of the vehicle, but most modern vehicles have abandoned this custom and only use right-handed, tapered lug nuts on all sides of the vehicle. Other classical machines such as the bicycle continue to use different handed threads on each side while other machines such as, bench grinders, circular saws and brush cutters still use left-handed threads to fasten rotating components. Despite the continued use of left-handed fasteners, the rationale and analysis of left-handed threads to mitigate self-loosening of fasteners in rotating applications is not commonly, if at all, discussed in the literature or design textbooks. Without scientific literature to support these design selections, these implementations may be the result of experimental findings or aged institutional knowledge. Based on a review of rotating applications, historical documents and mechanical design references, a formal study of the paradoxical nature of left-handed threads in various applications is merited.

Keywords: rotating machinery, self-loosening fasteners, wheel fastening, vibration loosening

Procedia PDF Downloads 138