Search results for: vision zero

Authors: Simiao Ren, En Wei

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Drowning is a significant safety issue worldwide, and a robust computer vision-based alert system can easily prevent such tragedies in swimming pools. However, due to domain shift caused by the visual gap (potentially due to lighting, indoor scene change, pool floor color etc.) between the training swimming pool and the test swimming pool, the robustness of such algorithms has been questionable. The annotation cost for labeling each new swimming pool is too expensive for mass adoption of such a technique. To address this issue, we propose a domain-aware data augmentation pipeline based on Gaussian Poisson Generative Adversarial Network (GP-GAN). Combined with YOLOv8, we demonstrate that such a domain adaptation technique can significantly improve the model performance (from 0.24 mAP to 0.82 mAP) on new test scenes. As the augmentation method only require background imagery from the new domain (no annotation needed), we believe this is a promising, practical route for preventing swimming pool drowning.

Keywords: computer vision, deep learning, YOLOv8, detection, swimming pool, drowning, domain adaptation, generative adversarial network, GAN, GP-GAN

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Authors: Kashika P. H.

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

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

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Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

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Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

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Authors: Faisal Mahroogi, Mahmoud Bady, Ahmed Alsisi

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The Saudi Vision 2030 program is a government initiative aimed at increasing economic, social, and cultural diversification. Dedicated to clean energy, the Kingdom has been working on solutions such as the circular carbon economy (CCE) and diversifying its energy mix to address energy and climate challenges. With a goal of a Net Zero future by 2060, Saudi Arabia's Vision 2030 emphasizes sustainability. Vision 2030 approa ches today's energy and climate challenges responsibly and creatively as a model for a sustainable future. As per the Ambitions of the National Environment Strategy of the Saudi Ministry of Environment, Agriculture, and Water (MEWA), raising environmental compliance across all sectors and reducing pollution and adverse environmental impacts are critical focus areas.Therefore, the present paper introduces an experimental investigation of a diesel engine's performance and exhaust emissions operating with waste cooking oil (WCO) as a diesel additive. The engine type used is a one-cylinder natural-aspirated constant-speed direct-injection diesel engine. The main variables of the study were the load and the fuel type. The engine performance and emission characteristics were investigated when fueled with three blends. The first blend (D70B10W10DD10) is composed of 70% diesel, 10% butanol,10% WCO, and 10% diethyl ether. The second blend (D60B10W20DD10) is composed of 60% diesel, 10% butanol, 20% WCO, and 10% diethyl ether. The third blend (D50B10W30DD10) comprises 50% diesel, 10% butanol, 30% WCO, and 10% diethyl ether. The study results show that the engine emissions of carbon monoxide (CO) and nitrogen oxides (NOX) vary considerably with the fuel composition and applied load. Concerning engine performance, the cylinder pressure is sensitive to the load and fuel type variation.

Keywords: ICE, waste cooking oil, bio additives, butanol, combustion and emission characteristics

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Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone

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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.

Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder

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Authors: Omer Cahana, Maya Herman, Ofer Levi

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Magnetic resonance imaging (MRI) is a long medical scan that stems from a long acquisition time. This length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach, such as compress sensing (CS) or parallel imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. In order to achieve that, two properties have to exist: i) the signal must be sparse under a known transform domain, ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm needs to be applied to recover the signal. While the rapid advance in the deep learning (DL) field, which has demonstrated tremendous successes in various computer vision task’s, the field of MRI reconstruction is still in an early stage. In this paper, we present an extension of the state-of-the-art model in MRI reconstruction -VarNet. We utilize VarNet by using dilated convolution in different scales, which extends the receptive field to capture more contextual information. Moreover, we simplified the sensitivity map estimation (SME), for it holds many unnecessary layers for this task. Those improvements have shown significant decreases in computation costs as well as higher accuracy.

Keywords: MRI, deep learning, variational network, computer vision, compress sensing

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Authors: Obulesh Avuku, Satwik Sunnam, Sri Charan Mohan Janthuka, Keerthi Yalamaddi

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In the United States alone, there are over 1.5 million spine fractures per year, resulting in about 17,730 spinal cord injuries. The cervical spine is where fractures in the spine most frequently occur. The prevalence of spinal fractures in the elderly has increased, and in this population, fractures may be harder to see on imaging because of coexisting degenerative illness and osteoporosis. Nowadays, computed tomography (CT) is almost completely used instead of radiography for the imaging diagnosis of adult spine fractures (x-rays). To stop neurologic degeneration and paralysis following trauma, it is vital to trace any vertebral fractures at the earliest. Many approaches have been proposed for the classification of the cervical spine [2d models]. We are here in this paper trying to break the bounds and use the vision transformers, a State-Of-The-Art- Model in image classification, by making minimal changes possible to the architecture of ViT and making it 3D-enabled architecture and this is evaluated using a weighted multi-label logarithmic loss. We have taken this problem statement from a previously held Kaggle competition, i.e., RSNA 2022 Cervical Spine Fracture Detection.

Keywords: cervical spine, spinal fractures, osteoporosis, computed tomography, 2d-models, ViT, multi-label logarithmic loss, Kaggle, public score, private score

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Authors: Sathyamangalam Rangasamy Guru Prasath

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Due to the increasing homogeneity in product offerings, the attendant services provided are emerging as a key differentiator in the mind of the consumers. Services marketing are a sub field of marketing which covers the marketing of both goods and services. Service marketing differs from product marketing due to the face that services are intangible and typically require personal interaction with the customer. Relationships are a key factor when it comes to the marketing of services. The role of interpersonal relationships distinguishes service and product marketing in strategic vision and organizational considerations. This paper explores some of the trends in service marketing as they relate to strategic vision, operational and organizational changes, and marketing tactics. The presence of the customer in the service facility means that capacity management becomes an important driver of the firm’s profitability service marketing is a process from the organization’s point of view, but an experience from the customer’s perspective. The quality of the experience is a function of the careful design of customer service processes, adoption of standardized procedures, rigorous management of service quality, high standards of training and automation. Services marketing helps to ensure that these processes are designed from the customer’s perspective. Services marketing includes customer loyalty, managing relationships, complaint handling, improving service quality and productivity of service operations, and how to become a service leader in your industry.

Keywords: customer perspective, product marketing, service marketing, rigorous management

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Authors: Shreyansh Jain Jeetmal, Shobith P. Chadaga, Shreyas H. Srinivas

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Internet of Things (IoT) is seen as the next major step in the ongoing revolution in the Information Age. It is predicted that in the near future billions of embedded devices will be communicating with each other to perform a plethora of tasks with or without human intervention. One of the major ongoing hotbed of research activity in IoT is Human Computer Interaction (HCI). HCI is used to facilitate communication between an intelligent system and a user. An intelligent system typically comprises of a system consisting of various sensors, actuators and embedded controllers which communicate with each other to monitor data collected from the environment. Communication by the user to the system is typically done using voice. One of the major ongoing applications of HCI is in home automation as a personal assistant. The prime objective of our project is to implement a use case of HCI for home automation. Our system is designed to detect and recognize the users and personalize the appliances in the house according to their individual preferences. Our HCI system is also capable of speaking with the user when certain commands are spoken such as searching on the web for information and controlling appliances. Our system can also monitor the environment in the house such as air quality and gas leakages for added safety.

Keywords: human computer interaction, internet of things, computer vision, sensor networks, speech to text, text to speech, android

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Authors: Aminul Haque, Aminul Islam, Prabal Kumar Chowdhury

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One of the world’s most pressing issues right now is the lack of a competent waste management system, particularly in emerging and underdeveloped countries. Recycling solid waste, which comprises numerous dangerous non-biodegradable sub-stances like glass, metals, plastics, etc, is the most essential step in reducing waste-related issues in the environment. Typically, collected waste includes all types of waste that must be thoroughly sorted to be recycled efficiently. Most countries use manual waste sorting techniques, which are efficient. Nevertheless, the waste sorting process by human beings is not safe as there is always a risk of exposing themselves to toxic wastes, which could be serious for their health. Our thesis presents a Deep Learning technique based on computer vision for automatically identifying waste. To construct the model, we used Convolutional Neural Networks, real-time object detection systems, such as YOLOv5 and YOLOv7, as well as several transfers learning-based architectures, including VGG16, MobileNet, Inception-Resnet-v2. The model is trained on numerous images for each type of waste to ensure no overfitting and greater accuracy. The highest accuracy we achieved for our waste detection model YOLOv5x, is 93.7%.

Keywords: deep learning, object detection, YOLOv7, image processing, computer vision

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Authors: T. Qasim, M. Obeidat, S. Al-Sharairi

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The objective of this study is to investigate the effect of the excessive use of smartphones. Smartphones have enormous effects on the human body in that some musculoskeletal disorders (MSDs) and health problems might evolve. These days, there is a wide use of the smartphones among all age groups of society, thus, the focus on smartphone effects on human behavior and health, especially on the young and elderly people, becomes a crucial issue. This study was conducted in Jordan on smartphone users for different genders and ages, by conducting a survey to collect data related to the symptoms and MSDs that are resulted from the excessive use of smartphones. A total of 357 responses were used in the analysis. The main related symptoms were numbness, fingers pain, and pain in arm, all linked to age and gender for comparative reasons. A statistical analysis was performed to find the effects of extensive usage of a smartphone for long periods of time on the human body. Results show that the significant variables were the vision problems and the time spent when using the smartphone that cause vision problems. Other variables including age of user and ear problems due to the use of the headsets were found to be a border line significant.

Keywords: smart phone, age group, musculoskeletal disorders (MSDs), health problems

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Authors: Arne Hitzmann, Philipp Wentscher, Alexander Gabel, Reinhard Gerndt

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Autonomous mobile robots can be found in a wide field of applications. Their types range from household robots over workshop robots to autonomous cars and many more. All of them undergo a number of testing steps during development, production and maintenance. This paper describes an approach to improve testing of robot behavior. It was inspired by the RoboCup @work competition that itself reflects a robotics benchmark for industrial robotics. There, scaled down versions of mobile industrial robots have to navigate through a workshop-like environment or operation area and have to perform tasks of manipulating and transporting work pieces. This paper will introduce an approach of automated vision-based testing of the behavior of the so called youBot robot, which is the most widely used robot platform in the RoboCup @work competition. The proposed system allows automated testing of multiple tries of the robot to perform a specific missions and it allows for the flexibility of the robot, e.g. selecting different paths between two tasks within a mission. The approach is based on a multi-camera setup using, off the shelf cameras and optical markers. It has been applied for test-driven development (TDD) and maintenance-like verification of the robot behavior and performance.

Keywords: supervisory control, testing, markers, mono vision, automation

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Authors: Ming-Yen Chang, Sheng-Hung Ke

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This research focuses on the development of a speed bump identification system for real-time control of adjustable shock absorbers in vehicular suspension systems. The study initially involved the collection of images of various speed bumps, and rubber speed bump profiles found on roadways. These images were utilized for training and recognition purposes through the deep learning object detection algorithm YOLOv5. Subsequently, the trained speed bump identification program was integrated with an in-vehicle camera system for live image capture during driving. These images were instantly transmitted to a computer for processing. Using the principles of monocular vision ranging, the distance between the vehicle and an approaching speed bump was determined. The appropriate control distance was established through both practical vehicle measurements and theoretical calculations. Collaboratively, with the electronically adjustable shock absorbers equipped in the vehicle, a shock absorber control system was devised to dynamically adapt the damping force just prior to encountering a speed bump. This system effectively mitigates passenger discomfort and enhances ride quality.

Keywords: adjustable shock absorbers, image recognition, monocular vision ranging, ride

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Authors: Harshan Baskar, Anirudh S. Chakravarthy, Prateek Garg, Divyam Goel, Abhijith S. Raj, Kshitij Kumar, Lakshya, Ravichandra Parvatham, V. Sushant, Bijay Kumar Rout

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In this paper, we introduce a new computer vision task called nighttime dehaze-enhancement. This task aims to jointly perform dehazing and lightness enhancement. Our task fundamentally differs from nighttime dehazing – our goal is to jointly dehaze and enhance scenes, while nighttime dehazing aims to dehaze scenes under a nighttime setting. In order to facilitate further research on this task, we release a new benchmark dataset called Reside-β Night dataset, consisting of 4122 nighttime hazed images from 2061 scenes and 2061 ground truth images. Moreover, we also propose a new network called NDENet (Nighttime Dehaze-Enhancement Network), which jointly performs dehazing and low-light enhancement in an end-to-end manner. We evaluate our method on the proposed benchmark and achieve SSIM of 0.8962 and PSNR of 26.25. We also compare our network with other baseline networks on our benchmark to demonstrate the effectiveness of our approach. We believe that nighttime dehaze-enhancement is an essential task, particularly for autonomous navigation applications, and we hope that our work will open up new frontiers in research. Our dataset and code will be made publicly available upon acceptance of our paper.

Keywords: dehazing, image enhancement, nighttime, computer vision

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Authors: Wolfgang Haupt

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When considering the future city one repeatedly comes across two sometimes sparsely differentiated terms: Sustainable and smart. ‘A European Strategy for Smart, Sustainable, and Inclusive Growth’, this is how the European Commission named its current growth strategy. Thus, Europe should become smarter and more sustainable. Both, the smart and the sustainable city represent a positive vision of urban development as well as a subject area for contemporary and future urban policies. However, more clarity on what is actually behind these terminologies is required. The paper analyses how the terms are defined academically and how this academic understanding is represented in the funding mechanisms of European urban policies. The theoretical framework is mainly based on sources such as journal articles and policy reports. It became clear that despite some similarities, such as the broad field of work or the tendency to operationalize the terms by defining sub-categories, both ideas are distinctly different in terms of the development history, the main driving forces behind and the theoretical scope. Moreover, the significantly more comprehensively defined term sustainability has found its way into the centre of European regional funding policies. On the contrary, the smart city vision still lacks terminological and content-related clarity and as a consequence, the corresponding European funding landscape is more small-scaled and less customized.

Keywords: European spatial policy, European union, smart city, urban sustainable development

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Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Ritesh Verma, Manisha Rathi, Chand Singh Dhull, Sumit Sachdeva, Jitender Phogat

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A Rathke's cleft cyst is a benign growth found on the pituitary gland in the brain, specifically a fluid-filled cyst in the posterior portion of the anterior pituitary gland. It occurs when the Rathke's pouch does not develop properly and ranges in size from 2 to 40mm in diameter. A 38-year-old male presented to the outpatient department with loss of vision in the inferior quadrant of the left eye since 15 days. Visual acuity was 6/6 in the right eye and 6/9 in the left eye. Visual field analysis by HFA-24-2 revealed an inferior field defect extending to the supero-temporal quadrant in the left eye. MRI brain and orbit was advised to the patient and it revealed a well defined cystic pituitary adenoma indenting left optic nerve near optic chiasm consistent with the diagnosis of Rathke’s cleft cyst (RCC). The patient was referred to neurosurgery department for further management. Symptoms vary greatly between individuals having RCCs. RCCs can be non-functioning, functioning, or both. Besides headaches, neurocognitive deficits are almost always present but have a high rate of immediate reversal if the cyst is properly treated or drained.

Keywords: pituitary tumors, rathke’s cleft cyst, visual field defects, vision loss

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Authors: Cheng Fang, Lingwei Quan, Cunyue Lu

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Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks.

Keywords: computer vision, pose estimation, pose tracking, Siamese network

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Authors: Emily S. M. Chow

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The word ‘utopia’ was coined by Thomas More in Utopia (1516). Its Greek roots ‘ou’ means ‘not’ and ‘topos’ means ‘place.’ In other words, it literally refers to ‘no-place.’ However, the possibility of having an alternative and better future society has always been appealing. In fact, at the core of every utopianism is the search for a future alternative state with the anticipation of a better life. Nonetheless, the practicalities of such ideas have never ceased to be questioned. At times, building a utopia presents itself as a divisive act. In addition to the violence that must be employed to sweep away the old regime in order to make space for the new, all utopias carry within them the potential for bringing catastrophic consequences to human life. After all, every utopia seeks to remodel the individual in a very particular way for the benefit of the masses. In this sense, utopian thinking has the potential both to create and destroy the future. While writing during a traumatic transitional period in Zimbabwe’s history, Dambudzo Marechera witnessed an age of upheavals in which different parties battled for power over Zimbabwe. Being aware of the fact that all institutionalized narratives, be they originated from the governance of the UK, Ian Smith’s white minority regime or Zimbabwe’s revolutionary parties, revealed themselves to be nothing more than fiction, Marechera realized the impossibility of determining reality absolutely. As such, this thesis concerns the writing of the Zimbabwean maverick, Dambudzo Marechera. It argues that Marechera writes a unique vision of utopia. In short, for Marechera utopia is not a static entity but a moment of perpetual change. He rethinks utopia in the sense that he phrases it as an event that ceaselessly contests institutionalized and naturalized narratives of a post-colonial self and its relationship to society. Marechera writes towards a vision of an alternative future of the country. Yet, it is a vision that does not constitute a fully rounded sense of utopia. Being cautious about the world and the operation of power upon the people, rather than imposing his own utopian ideals, Marechera chooses to instead peeling away the narrative constitution of the self in relation to society in order to turn towards a truly radical utopian thinking that empowers the individual.

Keywords: African literature, Marechera, post-colonial literature, utopian studies

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Authors: Nayden Chivarov, Denis Chikurtev, Kaloyan Yovchev, Nedko Shivarov

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This paper represents methods for improving the efficiency and precision of service mobile robot. This robot is used for increasing the quality of life of elderly and disabled people. The key concept of the proposed Intelligent Service Mobile Robot is its easier adaptability to achieve services for a wide range of Elderly or Disabled Person’s needs, by performing different tasks for supporting Elderly or Disabled Persons care. We developed robot autonomous navigation and computer vision systems in order to recognize different objects and bring them to the people. Web based user interface is developed to provide easy access and tele-control of the robot by any device through the internet. In this study algorithms for object recognition and localization are proposed for providing successful object recognition and accuracy in the positioning. Different methods for sending movement commands to the mobile robot system are proposed and evaluated. After executing some experiments to show the results of the research, we can summarize that these systems and algorithms provide good control of the service mobile robot and it will be more useful to help the elderly and disabled persons.

Keywords: service robot, mobile robot, autonomous navigation, computer vision, web user interface, ROS

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Authors: Morteza Khorrami

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The idea of final triumph of peace and justice on evil force, conflict and global spread of the religious faith, the full deployment of human values, constitute a utopia and the ideal society is discussed by many of religions. Thus, mankind has always been waiting for a savior and has received good tidings for coming of Great Savior at the end of Time. Of course, various persons were introduced as the Promised Saviors by different religions, but all of the religions share in this fact that the future of humanity is very bright and promising and the future will belong to the righteous and justice. In this article which is written with a descriptive and analytic method, the author tries to show the vision of global justice at the end of time. The opinion of various religions such as Judaism, Christianity, Zoroastrianism, Islam and even idolatry about the great savior as well as the justice status in his era in the world will be discussed. Also the viewpoint of Muslims and specially Shiites, which is explained clearly in their scripts, will be depicted. Current human responsibility towards this golden era will be discussed, too. Based on paper findings, religious doctrine promises that a heaven person and sacred character will come as a reformer of the world. In his era, humanity will be saved from tyranny, oppression and inequality, and the earth will be filled with peace, security, justice, and equity. Moreover promoting justice, truth and spreading religion in the world, economic, scientific, political and moral development will be happened.

Keywords: future of humanity, global justice, islam, religions

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Authors: Ma. Eliza Jijeth V. dela Cruz

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Technology is a recent prodigy in people’s everyday life that has taken off. It infiltrated almost every aspect of one’s lives, changing how people work, how people learn and how people perceive things. Academic Institutions, just like other organizations, have deeply modified its strategies to integrate technology into the institutional vision and corporate strategy that has never been greater. Information and Communications Technology (ICT) continues to be recognized as a major factor in organizations realizing its aims and objectives. Consequently, ICT has an important role in the mobilization of an academic institution’s strategy to support the delivery of operational, strategic or transformational objectives. This ICT strategy should align the institution with the radical changes of the ICT world through the use of Enterprise Architecture (EA). Hence, EA’s objective is to optimize the islands of legacy processes to be integrated that is receptive to change and supportive of the delivery of the strategy. In this paper, the focus is to explore the motivational antecedents during the adoption of EA in a Higher Education Institution in the Philippines for its ICT strategic plan. The seven antecedents (viewpoint, stakeholders, human traits, vision, revolutionary innovation, techniques and change components) provide understanding into EA adoption and the antecedents that influences the process of EA adoption.

Keywords: Enterprise Architecture, Adoption, Antecedents, Higher Educational Institutions

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Authors: Arif Budiman

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Any organization or company that wishes to achieve vision, mission, and goals of the organization is required to implement a performance management system or known as the Performance Management System (PMS) in every part of the whole organization. PMS is a tool to help visualize the direction and work program of the organization to achieve the goal. The challenge is PMS should not stop merely as a visualization tool to achieve the vision and mission of the organization, but PMS should also be able to create a high-performance culture that is inherent in each individual of the organization. Establishment of a culture within an organization requires the support of top leaders and also requires a system or governance that encourages every individual in the organization to be involved in any work program of the organization. Keywords of creating a high-performance culture are the formation of communication pattern involving the whole individual, either vertically or horizontally, and performed consistently and persistently by all individuals in each line of the organization. PT Pertamina (Persero) as the state-owned national energy company holds a system to internalize the culture of high performance through a system called Performance Management System Cycle (PMS Cycle). This system has 7 stages of the cycle, those are: (1) defining vision, mission and strategic plan of the company, (2) defining key performance indicator of each line and the individual (‘expectation setting conversation’), (3) defining performance target and performance agreement, (4) monitoring performance on a monthly regular basis (‘pulse check’), (5) implementing performance dialogue between leaders and staffs periodically every 3 months (‘performance dialogue’), (6) defining rewards and consequences based on the achievement of the performance of each line and the individual, and (7) calculating the final performance value achieved by each line and individual from one period of the current year. Perform PMS is a continual communication running throughout the year, that is why any three performance discussion that should be performed, include expectation setting conversations, pulse check and performance dialogue. In addition, another significant point and necessary undertaken to complete the assessment of individual performance assessment is soft competencies through 360-degree assessment by leaders, staffs, and peers.

Keywords: 360-degree assessment, expectation setting conversation, performance management system cycle, performance dialogue, pulse check

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Authors: Dante Jose R. Amisola, Glenford M. Prospero

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'Driving What’s Next' is a strong campaign of the new administration of De La Salle Lipa in promoting social innovation in quality education. The new leadership directs social innovation in quality education in the institutional directions and initiatives to address real-world challenges with real-world solutions. This research under study aims to qualify the commitment of the institution to extend the Lasallian quality human and Christian education to all, as expressed in the Institution’s new mission-vision statement. The Classic Grounded Theory methodology is employed in the process of generating concepts in reference to the documents, a series of meetings, focus group discussions and other related activities that account for the conceptualization and formulation of the new mission-vision along with the new education innovation framework. Notably, Driving What’s Next is the emergent theory that encapsulates the commitment of giving quality human and Christian education to all. It directs the new leadership in driving social innovation in quality education initiatives. Correspondingly, Driving What’s Next is continually resolved through four interrelated strategies also termed as the institution's four strategic directions, namely: (1) driving social innovation in quality education, (2) embracing our shared humanity and championing social inclusion and justice initiatives, (3) creating sustainable futures and (4) engaging diverse stakeholders in our shared mission. Significantly, the four strategic directions capture and integrate the 17 UN sustainable development goals, making the innovative curriculum locally and globally relevant. To conclude, the main concern of the new administration and how it is continually resolved, provide meaningful and fun learning experiences and promote a new way of learning in the light of the 21^st century skills among the members of the academic community including stakeholders and extended communities at large, which are defined as: learning together and by association (collaboration), learning through engagement (communication), learning by design (creativity) and learning with social impact (critical thinking).

Keywords: DLSL four strategic directions , DLSL Lipa mission-vision, driving what's next, social innovation in quality education

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Authors: Aikaterini Tavoulari, Michael Proulx, Karin Petrini

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Objective: This study aims to explore the unique challenges faced by young individuals with vision impairment (VI) during key life transitions, utilizing a community-based participatory research (CBPR) approach to identify limitations and positive aspects of existing support systems, with a focus on accessibility and diversity. Design: The study employs a qualitative CBPR design, engaging young participants with VI through online and in-person working groups over six months, prioritizing their active involvement and diverse perspectives. Methods: Twenty-one young individuals with VI from across the UK and with different VI conditions were recruited to participate in the study via a climbing and virtual reality event and stakeholders’ support. Data collection methods included open discussions, forum exchanges, and qualitative questionnaires. The data were analyzed with NVivo using inductive thematic analysis to identify key themes and patterns related to the challenges and experiences of life transitions for this diverse population. Results: The analysis revealed barriers to accessibility, such as assumptions about what a person with VI can do, inaccessibility to material, noisy environments, and insufficient training with assistive technologies. Enablers included guidance from diverse professionals and peers, multisensory approaches (beyond tactile), and peer collaborations. This study underscores the need for developing accessible and tailored strategies together with these young people to address the specific needs of this diverse population during critical life transitions (e.g., to independent living, employment and higher education). Conclusion: Engaging and co-designing effective approaches and tools with young people with VI is key to tackling the specific accessibility barriers they encounter. These approaches should be targeted at different transitional periods of their life journey, promoting diversity and inclusion.

Keywords: vision impairement, life transitions, qualitative research, community-based participatory design, accessibility

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Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

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Authors: Melissa Lubitz

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Water scarcity is one of the crucial challenges of our time. There needs to be a focus on creating a society where people and nature flourish, regardless of climatic conditions. One of the solutions we can look to is decentralized greywater recycling. The vision is simple. Every building has its own water source being greywater from the bath, shower, sink and washing machine. By treating this in the home, you can save 25-45% of potable water use and wastewater production, a reduction in energy consumption and CO2 emissions. This reusable water is clean, and safe to be used for toilet flushing, washing machine, and outdoor irrigation. Companies like Hydraloop have been committed to the greywater recycle-ready building concept for years. This means that drinking water conservation and water reuse are included as standards in the design of all new buildings. Sustainability and renewal go hand in hand. This vision includes not only optimizing water savings and waste reduction but also forging strong partnerships that bring this ambition to life. Together with regulators, municipalities and builders, a sustainable and water-conscious future is pursued. This is an opportunity to be part of a movement that is making a difference. By pushing this initiative forward, we become part of a growing community that resists dehydration, believes in sustainability, and is committed to a living environment at the forefront of change: sustainable living, where saving water is the norm and where we shape the future together.

Keywords: greywater, wastewater treatment, water conservation, circular water society

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Authors: Artur Saraiva, Moritz von Schwedler, Emília Fernandes

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In recent years, the organic sector has increased significantly. However, with the ‘conventionalization’ of these products, it has been questioned whether these products have been losing their original vision. Accordingly, this research based on 31 phenomenological interviews with committed organic consumers in urban and rural areas of Portugal, aims to analyse how ethical motivations and ecological awareness are related to organic food consumption. The content thematic analysis highlights aspects related to society and environmental concerns. On an individual level, the importance of internal coherence, peace of mind and balance that these consumers find in the consumption of local organic products was stressed. For these consumers, local organic products consumption made for significant changes in their lives, aiding in the establishment of a green identity, and involves a certain philosophy of life. This vision of an organic lifestyle is grounded in a political and ecological perspective, beyond the usual organic definition, as a ‘post-organic era’. The paper contributes to better understand how an ideological environmental discourse allows highlighting the relationship between consumers’ environmental concerns and the politics of food, resulting in a possible transition to new sustainable consumption practices.

Keywords: organic consumption, localism, content thematic analysis, pro-environmental discourse, political consumption, Portugal

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Authors: Sibonginkosi Mazibuko

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The “adoption” of the Freedom Charter in 1955 at Kliptown south of Johannesburg, South Africa represented a desire to create a society that is based on common citizenship, and democracy. The architects of the Charter had a vision of a society that lived in peace with itself. Today, the Charter is still promoted as the best thing that ever happened to a society ravaged by racism, dispossession, oppression and exploitation – a society divided in all aspects of its life. This paper moves from the understanding that land is fundamental to all life. It interrogates the Charter’s claim on land. At a time when the colonised world sought to free themselves from the chains of colonialism and Africans throughout the continent demanded Africa for the Africans, the Freedom Charter claimed South Africa for all who lived in it. To the extent that this paper problematizes the philosophical underpinnings of the Charter, it uses the methodology of dialectic materialism to understand the theoretical basis of the Freedom Charter. The paper argues that the understanding, desire and the vision of the Freedom Charter were, as they are today, irreconcilable. To that effect and in pursuit of narrow class interests, the Charter justified land dispossession and unsustainable living conditions for the dispossessed majority. The paper then concludes that, by misrepresenting the critically fundamental land question, the Charter tried to reconcile the dispossessed with their dispossession and thus reflected coloniality and whiteness long before colonialism and settler-colonialism came to an end in South Africa.

Keywords: colonialism, contradictions, freedom charter, South Africa

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Authors: Ecem Deniz Kırkpantur, Ozge Ecmel Onur, Tuba Cimilli Ozturk, Ebru Unal Akoglu

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Moyamoya disease is a unique chronic progressive cerebrovascular disease characterized by bilateral stenosis or occlusion of the arteries around the circle of Willis with prominent arterial collateral circulation. The occurrence of Moyamoya disease is related to immune, genetic and other factors. There is no curative treatment for Moyamoya disease. Secondary prevention for patients with symptomatic Moyamoya disease is largely centered on surgical revascularization techniques. We present here a 62-year old male presented with headache and vision loss for 2 days. He was previously diagnosed with hypertension and glaucoma. On physical examination, left eye movements were restricted medially, both eyes were hyperemic and their movements were painful. Other neurological and physical examination were normal. His vital signs and laboratory results were within normal limits. Computed tomography (CT) showed dilated vascular structures around both lateral ventricles and atherosclerotic changes inside the walls of internal carotid artery (ICA). Magnetic resonance imaging (MRI) and angiography (MRA) revealed dilated venous vascular structures around lateral ventricles and hyper-intense gliosis in periventricular white matter. Ischemic gliosis around the lateral ventricles were present in the Digital Subtracted Angiography (DSA). After the neurology, ophthalmology and neurosurgery consultation, the patient was diagnosed with Moyamoya disease, pulse steroid therapy was started for vision loss, and super-selective DSA was planned for further investigation. Moyamoya disease is a rare condition, but it can be an important cause of stroke in both children and adults. It generally affects anterior circulation, but posterior cerebral circulation may also be affected, as well. In the differential diagnosis of acute vision loss, occipital stroke related to Moyamoya disease should be considered. Direct and indirect surgical revascularization surgeries may be used to effectively revascularize affected brain areas, and have been shown to reduce risk of stroke.

Keywords: headache, Moyamoya disease, stroke, visual loss

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