Search results for: 2023 vision

Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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Authors: A. P. Mikhailovich, V. V. Fomin, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

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Woody vegetation among the upper limit of its habitat is a sensitive indicator of biota reaction to regional climate changes. Quantitative assessment of temporal and spatial changes in the distribution of trees and plant biocenoses calls for the development of new modeling approaches based upon selected data from measurements on the ground level and ultra-resolution aerial photography. Statistical models were developed for the study area located in the Polar Urals. These models allow obtaining probabilistic estimates for placing Siberian Larch trees into one of the three age intervals, namely 1-10, 11-40 and over 40 years, based on the Weilbull distribution of the maximum horizontal crown projection. Authors developed the distribution map for larch trees with crown diameters exceeding twenty centimeters by deciphering aerial photographs made by a UAV from an altitude equal to fifty meters. The total number of larches was equal to 88608, forming the following distribution row across the abovementioned intervals: 16980, 51740, and 19889 trees. The results demonstrate that two processes can be observed in the course of recent decades: first is the intensive forestation of previously barren or lightly wooded fragments of the study area located within the patches of wood, woodlands, and sparse stand, and second, expansion into mountain tundra. The current expansion of the Siberian Larch in the region replaced the depopulation process that occurred in the course of the Little Ice Age from the late 13ᵗʰ to the end of the 20ᵗʰ century. Using data from field measurements of Siberian larch specimen biometric parameters (including height, diameter at root collar and at 1.3 meters, and maximum projection of the crown in two orthogonal directions) and data on tree ages obtained at nine circular test sites, authors developed a model for artificial neural network including two layers with three and two neurons, respectively. The model allows quantitative assessment of a specimen's age based on height and maximum crone projection values. Tree height and crown diameters can be quantitatively assessed using data from aerial photographs and lidar scans. The resulting model can be used to assess the age of all Siberian larch trees. The proposed approach, after validation, can be applied to assessing the age of other tree species growing near the upper tree boundaries in other mountainous regions. This research was collaboratively funded by the Russian Ministry for Science and Education (project No. FEUG-2023-0002) and Russian Science Foundation (project No. 24-24-00235) in the field of data modeling on the basis of artificial neural network.

Keywords: treeline, dynamic, climate, modeling

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Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

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Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

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Authors: Min Jindong, Wang Mingxia

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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

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Authors: Muhammad Izzam Bin Mohd Khazar, Ruqayyah Binti Mohamad Ali, Nurul Atiqah Binti Yusri

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Value-based intermediation (VBI) has been introduced by Bank Negara Malaysia (BNM) as the next strategic direction and growth driver for Islamic banking institutions. The aim of VBI is to deliver the intended outcome of Shariah through practices, conducts, and offerings that generate positive and sustainable impact to the economy, community and environment which is aligned to Maqasid Shariah in preserving the common interest of society by preventing harm and maximizing benefit. Hence, upon its implementation, VBI will experiment the current Shariah compliance treatment and revolutionise new policies and systems that can meritoriously entrench and convey the objectives of Shariah. However, discussion revolving VBI in the light of Maqasid analysis is still scarce hence further research needs to be undertaken. The idea of implementation of VBI vision into quantifiable Maqasid Shariah measurement is yet to be explored due to the nature of Maqasid that is variable. The contemporary scholars also have different views on the implementation of VBI. This paper aims to discuss on the importance of Maqasid Shariah in the current Islamic finance transactions by providing Shariah index measurement in the application of VBI. This study also intends to explore basic Shariah guidelines and parameters based on the objectives of Shariah; preservation of the five pillars (religion, life, progeny, intellect and wealth) with further elaboration on preservation of wealth under five headings: rawaj (circulation and marketability); wuduh (transparency); hifz (preservation); thabat (durability and tranquillity); and ‘adl (equity and justice). In alignment with these headings, Islamic finance can be innovated for VBI implementation, particularly in Maybank Islamic being a significant leader in the IFI market.

Keywords: Islamic Financial Institutions, Maqasid Index, Maqasid Shariah, sustainability, value-based intermediation

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Authors: Repaul Kanji, Rajat Agrawal

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In this era where issues like climate change and disasters are the topics of discussion at national and international forums, it is very often that humanity questions the causative role of corporates in such events. It is beyond any doubt that rapid industrialisation and development has taken a toll in the form of climate change and even disasters, in some case. Thus, demanding to fulfill a corporate's responsibilities in the form of rescue and relief in times of disaster, rehabilitation and even mitigation and preparedness to adapt to the oncoming changes is obvious. But how can the responsibilities of the corporates be channelised to ensure all this, i.e., develop a resilient society? More than that, which factors, when emphasised upon, can lead to the holistic development of the society. To answer this query, an extensive literature review was done to identify several enablers like legislations of a nation, the role of brand and reputation, ease of doing Corporate Social Responsibility, mission and vision of an organisation, religion and culture, etc. as a tool for building disaster resilience. A questionnaire survey, interviews with experts and academicians followed by interpretive structural modelling (ISM) were used to construct a multi-hierarchy model depicting the contextual relationship among the identified enablers. The study revealed that culture and religion are the most powerful driver, which affects other enablers either directly or indirectly. Taking cognisance of the fact that an idea of separation between religion and workplace (business) resides subconsciously within the society, the study tries to interpret the outcome of the ISM through the lenses of past researches (The Integrating Box) and explores how it can be leveraged to build a resilient society.

Keywords: corporate social responsibility, interpretive structural modelling, disaster resilience and risk reduction, the integration box (TIB)

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Authors: K. Doi, T. Nishimura, H. Fujimoto, Y. Hoshikawa, T. Wada

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Japanese industrial standard (JIS) association established one JIS (JIS S 0021) regarding packaging accessible design for people with visual impairments and elderly people in 2000. Recently, tactile symbol on shampoo bottle has been known as one of package accessible design and more effectively used. However, it has been said that people with visual impairment have been not been in trouble with difficulty of identifying body soap bottle between three bottles such as body soap bottle, shampoo bottle, and conditioner bottle. Japanese low vision association asked JIS association to solve this problem. JIS association and Japan cosmetic industry association constituted one review team for solving the problem. The review team asked our research team to make a proposal regarding new tactile symbol on body soap bottle. We conducted user survey and maker survey regarding tactile symbol on body soap bottle with easily identification. Seven test tactile symbol marks were elected in our proposed tactile symbols. In this study, we evaluate easily identification of tactile symbol on body soap bottle. Six visual impaired subjects were participated in our experiment. These subjects were asked to identify body soap bottle between three bottles such as body soap bottle, shampoo bottle, and conditioner bottle. The test tactile symbol on body soap were presented in random order. The test tactile symbols were produced by use of our originally developed 3D raised equipment. From our study, test tactile symbol marks with easily identification were made a short list of our proposed tactile symbols. This knowledge will be helpful in revision of ISO 11156.

Keywords: tactile symbol, easily identification, body soap, people with visual impairments

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Authors: Abid Kousay

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Appeared and developed essentially in large companies and multinationals, Talent Management (TM) in Small and Medium-Sized Enterprises (SMEs) has remained an under-explored subject till today. Although the literature on TM in the Anglo-Saxon context is developing, it remains monopolized in non-European contexts, especially in France. Therefore, this article aims to address these shortcomings through contributing to TM issues, by adopting a multilevel approach holding the goal of reaching a global holistic vision of interactions between various levels, while applying TM. A qualitative research study carried out within 12 SMEs in France, built on the methodological perspective of grounded theory, will be used in order to go beyond description, to generate or discover a theory or even a unified theoretical explanation. Our theoretical contributions are the results of the grounded theory, the fruit of context considerations and the dynamic of the multilevel approach. We aim firstly to determine the perception of talent and TM in SMEs. Secondly, we formalize TM in SME through the empowerment of all 3 levels in the organization (individual, collective, and organizational). And we generate a multilevel dynamic system model, highlighting the institutionalization dimension in SMEs and the managerial conviction characterized by the domination of the leader's role. Thirdly, this first study shed the light on the importance of rigorous implementation of TM in SMEs in France by directing CEO and HR and TM managers to focus on elements that upstream TM implementation and influence the system internally. Indeed, our systematic multilevel approach policy reminds them of the importance of the strategic alignment while translating TM policy into strategies and practices in SMEs.

Keywords: French context, institutionalization, talent, multilevel approach, talent management system

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Authors: Abdullah Al-Alaian, Ahmad Al-Enzi, Hasan Al-Herz, Ahmad Bakri, Shant Tatorian, Amr Nounou

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Kuwait is a country that has an imbalanced economy since most of its national outcome comes from the oil trade. It is so risky for a country to be dependent on a single source for income, and this increases the need to diversify its economy. In addition, according to the Public Authority for Industry, the contribution of the industrial sector to the current Gross Domestic Product (GDP) of Kuwait is low which is about 4.33%. Therefore, the development of the industrial sector can be one of the means to diversify the economy and increase the industry's contribution to the national outcome. This is in accordance with Kuwait’s vision of 2035 which aims at increasing the contribution of the industrial sector to the GDP to 12%. In order to do so, this study aims at proposing a strategic plan that will accomplish certain objectives when implemented. It is based on analyzing the industrial sectors in Kuwait taking into consideration studying the strengths, weaknesses, opportunities, and threats facing them. At the same time, it tends to gain from the experience of leading models and neighboring countries regarding the development of the industrial sector. In this study, the SWOT analysis technique will be conducted on all industrial sectors based on evaluation criteria in which it is determined whether any of them has a potential for improvement or not. In other words, it is determined whether the sectors are able to compete locally, regionally, or globally. Based on the results of the SWOT analysis, certain sectors will be chosen, assessed based on an assessment scheme, and their potentials for improvement will be aligned with the overall objectives. To ensure the achievement of the study’s objectives, an action plan will be proposed regarding recommendations for the related authorities, and for entrepreneurs. In addition, monitoring tools are going to be provided for the purpose of periodically checking the progress made in the implementation of the plan.

Keywords: industrial sector, SWOT analysis, productivity, competitiveness, GDP, Kuwait, economy

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Authors: Jalil Salimi, Mandana Asadi, Naser Fathi

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Urmia Lake (UL) has undergone a significant decline in water levels, resulting in severe environmental, socioeconomic, and health-related challenges. This paper examines the restoration process of UL from a water governance perspective. By applying a water governance model, the study evaluates the process based on six selected principles: stakeholder engagement, transparency and accountability, effectiveness, equitable water use, adaptation capacity, and water usage efficiency. The dominance of structural and physicalist approaches to water governance has led to a weak understanding of social and environmental issues, contributing to social crises. Urgent efforts are required to address the water crisis and reform water governance in the country, making water-related issues a top national priority. The UL restoration process has achieved significant milestones, including stakeholder consensus, scientific and participatory planning, environmental vision, intergenerational justice considerations, improved institutional environment for NGOs, investments in water infrastructure, transparency promotion, environmental effectiveness, and local issue resolutions. However, challenges remain, such as power distribution imbalances, bureaucratic administration, weak conflict resolution mechanisms, financial constraints, accountability issues, limited attention to social concerns, overreliance on structural solutions, legislative shortcomings, program inflexibility, and uncertainty management weaknesses. Addressing these weaknesses and challenges is crucial for the successful restoration and sustainable governance of UL.

Keywords: evaluation, restoration process, Urmia Lake, water governance, water resource management

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Authors: Aliya K. Salahova

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Scientific thinking, characterized by purposeful knowledge-seeking and the harmonization of theory and facts, holds a crucial role in preparing young minds for an increasingly complex and technologically advanced world. This abstract presents a research study aimed at fostering scientific thinking in early childhood, focusing on children aged 5 to 9 years, through experiential learning in Kids Science Labs (STEM). The study utilized a longitudinal exploration design, spanning 240 weeks from September 2018 to April 2023, to evaluate the effectiveness of the Kids Science Labs program in developing scientific thinking skills. Participants in the research comprised 72 children drawn from local schools and community organizations. Through a formative psychology-pedagogical experiment, the experimental group engaged in weekly STEM activities carefully designed to stimulate scientific thinking, while the control group participated in daily art classes for comparison. To assess the scientific thinking abilities of the participants, a registration table with evaluation criteria was developed. This table included indicators such as depth of questioning, resource utilization in research, logical reasoning in hypotheses, procedural accuracy in experiments, and reflection on research processes. The data analysis revealed dynamic fluctuations in the number of children at different levels of scientific thinking proficiency. While the development was not uniform across all participants, a main leading factor emerged, indicating that the Kids Science Labs program and formative experiment exerted a positive impact on enhancing scientific thinking skills in children within this age range. The study's findings support the hypothesis that systematic implementation of STEM activities effectively promotes and nurtures scientific thinking in children aged 5-9 years. Enriching education with a specially planned STEM program, tailoring scientific activities to children's psychological development, and implementing well-planned diagnostic and corrective measures emerged as essential pedagogical conditions for enhancing scientific thinking abilities in this age group. The results highlight the significant and positive impact of the systematic-activity approach in developing scientific thinking, leading to notable progress and growth in children's scientific thinking abilities over time. These findings have promising implications for educators and researchers, emphasizing the importance of incorporating STEM activities into educational curricula to foster scientific thinking from an early age. This study contributes valuable insights to the field of science education and underscores the potential of STEM-based interventions in shaping the future scientific minds of young children.

Keywords: Scientific thinking, education, STEM, intervention, Psychology, Pedagogy, collaborative learning, longitudinal study

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Authors: Laura Mion

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The implementation of quality management systems in higher education in different countries is determined by national regulatory choices and supranational indications (such as the European Standard Guidelines for Quality Assurance). The effective functioning and transformative capacity of these quality management systems largely depend on the organizational context in which they are applied and, more specifically, on the culture of quality developed in single universities or in single countries. The University's concept of quality culture integrates the structural dimension of QA (quality management manuals, process definitions, tools) with the value dimension of an organization (principles, skills, and attitudes). Within the EHEA (European Higher Education Area), countries such as Portugal, the Netherlands, the UK, and Norway demonstrate a greater integration of QA principles in the various organizational levels and areas of competence of university institutions or have greater experience in implementation or scientific and political debate on the matter. Therefore, the study, through an integrative literature review, of the quality management systems of these countries is aimed at determining a framework of the culture of quality, helpful in defining the elements which, both in structural-organizational terms and in terms of values and skills and attitudes, have proved to be factors of success in the effective implementation of quality assurance systems in universities and in the countries considered in the research. In order for a QA system to effectively aim for continuous improvement in a complex and dynamic context such as the university one, it must embrace a holistic vision of quality from an integrative perspective, focusing on the objective of transforming the reality being evaluated.

Keywords: higher education, quality assurance, quality culture, Portugal, Norway, Netherlands, United Kingdom

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Authors: Daohong Yang, Xiang Zhang, Lei Li, Wanting Zhou

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Visual Simultaneous Localization and Mapping (VSLAM) is a technology that obtains information in the environment for self-positioning and mapping. It is widely used in computer vision, robotics and other fields. Many visual SLAM systems, such as OBSLAM3, employ a constant-speed motion model that provides the initial pose of the current frame to improve the speed and accuracy of feature matching. However, in actual situations, the constant velocity motion model is often difficult to be satisfied, which may lead to a large deviation between the obtained initial pose and the real value, and may lead to errors in nonlinear optimization results. Therefore, this paper proposed a motion model based on acceleration, which can be applied on most SLAM systems. In order to better describe the acceleration of the camera pose, we decoupled the pose transformation matrix, and calculated the rotation matrix and the translation vector respectively, where the rotation matrix is represented by rotation vector. We assume that, in a short period of time, the changes of rotating angular velocity and translation vector remain the same. Based on this assumption, the initial pose of the current frame is estimated. In addition, the error of constant velocity model was analyzed theoretically. Finally, we applied our proposed approach to the ORBSLAM3 system and evaluated two sets of sequences on the TUM dataset. The results showed that our proposed method had a more accurate initial pose estimation and the accuracy of ORBSLAM3 system is improved by 6.61% and 6.46% respectively on the two test sequences.

Keywords: error estimation, constant acceleration motion model, pose estimation, visual SLAM

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Authors: Sumeeta Khurana, Kirti Megha, Amit Gupta, Rakesh Sehgal

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Background: Amoebic keratitis is a painful vision threatening infection caused by a free living pathogenic amoeba Acanthamoeba. It can be misdiagnosed and very difficult to treat if not suspected early. The epidemiology of Acanthamoeba genotypes causing infection in our geographical area is not yet known to the best of our knowledge. Objective: To characterize Acanthamoeba isolates from amoebic keratitis patients. Methods: A total of 19 isolates obtained from patients with amoebic keratitis presenting to the Advanced Eye Centre at Postgraduate Institute of Medical Education and Research, a tertiary care centre of North India over a period of last 10 years were included. Their corneal scrapings, lens solution and lens case (in case of lens wearer) were collected for microscopic examination, culture and molecular diagnosis. All the isolates were maintained in the Non Nutrient agar culture medium overlaid with E.coli and 13 strains were axenised and maintained in modified Peptone Yeast Dextrose Agar. Identification of Acanthamoeba genotypes was based on amplification of diagnostic fragment 3 (DF3) region of the 18srRNA gene followed by sequencing. Nucleotide similarity search was performed by BLAST search of sequenced amplicons in GenBank database (http//www.ncbi.nlm.nih.gov/blast). Multiple Sequence alignments were determined by using CLUSTAL X. Results: Nine out of 19 Acanthamoeba isolates were found to belong to Genotype T4 followed by 6 isolates of genotype T11, 3 T5 and 1 T3 genotype. Conclusion: T4 is the predominant Acanthamoeba genotype in our geographical area. Further studies should focus on differences in pathogenicity of these genotypes and their clinical significance.

Keywords: Acanthamoeba, free living amoeba, keratitis, genotype, ocular

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Authors: Johanna Lundqvist

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Third cycle supervision is a multifaceted and complex task for supervisors in higher education. It progresses over several years and is affected by several proximal and distal factors. It can result in positive learning outcomes for doctoral students and high-quality publications. However, not all doctoral students thrive during their doctoral studies; nor do they all complete their studies. This is problematic for both the individuals themselves as well as society at large: doctoral students are valuable and important in current research, future research and higher education. The aim of this literature review is to elucidate what responsible third cycle supervision can include and be in practice. The question posed is as follows: according to recent literature, what is it that characterises responsible third cycle supervision in which doctoral students can thrive and develop their research knowledge and skills? A literature review was conducted, and the data gathered from the literature regarding responsible third cycle supervision was analysed by means of a thematic analysis. The analysis was inspired by the notion of responsible inclusion outlined by David Mitchell. In this study, the term literature refers to research articles and regulations. The results (preliminary) show that responsible third cycle supervision is associated with a number of interplaying factors (themes). These are as follows: committed supervisors and doctoral students; a clear vision and research problem; an individual study plan; adequate resources; interaction processes and constructive feedback; creativity; cultural awareness; respect and research ethics; systematic quality work and improvement efforts; focus on overall third cycle learning goals; and focus on research presentations and publications. Thus, responsible third cycle supervision can occur if these factors are realized in practice. This literature review is of relevance to evaluators, researchers, and management in higher education, as well as third cycle supervisors.

Keywords: doctoral student, higher education, third cycle supervisors, third cycle programmes

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Authors: Clara Stella Anugerah

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This study actually is a reflection of the general election in 2014. The researcher was interested in this case as the assessment of several phenomenons that happened recently. One of them is the use of social media for the campaign. By this modern era, social media becomes closer with society. It gains the communication process, and by the time being communicating others also becomes easier than before. Furthermore, social media can minimize the cost of communication with many people as a far distance that often comes to be an obstacle of communication does not become a big problem anymore. In Indonesia, the advantages of social media were used by a political party, Gerindra, to face the election that was held on 2014. Actually Gerindra is a newly formed political party that was established in 2008. In spite of Gerindra is the new comer in the election, according to the General Election Committee’s data in Indonesia, Gerindra has the biggest budget than others to cost campaign in social media. Because of that, this research wants to look “how is the pattern of Gerindra party’s campaign to face the general election in 2014? To ask that question, the theory used for this research is campaign method based on ICT (Information Communication Technology) by Rummele. According to the rummele, Gerindra was a party that used a product of social media massively, mainly facebook and twitter. According to that observation, this research focus on campaign that had been done by Gerindra in both of those social media by the time window given by KPU (General Election Committee) on Maret 16th until April 5th, 2014. The conclusion was derived by content analysis method that was used in the methodology. In this context, that method was used while interpreting the content uploaded by Gerindra to facebook or twitter, such as picture and writing. Finally, by that method and reflecting the rummele theory, this research inferred that the patern used for Gerindra’s campaign in social media tends to be top-down. It means: Gerindra showed uncommunicative tendency in social media and only want to catch much mass without mentioned a mission and vision clearly.

Keywords: Gerindra party, political party, social media, campaign, general election on 2014

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Authors: Naim Izet Kajtazi

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Context: Frequently, the cause of raised intracranial pressure remains unresolved and rarely is related to spinal tumors, moreover less to spinal medulloblastoma without primary brain focus. Process: An 18-year-old woman had a 3-month history of headaches and impaired vision. Neurological examination revealed bilateral sixth cranial nerve palsies with bilateral papilloedema of grade III. No focal brain or spine lesion was found on imaging. Consecutive lumbar punctures showed high opening pressure and subsequent increasing protein level. The meningeal biopsy was negative. At one point, she developed an increasing headache, vomiting and back pain. Spine MRI showed diffuse nodular leptomeningeal enhancement with the largest nodule at T6–T7. Malignant cells were detected in cerebrospinal fluid. She underwent laminectomy with excisional biopsy, and pathology showed medulloblastoma WHO grade IV. Outcome: She was treated with chemotherapy and craniospinal irradiation and made a good recovery. Relevance: Primary spinal leptomeningeal medulloblastoma is extremely rare, especially without primary brain focus, but may cause increased intracranial pressure, even in the early microscopic phases, and it should be considered in the differential diagnosis if conventional and aggressive treatment of idiopathic intracranial hypertension fails. We assume that arachnoiditis from tumor seeding caused increased intracranial pressure. Appropriate neurosurgical intervention and surgical biopsy are mandated if a suspicious lesion is detected. Consider proper rescreening of the whole neuroaxis in refractory cases of intracranial hypertension.

Keywords: CNS infection, IIH, headache, primary spinal leptomeningeal medulloblastoma

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Authors: Janaki Rama Raju Patchamatla, Emani Pavan Kumar

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The idea of increasing the existing train speeds and introduction of the high-speed trains in India as a part of Vision-2020 is really challenging from both economic viability and technical feasibility. More than economic viability, technical feasibility has to be thoroughly checked for safe operation and execution. Trains moving at high speeds need a well-established firm and safe track thoroughly tested against vibration effects. With increased speeds of trains, the track structure and layered soil-structure interaction have to be critically assessed for vibration and displacements. Physical establishment of track, testing and experimentation is a costly and time taking process. Software-based modelling and simulation give relatively reliable, cost-effective means of testing effects of critical parameters like sleeper design and density, properties of track and sub-grade, etc. The present paper reports the applicability of infinite elements in reducing the unrealistic stress-wave reflections from so-called soil-structure interface. The influence of the infinite elements is quantified in terms of the displacement time histories of adjoining soil and the deformation pattern in general. In addition, the railhead response histories at various locations show that the numerical model is realistic without any aberrations at the boundaries. The numerical model is quite promising in its ability to simulate the critical parameters of track design.

Keywords: high speed railway track, finite element method, Infinite elements, vibration analysis, soil-structure interface

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Authors: C. Galasso

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The ancestral relationship between humans and geographical environment has long been at the center of an interdisciplinary dialogue, which sees one of its main research nodes in the relationship between memory and places. Given its deep complexity, this symbiotic connection continues to look for a proper definition that appears increasingly negotiated by different disciplines. Numerous fields of knowledge are involved, from anthropology to semiotics of space, from photography to architecture, up to subjects traditionally far from these reasonings. This is the case of Design of Communication, a young discipline, now confident in itself and its objectives, aimed at finding and investigating original forms of visualization and representation, between sedimented knowledge and new technologies. In particular, Design of Communication for the Territory offers an alternative perspective to the debate, encouraging the reactivation and reconstruction of the memory of places. Recognizing mnemotopes as a cultural object of vertical interpretation of the memory-place relationship, design can become a real mediator of the territorial fixation of memories, making them increasingly accessible and perceptible, contributing to build a topography of memory. According to a mnemotopic vision, Communication Design can support the passage from a memory in which the observer participates only as an individual to a collective form of memory. A mnemotopic form of Communication Design can, through geolocation and content map-based systems, make chronology a topography rooted in the territory and practicable; it can be useful to understand how the perception of the memory of places changes over time, considering how to insert them in the contemporary world. Mnemotopes can be materialized in different format of translation, editing and narration and then involved in complex systems of communication. The memory of places, therefore, if stabilized by the tools offered by Communication Design, can make visible ruins and territorial stratifications, illuminating them with new communicative interests that can be shared and participated.

Keywords: memory of places, design of communication, territory, mnemotope, topography of memory

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Authors: Siham Rahoui, Amr Mahfouz, Amr Arisha

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In a highly competitive environment characterised by uncertainty and disruptions, such as the recent COVID-19 outbreak, supply chains (SC) face the challenge of maintaining their cost at minimum levels while continuing to provide customers with high-quality products and services. More importantly, businesses in such an economic context strive to maintain survival by keeping the cost of undertaken activities (such as logistics) low and in-house. To do so, managers need to understand the costs associated with different products and services in order to have a clear vision of the SC performance, maintain profitability levels, and make strategic decisions. In this context, SC literature explored different costing models that sought to determine the costs of undertaking supply chain-related activities. While some cost accounting techniques have been extensively explored in the SC context, more contributions are needed to explore the potential of time driven activity-based costing (TDABC). More specifically, more applications are needed in the manufacturing context of the SC, where the debate is ongoing. The aim of the study is to assess the capability of the technique to assess the operational performance of the logistics function. Through a case study methodology applied to a manufacturing company operating in the automotive industry, TDABC evaluates the efficiency of the current configuration and its logistics processes. The study shows that monitoring the process efficiency and cost efficiency leads to strategic decisions that contributed to improve the overall efficiency of the logistics processes.

Keywords: efficiency, operational performance, supply chain costing, time driven activity based costing

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Authors: Jingjue Bao, Ye Li, Yujie Qi

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The explosive growth of ride-hailing has reshaped residents' travel behavior and plays a crucial role in urban mobility within the built environment. Contributing to the research of the spatial variation of ride-hailing demand and its relationship to the built environment and socioeconomic factors, this study utilizes multi-source data from Haikou, China, to construct a Multi-scale Geographically Weighted Regression model (MGWR), considering spatial scale heterogeneity. The regression results showed that MGWR model was demonstrated superior interpretability and reliability with an improvement of 3.4% on R2 and from 4853 to 4787 on AIC, compared with Geographically Weighted Regression model (GWR). Furthermore, to precisely identify the surrounding environment of sampling point, DeepLabv3+ model is employed to segment street-level images. Features extracted from these images are incorporated as variables in the regression model, further enhancing its rationality and accuracy by 7.78% improvement on R2 compared with the MGWR model only considered region-level variables. By integrating multi-scale geospatial data and utilizing advanced computer vision techniques, this study provides a comprehensive understanding of the spatial dynamics between ride-hailing demand and the urban built environment. The insights gained from this research are expected to contribute significantly to urban transportation planning and policy making, as well as ride-hailing platforms, facilitating the development of more efficient and effective mobility solutions in modern cities.

Keywords: travel behavior, ride-hailing, spatial relationship, built environment, street-level image

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Authors: Mary Cheptanui Sambu

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Teaching practice is an integral component of students who are training to be teachers, as it provides them with an opportunity to gain experience in an actual teaching and learning environment. This study explored the experiences of trainee teachers from a local university in Kenya, undergoing a three-month teaching practice in Special Secondary schools in the country. The main aim of the study was to understand the trainees’ experiences, their expectations, and the realities encountered during the teaching practice period. The study focused on special secondary schools for learners with hearing impairment. A descriptive survey design was employed and a sample size of forty-four respondents from special secondary schools for learners with hearing impairment was purposively selected. A questionnaire was administered to the respondents and the data obtained analysed using the Statistical Package for the Social Sciences (SPSS). Preliminary analysis shows that challenges facing special secondary schools include inadequate teaching and learning facilities and resources, low academic performance among learners with hearing impairment, an overloaded curriculum and inadequate number of teachers for the learners. The study findings suggest that the Kenyan government should invest more in the education of special needs children, particularly focusing on increasing the number of trained teachers. In addition, the education curriculum offered in special secondary schools should be tailored towards the needs and interest of learners. These research findings will be useful to policymakers and curriculum developers, and will provide information that can be used to enhance the education of learners with hearing impairment; this will lead to improved academic performance, consequently resulting in better transitions and the realization of Vision 2030.

Keywords: hearing impairment, special secondary schools, trainee, teaching practice

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Authors: Xiaoyuan Suo

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3D object reconstruction is a broad research area within the computer vision field involving many stages and still open problems. One of the existing challenges in this field lies with micromotion, such as the facial expressions on the appearance of the human or animal face. Similar literatures in this field focuses on 3D reconstruction in stable conditions such as an existing image or photos taken in a rather static environment, while the purpose of this work is to discuss a flexible scan system using multiple cameras that can correctly reconstruct 3D stable and moving objects -- human face with expression in particular. Further, a mathematical model is proposed at the end of this literature to automate the 3D object reconstruction process. The reconstruction process takes several stages. Firstly, a set of simple 2D lines would be projected onto the object and hence a set of uneven curvy lines can be obtained, which represents the 3D numerical data of the surface. The lines and their shapes will help to identify object’s 3D construction in pixels. With the two-recorded angles and their distance from the camera, a simple mathematical calculation would give the resulting coordinate of each projected line in an absolute 3D space. This proposed research will benefit many practical areas, including but not limited to biometric identification, authentications, cybersecurity, preservation of cultural heritage, drama acting especially those with rapid and complex facial gestures, and many others. Specifically, this will (I) provide a brief survey of comparable techniques existing in this field. (II) discuss a set of specialized methodologies or algorithms for effective reconstruction of 3D objects. (III)implement, and testing the developed methodologies. (IV) verify findings with data collected from experiments. (V) conclude with lessons learned and final thoughts.

Keywords: 3D photogrammetry, 3D object reconstruction, facial expression recognition, facial recognition

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Authors: Hu Zhenxing, Gao Jianxin

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Stereo-based digital image correlation (also referred to as three-dimensional (3D) digital image correlation (DIC)) is a technique for both 3D shape and surface deformation measurement of a component, which has found increasing applications in academia and industries. The accuracy of the reconstructed coordinate depends on many factors such as configuration of the setup, stereo-matching, distortion, etc. Most of these factors have been investigated in literature. For instance, the configuration of a binocular vision system determines the systematic errors. The stereo-matching errors depend on the speckle quality and the matching algorithm, which can only be controlled in a limited range. And the distortion is non-linear particularly in a complex imaging acquisition system. Thus, the distortion correction should be carefully considered. Moreover, the distortion function is difficult to formulate in a complex imaging acquisition system using conventional models in such cases where microscopes and other complex lenses are involved. The errors of the distortion correction will propagate to the reconstructed 3D coordinates. To address the problem, an accurate mapping method based on 2D B-spline functions is proposed in this study. The mapping functions are used to convert the distorted coordinates into an ideal plane without distortions. This approach is suitable for any image acquisition distortion models. It is used as a prior process to convert the distorted coordinate to an ideal position, which enables the camera to conform to the pin-hole model. A procedure of this approach is presented for stereo-based DIC. Using 3D speckle image generation, numerical simulations were carried out to compare the accuracy of both the conventional method and the proposed approach.

Keywords: distortion, stereo-based digital image correlation, b-spline, 3D, 2D

Procedia PDF Downloads 476

Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

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The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

Procedia PDF Downloads 338

Authors: Tania Breton, Dorina Simeonov, Shauna MacEachern

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Ontario’s 10 Year Mental Health and Addictions Strategy has included the establishment of 18 Service Collaborative across the province; cross-sector tables in a specific region coming together to explore mental health and addiction system needs and adopting an intervention to address that need. The process is community led and supported by implementation teams from the Centre for Addiction and Mental Health (CAMH), using the framework of implementation science (IS) to enable evidence-based and sustained change. These justice initiatives are focused on the intersection of the justice system and the mental health and addiction systems. In this presentation, we will share the learnings, achievements and challenges of implementing innovative practices to the mental health and addictions needs of Ontarians within the justice system. Specifically, we will focus on the key points across the justice system - from early intervention and trauma-informed, culturally appropriate services to post-sentence support and community reintegration. Our approach to this work involves external implementation support from the CAMH team including coaching, knowledge exchange, evaluation, Aboriginal engagement and health equity expertise. Agencies supported the implementation of tools and processes which changed practice at the local level. These practices are being scaled up across Ontario and community agencies have come together in an unprecedented collaboration and there is a shared vision of the issues overlapping between the mental health, addictions and justice systems. Working with ministry partners has allowed space for innovation and created an environment where better approaches can be nurtured and spread.

Keywords: implementation, innovation, early identification, mental health and addictions, prevention, systems

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Authors: Przemyslaw Nogly, Tobias Weinert, Daniel James, Sergio Carbajo, Dmitry Ozerov, Antonia Furrer, Dardan Gashi, Veniamin Borin, Petr Skopintsev, Kathrin Jaeger, Karol Nass, Petra Bath, Robert Bosman, Jason Koglin, Matthew Seaberg, Thomas Lane, Demet Kekilli, Steffen Brünle, Tomoyuki Tanaka, Wenting Wu, Christopher Milne, Thomas A. White, Anton Barty, Uwe Weierstall, Valerie Panneels, Eriko Nango, So Iwata, Mark Hunter, Igor Schapiro, Gebhard Schertler, Richard Neutze, Jörg Standfuss

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Ultrafast isomerization of retinal is the primary step in a range of photoresponsive biological functions including vision in humans and ion-transport across bacterial membranes. We studied the sub-picosecond structural dynamics of retinal isomerization in the light-driven proton pump bacteriorhodopsin using an X-ray laser. Twenty snapshots with near-atomic spatial and temporal resolution in the femtosecond regime show how the excited all-trans retinal samples conformational states within the protein binding pocket prior to passing through a highly-twisted geometry and emerging in the 13-cis conformation. The aspartic acid residues and functional water molecules in proximity of the retinal Schiff base respond collectively to formation and decay of the initial excited state and retinal isomerization. These observations reveal how the protein scaffold guides this remarkably efficient photochemical reaction.

Keywords: bacteriorhodopsin, free-electron laser, retinal isomerization mechanism, time-resolved crystallography

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Authors: Niina Jallinoja, Anu Moisio

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Focus on adult learning is vital to overcome economic challenges as well as to respond to the demand for new competencies and sustained productivity in the digitalized world economy. Employees of all ages must be able to carry on continuous professional development to remain competitive in the labor market. According to EU policies, countries should offer more flexible opportunities for adult learners who study online and in so-called ‘second chance’ qualification programmes. Traditionally, adult education in Finland has comprised of not only liberal adult education but also the government funding to study for Bachelor, Master's, and Ph.D. degrees in Finnish Universities and Universities of Applied Sciences (UAS). From the beginning of 2021, public funding is allocated not only to degrees but also to courses to achieve new competencies for adult learners in Finland. Consequently, there will be degree students (often younger of age) and adult learners studying in the same evening, online and blended courses. The question is thus: How are combined studies meeting the different needs of degree students and adult learners? Haaga-Helia University of Applied Sciences (UAS), located in the metropolitan area of Finland, is taking up the challenge of continuous learning for adult learners. Haaga-Helia has been reforming the bachelor level education and respective shorter courses from 2019 in the biggest project in its history. By the end of 2023, Haaga-Helia will have a flexible, modular curriculum for the bachelor's degrees of hospitality management, business administration, business information technology, journalism and sports management. Building on the shared key competencies, degree students will have the possibility to build individual study paths more flexibly, thanks to the new modular structure of the curriculum. They will be able to choose courses across all degrees, and thus, build their own unique competence combinations. All modules can also be offered as separate courses or learning paths to non-degree students, both publicly funded and as commercial services for employers. Consequently, there will be shared course implementations for degree studies and adult learners with various competence requirements. The newly designed courses are piloted in parallel of the designing of the curriculum in Haaga-Helia during 2020 and 2021. Semi-structured online surveys are composed among the participants for the key competence courses. The focus of the research is to understand how students in the bachelor programme and adult learners from Open UAE perceive the learning experience in such a diverse learning group. A comparison is also executed between learning methods of in-site teaching, online implementation, blended learning and virtual self-learning courses to understand how the pedagogy is meeting the learning objectives of these two different groups. The new flexible curricula and the study modules are to be designed to fill the most important competence gaps that exist in the Finnish labor markets. The new curriculum will be dynamic and constantly evolving over time according to the future competence needs in the labor market. This type of approach requires constant dialogue between Haaga-Helia and workplaces during and after designing of the shared curriculum.

Keywords: ccompetence development, continuous learning, curriculum, higher education

Procedia PDF Downloads 106

Authors: Kamal KC, Zhendong Yin, Dasen Li, Zhilu Wu

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Intra-plant disease classification based on leaf images is a challenging computer vision task due to similarities in texture, color, and shape of leaves with a slight variation of leaf spot; and external environmental changes such as lighting and background noises. Deep convolutional neural network (DCNN) has proven to be an effective tool for binary classification. In this paper, two methods for binary classification of diseased plant leaves using DCNN are presented; model created from scratch and transfer learning. Our main contribution is a thorough evaluation of 4 networks created from scratch and transfer learning of 5 pre-trained models. Training and testing of these models were performed on a plant leaf images dataset belonging to 16 distinct classes, containing a total of 22,265 images from 8 different plants, consisting of a pair of healthy and diseased leaves. We introduce a deep CNN model, Optimized MobileNet. This model with depthwise separable CNN as a building block attained an average test accuracy of 99.77%. We also present a fine-tuning method by introducing the concept of a convolutional block, which is a collection of different deep neural layers. Fine-tuned models proved to be efficient in terms of accuracy and computational cost. Fine-tuned MobileNet achieved an average test accuracy of 99.89% on 8 pairs of [healthy, diseased] leaf ImageSet.

Keywords: deep convolution neural network, depthwise separable convolution, fine-grained classification, MobileNet, plant disease, transfer learning

Procedia PDF Downloads 159

Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: human machine interface, industrial internet of things, internet of things, optical character recognition, video analytics

Procedia PDF Downloads 86