Search results for: contractual complexity

Authors: D. W. M. S. Samarathunga, Isuru Dharmarathne

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In aphasia, various levels of symbolic language processing (semantics) are affected. It is shown that Persons with Aphasia (PWA) often experience more problems comprehending some categories of words than others. The study aimed to determine lexical semantic deficits seen in Auditory Comprehension (AC) and to describe lexical-semantic deficits across six selected word categories. Thirteen (n =13) persons diagnosed with post-stroke aphasia (PSA) were recruited to perform an AC task. Foods, objects, clothes, vehicles, body parts and animals were selected as the six categories. As the test stimuli, black and white line drawings were adapted from a picture set developed for semantic studies by Snodgrass and Vanderwart. A pilot study was conducted with five (n=5) healthy nonbrain damaged Sinhala speaking adults to decide familiarity and applicability of the test material. In the main study, participants were scored based on the accuracy and number of errors shown. The results indicate similar trends of lexical semantic deficits identified in the literature confirming ‘animals’ to be the easiest category to comprehend. Mann-Whitney U test was performed to determine the association between the selected variables and the participants’ performance on AC task. No statistical significance was found between the errors and the type of aphasia reflecting similar patterns described in aphasia literature in other languages. The current study indicates the presence of selectivity of lexical semantic deficits in AC and a hierarchy was developed based on the complexity of the categories to comprehend by Sinhala speaking PWA, which might be clinically beneficial when improving language skills of Sinhala speaking persons with post-stroke aphasia. However, further studies on aphasia should be conducted with larger samples for a longer period to study deficits in Sinhala and other Sri Lankan languages (Tamil and Malay).

Keywords: aphasia, auditory comprehension, selective lexical-semantic deficits, semantic categories

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Authors: Julia Zimmerman, Gaurav Savant

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This study aims to evaluate the efficacy of the U.S. Army Corp of Engineers’ River Analysis System (HEC-RAS) application to modeling the hydraulics of estuaries. HEC-RAS has been broadly used for a variety of riverine applications. However, it has not been widely applied to the study of circulation in estuaries. This report details the model development and validation of a combined 1D/2D unsteady flow hydraulic model using HEC-RAS for estuaries and they are associated with tidally influenced rivers. Two estuaries, Galveston Bay and Delaware Bay, were used as case studies. Galveston Bay, a bar-built, vertically mixed estuary, was modeled for the 2005 calendar year. Delaware Bay, a drowned river valley estuary, was modeled from October 22, 2019, to November 5, 2019. Water surface elevation was used to validate both models by comparing simulation results to NOAA’s Center for Operational Oceanographic Products and Services (CO-OPS) gauge data. Simulations were run using the Diffusion Wave Equations (DW), the Shallow Water Equations, Eulerian-Lagrangian Method (SWE-ELM), and the Shallow Water Equations Eulerian Method (SWE-EM) and compared for both accuracy and computational resources required. In general, the Diffusion Wave Equations results were found to be comparable to the two Shallow Water equations sets while requiring less computational power. The 1D/2D combined approach was valid for study areas within the 2D flow area, with the 1D flow serving mainly as an inflow boundary condition. Within the Delaware Bay estuary, the HEC-RAS DW model ran in 22 minutes and had an average R² value of 0.94 within the 2-D mesh. The Galveston Bay HEC-RAS DW ran in 6 hours and 47 minutes and had an average R² value of 0.83 within the 2-D mesh. The longer run time and lower R² for Galveston Bay can be attributed to the increased length of the time frame modeled and the greater complexity of the estuarine system. The models did not accurately capture tidal effects within the 1D flow area.

Keywords: Delaware bay, estuarine hydraulics, Galveston bay, HEC-RAS, one-dimensional modeling, two-dimensional modeling

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Authors: Maiko Kiyohara, Toshiki Ito

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In this study, we used a psychotherapy process for patient with dissociative disorder and the graphic Rorschach (Digital version) (GRD). A dissociative disorder is a type of dissociation characterized by multiple alternating personalities (also called alternate identity or another identity). "dissociation" is a state in which consciousness, memory, thinking, emotion, perception, behavior, body image, and so on are divided and experienced. Dissociation symptoms, such as lack of memory, are seen, and the repetition of blanks in daily events causes serious problems in life. Although the pathological mechanism of dissociation has not yet been fully elucidated, it is said that it is caused by childhood abuse or shocking trauma. In case of Japan, no reliable data has been reported on the number of patients and prevalence of dissociative disorders, no drug is compatible with dissociation symptoms, and no clear treatment has been established. GRD is a method that the author revised in 2017 to a Graphic Rorschach, which is a special technique for subjects to draw language responses when enforce Rorschach. GRD reduces the burden on both the subject and the examiner, reduces the complexity of organizing data, improves the simplicity of organizing data, and improves the accuracy of interpretation by introducing a tablet computer during the drawing reaction. We are conducting research for the purpose. The patient in this case is a woman in her 50s, and has multiple personalities since childhood. At present, there are about 10 personalities whose main personality is just grasped. The patients is raising her junior high school sons as single parent, but personal changes often occur at home, which makes the home environment inferior and economically oppressive, and has severely hindered daily life. In psychotherapy, while a personality different from the main personality has appeared, I have also conducted psychotherapy with her son. In this case, the psychotherapy process and the GRD were performed to understand the personality characteristics, and the possibility of therapeutic significance to personality integration is reported.

Keywords: GRD, dissociative disorder, a case study of psychotherapy process, dissociation

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Authors: Rajashree Naik, Laxmi Kant Sharma

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Sambhar lake is the largest inland Salt Lake of India, declared as a Ramsar site on 23 March 1990. Due to high salinity and alkalinity condition its biodiversity richness is contributed by haloalkaliphilic flora and fauna along with the diverse land cover including waterbody, wetland, salt crust, saline soil, vegetation, scrub land and barren land which welcome large number of flamingos and other migratory birds for winter harboring. But with the gradual increase in the irrational salt extraction activities, the ecological diversity is at stake. There is an urgent need to assess the ecosystem. Advanced technology like remote sensing and GIS has enabled to look into the past, compare with the present for the future planning and management of the natural resources in a judicious way. This paper is a research work intended to present a vegetation in typical inland lake environment of Sambhar wetland using satellite data of NASA’s EO-1 Hyperion sensor launched in November 2000. With the spectral range of 0.4 to 2.5 micrometer at approximately 10nm spectral resolution with 242 bands 30m spatial resolution and 705km orbit was used to produce a vegetation map for a portion of the wetland. The vegetation map was tested for classification accuracy with a pre-existing detailed GIS wetland vegetation database. Though the accuracy varied greatly for different classes the algal communities were successfully identified which are the major sources of food for flamingo. The results from this study have practical implications for uses of spaceborne hyperspectral image data that are now becoming available. Practical limitations of using these satellite data for wetland vegetation mapping include inadequate spatial resolution, complexity of image processing procedures, and lack of stereo viewing.

Keywords: Algal community, NASA’s EO-1 Hyperion, salt-tolerant species, wetland vegetation mapping

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Authors: Salim Al Harthy, Alexandre A. Bachkirov

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This study delves into the complexities of competitive aggressiveness in the oil and gas industry, focusing on the characteristics of the identified competitive actions. The current quantitative research on competitive aggressiveness lacks agreement on the connection between antecedents and outcomes, prompting a qualitative investigation. To address this gap, the research utilizes qualitative interviews with CEOs from Oman's oil and gas service industry to explore the dynamics of competitive aggressiveness. Using Noklenain's typology, the study categorizes and analyzes identified actions, shedding light on the spectrum of competitive behaviors within the industry. Notably, actions predominantly fall under the "Bring about" and "Preserve" elements, with a notable absence in the "Forebear" and "Destroy" categories, possibly linked to the study's focus on service-oriented businesses. The study also explores the detectability of actions, revealing that "Bring about" actions are detectable, while those in "Preserve" and "Suppress" are not. This challenges conventional definitions of competitive aggressiveness, suggesting that not all actions are readily detectable despite being considered competitive. The presence of non-detectable actions introduces complexity to measurement methods reliant on visible empirical data. Moreover, the study contends that companies can adopt an aggressive competitive approach without directly challenging rivals. This challenges traditional views and emphasizes the innovative and entrepreneurial aspects of actions not explicitly aimed at competitors. By not revealing strategic intentions, such actions put rivals at a disadvantage, underscoring the need for a nuanced understanding of competitive aggressiveness. In summary, the lack of consensus in existing literature regarding the relationship between antecedents and outcomes in competitive aggressiveness is addressed. The study reveals a spectrum of detectable and undetectable actions, posing challenges in measurement and emphasizing the need for alternative methods to assess undetectable actions in competitive behavior. This research contributes to a more nuanced understanding of competitive aggressiveness, acknowledging the diverse actions shaping a company's strategic positioning in dynamic business environments.

Keywords: competitive aggressiveness, qualitative exploration, noklenain's typology, oil and gas industry

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Authors: Jian-Heng Wu, Bor-Shen Lin

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The temperature-salinity relationship is one of the most important characteristics used for identifying water masses in marine research. Temperature-salinity characteristics, however, may change dynamically with respect to the geographic location and is quite sensitive to the depth at the same location. When depth is taken into consideration, however, it is not easy to compare the characteristics of different water masses efficiently for a wide range of areas of the ocean. In this paper, the Gaussian mixture model was proposed to analyze the temperature-salinity-depth characteristics of water masses, based on which comparison between water masses may be conducted. Gaussian mixture model could model the distribution of a random vector and is formulated as the weighting sum for a set of multivariate normal distributions. The temperature-salinity-depth data for different locations are first used to train a set of Gaussian mixture models individually. The distance between two Gaussian mixture models can then be defined as the weighting sum of pairwise Bhattacharyya distances among the Gaussian distributions. Consequently, the distance between two water masses may be measured fast, which allows the automatic and efficient comparison of the water masses for a wide range area. The proposed approach not only can approximate the distribution of temperature, salinity, and depth directly without the prior knowledge for assuming the regression family, but may restrict the complexity by controlling the number of mixtures when the amounts of samples are unevenly distributed. In addition, it is critical for knowledge discovery in marine research to represent, manage and share the temperature-salinity-depth characteristics flexibly and responsively. The proposed approach has been applied to a real-time visualization system of ocean data, which may facilitate the comparison of water masses by aggregating the data without degrading the discriminating capabilities. This system provides an interface for querying geographic locations with similar temperature-salinity-depth characteristics interactively and for tracking specific patterns of water masses, such as the Kuroshio near Taiwan or those in the South China Sea.

Keywords: water mass, Gaussian mixture model, data visualization, system framework

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Authors: Vishal Pareek, Shubham Gupta, Sushil Chandra Jain

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With increasing high-speed computation demand the power consumption, heat dissipation and chip size issues are posing challenges for logic design with conventional technologies. Recovery of bit loss and bit errors is other issues that require reversibility and fault tolerance in the computation. The reversible computing is emerging as an alternative to conventional technologies to overcome the above problems and helpful in a diverse area such as low-power design, nanotechnology, quantum computing. Bit loss issue can be solved through unique input-output mapping which require reversibility and bit error issue require the capability of fault tolerance in design. In order to incorporate reversibility a number of combinational reversible logic based circuits have been developed. However, very few sequential reversible circuits have been reported in the literature. To make the circuit fault tolerant, a number of fault model and test approaches have been proposed for reversible logic. In this paper, we have attempted to incorporate fault tolerance in sequential reversible building blocks such as D flip-flop, T flip-flop, JK flip-flop, R-S flip-flop, Master-Slave D flip-flop, and double edge triggered D flip-flop by making them parity preserving. The importance of this proposed work lies in the fact that it provides the design of reversible sequential circuits completely testable for any stuck-at fault and single bit fault. In our opinion our design of reversible building blocks is superior to existing designs in term of quantum cost, hardware complexity, constant input, garbage output, number of gates and design of online testable D flip-flop have been proposed for the first time. We hope our work can be extended for building complex reversible sequential circuits.

Keywords: parity preserving gate, quantum computing, fault tolerance, flip-flop, sequential reversible logic

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Authors: Batool Ismaeel, Umair Farooq, Saad Mushtaq

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Construction projects in the oil industry can be very complex, having unknown outcomes and uncertainties that cannot be easily predicted. Each project has its unique risks generated by a number of factors which, if not controlled, will impact the successful completion of the project mainly in terms of schedule, cost, quality, and safety. This paper highlights the historic risks associated with projects in the south and east region of Kuwait Oil Company (KOC) collated from the company’s lessons learned database. Starting from Contract Award through to handover of the project to the Asset owner, the gaps in project execution in terms of managing risk will be brought to discussion and where a well-defined systematic approach in project risk management reflecting many claims, change of scope, exceeding budget, delays in engineering phase as well as in the procurement and fabrication of long lead items should be adopted. This study focuses on a proposed feasible approach in risk management for engineering, procurement and construction (EPC) level projects including the various stakeholders involved in executing the works from International to local contractors and vendors in KOC. The proposed approach covers the areas categorized into organizational, design, procurement, construction, pre-commissioning, commissioning and project management in which the risks are identified and require management and mitigation. With the effective deployment and implementation of the proposed risk management system and the consideration of it as a vital key in achieving the project’s target, the outcomes will be more predictable in the future, and the risk triggers will be managed and controlled. The correct resources can be allocated on a timely basis for the company for avoiding any unpredictable outcomes during the execution of the project. It is recommended in this paper to apply this risk management approach as an integral part of project management and investigate further in the future, the effectiveness of this proposed system for newly awarded projects and compare the same with those projects of similar budget/complexity that have not applied this approach to risk management.

Keywords: construction, project completion, risk management, uncertainties

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Authors: Joseph Udofia, Isaac Olufadewa

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Everyday, the size of Electronic Health Records data keeps increasing as new patients visit health practitioner and returning patients fulfil their appointments. As these data grow, so is their susceptibility to cyber-attacks from criminals waiting to exploit this data. In the US, the damages for cyberattacks were estimated at $8 billion (2018), $11.5 billion (2019) and $20 billion (2021). These attacks usually involve the exposure of PII. Health data is considered PII, and its exposure carry significant impact. To this end, an enhancement of Health Policy and Standards in relation to data security, especially among patients and their clinical providers, is critical to ensure ethical practices, confidentiality, and trust in the healthcare system. As Clinical accelerators and applications that contain user data are used, it is expedient to have a review and revamp of policies like the Payment Card Industry Data Security Standard (PCI DSS), the Health Insurance Portability and Accountability Act (HIPAA), the Fast Healthcare Interoperability Resources (FHIR), all aimed to ensure data protection and security in healthcare. FHIR caters for healthcare data interoperability, FHIR caters to healthcare data interoperability, as data is being shared across different systems from customers to health insurance and care providers. The astronomical cost of implementation has deterred players in the space from ensuring compliance, leading to susceptibility to data exfiltration and data loss on the security accuracy of protected health information (PHI). Though HIPAA hones in on the security accuracy of protected health information (PHI) and PCI DSS on the security of payment card data, they intersect with the shared goal of protecting sensitive information in line with industry standards. With advancements in tech and the emergence of new technology, it is necessary to revamp these policies to address the complexity and ambiguity, cost barrier, and ever-increasing threats in cyberspace. Healthcare data in the wrong hands is a recipe for disaster, and we must enhance its protection and security to protect the mental health of the current and future generations.

Keywords: cloud security, healthcare, cybersecurity, policy and standard

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Authors: Lourenço Bastos, Filipa Carneiro, Bruno Vale, Rita Marques Joana Silva, Ricardo Freitas, Ângelo Marques, Sara Cortez, Alberta Coelho, Pedro Parreira, Liliana Sousa, Anabela Salgueiro, Bruno Silva

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The process of flushing is considered to be an adequate technique to reduce the risk of infection during the clinical practice of venous catheterization. Nonetheless, there is still a lack of adhesion to this method, in part due to the complexity of this procedure. The project SeringaDuo aimed to develop an innovative double-chamber syringe for intravenous sequential administration of drugs and serums. This device served the purpose of improving the adherence to the practice, through the reduction of manipulations needed, which also improves patient safety, and though the promotion of flushing practice by health professionals, by simplifying this task. To assist on the development of this innovative syringe, a numerical methodology was developed and validated in order to predict the syringe’s mechanical and flow behavior during the fluids’ loading and administration phases, as well as to allow the material behavior evaluation during its production. For this, three commercial numerical simulation software was used, namely ABAQUS, ANSYS/FLUENT, and MOLDFLOW. This methodology aimed to evaluate the concepts feasibility and to optimize the geometries of the syringe’s components, creating this way an iterative process for product development based on numerical simulations, validated by the production of prototypes. Through this methodology, it was possible to achieve a final design that fulfils all the characteristics and specifications defined. This iterative process based on numerical simulations is a powerful tool for product development that allows obtaining fast and accurate results without the strict need for prototypes. An iterative process can be implemented, consisting of consecutive constructions and evaluations of new concepts, to obtain an optimized solution, which fulfils all the predefined specifications and requirements.

Keywords: Venous catheterization, flushing, syringe, numerical simulation

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Authors: Kingston Rajiah, Mari Kannan Maharajan, Si Jen Yeen, Sara Lew

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Parkinson’s disease (PD) is a progressive neurodegenerative disorder with evolving layers of complexity. Both motor and non-motor symptoms of PD may affect patients’ quality of life (QoL). Life expectancy for an individual with Parkinson’s disease depends on the level of care the individual has access to, can have a direct impact on length of life. Therefore, improvement of the QoL is a significant part of therapeutic plans. Patients with PD, especially those who are in advanced stages, are in great need of assistance, mostly from their family members or caregivers in terms of medical, emotional, and social support. The role of a caregiver becomes increasingly important with the progression of PD, the severity of motor impairment and increasing age of the patient. The nature and symptoms associated with PD can place significant stresses on the caregivers’ burden. As the prevalence of PD is estimated to more than double by 2030, it is important to recognize and alleviate the burden experienced by caregivers. This study focused on the impact of the clinical features on the QoL of PD patients, and of their caregivers. This study included PD patients along with their caregivers and was undertaken at the Malaysian Parkinson's Disease Association from June 2016 to November 2016. Clinical features of PD patients were assessed using the Movement Disorder Society revised Unified Parkinson Disease Rating Scale (MDS-UPDRS); the Hoehn and Yahr Staging of Parkinson's Disease were used to assess the severity and Parkinson's disease activities of daily living scale were used to assess the disability of Parkinson’s disease patients. QoL of PD patients was measured using the Parkinson's Disease Questionnaire-39 (PDQ-39). The revised version of the Zarit Burden Interview assessed caregiver burden. At least one of the clinical features affected PD patients’ QoL, and at least one of the QoL domains affected the caregivers’ burden. Clinical features ‘Saliva and Drooling’, and ‘Dyskinesia’ explained 29% of variance in QoL of PD patients. The QoL domains ‘stigma’, along with ‘emotional wellbeing’ explained 48.6% of variance in caregivers’ burden. Clinical features such as saliva, drooling and dyskinesia affected the QoL of PD patients. The PD patients’ QoL domains such as ‘stigma’ and ‘emotional well-being’ influenced their caregivers’ burden.

Keywords: carers, quality of life, clinical features, Malaysia

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Authors: Mehena Fedoul

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This paper examines the intersection of race, gender, and disability through a Critical disability race theory and black feminist disability perspective in Keah Brown's memoir, "The Pretty One." The background of the study highlights the significance of intersectionality in understanding the multifaceted experiences of individuals who navigate multiple marginalized identities. The study contributes to the underrepresented field of disability studies from a Critical race and black feminist perspectives, shedding light on the unique challenges and resilience of black disabled women. The study employs a qualitative analysis of Keah Brown's memoir as a primary text. Drawing on intersectionality theory and black feminist disability scholarship, the analysis focuses on how Brown's memoir illuminates the ways in which her race, gender, and disability intersect and shape her lived experiences. The analysis reveals how Brown's memoir challenges traditional notions of disability, beauty, and empowerment through her unapologetic celebration of her blackness, femaleness, and disability. The major findings of the study indicate that Brown's memoir provides a powerful narrative of the complexity, uniqueness and richness of the lived experiences of black disabled women. It demonstrates how the intersectionality of race, gender, and disability shapes Brown's identity, body image, relationships, and societal interactions. The paper also highlights how Brown's memoir emphasizes the importance of inclusivity and intersectionality in understanding and addressing the challenges faced by black disabled women. In conclusion, this study offers a critical analysis of the intersection of race, gender, and disability in Keah Brown's memoir, "The Pretty One," from a black feminist disability perspective. It contributes to the growing body of literature that recognizes the significance of intersectionality in understanding the experiences of marginalized individuals in the disability community. The study underscores the need for more inclusive and intersectional perspectives in disability studies and advocates for greater recognition of the voices and experiences of black disabled women in academic and societal discourse.

Keywords: Intersectionality, black feminism, disability studies, keah brown

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Authors: T. Praveenkumar, Kulpreet Singh, Divy Bhanpuriya, M. Saimurugan

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This study analysed the classification accuracy for gearbox faults using Machine Learning Techniques. Gearboxes are widely used for mechanical power transmission in rotating machines. Its rotating components such as bearings, gears, and shafts tend to wear due to prolonged usage, causing fluctuating vibrations. Increasing the dependability of mechanical components like a gearbox is hampered by their sealed design, which makes visual inspection difficult. One way of detecting impending failure is to detect a change in the vibration signature. The current study proposes various machine learning algorithms, with aid of these vibration signals for obtaining the fault classification accuracy of an automotive 4-Speed synchromesh gearbox. Experimental data in the form of vibration signals were acquired from a 4-Speed synchromesh gearbox using Data Acquisition System (DAQs). Statistical features were extracted from the acquired vibration signal under various operating conditions. Then the extracted features were given as input to the algorithms for fault classification. Supervised Machine Learning algorithms such as Support Vector Machines (SVM) and unsupervised algorithms such as Deep Feed Forward Neural Network (DFFNN), Deep Belief Networks (DBN) algorithms are used for fault classification. The fusion of DBN & DFFNN classifiers were architected to further enhance the classification accuracy and to reduce the computational complexity. The fault classification accuracy for each algorithm was thoroughly studied, tabulated, and graphically analysed for fused and individual algorithms. In conclusion, the fusion of DBN and DFFNN algorithm yielded the better classification accuracy and was selected for fault detection due to its faster computational processing and greater efficiency.

Keywords: deep belief networks, DBN, deep feed forward neural network, DFFNN, fault diagnosis, fusion of algorithm, vibration signal

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Authors: Mst Shapna Akter, Hossain Shahriar

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One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a largescale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of opensource functions that point to potential exploits. We developed an efficient and scalable vulnerability detection method based on deep neural network models that learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the dependency. Moreover, we keep the semantic and syntactic information using state-of-the-art word embedding algorithms such as glove and fastText. The embedded vectors are subsequently fed into deep learning networks such as LSTM, BilSTM, LSTM-Autoencoder, word2vec, BERT, and GPT-2 to classify the possible vulnerabilities. Furthermore, we proposed a neural network model which can overcome issues associated with traditional neural networks. Evaluation metrics such as f1 score, precision, recall, accuracy, and total execution time have been used to measure the performance. We made a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. We found that all of the deep learning models provide comparatively higher accuracy when we use semantic and syntactic information as the features but require higher execution time as the word embedding the algorithm puts on a bit of complexity to the overall system.

Keywords: cyber security, vulnerability detection, neural networks, feature extraction

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Authors: Rahul Paul, Peter Mctaggart, Luke Skinner

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Maintaining public safety and network reliability are the core objectives of all electricity distributors globally. For many electricity distributors, managing vegetation clearances from their above ground assets (poles and conductors) is the most important and costly risk mitigation control employed to meet these objectives. Light Detection And Ranging (LiDAR) is widely used by utilities as a cost-effective method to inspect their spatially-distributed assets at scale, often captured using high powered LiDAR scanners attached to fixed wing or rotary aircraft. The resulting 3D point cloud model is used by these utilities to perform engineering grade measurements that guide the prioritisation of vegetation cutting programs. Advances in computer vision and machine-learning approaches are increasingly applied to increase automation and reduce inspection costs and time; however, real-world LiDAR capture variables (e.g., aircraft speed and height) create complexity, noise, and missing data, reducing the effectiveness of these approaches. This paper proposes a method for identifying each conductor from LiDAR data via clustering methods that can precisely reconstruct conductors in complex real-world configurations in the presence of high levels of noise. It proposes 3D catenary models for individual clusters fitted to the captured LiDAR data points using a least square method. An iterative learning process is used to identify potential conductor models between pole pairs. The proposed method identifies the optimum parameters of the catenary function and then fits the LiDAR points to reconstruct the conductors.

Keywords: point cloud, LİDAR data, machine learning, computer vision, catenary curve, vegetation management, utility industry

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Authors: Lukasz Mierczak, Patrick Denke, Piotr Klimczyk, Stefan Siebert

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Due to the high complexity of the magnetization in electrical machines and influence of the manufacturing processes on the magnetic properties of their components, the assessment and prediction of hysteresis and eddy current losses has remained a challenge. In the design process of electric motors and generators, the power losses of stators and rotors are calculated based on the material supplier’s data from standard magnetic measurements. This type of data does not include the additional loss from non-sinusoidal multi-harmonic motor excitation nor the detrimental effects of residual stress remaining in the motor laminations after manufacturing processes, such as punching, housing shrink fitting and winding. Moreover, in production, considerable attention is given to the measurements of mechanical dimensions of stator and rotor cores, whereas verification of their magnetic properties is typically neglected, which can lead to inconsistent efficiency of assembled motors. Therefore, to enable a comprehensive characterization of motor materials and components, Brockhaus Measurements developed a range of in-line and offline measurement technologies for testing their magnetic properties under actual motor operating conditions. Multiple sets of experimental data were obtained to evaluate the influence of various factors, such as elevated temperature, applied and residual stress, and arbitrary magnetization on the magnetic properties of different grades of non-oriented steel. Measured power loss for tested samples and stator cores varied significantly, by more than 100%, comparing to standard measurement conditions. Quantitative effects of each of the applied measurement were analyzed. This research and applied Brockhaus measurement methodologies emphasized the requirement for advanced characterization of magnetic materials used in electric drives and automotive applications.

Keywords: magnetic materials, measurement technologies, permanent magnets, stator and rotor cores

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Authors: Medha Basu, Kumardeb Banerjee, Dipak Ghosh

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After the massive blow of the COVID-19 pandemic, several health hazards have been reported all over the world. Serious cases of Major Depressive Disorder (MDD) are seen to be common in about 15% of the global population, making depression one of the leading mental health diseases, as reported by the World Health Organization. Various psychological and pharmacological treatment techniques are regularly being reported. Music, a globally accepted mode of entertainment, is often used as a therapeutic measure to treat various health conditions. We have tried to understand how Indian Classical Music can affect the overall well-being of the human brain. A case study has been reported here, where a Flute-rendition has been chosen from a detailed audience response survey, and the effects of that clip on human brain conditions have been studied from both psychological and neural perspectives. Taking help from internationally-accepted depression-rating scales, two questionnaires have been designed to understand both the prolonged and immediate effect of music on various emotional states of human lives. Thereafter, from EEG experiments on 5 participants using the same clip, the parameter ‘ALAY’, alpha frontal asymmetry (alpha power difference of right and left frontal hemispheres), has been calculated. Works of Richard Davidson show that an increase in the ‘ALAY’ value indicates a decrease in depressive symptoms. Using the non-linear technique of MFDFA on EEG analysis, we have also calculated frontal asymmetry using the complexity values of alpha-waves in both hemispheres. The results show a positive correlation between both the psychological survey and the EEG findings, revealing the prominent role of music on the human brain, leading to a decrease in mental unrest and an increase in overall well-being. In this study, we plan to propose the scientific foundation of music therapy, especially from a neurocognition perspective, with appropriate neural bio-markers to understand the positive and remedial effects of music on the human brain.

Keywords: music therapy, EEG, psychological survey, frontal alpha asymmetry, wellbeing

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Authors: Ebru Cubukcu, Gozde Eksioglu Cetintahra, Burcin Hepguzel Hatip, Mert Cubukcu

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Obesity and overweight cause serious health problems. Public and private organizations aim to encourage walking in various ways in order to cope with the problem of obesity and overweight. This study aims to understand how the spatial characteristics of urban street pattern, connectivity and complexity influence young people’s choice to walk or not. 185 public university students in Izmir, the third largest city in Turkey, participated in the study. Each participant had worn an accelerometer and a global positioning (GPS) device for a week. The accelerometer device records data on the intensity of the participant’s activity at a specified time interval, and the GPS device on the activities’ locations. Combining the two datasets, activity maps are derived. These maps are then used to differentiate the participants’ walk trips and motor vehicle trips. Given that, the frequency of walk and motor vehicle trips are calculated at the street segment level, and the street segments are then categorized into two as ‘preferred by pedestrians’ and ‘preferred by motor vehicles’. Graph Theory-based accessibility indices are calculated to quantify the spatial characteristics of the streets in the sample. Six different indices are used: (I) edge density, (II) edge sinuosity, (III) eta index, (IV) node density, (V) order of a node, and (VI) beta index. T-tests show that the index values for the ‘preferred by pedestrians’ and ‘preferred by motor vehicles’ are significantly different. The findings indicate that the spatial characteristics of the street network have a measurable effect on young people’s choice to walk or not. Policy implications are discussed. This study is funded by the Scientific and Technological Research Council of Turkey, Project No: 116K358.

Keywords: graph theory, walkability, accessibility, street network

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Authors: Bin Feng, Zhulin Zong

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Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

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Authors: Zahid Ullah, Atlas Khan

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This research endeavors to explore the regularity properties associated with a specific class of equations, namely extremely degenerate elliptic equations. These equations hold significance in understanding complex physical systems like porous media flow, with applications spanning various branches of mathematics. The focus is on unraveling and analyzing regularity results to gain insights into the smoothness of solutions for these highly degenerate equations. Elliptic equations, fundamental in expressing and understanding diverse physical phenomena through partial differential equations (PDEs), are particularly adept at modeling steady-state and equilibrium behaviors. However, within the realm of elliptic equations, the subset of extremely degenerate cases presents a level of complexity that challenges traditional analytical methods, necessitating a deeper exploration of mathematical theory. While elliptic equations are celebrated for their versatility in capturing smooth and continuous behaviors across different disciplines, the introduction of degeneracy adds a layer of intricacy. Extremely degenerate elliptic equations are characterized by coefficients approaching singular behavior, posing non-trivial challenges in establishing classical solutions. Still, the exploration of extremely degenerate cases remains uncharted territory, requiring a profound understanding of mathematical structures and their implications. The motivation behind this research lies in addressing gaps in the current understanding of regularity properties within solutions to extremely degenerate elliptic equations. The study of extreme degeneracy is prompted by its prevalence in real-world applications, where physical phenomena often exhibit characteristics defying conventional mathematical modeling. Whether examining porous media flow or highly anisotropic materials, comprehending the regularity of solutions becomes crucial. Through this research, the aim is to contribute not only to the theoretical foundations of mathematics but also to the practical applicability of mathematical models in diverse scientific fields.

Keywords: elliptic equations, extremely degenerate, regularity results, partial differential equations, mathematical modeling, porous media flow

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Authors: M. Miljkovic, A. Urakpo, M. Simic-Koumoutsaris

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Benefit-risk assessment (BRA) is a valuable tool that takes place in multiple stages during a medicine's lifecycle, and this assessment can be conducted in a variety of ways. The aim was to summarize current BRA methods used during approval decisions and in post-approval settings and to see possible future directions. Relevant reviews, recommendations, and guidelines published in medical literature and through regulatory agencies over the past five years have been examined. BRA implies the review of two dimensions: the dimension of benefits (determined mainly by the therapeutic efficacy) and the dimension of risks (comprises the safety profile of a drug). Regulators, industry, and academia have developed various approaches, ranging from descriptive textual (qualitative) to decision-analytic (quantitative) models, to facilitate the BRA of medicines during the product lifecycle (from Phase I trials, to authorization procedure, post-marketing surveillance and health technology assessment for inclusion in public formularies). These approaches can be classified into the following categories: stepwise structured approaches (frameworks); measures for benefits and risks that are usually endpoint specific (metrics), simulation techniques and meta-analysis (estimation techniques), and utility survey techniques to elicit stakeholders’ preferences (utilities). All these approaches share the following two common goals: to assist this analysis and to improve the communication of decisions, but each is subject to its own specific strengths and limitations. Before using any method, its utility, complexity, the extent to which it is established, and the ease of results interpretation should be considered. Despite widespread and long-time use, BRA is subject to debate, suffers from a number of limitations, and currently is still under development. The use of formal, systematic structured approaches to BRA for regulatory decision-making and quantitative methods to support BRA during the product lifecycle is a standard practice in medicine that is subject to continuous improvement and modernization, not only in methodology but also in cooperation between organizations.

Keywords: benefit-risk assessment, benefit-risk profile, product lifecycle, quantitative methods, structured approaches

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Authors: Kiana Zeighami, Morteza Ozlati Moghadam

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Designing a high accuracy and high precision motion controller is one of the important issues in today’s industry. There are effective solutions available in the industry but the real-time performance, smoothness and accuracy of the movement can be further improved. This paper discusses a complete solution to carry out the movement of three stepper motors in three dimensions. The objective is to provide a method to design a fully integrated System-on-Chip (SOC)-based motion controller to reduce the cost and complexity of production by incorporating Field Programmable Gate Array (FPGA) into the design. In the proposed method the FPGA receives its commands from a host computer via wireless internet communication and calculates the motion trajectory for three axes. A profile generator module is designed to realize the interpolation algorithm by translating the position data to the real-time pulses. This paper discusses an approach to implement the linear interpolation algorithm, since it is one of the fundamentals of robots’ movements and it is highly applicable in motion control industries. Along with full profile trajectory, the triangular drive is implemented to eliminate the existence of error at small distances. To integrate the parallelism and real-time performance of FPGA with the power of Central Processing Unit (CPU) in executing complex and sequential algorithms, the NIOS II soft-core processor was added into the design. This paper presents different operating modes such as absolute, relative positioning, reset and velocity modes to fulfill the user requirements. The proposed approach was evaluated by designing a custom-made FPGA board along with a mechanical structure. As a result, a precise and smooth movement of stepper motors was observed which proved the effectiveness of this approach.

Keywords: 3-axis linear interpolation, FPGA, motion controller, micro-stepping

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Authors: Sinan Bilgen, Bekir Ozer Ay, Nilay Sezer Uzol

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After decades of conventional shapes, irregular forms with complex geometries are getting more popular for form generation of tall buildings all over the world. This trend has recently brought out diverse building forms such as twisting tall buildings. This study investigates both the aerodynamic and design features of twisting tall buildings through comparative analyses. Since twisting a tall building give rise to additional complexities related with the form and structural system, lateral load effects become of greater importance on these buildings. The aim of this study is to analyze the inherent characteristics of these iconic forms by comparing the wind loads on twisting tall buildings with those on their prismatic twins. Through a case study research, aerodynamic analyses of an existing twisting tall building and its prismatic counterpart were performed and the results have been compared. The prismatic twin of the original building were generated by removing the progressive rotation of its floors with the same plan area and story height. Performance-based measures under investigation have been evaluated in conjunction with the architectural design. Aerodynamic effects have been analyzed by both wind tunnel tests and computational methods. High frequency base balance tests and pressure measurements on 3D models were performed to evaluate wind load effects on a global and local scale. Comparisons of flat and real surface models were conducted to further evaluate the effects of the twisting form without façade texture contribution. Comparisons highlighted that, the twisting form under investigation shows better aerodynamic behavior both for along wind but particularly for across wind direction. Compared to the prismatic counterpart; twisting model is superior on reducing vortex-shedding dynamic response by disorganizing the wind vortices. Consequently, despite the difficulties arisen from inherent complexity of twisted forms, they could still be feasible and viable with their attractive images in the realm of tall buildings.

Keywords: aerodynamic tests, motivation for twisting, tall buildings, twisted forms, wind excitation

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Authors: Theophilus O. Odunlami, Hasan Haroglu, Nader Saleh-Matter

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The challenges facing the construction industry are often worsened by the compounded nature of projects coupled with the complexity of key stakeholders involved at different stages of the project. Projects are planned to achieve outlined benefits in line with the business case; however, a lack of effective management of key stakeholders can result in unrealistic delivery aspirations, unnecessary re-works, and overruns. The aim of this study is to examine the early stages of a project lifecycle and investigate the stakeholder management and involvement processes and their impact on the successful delivery of the project. The research engaged with conventional construction organisations and project personnel and stakeholders on diverse projects, using a research strategy to analyse existing project case studies, narrative enquiries, interviews, and surveys using a combined qualitative, quantitative, and mixed method of analysis. Research findings have shown that the involvement of stakeholders at different levels during the early stages has pronounced effects on project delivery; it helps to forge synergy and promotes a clear understanding of individual responsibilities, strengths, and weaknesses. This has often fostered a positive sense of productive collaboration right through the early stages of the project. These research findings intend to contribute to the development of a process framework for stakeholder and project team involvement in the early stages of a project. This framework will align with the selection criteria for stakeholders, contractors, and resources, ultimately contributing to the successful completion of projects. The primary question addressed in this study is stakeholder involvement and management of the early stages of a building project life cycle impacts project delivery. Findings showed that early-stage stakeholder involvement and collaboration between project teams and contractors significantly contribute to project success. However, a strong and healthy communication strategy would be required to maintain the flow of value-added ideas among stakeholders at the early stages to benefit the project at the execution stage.

Keywords: early stages, project lifecycle, stakeholders, decision-making strategy, project framework

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Authors: Mehena Fedoul

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This paper examines the intersection of race, gender, and disability through a Critical disability race theory and black feminist disability perspective in Keah Brown's memoir, "The Pretty One." The background of the study highlights the significance of intersectionality in understanding the multifaceted experiences of individuals who navigate multiple marginalized identities. The study contributes to the underrepresented field of disability studies from Critical race and black feminist perspectives, shedding light on the unique challenges and resilience of black disabled women. The study employs a qualitative analysis of Keah Brown's memoir as a primary text. Drawing on intersectionality theory and black feminist disability scholarship, the analysis focuses on how Brown's memoir illuminates the ways in which her race, gender, and disability intersect and shape her lived experiences. The analysis reveals how Brown's memoir challenges traditional notions of disability, beauty, and empowerment through the unapologetic celebration of her blackness, femaleness, and disability. The major findings of the study indicate that Brown's memoir provides a powerful narrative of the complexity, uniqueness and richness of the lived experiences of black disabled women. It demonstrates how the intersectionality of race, gender, and disability shapes Brown's identity, body image, relationships, and societal interactions. The paper also highlights how Brown's memoir emphasizes the importance of inclusivity and intersectionality in understanding and addressing the challenges faced by black disabled women. In conclusion, this study offers a critical analysis of the intersection of race, gender, and disability in Keah Brown's memoir, "The Pretty One," from a black feminist disability perspective. It contributes to the growing body of literature that recognizes the significance of intersectionality in understanding the experiences of marginalized individuals in the disability community. The study underscores the need for more inclusive and intersectional perspectives in disability studies and advocates for greater recognition of the voices and experiences of black disabled women in academic and societal discourse.

Keywords: disability studies, intersectionality, black feminism, Keah Brown

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Authors: Chitsanzo Isaac

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Across the world, the ongoing Covid-19 pandemic has challenged urban systems and policy frameworks, highlighting societal vulnerabilities and systemic inequities among many communities. Measures of confinement and social distancing to contain the Covid-19 virus have fragmented the physical and social fabric of cities. This has caused urban dwellers to reassess how they engage with their urban surroundings and maintain social ties. Urbanists have presented strategies that would allow communities to survive and even thrive, in extraordinary times of crisis like the pandemic. Tactical Urbanism, particularly the 15-Minute City, has gained popularity. It is considered a resilient approach in the global north, however, it’s transferability to the global south has been called into question. To this end, this paper poses the question: to what extent is the 15-Minute City framework integral sustainable design, and are there processes that make it adoptable by cities in the global south? This paper explores four issues using secondary quantitative data analysis and convergence analysis in the Paris and Blantyre urban regions. First, it questions how the 15-Minute City has been defined and measured, and how it impacts urban dwellers. Second, it examines the extent to which the 15-minute city performs under the lens of frameworks such as Wilber’s integral theory and Fleming’s integral sustainable design theory. Thirdly this work examines the processes that can be transferred to developing cities which foster community resilience through the perspectives of experience, behaviors, cultures, and systems. Finally, it reviews the principal ways in which a multi-perspective reality can be the basis for resilient community design and sustainable urban development. This work will shed a light on the importance of a multi-perspective reality as a means of achieving sustainable urban design goals in developing urban areas.

Keywords: 15-minute city, developing cities, global south, community resilience, integral sustainable design, systems thinking, complexity, tactical urbanism

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Authors: Fang Liu, JunShuai Xue, JiaJia Yao, XueYan Yang, ZuMao Li, GuanLin Wu, HePeng Zhang, ZhiPeng Sun

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III-Nitride resonant tunneling diode (RTD) is one of the most promising candidates for multiple-valued logic (MVL) elements. Here, we report a monolithic integration of GaN resonant tunneling diodes to realize multiple negative differential resistance (NDR) regions for MVL application. GaN RTDs, composed of a 2 nm quantum well embedded in two 1 nm quantum barriers, are grown by plasma-assisted molecular beam epitaxy on free-standing c-plane GaN substrates. Negative differential resistance characteristic with a peak current density of 178 kA/cm² in conjunction with a peak-to-valley current ratio (PVCR) of 2.07 is observed. Statistical properties exhibit high consistency showing a peak current density standard deviation of almost 1%, laying the foundation for the monolithic integration. After complete electrical isolation, two diodes of the designed same area are connected in series. By solving the Poisson equation and Schrodinger equation in one dimension, the energy band structure is calculated to explain the transport mechanism of the differential negative resistance phenomenon. Resonant tunneling events in a sequence of the series-connected RTD pair (SCRTD) form multiple NDR regions with nearly equal peak current, obtaining three stable operating states corresponding to ternary logic. A frequency multiplier circuit achieved using this integration is demonstrated, attesting to the robustness of this multiple peaks feature. This article presents a monolithic integration of SCRTD with multiple NDR regions driven by the resonant tunneling mechanism, which can be applied to a multiple-valued logic field, promising a fast operation speed and a great reduction of circuit complexity and demonstrating a new solution for nitride devices to break through the limitations of binary logic.

Keywords: GaN resonant tunneling diode, multiple-valued logic system, frequency multiplier, negative differential resistance, peak-to-valley current ratio

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Authors: Dejana Bouillet, Vlatka Domović

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Both policymakers and researchers recognize that participating in early childhood education and care (ECEC) is useful for all children, especially for those who are exposed to the high risk of social exclusion. Social exclusion of children is understood as a multidimensional construct including economic, social, cultural, health, and other aspects of disadvantage and deprivation, which individually or combined can have an unfavorable effect on the current life and development of a child, as well as on the child’s development and on disadvantaged life chances in adult life. ECEC institutions should be able to promote educational approaches that portray developmental, cultural, language, and other diversity amongst children. However, little is known about the ways in which Croatian ECEC institutions recognize and respect the diversity of children and their families and how they respond to their educational needs. That is why this paper is dedicated to the analysis of the capacities of ECEC professionals to respond to the demands of educational needs of this very diverse group of children and their families. The results obtained in the frame of the project “Models of response to educational needs of children at risk of social exclusion in ECEC institutions,” funded by the Croatian Science Foundation, will be presented. The research methodology arises from explanations of educational processes and risks of social exclusion as a complex and heterogeneous phenomenon. The preliminary results of the qualitative data analysis of educational practices regarding capacities to identify and appropriately respond to the requirements of children at risk of social exclusion will be presented. The data have been collected by interviewing educational staff in 10 Croatian ECEC institutions (n = 10). The questions in the interviews were related to various aspects of inclusive institutional policy, culture, and practices. According to the analysis, it is possible to conclude that Croatian ECEC professionals are still faced with great challenges in the process of implementation of inclusive policies, culture, and practices. There are several baselines of this conclusion. The interviewed educational professionals are not familiar enough with the whole complexity and diversity of needs of children at risk of social exclusion, and the ECEC institutions do not have enough resources to provide all interventions that these children and their families need.

Keywords: children at risk of social exclusion, ECEC professionals, inclusive policies, culture and practices, quallitative analysis

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Authors: Thomas Louis, Irina Primac, Florent Morfoisse, Tania Durre, Silvia Blacher, Agnes Noel

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In vitro and in vivo lymphangiogenesis assays are essential for the identification of potential lymphangiogenic agents and the screening of pharmacological inhibitors. In the present study, we analyse three biological models: in vitro lymphatic endothelial cell spheroids, in vivo ear sponge assay, and in vivo lymph node colonisation by tumour cells. These assays provide suitable 3D models to test pro- and anti-lymphangiogenic factors or drugs. 3D images were acquired by confocal laser scanning and light sheet fluorescence microscopy. Virtual scan microscopy followed by 3D reconstruction by image aligning methods was also used to obtain 3D images of whole large sponge and ganglion samples. 3D reconstruction, image segmentation, skeletonisation, and other image processing algorithms are described. Fixed and time-lapse imaging techniques are used to analyse lymphatic endothelial cell spheroids behaviour. The study of cell spatial distribution in spheroid models enables to detect interactions between cells and to identify invasion hierarchy and guidance patterns. Global measurements such as volume, length, and density of lymphatic vessels are measured in both in vivo models. Branching density and tortuosity evaluation are also proposed to determine structure complexity. Those properties combined with vessel spatial distribution are evaluated in order to determine lymphangiogenesis extent. Lymphatic endothelial cell invasion and lymphangiogenesis were evaluated under various experimental conditions. The comparison of these conditions enables to identify lymphangiogenic agents and to better comprehend their roles in the lymphangiogenesis process. The proposed methodology is validated by its application on the three presented models.

Keywords: 3D image segmentation, 3D image skeletonisation, cell invasion, confocal microscopy, ear sponges, light sheet microscopy, lymph nodes, lymphangiogenesis, spheroids

Procedia PDF Downloads 375

Authors: Kwan Hee Han

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External environment of enterprise is rapidly changing majorly by global competition, cost reduction pressures, and new technology. In these situations, production scheduling function plays a critical role to meet customer requirements and to attain the goal of operational efficiency. It deals with short-term decision making in the production process of the whole supply chain. The major task of production scheduling is to seek a balance between customer orders and limited resources. In manufacturing companies, this task is so difficult because it should efficiently utilize resource capacity under the careful consideration of many interacting constraints. At present, many computerized software solutions have been utilized in many enterprises to generate a realistic production schedule to overcome the complexity of schedule generation. However, most production scheduling systems do not provide sufficient information about the validity of the generated schedule except limited statistics. Process mining only recently emerged as a sub-discipline of both data mining and business process management. Process mining techniques enable the useful analysis of a wide variety of processes such as process discovery, conformance checking, and bottleneck analysis. In this study, the performance of generated production schedule is evaluated by mining event log data of production scheduling software system by using the process mining techniques since every software system generates event logs for the further use such as security investigation, auditing and error bugging. An application of process mining approach is proposed for the validation of the goodness of production schedule generated by scheduling software systems in this study. By using process mining techniques, major evaluation criteria such as utilization of workstation, existence of bottleneck workstations, critical process route patterns, and work load balance of each machine over time are measured, and finally, the goodness of production schedule is evaluated. By using the proposed process mining approach for evaluating the performance of generated production schedule, the quality of production schedule of manufacturing enterprises can be improved.

Keywords: data mining, event log, process mining, production scheduling

Procedia PDF Downloads 279