Search results for: real-time edge computing

Authors: Linjie Zhang, Baifen Ren, Xi Zhang, Genwang Liu

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Ship detection is of great significance for both military and civilian applications. Synthetic aperture radar (SAR) with all-day, all-weather, ultra-long-range characteristics, has been used widely. In view of the low time resolution of low orbit SAR and the needs for high time resolution SAR data, GEO (Geosynchronous orbit) SAR is getting more and more attention. Since GEO SAR has short revisiting period and large coverage area, it is expected to be well utilized in marine ship targets monitoring. However, the height of the orbit increases the time of integration by almost two orders of magnitude. For moving marine vessels, the utility and efficacy of GEO SAR are still not sure. This paper attempts to find the feasibility of GEO SAR by giving a GEO SAR simulator of moving ships. This presented GEO SAR simulator is a kind of geometrical-based radar imaging simulator, which focus on geometrical quality rather than high radiometric. Inputs of this simulator are 3D ship model (.obj format, produced by most 3D design software, such as 3D Max), ship's velocity, and the parameters of satellite orbit and SAR platform. Its outputs are simulated GEO SAR raw signal data and SAR image. This simulating process is accomplished by the following four steps. (1) Reading 3D model, including the ship rotations (pitch, yaw, and roll) and velocity (speed and direction) parameters, extract information of those little primitives (triangles) which is visible from the SAR platform. (2) Computing the radar scattering from the ship with physical optics (PO) method. In this step, the vessel is sliced into many little rectangles primitives along the azimuth. The radiometric calculation of each primitive is carried out separately. Since this simulator only focuses on the complex structure of ships, only single-bounce reflection and double-bounce reflection are considered. (3) Generating the raw data with GEO SAR signal modeling. Since the normal ‘stop and go’ model is not available for GEO SAR, the range model should be reconsidered. (4) At last, generating GEO SAR image with improved Range Doppler method. Numerical simulation of fishing boat and cargo ship will be given. GEO SAR images of different posture, velocity, satellite orbit, and SAR platform will be simulated. By analyzing these simulated results, the effectiveness of GEO SAR for the detection of marine moving vessels is evaluated.

Keywords: GEO SAR, radar, simulation, ship

Procedia PDF Downloads 148

Authors: Veronica S. Moertini, Vinsensius Kevin, Gede Karya

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Customer reviews have been collected by many kinds of e-commerce websites selling products, services, hotel rooms, tickets and so on. Each website collects its own customer reviews. The reviews can be crawled, collected from those websites and stored as big data. Text analysis techniques can be used to analyze that data to produce summarized information, such as customer opinions. Then, these opinions can be published by independent service provider websites and used to help customers in choosing the most suitable products or services. As the opinions are analyzed from big data of reviews originated from many websites, it is expected that the results are more trusted and accurate. Indonesian customers write reviews in Indonesian language, which comes with its own structures and uniqueness. We found that most of the reviews are expressed with “daily language”, which is informal, do not follow the correct grammar, have many abbreviations and slangs or non-formal words. Hadoop is an emerging platform aimed for storing and analyzing big data in distributed systems. A Hadoop cluster consists of master and slave nodes/computers operated in a network. Hadoop comes with distributed file system (HDFS) and MapReduce framework for supporting parallel computation. However, MapReduce has weakness (i.e. inefficient) for iterative computations, specifically, the cost of reading/writing data (I/O cost) is high. Given this fact, we conclude that MapReduce function is best adapted for “one-pass” computation. In this research, we develop an efficient technique for extracting or mining opinions from big data of Indonesian reviews, which is based on MapReduce with one-pass computation. In designing the algorithm, we avoid iterative computation and instead adopt a “look up table” technique. The stages of the proposed technique are: (1) Crawling the data reviews from websites; (2) cleaning and finding root words from the raw reviews; (3) computing the frequency of the meaningful opinion words; (4) analyzing customers sentiments towards defined objects. The experiments for evaluating the performance of the technique were conducted on a Hadoop cluster with 14 slave nodes. The results show that the proposed technique (stage 2 to 4) discovers useful opinions, is capable of processing big data efficiently and scalable.

Keywords: big data analysis, Hadoop MapReduce, analyzing text data, mining Indonesian reviews

Procedia PDF Downloads 183

Authors: D. Heinemann, S. Schramm, S. Knabner, D. Baumgarten

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Purpose: Applying solder paste to printed circuit boards (PCB) with stencils has been the method of choice over the past years. A new method uses a jet printer to deposit tiny droplets of solder paste through an ejector mechanism onto the board. This allows for more flexible PCB layouts with smaller components. Due to the viscosity of the solder paste, air blisters can be trapped in the cartridge. This can lead to missing solder joints or deviations in the applied solder volume. Therefore, a built-in and real-time inspection of the printing process is needed to minimize uncertainties and increase the efficiency of the process by immediate correction. The objective of the current study is the design of an optimal imaging system and the development of an automatic algorithm for the detection of applied solder joints from optical from the captured images. Methods: In a first approach, a camera module connected to a microcomputer and LED strips are employed to capture images of the printed circuit board under four different illuminations (white, red, green and blue). Subsequently, an improved system including a ring light, an objective lens, and a monochromatic camera was set up to acquire higher quality images. The obtained images can be divided into three main components: the PCB itself (i.e., the background), the reflections induced by unsoldered positions or screw holes and the solder joints. Non-uniform illumination is corrected by estimating the background using a morphological opening and subtraction from the input image. Image sharpening is applied in order to prevent error pixels in the subsequent segmentation. The intensity thresholds which divide the main components are obtained from the multimodal histogram using three probability density functions. Determining the intersections delivers proper thresholds for the segmentation. Remaining edge gradients produces small error areas which are removed by another morphological opening. For quantitative analysis of the segmentation results, the dice coefficient is used. Results: The obtained PCB images show a significant gradient in all RGB channels, resulting from ambient light. Using different lightings and color channels 12 images of a single PCB are available. A visual inspection and the investigation of 27 specific points show the best differentiation between those points using a red lighting and a green color channel. Estimating two thresholds from analyzing the multimodal histogram of the corrected images and using them for segmentation precisely extracts the solder joints. The comparison of the results to manually segmented images yield high sensitivity and specificity values. Analyzing the overall result delivers a Dice coefficient of 0.89 which varies for single object segmentations between 0.96 for a good segmented solder joints and 0.25 for single negative outliers. Conclusion: Our results demonstrate that the presented optical imaging system and the developed algorithm can robustly detect solder joints on printed circuit boards. Future work will comprise a modified lighting system which allows for more precise segmentation results using structure analysis.

Keywords: printed circuit board jet-printing, inspection, segmentation, solder paste detection

Procedia PDF Downloads 311

Authors: A. Assad, T. Zayed

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Water networks (WNs) are responsible of providing adequate amounts of safe, high quality, water to the public. As other critical infrastructure systems, WNs are subjected to deterioration which increases the number of breaks and leaks and lower water quality. In Canada, 35% of water assets require critical attention and there is a significant gap between the needed and the implemented investments. Thus, the need for efficient rehabilitation programs is becoming more urgent given the paradigm of aging infrastructure and tight budget. The first step towards developing such programs is to formulate a Performance Index that reflects the current condition of water assets along with its criticality. While numerous studies in the literature have focused on various aspects of condition assessment and reliability, limited efforts have investigated the criticality of such components. Critical water mains are those whose failure cause significant economic, environmental or social impacts on a community. Inclusion of criticality in computing the performance index will serve as a prioritizing tool for the optimum allocating of the available resources and budget. In this study, several social, economic, and environmental factors that dictate the criticality of a water pipelines have been elicited from analyzing the literature. Expert opinions were sought to provide pairwise comparisons of the importance of such factors. Subsequently, Fuzzy Logic along with Analytical Network Process (ANP) was utilized to calculate the weights of several criteria factors. Multi Attribute Utility Theories (MAUT) was then employed to integrate the aforementioned weights with the attribute values of several pipelines in Montreal WN. The result is a criticality index, 0-1, that quantifies the severity of the consequence of failure of each pipeline. A novel contribution of this approach is that it accounts for both the interdependency between criteria factors as well as the inherited uncertainties in calculating the criticality. The practical value of the current study is represented by the automated tool, Excel-MATLAB, which can be used by the utility managers and decision makers in planning for future maintenance and rehabilitation activities where high-level efficiency in use of materials and time resources is required.

Keywords: water networks, criticality assessment, asset management, fuzzy analytical network process

Procedia PDF Downloads 129

Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

Procedia PDF Downloads 95

Authors: Nihar Bheda

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Protecting digital assets such as networks, systems, and data from advanced cyber threats is the aim of Digital Immunity Systems (DIS), which are a subset of cybersecurity. With features like continuous monitoring, coordinated reactions, and long-term adaptation, DIS seeks to mimic biological immunity. This minimizes downtime by automatically identifying and eliminating threats. Traditional security measures, such as firewalls and antivirus software, are insufficient for enterprises, such as healthcare providers, given the rapid evolution of cyber threats. The number of medical record breaches that have occurred in recent years is proof that attackers are finding healthcare data to be an increasingly valuable target. However, obstacles to enhancing security include outdated systems, financial limitations, and a lack of knowledge. DIS is an advancement in cyber defenses designed specifically for healthcare settings. Protection akin to an "immune system" is produced by core capabilities such as anomaly detection, access controls, and policy enforcement. Coordination of responses across IT infrastructure to contain attacks is made possible by automation and orchestration. Massive amounts of data are analyzed by AI and machine learning to find new threats. After an incident, self-healing enables services to resume quickly. The implementation of DIS is consistent with the healthcare industry's urgent requirement for resilient data security in light of evolving risks and strict guidelines. With resilient systems, it can help organizations lower business risk, minimize the effects of breaches, and preserve patient care continuity. DIS will be essential for protecting a variety of environments, including cloud computing and the Internet of medical devices, as healthcare providers quickly adopt new technologies. DIS lowers traditional security overhead for IT departments and offers automated protection, even though it requires an initial investment. In the near future, DIS may prove to be essential for small clinics, blood banks, imaging centers, large hospitals, and other healthcare organizations. Cyber resilience can become attainable for the whole healthcare ecosystem with customized DIS implementations.

Keywords: digital immunity system, cybersecurity, healthcare data, emerging technology

Procedia PDF Downloads 39

Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

Procedia PDF Downloads 118

Authors: Anne Mastamet-Mason

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Crimes against women is a global concern, and South Africa, in particular, is in a dilemma of dealing with constant criminal acts that face the country. Debates on violence against women in South Africa cannot be overemphasised any longer as crimes continue to rise year by year. The recent death of a university student at the University of Cape Town, as well as many other cases, continues to strengthen the need to find solutions from all the spheres of South African society. The advanced textiles market contains a high number and variety of technologies, many of which have protected status and constitute a relatively small portion of the textiles used for the consumer market. Examples of advanced textiles include nanomaterials, such as silver, titanium dioxide and zinc oxide, designed to create an anti-microbial and self-cleaning layer on top of the fibers, thereby reducing body smell and soiling. Smart textiles propose materials and fabrics versatile and adaptive to different situations and functions. Integrating textiles and computing technologies offer an opportunity to come up with differentiated characteristics and functionality. This paper presents a proposal to design a smart camisole/Yoga sports brazier and a smart Yoga sports pant garment to be worn by women while alone and while in purported danger zones. The smart garments are to be worn under normal clothing and cannot be detected or seen, or suspected by perpetrators. The garments are imbued with devices to sense any physical aggression and any abnormal or accelerated heartbeat that may be exhibited by the victim of violence. The signals created during the attack can be transmitted to the police and family members who own a mobile application system that accepts signals emitted. The signals direct the receiver to the exact location of the offence, and the victim can be rescued before major violations are committed. The design of the Yoga sports garments will be done by Professor Mason, who is a fashion designer by profession, while the mobile phone application system will be developed by Mr. Amos Yegon, who is an independent software developer.

Keywords: smart clothing, wearable technology, south africa, 4th industrial revolution

Procedia PDF Downloads 175

Authors: Noury Bakrim

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Formalization is indeed a foundational Mathematical Linguistics as demonstrated by the pioneering works. While dialoguing with this frame, we nonetheless propone, in our approach of language as a real object, a mathematical linguistics/biosemiotics defined as a dialectical synthesis between induction and computational deduction. Therefore, relying on the parametric interaction of cycles, rules, and features giving way to a sub-hypothetic biological point of view, we first hypothesize a factorial equation as an explanatory principle within Category Mathematics of the Ergobrain: our computation proposal of Universal Grammar rules per cycle or a scalar determination (multiplying right/left columns of the determinant matrix and right/left columns of the logarithmic matrix) of the transformable matrix for rule addition/deletion and cycles within representational mapping/cycle heredity basing on the factorial example, being the logarithmic exponent or power of rule deletion/addition. It enables us to propone an extension of minimalist merge/label notions to a Language Merge (as a computing principle) within cycle recursion relying on combinatorial mapping of rules hierarchies on external Entax of the Event Sequence. Therefore, to define combinatorial maps as language merge of features and combinatorial hierarchical restrictions (governing, commanding, and other rules), we secondly hypothesize from our results feature/hierarchy exponentiation on graph representation deriving from Gromov's Symbolic Dynamics where combinatorial vertices from Fe are set to combinatorial vertices of Hie and edges from Fe to Hie such as for all combinatorial group, there are restriction maps representing different derivational levels that are subgraphs: the intersection on I defines pullbacks and deletion rules (under restriction maps) then under disjunction edges H such that for the combinatorial map P belonging to Hie exponentiation by intersection there are pullbacks and projections that are equal to restriction maps RM₁ and RM₂. The model will draw on experimental biomathematics as well as structural frames with focus on Amazigh and English (cases from phonology/micro-semantics, Syntax) shift from Structure to event (especially Amazigh formant principle resolving its morphological heterogeneity).

Keywords: rule/cycle addition/deletion, bio-mathematical methodology, general merge calculation, feature exponentiation, combinatorial maps, event sequence

Procedia PDF Downloads 102

Authors: F. Tang, S. Boskovich, A. Raheja, Z. Aliyazicioglu, S. Bhandari, N. Tsuchiya

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Calpoly Autonomous Transportation Experience (CATE) is a driverless vehicle that we are developing to provide safe, accessible, and efficient transportation of passengers throughout the Cal Poly Pomona campus for events such as orientation tours. Unlike the other self-driving vehicles that are usually developed to operate with other vehicles and reside only on the road networks, CATE will operate exclusively on walk-paths of the campus (potentially narrow passages) with pedestrians traveling from multiple locations. Safety becomes paramount as CATE operates within the same environment as pedestrians. As driverless vehicles assume greater roles in today’s transportation, this project will contribute to autonomous driving with pedestrian traffic in a highly dynamic environment. The CATE project requires significant interdisciplinary work. Researchers from mechanical engineering, electrical engineering and computer science are working together to attack the problem from different perspectives (hardware, software and system). In this abstract, we describe the software aspects of the project, with a focus on the requirements and the major components. CATE shall provide a GUI interface for the average user to interact with the car and access its available functionalities, such as selecting a destination from any origin on campus. We have developed an interface that provides an aerial view of the campus map, the current car location, routes, and the goal location. Users can interact with CATE through audio or manual inputs. CATE shall plan routes from the origin to the selected destination for the vehicle to travel. We will use an existing aerial map for the campus and convert it to a spatial graph configuration where the vertices represent the landmarks and edges represent paths that the car should follow with some designated behaviors (such as stay on the right side of the lane or follow an edge). Graph search algorithms such as A* will be implemented as the default path planning algorithm. D* Lite will be explored to efficiently recompute the path when there are any changes to the map. CATE shall avoid any static obstacles and walking pedestrians within some safe distance. Unlike traveling along traditional roadways, CATE’s route directly coexists with pedestrians. To ensure the safety of the pedestrians, we will use sensor fusion techniques that combine data from both lidar and stereo vision for obstacle avoidance while also allowing CATE to operate along its intended route. We will also build prediction models for pedestrian traffic patterns. CATE shall improve its location and work under a GPS-denied situation. CATE relies on its GPS to give its current location, which has a precision of a few meters. We have implemented an Unscented Kalman Filter (UKF) that allows the fusion of data from multiple sensors (such as GPS, IMU, odometry) in order to increase the confidence of localization. We also noticed that GPS signals can easily get degraded or blocked on campus due to high-rise buildings or trees. UKF can also help here to generate a better state estimate. In summary, CATE will provide on-campus transportation experience that coexists with dynamic pedestrian traffic. In future work, we will extend it to multi-vehicle scenarios.

Keywords: driverless vehicle, path planning, sensor fusion, state estimate

Procedia PDF Downloads 120

Authors: Sonja Giese, Tess N. Peacock

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South African based Innovation Edge is experimenting with technology to drive positive behavior change, enable data-driven decision making, and scale quality early years services. This paper uses five case studies to illustrate how technology can be used in resource-constrained environments to first, encourage parenting practices that build early language development (using a stage-based mobile messaging pilot, ChildConnect), secondly, to improve the quality of ECD programs (using a mobile application, CareUp), thirdly, how to affordably scale services for the early detection of visual and hearing impairments (using a mobile tool, HearX), fourthly, how to build a transparent and accountable system for the registration and funding of ECD (using a blockchain enabled platform, Amply), and finally enable rapid data collection and feedback to facilitate quality enhancement of programs at scale (the Early Learning Outcomes Measure). ChildConnect and CareUp were both developed using a design based iterative research approach. The usage and uptake of ChildConnect and CareUp was evaluated with qualitative and quantitative methods. Actual child outcomes were not measured in the initial pilots. Although parents who used and engaged on either platform felt more supported and informed, parent engagement and usage remains a challenge. This is contrast to ECD practitioners whose usage and knowledge with CareUp showed both sustained engagement and knowledge improvement. HearX is an easy-to-use tool to identify hearing loss and visual impairment. The tool was tested with 10000 children in an informal settlement. The feasibility of cost-effectively decentralising screening services was demonstrated. Practical and financial barriers remain with respect to parental consent and for successful referrals. Amply uses mobile and blockchain technology to increase impact and accountability of public services. In the pilot project, Amply is being used to replace an existing paper-based system to register children for a government-funded pre-school subsidy in South Africa. Early Learning Outcomes Measure defines what it means for a child to be developmentally ‘on track’ at aged 50-69 months. ELOM administration is enabled via a tablet which allows for easy and accurate data collection, transfer, analysis, and feedback. ELOM is being used extensively to drive quality enhancement of ECD programs across multiple modalities. The nature of ECD services in South Africa is that they are in large part provided by disconnected private individuals or Non-Governmental Organizations (in contrast to basic education which is publicly provided by the government). It is a disparate sector which means that scaling successful interventions is that much harder. All five interventions show the potential of technology to support and enhance a range of ECD services, but pathways to scale are still being tested.

Keywords: assessment, behavior change, communication, data, disabilities, mobile, scale, technology, quality

Procedia PDF Downloads 115

Authors: Islam Sherif, Ahmed Ashour, Ahmed Hassan, Hatem Osman

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Anterior Cruciate Ligament (ACL) injuries are common among athletes and individuals participating in sports with sudden stops, pivots, and changes in direction. Arthroscopic surgery is the gold standard for ACL reconstruction, aiming to restore knee stability and function. Recent years have witnessed significant advancements in arthroscopic surgery techniques, graft materials, and technological innovations, revolutionizing the field of ACL reconstruction. This presentation delves into the latest advancements in arthroscopic surgery techniques for ACL reconstruction and their potential impact on patient outcomes. Traditionally, autografts from the patellar tendon, hamstring tendon, or quadriceps tendon have been commonly used for ACL reconstruction. However, recent studies have explored the use of allografts, synthetic scaffolds, and tissue-engineered grafts as viable alternatives. This abstract evaluates the benefits and potential drawbacks of each graft type, considering factors such as graft incorporation, strength, and risk of graft failure. Moreover, the application of augmented reality (AR) and virtual reality (VR) technologies in surgical planning and intraoperative navigation has gained traction. AR and VR platforms provide surgeons with detailed 3D anatomical reconstructions of the knee joint, enhancing preoperative visualization and aiding in graft tunnel placement during surgery. We discuss the integration of AR and VR in arthroscopic ACL reconstruction procedures, evaluating their accuracy, cost-effectiveness, and overall impact on surgical outcomes. Beyond graft selection and surgical navigation, patient-specific planning has gained attention in recent research. Advanced imaging techniques, such as MRI-based personalized planning, enable surgeons to tailor ACL reconstruction procedures to each patient's unique anatomy. By accounting for individual variations in the femoral and tibial insertion sites, this personalized approach aims to optimize graft placement and potentially improve postoperative knee kinematics and stability. Furthermore, rehabilitation and postoperative care play a crucial role in the success of ACL reconstruction. This abstract explores novel rehabilitation protocols, emphasizing early mobilization, neuromuscular training, and accelerated recovery strategies. Integrating technology, such as wearable sensors and mobile applications, into postoperative care can facilitate remote monitoring and timely intervention, contributing to enhanced rehabilitation outcomes. In conclusion, this presentation provides an overview of the cutting-edge advancements in arthroscopic surgery techniques for ACL reconstruction. By embracing innovative graft materials, augmented reality, patient-specific planning, and technology-driven rehabilitation, orthopedic surgeons and sports medicine specialists can achieve superior outcomes in ACL injury management. These developments hold great promise for improving the functional outcomes and long-term success rates of ACL reconstruction, benefitting athletes and patients alike.

Keywords: arthroscopic surgery, ACL, autograft, allograft, graft materials, ACL reconstruction, synthetic scaffolds, tissue-engineered graft, virtual reality, augmented reality, surgical planning, intra-operative navigation

Procedia PDF Downloads 66

Authors: Govind Kumar

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The concept of ‘e-governance’ that was brought about by the new wave of reforms, namely ‘LPG’ in the early 1990s, has been enabling governments across the globe to digitally transform themselves. Digital transformation is leading the governments with qualitative decisions, optimization in rational use of resources, facilitation of cost-benefit analyses, and elimination of redundancy and corruption with the help of ICT-based applications interface. ICT-based applications/technologies have enormous potential for impacting positive change in the social lives of the global citizenry. Supercomputers test and analyze millions of drug molecules for developing candidate vaccines to combat the global pandemic. Further, e-commerce portals help distribute and supply household items and medicines, while videoconferencing tools provide a visual interface between the clients and hosts. Besides, crop yields are being maximized with the help of drones and machine learning, whereas satellite data, artificial intelligence, and cloud computing help governments with the detection of illegal mining, tackling deforestation, and managing freshwater resources. Such e-applications have the potential to take governance an extra mile by achieving 5 Es (effective, efficient, easy, empower, and equity) of e-governance and six Rs (reduce, reuse, recycle, recover, redesign and remanufacture) of sustainable development. If such digital transformation gains traction within the government framework, it will replace the traditional administration with the digitalization of public administration. On the other hand, it has brought in a new set of challenges, like the digital divide, e-illiteracy, technological divide, etc., and problems like handling e-waste, technological obsolescence, cyber terrorism, e-fraud, hacking, phishing, etc. before the governments. Therefore, it would be essential to bring in a rightful mixture of technological and humanistic interventions for addressing the above issues. This is on account of the reason that technology lacks an emotional quotient, and the administration does not work like technology. Both are self-effacing unless a blend of technology and a humane face are brought in into the administration. The paper will empirically analyze the significance of the technological framework of digital transformation within the government set up for the digitalization of public administration on the basis of the synthesis of two case studies undertaken from two diverse fields of administration and present a future framework of the study.

Keywords: digital transformation, electronic governance, public administration, knowledge framework

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Authors: Cai J. T. Ladd, Mollie F. Duggan-Edwards, Tjeerd J. Bouma, Jordi F. Pages, Martin W. Skov

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Salt marshes are valued for their role in coastal flood protection, carbon storage, and for supporting biodiverse ecosystems. As a biogeomorphic landscape, marshes evolve through the complex interactions between sea level rise, sediment supply and wave/current forcing, as well as and socio-economic factors. Climate change and direct human modification could lead to a global decline marsh extent if left unchecked. Whilst the processes of saltmarsh erosion and expansion are well understood, empirical evidence on the key drivers of long-term lateral marsh dynamics is lacking. In a GIS, saltmarsh areal extent in 25 estuaries across Great Britain was calculated from historical maps and aerial photographs, at intervals of approximately 30 years between 1846 and 2016. Data on the key perceived drivers of lateral marsh change (namely sea level rise rates, suspended sediment concentration, bedload sediment flux rates, and frequency of both river flood and storm events) were collated from national monitoring centres. Continuous datasets did not extend beyond 1970, therefore predictor variables that best explained rate change of marsh extent between 1970 and 2016 was calculated using a Partial Least Squares Regression model. Information about the spread of Spartina anglica (an invasive marsh plant responsible for marsh expansion around the globe) and coastal engineering works that may have impacted on marsh extent, were also recorded from historical documents and their impacts assessed on long-term, large-scale marsh extent change. Results showed that salt marshes in the northern regions of Great Britain expanded an average of 2.0 ha/yr, whilst marshes in the south eroded an average of -5.3 ha/yr. Spartina invasion and coastal engineering works could not explain these trends since a trend of either expansion or erosion preceded these events. Results from the Partial Least Squares Regression model indicated that the rate of relative sea level rise (RSLR) and availability of suspended sediment concentration (SSC) best explained the patterns of marsh change. RSLR increased from 1.6 to 2.8 mm/yr, as SSC decreased from 404.2 to 78.56 mg/l along the north-to-south gradient of Great Britain, resulting in the shift from marsh expansion to erosion. Regional differences in RSLR and SSC are due to isostatic rebound since deglaciation, and tidal amplitudes respectively. Marshes exposed to low RSLR and high SSC likely leads to sediment accumulation at the coast suitable for colonisation by marsh plants and thus lateral expansion. In contrast, high RSLR with are likely not offset deposition under low SSC, thus average water depth at the marsh edge increases, allowing larger wind-waves to trigger marsh erosion. Current global declines in sediment flux to the coast are likely to diminish the resilience of salt marshes to RSLR. Monitoring and managing suspended sediment supply is not common-place, but may be critical to mitigating coastal impacts from climate change.

Keywords: lateral saltmarsh dynamics, sea level rise, sediment supply, wave forcing

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Authors: Swati Gautam, Amita Jain, Shyampyari Jaiswar

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Objective: To elucidate the role of (ApaI&TaqI) VDR gene polymorphism in the pathogenesis of female genital tuberculosis (FGTB) cases. Background: Female genital TB represents about 15-20% of total extra-pulmonary TB (EPTB). Female subjects with vitamin D deficiency have been shown to be at higher risk of pulmonary TB as well as FGTB. In same context few functional polymorphism in vitamin D receptor (VDR) gene has been considered as an important genetic risk factor that modulate the development of FGTB. Therefore we aimed, to elucidate the role of (ApaI&TaqI) VDR gene polymorphism in the pathogenesis of FGTB. Study design: Case-Control study. Sample size: Cases (60) and Controls (60). Study site: Department of Obstetrics & Gynecology & Department of Microbiology, K.G.M.U. Lucknow, (UP). Inclusion criteria: Cases: Women with age group 20-35 years, premenstrual endometrial aspiration collected and included in the study, those were positive with acid-fast bacilli (AFB)/ TB-PCR/ LJ culture/ liquid culture. Controls: Women with age group 20-35 years having no history of ATT and all test negative for TB recruited as control. Exclusion criteria: -Women with endometriosis, polycystic ovaries (PCOD), positive on Chlamydia & gonorrhea, already on anti-tubercular therapy (ATT) excluded. Materials and Methods: Blood samples were collected in EDTA tubes from cases and controls stored at -20ºC. Genomic DNA extraction was carried out by salting-out method. Genotyping of VDR gene (ApaI&TaqI) polymorphism was performed by using single amplification refractory mutation system (ARMS) PCR technique. PCR products were analyzed by electrophoresis on 2% agarose gel. Statistical analysis was done by SPSS16.3 software & computing odds ratio (OR) with 95% CI. Results: Increased risk of female genital tuberculosis was observed in AA genotype (OR =1.1419-6.212 95% CI, P*<0.036) and A allele (OR =1.255-3.518, 95% CI, P* < 0.006) in FGTB as compared to controls. Moreover A allele was found more frequent in FGTB patients. No significant difference was observed in TaqI gene polymorphism of VDR gene. Conclusion: The ApaI polymorphism is significantly associated with etiology of FGTB and plays an important role as a genetic risk factor in FGTB women.

Keywords: ARMS, ATT, EPTB, FGTB, VDR

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Authors: Ahmet Ozcan, Onder Alparslan, Anil Sezgin, Omer Cetin

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The use of unmanned systems for different purposes has become very popular over the past decade. Expectations from these systems have also shown an incredible increase in this parallel. But meeting the demands of the tasks are often not possible with the usage of a single unmanned vehicle in a mission, so it is necessary to use multiple autonomous vehicles with different abilities together in coordination. Therefore the usage of the same type of vehicles together as a swarm is helped especially to satisfy the time constraints of the missions effectively. In other words, it allows sharing the workload by the various numbers of homogenous platforms together. Besides, it is possible to say there are many kinds of problems that require the usage of the different capabilities of the heterogeneous platforms together cooperatively to achieve successful results. In this case, cooperative working brings additional problems beyond the homogeneous clusters. In the scenario presented as an example problem, it is expected that an autonomous ground vehicle, which is lack of its position information, manage to perform point-to-point navigation without losing its way in a previously unknown labyrinth. Furthermore, the ground vehicle is equipped with very limited sensors such as ultrasonic sensors that can detect obstacles. It is very hard to plan or complete the mission for the ground vehicle by self without lost its way in the unknown labyrinth. Thus, in order to assist the ground vehicle, the autonomous air drone is also used to solve the problem cooperatively. The autonomous drone also has limited sensors like downward looking camera and IMU, and it also lacks computing its global position. In this context, it is aimed to solve the problem effectively without taking additional support or input from the outside, just benefiting capabilities of two autonomous vehicles. To manage the point-to-point navigation in a previously unknown labyrinth, the platforms have to work together coordinated. In this paper, cooperative work of heterogeneous unmanned systems is handled in an applied sample scenario, and it is mentioned that how to work together with an autonomous ground vehicle and the autonomous flying platform together in a harmony to take advantage of different platform-specific capabilities. The difficulties of using heterogeneous multiple autonomous platforms in a mission are put forward, and the successful solutions are defined and implemented against the problems like spatially distributed tasks planning, simultaneous coordinated motion, effective communication, and sensor fusion.

Keywords: unmanned systems, heterogeneous autonomous vehicles, coordination, task planning

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Authors: Dana Zelicha

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The objective of this paper is to present innovative mindfulness tools specifically designed by OWBA—The Well Being Agency for organisations and corporate wellness programmes. The OWBA Mindfulness Tools (OWBA-MT) consist of practical mindfulness exercises to educate and train employees and business leaders to think, feel, and act more mindfully. Among these cutting-edge interventions are Mindful Meetings, Mindful Decision Making and Unitasking activities, intended to cultivate mindful communication and compassion in the workplace and transform organisational culture. In addition to targeting CEO’s and leaders within large corporations, OWBA-MT is also directed at the needs of specific populations such as entrepreneurs’ resilience and women empowerment. The goals of the OWBA-MT are threefold: to inform, inspire and implement. The first goal is to inform participants about the relationship between workplace stress, distractibility and miscommunication in the framework of mindfulness. The second goal is for the audience to be inspired to share those practices with other members of their organisation. The final objective is to equip participants with the tools to foster a compassionate, mindful and well-balanced work environment. To assess these tools, a 6-week case study was conducted as part of an employee wellness programme for a large international corporation. The OWBA-MT were introduced in a workshop forum once-a-week, with participants practicing these tools both in the office and at home. The workshops occurred 1 day a week (2 hours each), with themes and exercises varying weekly. To reinforce practice at home, participants received reflection forms and guided meditations online. Materials were sent via-email at the same time each day to ensure consistency and participation. To evaluate the effectiveness of the mindfulness intervention, improvements in four categories were measured: listening skills, mindfulness levels, prioritising skills and happiness levels. These factors were assessed using online self-reported questionnaires administered at the start of the intervention, and then again 4-weeks following completion. The measures included the Mindfulness Attention Awareness Scale (MAAS), Listening Skills Inventory (LSI), Time Management Behaviour Scale (TMBS) and a modified version of the Oxford Happiness Questionnaire (OHQ). All four parameters showed significant improvements from the start of the programme to the 4-week follow-up. Participant testimonials exhibited high levels of satisfaction and the overall results indicate that the OWBA-MT intervention substantially impacted the corporation in a positive way. The implications of these results suggest that OWBA-MT can improve employees’ capacities to listen and work well with others, to manage time effectively, and to experience enhanced satisfaction both at work and in life. Although corporate mindfulness programmes have proven to be effective, the challenge remains the low engagement levels at home in between training sessions and to implement the tools beyond the scope of the intervention. OWBA-MT has offered an innovative approach to enforce engagement levels at home by sending daily online materials outside the workshop forum with a personalised response. The limitations also noteworthy to consider for future research include the afterglow effect and lack of generalisability, as this study was conducted on a small and fairly homogenous sample.

Keywords: corporate mindfulness, listening skills, mindful leadership, mindfulness tools, organisational well being

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Authors: Saraswati Kerketta

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Tea industry is one of the oldest organised sector of India. It employs roughly 1.5 million people directly. Since the last decade Indian tea industry, especially in the northern region is experiencing worst crisis in the post-independence period. Due to many reason the prices of tea show steady decline. The workers are paid one of the lowest wage in tea industry in the world (1.5$ a day) below the UN's $2 a day for extreme poverty. The workers rely on addition benefits from plantation which includes food, housing and medical facilities. These have been effective means of enslavement of generations of labourers by the owners. There is hardly any change in the tea estates where the owners determine the fate of workers. When the tea garden is abandoned or is closed all the facilities disappear immediately. The workers are the descendants of tribes from central India also known as 'tea tribes'. Alienated from their native place, the geographical and social isolation compounded their vulnerability of these people. The economy of the region being totally dependent on tea has resulted in absolute unemployment for the workers of these tea gardens. With no other livelihood and no land to grow food, thousands of workers faced hunger and starvation. The Plantation Labour Act which ensures the decent working and living condition is violated continuously. The labours are forced to migrate and are also exposed to the risk of human trafficking. Those who are left behind suffers from starvation, malnutrition and disease. The condition in the sick tea plantation is no better. Wage are not paid regularly, subsidised food, fuel are also not supplied properly. Health care facilities are in very bad shape. Objectives: • To study the socio-cultural and demographic characteristics of the tea garden labourers in the study area. • To examine the social situation of workers in sick estates in dooars region. • To assess the magnitude of deprivation the impact of economic crisis on abandoned and closed tea estates in the region. Data Base: The study is based on data collected from field survey. Methods: Quantative: Cross-Tabulation, Regression analysis. Qualitative: Household Survey, Focussed Group Discussion, In-depth interview of key informants. Findings: Purchasing power parity has declined since in last three decades. There has been many fold increase in migration. Males migrates long distance towards central and west and south India. Females and children migrates both long and short distance. No one has reported to migrate back to the place of origin of their ancestors. Migrant males work mostly as construction labourers and as factory workers whereas females and children work as domestic help and construction labourers. In about 37 cases either they haven't contacted their families in last six months or are not traceable. The families with single earning members are more likely to migrate. Burden of disease and the duration of sickness, abandonment and closure of plantation are closely related. Death tolls are likely to rise 1.5 times in sick tea gardens and three times in closed tea estates. Sixty percent of the people are malnourished in the sick tea gardens and more than eighty five per cent in abandoned and sick tea gardens.

Keywords: migration, trafficking, starvation death, tea garden workers

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Authors: Sanjay Rathee, Arti Kashyap

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Extraction of useful information from large datasets is one of the most important research problems. Association rule mining is one of the best methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent patterns) is most important part of the association rule mining. There exist many algorithms to find frequent patterns but Apriori algorithm always remains a preferred choice due to its ease of implementation and natural tendency to be parallelized. Many single-machine based Apriori variants exist but massive amount of data available these days is above capacity of a single machine. Therefore, to meet the demands of this ever-growing huge data, there is a need of multiple machines based Apriori algorithm. For these types of distributed applications, MapReduce is a popular fault-tolerant framework. Hadoop is one of the best open-source software frameworks with MapReduce approach for distributed storage and distributed processing of huge datasets using clusters built from commodity hardware. However, heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes Hadoop inefficient. A number of MapReduce-based platforms are being developed for parallel computing in recent years. Among them, two platforms, namely, Spark and Flink have attracted a lot of attention because of their inbuilt support to distributed computations. Earlier we proposed a reduced- Apriori algorithm on Spark platform which outperforms parallel Apriori, one because of use of Spark and secondly because of the improvement we proposed in standard Apriori. Therefore, this work is a natural sequel of our work and targets on implementing, testing and benchmarking Apriori and Reduced-Apriori and our new algorithm ReducedAll-Apriori on Apache Flink and compares it with Spark implementation. Flink, a streaming dataflow engine, overcomes disk I/O bottlenecks in MapReduce, providing an ideal platform for distributed Apriori. Flink's pipelining based structure allows starting a next iteration as soon as partial results of earlier iteration are available. Therefore, there is no need to wait for all reducers result to start a next iteration. We conduct in-depth experiments to gain insight into the effectiveness, efficiency and scalability of the Apriori and RA-Apriori algorithm on Flink.

Keywords: apriori, apache flink, Mapreduce, spark, Hadoop, R-Apriori, frequent itemset mining

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Authors: Ahmed E. Hodaib, Mohamed A. Hashem

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In engineering applications, a design has to be as fully perfect as possible in some defined case. The designer has to overcome many challenges in order to reach the optimal solution to a specific problem. This process is called optimization. Generally, there is always a function called “objective function” that is required to be maximized or minimized by choosing input parameters called “degrees of freedom” within an allowed domain called “search space” and computing the values of the objective function for these input values. It becomes more complex when we have more than one objective for our design. As an example for Multi-Objective Optimization Problem (MOP): A structural design that aims to minimize weight and maximize strength. In such case, the Pareto Optimal Frontier (POF) is used, which is a curve plotting two objective functions for the best cases. At this point, a designer should make a decision to choose the point on the curve. Engineers use algorithms or iterative methods for optimization. In this paper, we will discuss the Evolutionary Algorithms (EA) which are widely used with Multi-objective Optimization Problems due to their robustness, simplicity, suitability to be coupled and to be parallelized. Evolutionary algorithms are developed to guarantee the convergence to an optimal solution. An EA uses mechanisms inspired by Darwinian evolution principles. Technically, they belong to the family of trial and error problem solvers and can be considered global optimization methods with a stochastic optimization character. The optimization is initialized by picking random solutions from the search space and then the solution progresses towards the optimal point by using operators such as Selection, Combination, Cross-over and/or Mutation. These operators are applied to the old solutions “parents” so that new sets of design variables called “children” appear. The process is repeated until the optimal solution to the problem is reached. Reliable and robust computational fluid dynamics solvers are nowadays commonly utilized in the design and analyses of various engineering systems, such as aircraft, turbo-machinery, and auto-motives. Coupling of Computational Fluid Dynamics “CFD” and Multi-Objective Evolutionary Algorithms “MOEA” has become substantial in aerospace engineering applications, such as in aerodynamic shape optimization and advanced turbo-machinery design.

Keywords: mathematical optimization, multi-objective evolutionary algorithms "MOEA", computational fluid dynamics "CFD", aerodynamic shape optimization

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Authors: Haowen Xu, Xiaobing Liu, Jin Dong, Jianming Lian

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Emerging smart buildings often employ cyberinfrastructure, cyber-physical systems, and Internet of Things (IoT) technologies to increase the automation and responsiveness of building operations for better energy efficiency and lower carbon emission. These operations include the control of Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems, which are often considered a major source of energy consumption in both commercial and residential buildings. Developing energy-saving control models for optimizing HVAC operations usually requires the collection of high-quality instrumental data from iterations of in-situ building experiments, which can be time-consuming and labor-intensive. This abstract describes a digital twin approach to automate building energy experiments for optimizing HVAC operations through the design and development of an adaptive web-based platform. The platform is created to enable (a) automated data acquisition from a variety of IoT-connected HVAC instruments, (b) real-time situational awareness through domain-based visualizations, (c) adaption of HVAC optimization algorithms based on experimental data, (d) sharing of experimental data and model predictive controls through web services, and (e) cyber-physical control of individual instruments in the HVAC system using outputs from different optimization algorithms. Through the digital twin approach, we aim to replicate a real-world building and its HVAC systems in an online computing environment to automate the development of building-specific model predictive controls and collaborative experiments in buildings located in different climate zones in the United States. We present two case studies to demonstrate our platform’s capability for real-time situational awareness and cyber-physical control of the HVAC in the flexible research platforms within the Oak Ridge National Laboratory (ORNL) main campus. Our platform is developed using adaptive and flexible architecture design, rendering the platform generalizable and extendable to support HVAC optimization experiments in different types of buildings across the nation.

Keywords: energy-saving buildings, digital twins, HVAC, cyber-physical system, BIM

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Authors: Victor Mantilla, Romeu Vicente, António Figueiredo, Victor Ferreira, Sandra Sorte

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Integrating dynamic facades into contemporary building design is shaping a new era of energy efficiency and user comfort. These innovative facades, often constructed using lightweight construction systems and materials, offer an opportunity to have a responsive and adaptive nature to the dynamic behavior of the outdoor climate. Therefore, in regions characterized by high fluctuations in daily temperatures, the ability to adapt to environmental changes is of paramount importance and a challenge. This paper presents a thorough review of the state of the art on double-skin facades (DSF), focusing on lightweight solutions for the external envelope. Dynamic facades featuring elements like movable shading devices, phase change materials, and advanced control systems have revolutionized the built environment. They offer a promising path for reducing energy consumption while enhancing occupant well-being. Lightweight construction systems are increasingly becoming the choice for the constitution of these facade solutions, offering benefits such as reduced structural loads and reduced construction waste, improving overall sustainability. However, the performance of dynamic facades based on low thermal inertia solutions in climatic contexts with high thermal amplitude is still in need of research since their ability to adapt is traduced in variability/manipulation of the thermal transmittance coefficient (U-value). Emerging technologies can enable such a dynamic thermal behavior through innovative materials, changes in geometry and control to optimize the facade performance. These innovations will allow a facade system to respond to shifting outdoor temperature, relative humidity, wind, and solar radiation conditions, ensuring that energy efficiency and occupant comfort are both met/coupled. This review addresses the potential configuration of double-skin facades, particularly concerning their responsiveness to seasonal variations in temperature, with a specific focus on addressing the challenges posed by winter and summer conditions. Notably, the design of a dynamic facade is significantly shaped by several pivotal factors, including the choice of materials, geometric considerations, and the implementation of effective monitoring systems. Within the realm of double skin facades, various configurations are explored, encompassing exhaust air, supply air, and thermal buffering mechanisms. According to the review places a specific emphasis on the thermal dynamics at play, closely examining the impact of factors such as the color of the facade, the slat angle's dimensions, and the positioning and type of shading devices employed in these innovative architectural structures.This paper will synthesize the current research trends in this field, with the presentation of case studies and technological innovations with a comprehensive understanding of the cutting-edge solutions propelling the evolution of building envelopes in the face of climate change, namely focusing on double-skin lightweight solutions to create sustainable, adaptable, and responsive building envelopes. As indicated in the review, flexible and lightweight systems have broad applicability across all building sectors, and there is a growing recognition that retrofitting existing buildings may emerge as the predominant approach.

Keywords: adaptive, control systems, dynamic facades, energy efficiency, responsive, thermal comfort, thermal transmittance

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Authors: Samuel Owoade, Zainab Idowu, Idris Ajibade, Abel Uzoka

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Cloud computing adoption continues to soar, with 83% of enterprise workloads estimated to be in the cloud by 2022. However, this rapid migration raises security concerns, needing strong security management solutions to safeguard sensitive data and essential applications. This paper investigates the critical role of technical project managers in orchestrating security management initiatives for cloud environments, evaluating their responsibilities, challenges, and best practices for assuring the resilience and integrity of cloud infrastructures. Drawing from a comprehensive review of industry reports and interviews with cloud security experts, this research highlights the multifaceted landscape of security management in cloud environments. Despite the rapid adoption of cloud services, only 25% of organizations have matured their cloud security practices, indicating a pressing need for effective management strategies. This paper proposes a strategy framework adapted to the demands of technical project managers, outlining the important components of effective cloud security management. Notably, 76% of firms identify misconfiguration as a major source of cloud security incidents, underlining the significance of proactive risk assessment and constant monitoring. Furthermore, the study emphasizes the importance of technical project managers in facilitating cross-functional collaboration, bridging the gap between cybersecurity professionals, cloud architects, compliance officers, and IT operations teams. With 68% of firms seeing difficulties integrating security policies into their cloud systems, effective communication and collaboration are critical to success. Case studies from industry leaders illustrate the practical use of security management projects in cloud settings. These examples demonstrate the importance of technical project managers in using their expertise to address obstacles and generate meaningful outcomes, with 92% of firms reporting improved security practices after implementing proactive security management tactics. In conclusion, this research underscores the critical role of technical project managers in safeguarding cloud environments against evolving threats. By embracing their role as guardians of the cloud realm, project managers can mitigate risks, optimize resource utilization, and uphold the trust and integrity of cloud infrastructures in an era of digital transformation.

Keywords: cloud security, security management, technical project management, cybersecurity, cloud infrastructure, risk management, compliance

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Authors: Loreta Kaklauskiene, Arturas Kaklauskas

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The Integrated Human Resources and Work Environment Management (HOWE) System optimises employee productivity, improves the work environment, and, at the same time, meets the employer’s strategic goals. The HOWE system has been designed to ensure an organisation can successfully compete in the global market, thanks to the high performance of its employees. The HOWE system focuses on raising workforce productivity and improving work conditions to boost employee performance and motivation. The methods used in our research are linear correlation, INVAR multiple criteria analysis, digital twin, and affective computing. The HOWE system is based on two patents issued in Lithuania (LT 6866, LT 6841) and one European Patent application (No: EP 4 020 134 A1). Our research analyses ways to make human resource management more efficient and boost labour productivity by improving and adapting a personalised work environment. The efficiency of human capital and labour productivity can be increased by applying personalised workplace improvement systems that can optimise lighting colours and intensity, scents, data, information, knowledge, activities, media, games, videos, music, air pollution, humidity, temperature, vibrations, and other workplace aspects. HOWE generates and maintains a personalised workspace for an employee, taking into account the person’s affective, physiological and emotional (APSE) states. The purpose of this project was to create a HOWE for the customisation of quality control in smart workspaces taking into account the user’s APSE states in an integrated manner as a single unit. This customised management of quality control covers the levels of lighting and colour intensities, scents, media, information, activities, learning materials, games, music, videos, temperature, energy efficiency, the carbon footprint of a workspace, humidity, air pollution, vibrations and other aspects of smart spaces. The system is based on Digital Twins technology, seen as a logical extension of BIM.

Keywords: human resource management, health economics, work environment, organizational behaviour and employee productivity, prosperity in work, smart system

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Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

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This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

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Authors: Adel S. Alanazi

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The transition of a student with a disability from school to work is the most crucial phase while moving from the stage of adolescence into early adulthood. In this process, young individuals face various difficulties and challenges in order to accomplish the next venture of life successfully. In this respect, this paper aims to examine the challenges encountered by the individuals with intellectual disabilities in transition to work in Saudi Arabia. For this purpose, this study has undertaken a qualitative research-based methodology; wherein interpretivist philosophy has been followed along with inductive approach and exploratory research design. The data for the research has been gathered with the help of semi-structured interviews, whose findings are analysed with the help of thematic analysis. Semi-structured interviews were conducted with parents of persons with intellectual disabilities, officials, supervisors and specialists of two vocational rehabilitation centres providing training to intellectually disabled students, in addition to that, directors of companies and websites in hiring those individuals. The total number of respondents for the interview was 15. The purposive sampling method was used to select the respondents for the interview. This sampling method is a non-probability sampling method which draws respondents from a known population and allows flexibility and suitability in selecting the participants for the study. The findings gathered from the interview revealed that the lack of awareness among their parents regarding the rights of their children who are intellectually disabled; the lack of adequate communication and coordination between various entities; concerns regarding their training and subsequent employment are the key difficulties experienced by the individuals with intellectual disabilities. Training in programmes such as bookbinding, carpentry, computing, agriculture, electricity and telephone exchange operations were involved as key training programmes. The findings of this study also revealed that information technology and media were playing a significant role in smoothing the transition to employment of individuals with intellectual disabilities. Furthermore, religious and cultural attitudes have been identified to be restricted for people with such disabilities in seeking advantages from job opportunities. On the basis of these findings, it can be implied that the information gathered through this study will serve to be highly beneficial for Saudi Arabian schools/ rehabilitation centres for individuals with intellectual disability to facilitate them in overcoming the problems they encounter during the transition to work.

Keywords: intellectual disability, transition services, rehabilitation centre, employment

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Authors: Michelle Eichinger, Upali Nanda

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Behavior choices during college years can establish the pattern of lifelong healthy living. Nearly 1/3rd of American college students are either overweight (25 < BMI < 30) or obese (BMI > 30). In addition, overweight/obesity contributes to depression, which is a rising epidemic among college students, affecting academic performance and college drop-out rates. Overweight and obesity result in an imbalance of energy consumption (diet) and energy expenditure (physical activity). Overweight/obesity is a significant contributor to heart disease, diabetes, stroke, physical disabilities and some cancers, which are the leading causes of death and disease in the US. There has been a significant increase in obesity and obesity-related disorders such as type 2 diabetes, hypertension, and dyslipidemia among people in their teens and 20s. Historically, the evidence-based interventions for obesity prevention focused on changing the health behavior at the individual level and aimed at increasing awareness and educating people about nutrition and physical activity. However, it became evident that the environmental context of where people live, work and learn was interdependent to healthy behavior change. As a result, a comprehensive approach was required to include altering the social and built environment to support healthy living. College campus provides opportunities to support lifestyle behavior and form a health-promoting culture based on some key point of decisions such as stairs/ elevator, walk/ bike/ car, high-caloric and fast foods/balanced and nutrient-rich foods etc. At each point of decision, design, can help/hinder the healthier choice. For example, stair well design and motivational signage support physical activity; grocery store/market proximity influence healthy eating etc. There is a need to collate the vast information that is in planning and public health domains on a range of successful point of decision prompts, and translate it into architectural guidelines that help define the edge condition for critical point of decision prompts. This research study aims to address healthy behaviors through the built environment with the questions, how can we make the healthy choice an easy choice through the design of critical point of decision prompts? Our hypothesis is that well-designed point of decision prompts in the built environment of college campuses can promote healthier choices by students, which can directly impact mental and physical health related to obesity. This presentation will introduce a combined health and architectural framework aimed to influence healthy behaviors through design applied for college campuses. The premise behind developing our concept, point-of-decision design (PODD), is healthy decision-making can be built into, or afforded by our physical environments. Using effective design intervention strategies at these 'points-of-decision' on college campuses to make the healthy decision the default decision can be instrumental in positively impacting health at the population level. With our model, we aim to advance health research by utilizing point-of-decision design to impact student health via core sectors of influences within college settings, such as campus facilities and transportation. We will demonstrate how these domains influence patterns/trends in healthy eating and active living behaviors among students. how these domains influence patterns/trends in healthy eating and active living behaviors among students.

Keywords: architecture and health promotion, college campus, design strategies, health in built environment

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Authors: Alice D. Dioquino, Olivia N. Buzon, Emilio F. Aguinaldo, Ruel Avila, Erwin R. Callo, Cristy Ocampo, Malvin R. Tabajen, Marla C. Papango, Marilou M. Ubina, Josephine Tondo, Cromwell L. Valeriano

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The main purpose of this study was to develop, evaluate and validate courseware on Selected Topics in Mathematics, Science, and the English Language. Specifically, it aimed to: 1. Identify the appropriate Instructional Systems Design (ISD) model in the development of the courseware material; 2. Assess the courseware material according to its: a. Content Characteristics; b. Instructional Characteristics; and c. Technical Characteristics 3. Find out if there is a significant difference in the performance of students before and after using the tutorial CAI. This research is developmental as well as a one group pretest-posttest design. The study had two phases. Phase I includes the needs analysis, writing of lessons and storyboard by the respective experts in each field. Phase II includes the digitization or the actual development of the courseware by the faculty of the ICT department. In this phase it adapted an instructional systems design (ISD) model which is the ADDIE model. ADDIE stands for Analysis, Design, Development, Implementation and Evaluation. Formative evaluation was conducted simultaneously with the different phases to detect and remedy any bugs in the courseware along the areas of content, instructional and technical characteristics. The expected output are the digitized lessons in Algebra, Biology, Chemistry, Physics and Communication Arts in English. Students and some IT experts validated the CAI material using the Evaluation Form by Wong & Wong. They validated the CAI materials as Highly Acceptable with an overall mean rating of 4.527and standard deviation of 0 which means that they were one in the ratings they have given the CAI materials. A mean gain was recorded and computing the t-test for dependent samples it showed that there were significant differences in the mean achievement of the students before and after the treatment (using CAI). The identified ISD model used in the development of the tutorial courseware was the ADDIE model. The quantitative analyses of data based on ratings given by the respondents’ shows that the tutorial courseware possess the characteristics and or qualities of a very good computer-based courseware. The ratings given by the different evaluators with regard to content, instructional, and technical aspects of the Tutorial Courseware are in conformity towards being excellent. Students performed better in mathematics, biology chemistry, physics and the English Communication Arts after they were exposed to the tutorial courseware.

Keywords: CAI, tutorial courseware, Instructional Systems Design (ISD) Model, education

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Authors: Torsten Hermanns, Thoufik Al Khawli, Wolfgang Schulz

Abstract:

In laser cutting as well as in long pulsed laser drilling of metals, it can be demonstrated that the ablation shape (the shape of cut faces respectively the hole shape) that is formed approaches a so-called asymptotic shape such that it changes only slightly or not at all with further irradiation. These findings are already known from the ultrashort pulse (USP) ablation of dielectric and semiconducting materials. The explanation for the occurrence of an asymptotic shape in laser cutting and long pulse drilling of metals is identified, its underlying mechanism numerically implemented, tested and clearly confirmed by comparison with experimental data. In detail, there now is a model that allows the simulation of the temporal (pulse-resolved) evolution of the hole shape in laser drilling as well as the final (asymptotic) shape of the cut faces in laser cutting. This simulation especially requires much less in the way of resources, such that it can even run on common desktop PCs or laptops. Individual parameters can be adjusted using sliders – the simulation result appears in an adjacent window and changes in real time. This is made possible by an application-specific reduction of the underlying ablation model. Because this reduction dramatically decreases the complexity of calculation, it produces a result much more quickly. This means that the simulation can be carried out directly at the laser machine. Time-intensive experiments can be reduced and set-up processes can be completed much faster. The high speed of simulation also opens up a range of entirely different options, such as metamodeling. Suitable for complex applications with many parameters, metamodeling involves generating high-dimensional data sets with the parameters and several evaluation criteria for process and product quality. These sets can then be used to create individual process maps that show the dependency of individual parameter pairs. This advanced simulation makes it possible to find global and local extreme values through mathematical manipulation. Such simultaneous optimization of multiple parameters is scarcely possible by experimental means. This means that new methods in manufacturing such as self-optimization can be executed much faster. However, the software’s potential does not stop there; time-intensive calculations exist in many areas of industry. In laser welding or laser additive manufacturing, for example, the simulation of thermal induced residual stresses still uses up considerable computing capacity or is even not possible. Transferring the principle of reduced models promises substantial savings there, too.

Keywords: asymptotic ablation shape, interactive process simulation, laser drilling, laser cutting, metamodeling, reduced modeling

Procedia PDF Downloads 197

Authors: Rutcher M. Lacaza, Stephen Jun V. Villejo

Abstract:

This paper investigated the patterns of private transfers in the Philippines using the Family Income Expenditure Survey (FIES) 2009, conducted by the Philippine government’s National Statistics Office (NSO) every three years. The paper performed bivariate analysis on net transfers, using the identified determinants for a household to be either a net receiver or a net giver. The household characteristics considered are the following: age, sex, marital status, employment status and educational attainment of the household head, and also size, location, pre-transfer income and the number of employed members of the household. The variables net receiver and net giver are determined by computing the net transfer, subtracting total gifts from total receipts. The receipts are defined as the sum of cash received from abroad, cash received from domestic sources, total gifts received and inheritance. While gifts are defined as the sum of contributions and donations to church and other religious institutions, contributions and donations to other institutions, gifts and contributions to others, and gifts and assistance to private individuals outside the family. Both in kind and in cash transfers are considered in the analysis. It also performed a multiple regression analysis on transfers received and income including other household characteristics to examine the motives for giving transfers – whether altruism or exchanged. It also used the binary logistic regression to estimate the probability of being a net receiver or net giver given the household characteristics. The study revealed that receiving tends to be universal – both the non-poor and the poor benefit although the poor receive substantially less than the non-poor. Regardless of whether households are net receivers or net givers, households in the upper deciles generally give and receive more than those in the lower deciles. It also appears that private transfers may just flow within economic groups. Big amounts of transfers are, therefore, directed to the non-poor and the small amounts go to the poor. This was also supported by the increasing function of gross transfers received and the income of households – the poor receiving less and the non-poor receiving more. This is contrary to the theory that private transfers can help equalize the distribution of income. This suggested that private transfers in the Philippines are not altruistically motivated but exchanged. However, bilateral data on transfers received or given is needed to test this theory directly. The results showed that transfers are much needed by the poor and it is important to understand the nature of private transfers, to ensure that government transfer programs are properly designed and targeted so as to prevent the duplication of private safety nets already present among the non-poor.

Keywords: private transfers, net receiver, net giver, altruism, exchanged.

Procedia PDF Downloads 190