Search results for: Integrated Circuit Visual Positioning

Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

Abstract:

Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

Procedia PDF Downloads 74

Authors: Syue-Wen Lin

Abstract:

Objective: This article explores the nursing experience of a 64-year-old female lung cancer patient who underwent a thoracoscopic left lower lobectomy and treatment. The patient has a history of diabetes. The nursing process included cancer treatment, postoperative pain management, wound care and healing, and family grief counseling. Methods: The nursing period is from March 11 to March 15, 2024. During this time, strict aseptic wound dressing procedures and advanced wound care techniques are employed to promote wound healing and prevent infection. Postoperatively, due to the development of aspiration pneumonia and worsening symptoms, re-intubation was necessary. Given the patient's advanced cancer and deteriorating condition, the nursing team provided comprehensive grief counseling and care tailored to both the patient's physical and psychological needs, as well as the emotional needs of the family. Considering the complexity of the patient's condition, including advanced cancer, palliative care was also integrated into the overall nursing process to alleviate discomfort and provide psychological support. Results: Using Gordon's Functional Health Patterns for assessment, including evaluating the patient's medical history, physical assessment, and interviews, to provide individualized nursing care, it is important to collect data that will help understand the patient's physical, psychological, social, and spiritual dimensions. The interprofessional critical care team collaborates with the hospice team to help understand the psychological state of the patient's family and develop a comprehensive approach to care. Family meetings should be convened, and support should be provided to patients during the final stages of their lives. Additionally, the combination of cancer care, pain management, wound care, and palliative care ensures comprehensive support for the patient throughout her recovery, thereby improving her quality of life. Conclusion: Lung cancer and aspiration pneumonia present significant challenges to patients, and the nursing team not only provides critical care but also addresses individual patient needs through cancer care, pain management, wound care, and palliative care interventions. These measures have effectively improved the quality of life of patients, provided compassionate palliative care to terminally ill patients, and allowed them to spend the last mile of their lives with their families. Nursing staff work closely with families to develop comprehensive care plans to ensure patients receive high-quality medical care as well as psychological support and a comfortable recovery environment.

Keywords: grief counseling, lung cancer, palliative care, nursing experience

Procedia PDF Downloads 9

Authors: Achirawatt Tungsombatsanti, Toansakul Santiboon, Kamon Ponkham

Abstract:

Strategies of the STEM education was aimed to prepare of an interdisciplinary and applied approach for the instructional of science, technology, engineering, and mathematics in an integrated students for enhancing engagement of their science skills to the Problem-Based Learning (PBL) method in Borabu School with a sample consists of 80 students in 2 classes at the 12th grade level of their learning achievements on electromagnetic issue. Research administrations were to separate on two different instructional model groups, the 40-experimental group was designed with the STEM instructional experimenting preparation and induction in a 40-student class and the controlling group using the PBL was designed to students identify what they already know, what they need to know, and how and where to access new information that may lead to the resolution of the problem in other class. The learning environment perceptions were obtained using the 35-item Physics Laboratory Environment Inventory (PLEI). Students’ creating attitude skills’ sustainable development toward physics were assessed with the Test Of Physics-Related Attitude (TOPRA) The term scaling was applied to the attempts to measure the attitude objectively with the TOPRA was used to assess students’ perceptions of their science attitude toward physics. Comparisons between pretest and posttest techniques were assessed students’ learning achievements on each their outcomes from each instructional model, differently. The results of these findings revealed that the efficiency of the PLB and the STEM based on criteria indicate that are higher than the standard level of the 80/80. Statistically, significant of students’ learning achievements to their later outcomes on the controlling and experimental physics class groups with the PLB and the STEM instructional designs were differentiated between groups at the .05 level, evidently. Comparisons between the averages mean scores of students’ responses to their instructional activities in the STEM education method are higher than the average mean scores of the PLB model. Associations between students’ perceptions of their physics classes to their attitudes toward physics, the predictive efficiency R2 values indicate that 77%, and 83% of the variances in students’ attitudes for the PLEI and the TOPRA in physics environment classes were attributable to their perceptions of their physics PLB and the STEM instructional design classes, consequently. An important of these findings was contributed to student understanding of scientific concepts, attitudes, and skills as evidence with STEM instructional ought to higher responding than PBL educational teaching. Statistically significant between students’ learning achievements were differentiated of pre and post assessments which overall on two instructional models.

Keywords: learning instructional managements, problem-based learning, STEM education, method, enhancement, students learning achievements, science attitude, physics classes

Procedia PDF Downloads 223

Authors: Ramoshweu Melvin Sethobya, Emmanuel Chirenje, Mihlali Hobo, Simon Sebothoma

Abstract:

The recent surge in residential infrastructure development around the metropolitan areas of South Africa has necessitated conditions for thorough geotechnical assessments to be conducted prior to site developments to ensure human and infrastructure safety. This paper appraises the success in the application of multi-method geophysical techniques for the delineation of sinkhole vulnerability in a residential landscape. Geophysical techniques ERT, MASW, VES, Magnetics and gravity surveys were conducted to assist in mapping sinkhole vulnerability, using an existing sinkhole as a constraint at Venterspost town, West of Johannesburg city. A combination of different geophysical techniques and results integration from those proved to be useful in the delineation of the lithologic succession around sinkhole locality, and determining the geotechnical characteristics of each layer for its contribution to the development of sinkholes, subsidence and cavities at the vicinity of the site. Study results have also assisted in the determination of the possible depth extension of the currently existing sinkhole and the location of sites where other similar karstic features and sinkholes could form. Results of the ERT, VES and MASW surveys have uncovered dolomitic bedrock at varying depths around the sites, which exhibits high resistivity values in the range 2500-8000ohm.m and corresponding high velocities in the range 1000-2400 m/s. The dolomite layer was found to be overlain by a weathered chert-poor dolomite layer, which has resistivities between the range 250-2400ohm.m, and velocities ranging from 500-600m/s, from which the large sinkhole has been found to collapse/ cave in. A compiled 2.5D high resolution Shear Wave Velocity (Vs) map of the study area was created using 2D profiles of MASW data, offering insights into the prevailing lithological setup conducive for formation various types of karstic features around the site. 3D magnetic models of the site highlighted the regions of possible subsurface interconnections between the currently existing large sinkhole and the other subsidence feature at the site. A number of depth slices were used to detail the conditions near the sinkhole as depth increases. Gravity surveys results mapped the possible formational pathways for development of new karstic features around the site. Combination and correlation of different geophysical techniques proved useful in delineation of the site geotechnical characteristics and mapping the possible depth extend of the currently existing sinkhole.

Keywords: resistivity, magnetics, sinkhole, gravity, karst, delineation, VES

Procedia PDF Downloads 69

Authors: Shengnan Chen, Shuhua Wang

Abstract:

Successful production of hydrocarbon from unconventional tight oil reserves has changed the energy landscape in North America. The oil contained within these reservoirs typically will not flow to the wellbore at economic rates without assistance from advanced horizontal well and multi-stage hydraulic fracturing. Efficient and economic development of these reserves is a priority of society, government, and industry, especially under the current low oil prices. Meanwhile, society needs technological and process innovations to enhance oil recovery while concurrently reducing environmental impacts. Recently, big data analysis and artificial intelligence become very popular, developing data-driven insights for better designs and decisions in various engineering disciplines. However, the application of data mining in petroleum engineering is still in its infancy. The objective of this research aims to apply intelligent data analysis and data-driven models to exploit unconventional oil reserves both efficiently and economically. More specifically, a comprehensive database including the reservoir geological data, reservoir geophysical data, well completion data and production data for thousands of wells is firstly established to discover the valuable insights and knowledge related to tight oil reserves development. Several data analysis methods are introduced to analysis such a huge dataset. For example, K-means clustering is used to partition all observations into clusters; principle component analysis is applied to emphasize the variation and bring out strong patterns in the dataset, making the big data easy to explore and visualize; exploratory factor analysis (EFA) is used to identify the complex interrelationships between well completion data and well production data. Different data mining techniques, such as artificial neural network, fuzzy logic, and machine learning technique are then summarized, and appropriate ones are selected to analyze the database based on the prediction accuracy, model robustness, and reproducibility. Advanced knowledge and patterned are finally recognized and integrated into a modified self-adaptive differential evolution optimization workflow to enhance the oil recovery and maximize the net present value (NPV) of the unconventional oil resources. This research will advance the knowledge in the development of unconventional oil reserves and bridge the gap between the big data and performance optimizations in these formations. The newly developed data-driven optimization workflow is a powerful approach to guide field operation, which leads to better designs, higher oil recovery and economic return of future wells in the unconventional oil reserves.

Keywords: big data, artificial intelligence, enhance oil recovery, unconventional oil reserves

Procedia PDF Downloads 280

Authors: Adeola Adenikinju, Olusanya E. Olubusoye, Lateef O. Akinpelu, Dilinna L. Nwobi

Abstract:

Since the enactment of the Fiscal Responsibility Act (2007), the Federal Government of Nigeria (FGN) has made public its fiscal budget and the subsequent implementation report. A critical review of these documents shows significant variations in the five macroeconomic variables which are inputs in each Presidential budget; oil Production target (mbpd), oil price ($), Foreign exchange rate(N/$), and Gross Domestic Product growth rate (%) and inflation rate (%). This results in underperformance of the Federal budget expected output in terms of non-oil and oil revenue aggregates. This paper evaluates first the existing variance between budgeted and actuals, then the relationship and causality between the determinants of Federal fiscal budget assumptions, and finally the determinants of FGN’s Gross Oil Revenue. The paper employed the use of descriptive statistics, the Autoregressive distributed lag (ARDL) model, and a Profit oil probabilistic model to achieve these objectives. This model permits for both the static and dynamic effect(s) of the independent variable(s) on the dependent variable, unlike a static model that accounts for static or fixed effect(s) only. It offers a technique for checking the existence of a long-run relationship between variables, unlike other tests of cointegration, such as the Engle-Granger and Johansen tests, which consider only non-stationary series that are integrated of the same order. Finally, even with small sample size, the ARDL model is known to generate a valid result, for it is the dependent variable and is the explanatory variable. The results showed that there is a long-run relationship between oil revenue as a proxy for budget performance and its determinants; oil price, produced oil quantity, and foreign exchange rate. There is a short-run relationship between oil revenue and its determinants; oil price, produced oil quantity, and foreign exchange rate. There is a long-run relationship between non-oil revenue and its determinants; inflation rate, GDP growth rate, and foreign exchange rate. The grangers’ causality test results show that there is a mono-directional causality between oil revenue and its determinants. The Federal budget assumptions only explain 68% of oil revenue and 62% of non-oil revenue. There is a mono-directional causality between non-oil revenue and its determinants. The Profit oil Model describes production sharing contracts, joint ventures, and modified carrying arrangements as the greatest contributors to FGN’s gross oil revenue. This provides empirical justification for the selected macroeconomic variables used in the Federal budget design and performance evaluation. The research recommends other variables, debt and money supply, be included in the Federal budget design to explain the Federal budget revenue performance further.

Keywords: ARDL, budget performance, oil price, oil quantity, oil revenue

Procedia PDF Downloads 163

Authors: Pukhrambam Helena Chanu, Janardan Yadav

Abstract:

This study investigates the potential of various fungal isolates to solubilize zinc and counteract rice pathogens, with the aim of mitigating zinc deficiency and disease prevalence in rice farming. Soil samples from the rhizosphere were collected, and zinc-solubilizing fungi were isolated and purified. Molecular analysis identified Talaromyces sp, Talaromyces versatilis, Talaromyces pinophilus, and Aspergillus terreus as effective zinc solubilizers. Through qualitative and quantitative assessments, it was observed that solubilization efficiencies varied among the isolates over time, with Talaromyces versatilis displaying the highest capacity for solubilization. This variability in solubilization rates may be attributed to differences in fungal metabolic activity and their ability to produce organic acids that facilitate zinc release from insoluble sources in the soil. In inhibition assays against rice pathogens, the fungal isolates exhibited antagonistic properties, with Talaromyces versatilis demonstrating the most significant inhibition rates. This antagonistic activity may be linked to the production of secondary metabolites, such as antibiotics or lytic enzymes by fungi, which inhibit the growth of rice pathogens. The ability of Talaromyces versatilis to outperform other isolates in both zinc solubilization and pathogen inhibition highlights its potential as a multifunctional biocontrol agent in rice cultivation systems. These findings emphasize the potential of fungi as natural solutions for enhancing zinc uptake and managing diseases in rice cultivation. Utilizing indigenous zinc-solubilizing fungi offers a sustainable and environmentally friendly approach to addressing zinc deficiency in soils, reducing the need for chemical fertilizers. Moreover, harnessing the antagonistic activity of these fungi can contribute to integrated disease management strategies, minimizing reliance on synthetic pesticides and promoting ecological balance in agroecosystems. Additionally, the study included the evaluation of dipping time under different concentrations, viz.,10 ppm, 20 ppm, and 30 ppm of biosynthesized nano ZnO on rice seedlings. This investigation aimed to optimize the application of nano ZnO for efficient zinc uptake by rice plants while minimizing potential risks associated with excessive nanoparticle exposure. Evaluating the effects of varying concentrations and dipping durations provides valuable insights into the safe and effective utilization of nano ZnO as a micronutrient supplement in rice farming practices.

Keywords: biosynthesized nano ZnO, rice, root dipping, zinc solubilizing fungi.

Procedia PDF Downloads 42

Authors: Salma A. Mahmoud

Abstract:

Epigenetic, or alteration in gene expression influenced by extragenetic factors, has emerged as one of the most promising areas that will address some of the gaps in our current knowledge in understanding patterns of human variation. In the last decade, the research investigating epigenetic mechanisms in many fields has flourished and witnessed significant progress. It paved the way for a new era of integrated research especially between anthropology/archeology and life sciences. Skeletal remains are considered the most significant source of information for studying human variations across history, and by utilizing these valuable remains, we can interpret the past events, cultures and populations. In addition to archeological, historical and anthropological importance, studying bones has great implications in other fields such as medicine and science. Bones also can hold within them the secrets of the future as they can act as predictive tools for health, society characteristics and dietary requirements. Bones in their basic forms are composed of cells (osteocytes) that are affected by both genetic and environmental factors, which can only explain a small part of their variability. The primary objective of this project is to examine the epigenetic landscape/signature within bones of archeological remains as a novel marker that could reveal new ways to conceptualize chronological events, gender differences, social status and ecological variations. We attempted here to address discrepancies in common variants such as methylome as well as novel epigenetic regulators such as chromatin remodelers, which to our best knowledge have not yet been investigated by anthropologists/ paleoepigenetists using plethora of techniques (biological, computational, and statistical). Moreover, extracting epigenetic information from bones will highlight the importance of osseous material as a vector to study human beings in several contexts (social, cultural and environmental), and strengthen their essential role as model systems that can be used to investigate and construct various cultural, political and economic events. We also address all steps required to plan and conduct an epigenetic analysis from bone materials (modern and ancient) as well as discussing the key challenges facing researchers aiming to investigate this field. In conclusion, this project will serve as a primer for bioarcheologists/anthropologists and human biologists interested in incorporating epigenetic data into their research programs. Understanding the roles of epigenetic mechanisms in bone structure and function will be very helpful for a better comprehension of their biology and highlighting their essentiality as interdisciplinary vectors and a key material in archeological research.

Keywords: epigenetics, archeology, bones, chromatin, methylome

Procedia PDF Downloads 101

Authors: Majid Manawer Alenezi, Gavin Lawrence, Hans-Peter Kubis

Abstract:

Imagery training could be an important treatment for muscle function improvements in patients who are facing limitations in exercise training by pain or other adverse symptoms. However, recent studies are mostly limited to small muscle groups and are often contradictory. Moreover, a possible bilateral transfer effect of imagery training has not been examined. We, therefore, investigated the effectiveness of unilateral imagery training in comparison with exercise training on hip abductor muscle strength and EMG. Additionally, both limbs were assessed to investigate bilateral transfer effects. Healthy individuals took part in an imagery or exercise training intervention for two weeks and were assesses pre and post training. Participants (n=30), after randomization into an imagery and an exercise group, trained 5 times a week under supervision with additional self-performed training on the weekends. The training consisted of performing, or to imagine, 5 maximal isometric hip abductor contractions (= one set), repeating the set 7 times. All measurements and trainings were performed laying on the side on a dynamometer table. The imagery script combined kinesthetic and visual imagery with internal perspective for producing imagined maximal hip abduction contractions. The exercise group performed the same number of tasks but performing the maximal hip abductor contractions. Maximal hip abduction strength and EMG amplitudes were measured of right and left limbs pre- and post-training period. Additionally, handgrip strength and right shoulder abduction (Strength and EMG) were measured. Using mixed model ANOVA (strength measures) and Wilcoxen-tests (EMGs), data revealed a significant increase in hip abductor strength production in the imagery group on the trained right limb (~6%). However, this was not reported for the exercise group. Additionally, the left hip abduction strength (not used for training) did not show a main effect in strength, however, there was a significant interaction of group and time revealing that the strength increased in the imagery group while it remained constant in the exercise group. EMG recordings supported the strength findings showing significant elevation of EMG amplitudes after imagery training on right and left side, while the exercise training group did not show any changes. Moreover, measures of handgrip strength and shoulder abduction showed no effects over time and no interactions in both groups. Experiments showed that imagery training is a suitable method for effectively increasing functional parameters of larger limb muscles (strength and EMG) which were enhanced on both sides (trained and untrained) confirming a bilateral transfer effect. Indeed, exercise training did not reveal any increases in the parameters above omitting functional improvements. The healthy individuals tested might not easily achieve benefits from exercise training within the time tested. However, it is evident that imagery training is effective in increasing the central motor command towards the muscles and that the effect seems to be segmental (no increase in handgrip strength and shoulder abduction parameters) and affects both sides (trained and untrained). In conclusion, imagery training was effective in functional improvements in limb muscles and produced a bilateral transfer on strength and EMG measures.

Keywords: imagery, exercise, physiotherapy, motor imagery

Procedia PDF Downloads 226

Authors: Gheorghe Braniste

Abstract:

The management of the training process in sports is closely related to the awareness of the close connection between performance and the morphological, functional and psychological characteristics of the athlete's body. Achieving high results in Olympic sports is influenced, on the one hand, by the genetically determined characteristics of the body and, on the other hand, by the morphological, functional and motor abilities of the athlete. Taking into account the importance of properly understanding the evolutionary specificity of athletes to assess their competitive potential, this study provides a comparative analysis of the parameters that characterize the growth and development of the level of adaptation of sweeping rowers, considering the growth interval between 12 and 20 years. The study established that, in the multi-annual training process, the bodies of the targeted athletes register significant adaptive changes while analyzing parameters of the morphological, functional, psychomotor and sports-technical spheres. As a result of the influence of physical efforts, both specific and non-specific, there is an increase in the adaptability of the body, its transfer to a much higher level of functionality within the parameters, useful and economical adaptive reactions influenced by environmental factors, be they internal or external. The research was carried out for 7 years, on a group of 28 athletes, following their evolution and recording the specific parameters of each age stage. In order to determine the level of physical, morpho-functional, psychomotor development and technical training of rowers, the screening data were applied at the State University of Physical Education and Sports in the Republic of Moldova. During the research, measurements were made on the waist, in the standing and sitting position, arm span, weight, circumference and chest perimeter, vital capacity of the lungs, with the subsequent determination of the vital index (tolerance level to oxygen deficiency in venous blood in Stange and Genchi breath-taking tests that characterize the level of oxygen saturation, absolute and relative strength of the hand and back, calculation of body mass and morphological maturity indices (Kettle index), body surface area (body gait), psychomotor tests (Romberg test), test-tepping 10 s., reaction to a moving object, visual and auditory-motor reaction, recording of technical parameters of rowing on a competitive distance of 200 m. At the end of the study it was found that highly performance is sports is to be associated on the one hand with the genetically determined characteristics of the body and, on the other hand, with favorable adaptive reactions and energy saving, as well as morphofunctional changes influenced by internal and external environmental factors. The importance of the results obtained at the end of the study was positively reflected in obtaining the maximum level of training of athletes in order to demonstrate performance in large-scale competitions and mostly in the Olympic Games.

Keywords: olympics, parameters, performance, peak

Procedia PDF Downloads 116

Authors: Lucia Liu, Matthew Koziol

Abstract:

Obsessive-compulsive disorder (OCD), a long-lasting anxiety disorder involving recurrent, intrusive thoughts, affects over 2 million adults in the United States. Transcranial magnetic stimulation (TMS) stands out as a noninvasive, cutting-edge therapy that has been shown to reduce symptoms in patients with treatment-resistant OCD. The Food and Drug Administration (FDA) approved protocol pairs TMS sessions with individualized symptom provocation, aiming to improve the susceptibility of brain circuits to stimulation. However, limited standardization or guidance exists on how to conduct symptom provocation and which methods are most effective. This study aims to compare the effect of internal versus external techniques to induce obsessional stress in a clinical setting during TMS therapy. Two symptom provocation methods, (i) Asking patients thought-provoking questions about their obsessions (internal) and (ii) Requesting patients to perform obsession-related tasks (external), were employed in a crossover design with repeated measurement. Thirty-six treatments of NeuroStar TMS were administered to each of two patients over 8 weeks in an outpatient clinic. Patient One received 18 sessions of internal provocation followed by 18 sessions of external provocation, while Patient Two received 18 sessions of external provocation followed by 18 sessions of internal provocation. The primary outcome was the level of self-reported obsessional stress on a visual analog scale from 1 to 10. The secondary outcome was self-reported OCD severity, collected biweekly in a four-level Likert-scale (1 to 4) of bad, fair, good and excellent. Outcomes were compared and tested between provocation arms through repeated measures ANOVA, accounting for intra-patient correlations. Ages were 42 for Patient One (male, White) and 57 for Patient Two (male, White). Both patients had similar moderate symptoms at baseline, as determined through the Yale-Brown Obsessive Compulsive Scale (YBOCS). When comparing obsessional stress induced across the two arms of internal and external provocation methods, the mean (SD) was 6.03 (1.18) for internal and 4.01 (1.28) for external strategies (P=0.0019); ranges were 3 to 8 for internal and 2 to 8 for external strategies. Internal provocation yielded 5 (31.25%) bad, 6 (33.33%) fair, 3 (18.75%) good, and 2 (12.5%) excellent responses for OCD status, while external provocation yielded 5 (31.25%) bad, 9 (56.25%) fair, 1 (6.25%) good, and 1 (6.25%) excellent responses (P=0.58). Internal symptom provocation tactics had a significantly stronger impact on inducing obsessional stress and led to better OCD status (non-significant). This could be attributed to the fact that answering questions may prompt patients to reflect more on their lived experiences and struggles with OCD. In the future, clinical trials with larger sample sizes are warranted to validate this finding. Results support the increased integration of internal methods into structured provocation protocols, potentially reducing the time required for provocation and achieving greater treatment response to TMS.

Keywords: obsessive-compulsive disorder, transcranial magnetic stimulation, mental health, symptom provocation

Procedia PDF Downloads 48

Authors: Tetyana Kendzerska, David T. Zhu, Michael Pugliese, Douglas Manuel, Mohsen Sadatsafavi, Marcus Povitz, Therese A. Stukel, Teresa To, Shawn D. Aaron, Sunita Mulpuru, Melanie Chin, Claire E. Kendall, Kednapa Thavorn, Rebecca Robillard, Andrea S. Gershon

Abstract:

The impact of the COVID-19 pandemic on the management of ambulatory care sensitive conditions (ACSCs) remains unknown. To compare observed and expected (projected based on previous years) trends in all-cause mortality and healthcare use for ACSCs in the first year of the pandemic (March 2020 - March 2021). A population-based study using provincial health administrative data.General adult population (Ontario, Canada). Monthly all-cause mortality, and hospitalizations, emergency department (ED) and outpatient visit rates (per 100,000 people at-risk) for seven combined ACSCs (asthma, COPD, angina, congestive heart failure, hypertension, diabetes, and epilepsy) during the first year were compared with similar periods in previous years (2016-2019) by fitting monthly time series auto-regressive integrated moving-average models. Compared to previous years, all-cause mortality rates increased at the beginning of the pandemic (observed rate in March-May 2020 of 79.98 vs. projected of 71.24 [66.35-76.50]) and then returned to expected in June 2020—except among immigrants and people with mental health conditions where they remained elevated. Hospitalization and ED visit rates for ACSCs remained lower than projected throughout the first year: observed hospitalization rate of 37.29 vs. projected of 52.07 (47.84-56.68); observed ED visit rate of 92.55 vs. projected of 134.72 (124.89-145.33). ACSC outpatient visit rates decreased initially (observed rate of 4,299.57 vs. projected of 5,060.23 [4,712.64-5,433.46]) and then returned to expected in June 2020. Reductions in outpatient visits for ACSCs at the beginning of the pandemic combined with reduced hospital admissions may have been associated with temporally increased mortality—disproportionately experienced by immigrants and those with mental health conditions. The Ottawa Hospital Academic Medical Organization

Keywords: COVID-19, chronic disease, all-cause mortality, hospitalizations, emergency department visits, outpatient visits, modelling, population-based study, asthma, COPD, angina, heart failure, hypertension, diabetes, epilepsy

Procedia PDF Downloads 85

Authors: Nareshkumar Harale, B. B. Meshram

Abstract:

The continued exponential growth of successful cyber intrusions against today’s businesses has made it abundantly clear that traditional perimeter security measures are no longer adequate and effective. We evolved the network trust architecture from trust-untrust to Zero-Trust, With Zero Trust, essential security capabilities are deployed in a way that provides policy enforcement and protection for all users, devices, applications, data resources, and the communications traffic between them, regardless of their location. Information exchange over the Internet, in spite of inclusion of advanced security controls, is always under innovative, inventive and prone to cyberattacks. TCP/IP protocol stack, the adapted standard for communication over network, suffers from inherent design vulnerabilities such as communication and session management protocols, routing protocols and security protocols are the major cause of major attacks. With the explosion of cyber security threats, such as viruses, worms, rootkits, malwares, Denial of Service attacks, accomplishing efficient and effective intrusion detection and prevention is become crucial and challenging too. In this paper, we propose a design and analysis model for next generation network intrusion detection and protection system as part of layered security strategy. The proposed system design provides intrusion detection for wide range of attacks with layered architecture and framework. The proposed network intrusion classification framework deals with cyberattacks on standard TCP/IP protocol, routing protocols and security protocols. It thereby forms the basis for detection of attack classes and applies signature based matching for known cyberattacks and data mining based machine learning approaches for unknown cyberattacks. Our proposed implemented software can effectively detect attacks even when malicious connections are hidden within normal events. The unsupervised learning algorithm applied to network audit data trails results in unknown intrusion detection. Association rule mining algorithms generate new rules from collected audit trail data resulting in increased intrusion prevention though integrated firewall systems. Intrusion response mechanisms can be initiated in real-time thereby minimizing the impact of network intrusions. Finally, we have shown that our approach can be validated and how the analysis results can be used for detecting and protection from the new network anomalies.

Keywords: network intrusion detection, network intrusion prevention, association rule mining, system analysis and design

Procedia PDF Downloads 223

Authors: Tassadit Issaadi Hamitouche, Nicolas Gillard, Jean Petit, Valerie Lavaste, Celine Mayousse

Abstract:

Water is a fundamental resource for the industry. It is taken from the environment either from municipal distribution networks or from various natural water sources such as the sea, ocean, rivers, aquifers, etc. Once used, water is discharged into the environment, reprocessed at the plant or treatment plants. These withdrawals and discharges have a direct impact on natural water resources. These impacts can apply to the quantity of water available, the quality of the water used, or to impacts that are more complex to measure and less direct, such as the health of the population downstream from the watercourse, for example. Based on the analysis of data (meteorological, river characteristics, physicochemical substances), we wish to predict water stress episodes and anticipate prefectoral decrees, which can impact the performance of plants and propose improvement solutions, help industrialists in their choice of location for a new plant, visualize possible interactions between companies to optimize exchanges and encourage the pooling of water treatment solutions, and set up circular economies around the issue of water. The development of a system for the collection, processing, and use of data related to water resources requires the functional constraints specific to the latter to be made explicit. Thus the system will have to be able to store a large amount of data from sensors (which is the main type of data in plants and their environment). In addition, manufacturers need to have 'near-real-time' processing of information in order to be able to make the best decisions (to be rapidly notified of an event that would have a significant impact on water resources). Finally, the visualization of data must be adapted to its temporal and geographical dimensions. In this study, we set up an infrastructure centered on the TICK application stack (for Telegraf, InfluxDB, Chronograf, and Kapacitor), which is a set of loosely coupled but tightly integrated open source projects designed to manage huge amounts of time-stamped information. The software architecture is coupled with the cross-industry standard process for data mining (CRISP-DM) data mining methodology. The robust architecture and the methodology used have demonstrated their effectiveness on the study case of learning the level of a river with a 7-day horizon. The management of water and the activities within the plants -which depend on this resource- should be considerably improved thanks, on the one hand, to the learning that allows the anticipation of periods of water stress, and on the other hand, to the information system that is able to warn decision-makers with alerts created from the formalization of prefectoral decrees.

Keywords: data mining, industry, machine Learning, shortage, water resources

Procedia PDF Downloads 118

Authors: B. Bricklin Zeff

Abstract:

This research explores the development and application of a specialized chatbot tailored for a nursing English course, with a primary objective of augmenting student engagement through situational content and responsiveness to key expressions and vocabulary. Introducing the chatbot, elucidating its purpose, and outlining its functionality are crucial initial steps in the research study, as they provide a comprehensive foundation for understanding the design and objectives of the specialized chatbot developed for the nursing English course. These elements establish the context for subsequent evaluations and analyses, enabling a nuanced exploration of the chatbot's impact on student engagement and language learning within the nursing education domain. The subsequent exploration of the intricate language model development process underscores the fusion of scientific methodologies and artistic considerations in this application of artificial intelligence (AI). Tailored for educators and curriculum developers in nursing, practical principles extending beyond AI and education are considered. Some insights into leveraging technology for enhanced language learning in specialized fields are addressed, with potential applications of similar chatbots in other professional English courses. The overarching vision is to illuminate how AI can transform language learning, rendering it more interactive and contextually relevant. The presented chatbot is a tangible example, equipping educators with a practical tool to enhance their teaching practices. Methodologies employed in this research encompass surveys and discussions to gather feedback on the chatbot's usability, effectiveness, and potential improvements. The chatbot system was integrated into a nursing English course, facilitating the collection of valuable feedback from participants. Significant findings from the study underscore the chatbot's effectiveness in encouraging more verbal practice of target expressions and vocabulary necessary for performance in role-play assessment strategies. This outcome emphasizes the practical implications of integrating AI into language education in specialized fields. This research holds significance for educators and curriculum developers in the nursing field, offering insights into integrating technology for enhanced English language learning. The study's major findings contribute valuable perspectives on the practical impact of the chatbot on student interaction and verbal practice. Ultimately, the research sheds light on the transformative potential of AI in making language learning more interactive and contextually relevant, particularly within specialized domains like nursing.

Keywords: chatbot, nursing, pragmatics, role-play, AI

Procedia PDF Downloads 54

Authors: Harris Niavis, Dimitra Politaki

Abstract:

The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.

Keywords: blockchain, data quality, industry4.0, product quality

Procedia PDF Downloads 180

Authors: Jutta Ransmayr

Abstract:

The digital age has long arrived at Austrian schools, so both society and educationalists demand that digital means should be integrated accordingly to day-to-day school routines. Therefore, the Austrian school-leaving exam (A-levels) can now be written either by hand or by using a computer. However, the choice of writing medium (pen and paper or computer) for written examination papers, which are considered 'high-stakes' exams, raises a number of questions that have not yet been adequately investigated and answered until recently, such as: What effects do the different conditions of text production in the written German A-levels have on the component of normative linguistic accuracy? How do the spelling skills of German A-level papers written with a pen differ from those that the students wrote on the computer? And how is the teacher's assessment related to this? Which practical desiderata for German didactics can be derived from this? In a trilateral pilot project of the Austrian Center for Digital Humanities (ACDH) of the Austrian Academy of Sciences and the University of Vienna in cooperation with the Austrian Ministry of Education and the Council for German Orthography, these questions were investigated. A representative Austrian learner corpus, consisting of around 530 German A-level papers from all over Austria (pen and computer written), was set up in order to subject it to a quantitative (corpus-linguistic and statistical) and qualitative investigation with regard to the spelling and punctuation performance of the high school graduates and the differences between pen- and computer-written papers and their assessments. Relevant studies are currently available mainly from the Anglophone world. These have shown that writing on the computer increases the motivation to write, has positive effects on the length of the text, and, in some cases, also on the quality of the text. Depending on the writing situation and other technical aids, better results in terms of spelling and punctuation could also be found in the computer-written texts as compared to the handwritten ones. Studies also point towards a tendency among teachers to rate handwritten texts better than computer-written texts. In this paper, the first comparable results from the German-speaking area are to be presented. Research results have shown that, on the one hand, there are significant differences between handwritten and computer-written work with regard to performance in orthography and punctuation. On the other hand, the corpus linguistic investigation and the subsequent statistical analysis made it clear that not only the teachers' assessments of the students’ spelling performance vary enormously but also the overall assessments of the exam papers – the factor of the production medium (pen and paper or computer) also seems to play a decisive role.

Keywords: exam paper assessment, pen and paper or computer, learner corpora, linguistics

Procedia PDF Downloads 162

Authors: Lujain Khraiba

Abstract:

Recently, there is a broad recognition that micro-climate conditions contribute to the quality of life in urban spaces outdoors, both from economical and social viewpoints. The consideration of urban micro-climate and outdoor thermal comfort in urban design and planning processes has become one of the important aspects in current related studies. However, these aspects are so far not considered in urban planning regulations in practice and these regulations are often poorly adapted to the local climate and culture. Therefore, there is a huge need to adapt the existing planning regulations to the local climate especially in cities that have extremely hot weather conditions. The overall aim of this study is to point out the complexity of the relationship between urban planning regulations, urban design, micro-climate and outdoor thermal comfort in the hot dry city of Damascus, Syria. The main aim is to investigate the temporal and spatial effects of micro-climate on urban surface temperatures and outdoor thermal comfort in different urban design patterns as a result of urban planning regulations during the extreme summer conditions. In addition, studying different alternatives of how to mitigate the surface temperature and thermal stress is also a part of the aim. The novelty of this study is to highlight the combined effect of urban surface materials and vegetation to develop the thermal environment. This study is based on micro-climate simulations using ENVI-met 3.1. The input data is calibrated according to a micro-climate fieldwork that has been conducted in different urban zones in Damascus. Different urban forms and geometries including the old and the modern parts of Damascus are thermally evaluated. The Physiological Equivalent Temperature (PET) index is used as an indicator for outdoor thermal comfort analysis. The study highlights the shortcomings of existing planning regulations in terms of solar protection especially at street levels. The results show that the surface temperatures in Old Damascus are lower than in the modern part. This is basically due to the difference in urban geometries that prevent the solar radiation in Old Damascus to reach the ground and heat up the surface whereas in modern Damascus, the streets are prescribed as wide spaces with high values of Sky View Factor (SVF is about 0.7). Moreover, the canyons in the old part are paved in cobblestones whereas the asphalt is the main material used in the streets of modern Damascus. Furthermore, Old Damascus is less stressful than the modern part (the difference in PET index is about 10 °C). The thermal situation is enhanced when different vegetation are considered (an improvement of 13 °C in the surface temperature is recorded in modern Damascus). The study recommends considering a detailed landscape code at street levels to be integrated in urban regulations of Damascus in order to achieve a better urban development in harmony with micro-climate and comfort. Such strategy will be very useful to decrease the urban warming in the city.

Keywords: micro-climate, outdoor thermal comfort, urban planning regulations, urban spaces

Procedia PDF Downloads 478

Authors: Bamikole J. Adeyemi, Prashant Jadhawar, Lateef Akanji

Abstract:

Theoretically, there exist two mathematical interfaces (fluid-solid and fluid-fluid) when a liquid film is present on solid surfaces. These interfaces overlap if the mineral surface is oil-wet or mixed wet, and therefore, the effects of disjoining pressure are significant on both boundaries. Hence, dewetting is a necessary process that could detach oil from the mineral surface. However, if the thickness of the thin water film directly in contact with the surface is large enough, disjoining pressure can be thought to be zero at the liquid-liquid interface. Recent studies show that the integration of fluid-fluid interactions with fluid-rock interactions is an important step towards a holistic approach to understanding smart water effects. Experiments have shown that the brine solution can alter the micro forces at oil-water interfaces, and these ion-specific interactions lead to oil emulsion formation. The natural emulsifiers present in crude oil behave as polyelectrolytes when the oil interfaces with low salinity water. Wettability alteration caused by low salinity waterflooding during Enhanced Oil Recovery (EOR) process results from the activities of divalent ions. However, polyelectrolytes are said to lose their viscoelastic property with increasing cation concentrations. In this work, the influence of cation concentrations on the dynamics of viscoelastic liquid-liquid interfaces is numerically investigated. The resultant ion concentrations at the crude oil/brine interfaces were estimated using a surface complexation model. Subsequently, the ion concentration parameter is integrated into a mathematical model to describe its effects on the dynamics of a viscoelastic interfacial thin film. The film growth, stability, and rupture were measured after different time steps for three types of fluids (Newtonian, purely elastic and viscoelastic fluids). The interfacial films respond to exposure time in a similar manner with an increasing growth rate, which resulted in the formation of more droplets with time. Increased surfactant accumulation at the interface results in a higher film growth rate which leads to instability and subsequent formation of more satellite droplets. Purely elastic and viscoelastic properties limit film growth rate and consequent film stability compared to the Newtonian fluid. Therefore, low salinity and reduced concentration of the potential determining ions in injection water will lead to improved interfacial viscoelasticity.

Keywords: liquid-liquid interfaces, surfactant concentrations, potential determining ions, residual oil mobilization

Procedia PDF Downloads 137

Authors: S. Mahdi Sadatmansouri, Maryam Khalili

Abstract:

World, nowadays, encounters serious water scarcity problem. During the past few years, by advent of Smart Energy and Water Meter (SEWM) and its installation at the electro-pumps of the water wells, one had believed that it could be the golden key to address the groundwater resources over-pumping issue. In fact, implementation of these Smart Meters managed to control the water table drawdown for short; but it was not a sustainable approach. SEWM has been considered as law enforcement facility at first; however, for solving a complex socioeconomic problem like shared groundwater resources management, more than just enforcement is required: participation to conserve common resources. The well owners or farmers, as water consumers, are the main and direct stakeholders of this system and other stakeholders could be government sectors, investors, technology providers, privet sectors or ordinary people. Designing a socio-technical system not only defines the role of each stakeholder but also can lubricate the communication to reach the system goals while benefits of each are considered and provided. Farmers, as the key participators for solving groundwater problem, do not trust governments but they would trust a fair system in which responsibilities, privileges and benefits are clear. Technology could help this system remained impartial and productive. Social aspects provide rules, regulations, social objects and etc. for the system and help it to be more human-centered. As the design methodology, Design Thinking provides probable solutions for the challenging problems and ongoing conflicts; it could enlighten the way in which the final system could be designed. Using Human Centered Design approach of IDEO helps to keep farmers in the center of the solution and provides a vision by which stakeholders’ requirements and needs are addressed effectively. Farmers would be considered to trust the system and participate in their groundwater resources management if they find the rules and tools of the system fair and effective. Besides, implementation of the socio-technical system could change farmers’ behavior in order that they concern more about their valuable shared water resources as well as their farm profit. This socio-technical system contains nine main subsystems: 1) Measurement and Monitoring system, 2) Legislation and Governmental system, 3) Information Sharing system, 4) Knowledge based NGOs, 5) Integrated Farm Management system (using IoT), 6) Water Market and Water Banking system, 7) Gamification, 8) Agribusiness ecosystem, 9) Investment system.

Keywords: human centered design, participatory management, smart energy and water meter (SEWM), social object, socio-technical system, water table drawdown

Procedia PDF Downloads 290

Authors: Leyla A. Sandoval Hamón, Fernando Casani

Abstract:

Sustainability has been integrated into the cities’ agenda due to the impact that they generate. The dimensions of greater proliferation of sustainability, which are taken as a reference, are economic, social and environmental. Thus, the decisions of management of the sustainable cities search a balance between these dimensions in order to provide environment-friendly alternatives. In this context, urban models (where water consumption, energy consumption, waste production, among others) that have emerged in harmony with the environment, are known as Ecocity. A similar model, but on a smaller scale, is ‘Ecocampus’ that is developed in universities (considered ‘small cities’ due to its complex structure). So, sustainable practices are being implemented in the management of university campus activities, following different relevant lines of work. The universities have a strategic role in society, and their activities can strengthen policies, strategies, and measures of sustainability, both internal and external to the organization. Because of their mission in knowledge creation and transfer, these institutions can promote and disseminate more advanced activities in sustainability. This model replica also implies challenges in the sustainable management of water, energy, waste, transportation, among others, inside the campus. The challenge that this paper focuses on is the water management, taking into account that the universities consume big amounts of this resource. The purpose of this paper is to analyze the sustainability experience, with emphasis on water management, of two different campuses belonging to two different Spanish universities - one urban campus in a historic city and the other a suburban campus in the outskirts of a large city. Both universities are in the top hundred of international rankings of sustainable universities. The methodology adopts a qualitative method based on the technique of in-depth interviews and focus-group discussions with administrative and academic staff of the ‘Ecocampus’ offices, the organizational units for sustainability management, from the two Spanish universities. The hypotheses indicate that sustainable policies in terms of water management are best in campuses without big green spaces and where the buildings are built or rebuilt with modern style. The sustainability efforts of the university are independent of the kind of (urban – suburban) campus but an important aspect to improve is the degree of awareness of the university community about water scarcity. In general, the paper suggests that higher institutions adapt their sustainability policies depending on the location and features of the campus and their engagement with the water conservation. Many Spanish universities have proposed policies, good practices, and measures of sustainability. In fact, some offices or centers of Ecocampus have been founded. The originality of this study is to learn from the different experiences of sustainability policies of universities.

Keywords: ecocampus, ecocity, sustainability, water management

Procedia PDF Downloads 214

Authors: Sven Tackenberg, Sönke Duckwitz, Andreas Petz, Christopher M. Schlick

Abstract:

This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem (RCPSP) to apply it to complex maintenance problems. The problem is to assign technicians to a team which has to process several tasks with multi-level skill requirements during a work shift. Here, several alternative activities for a task allow both, the temporal shift of activities or the reallocation of technicians and tools. As a result, switches from one valid work process variant to another can be considered and may be selected by the developed evolutionary algorithm based on the present skill level of technicians or the available tools. An additional complication of the observed scheduling problem is that the locations of the construction sites are only temporarily accessible during a day. Due to intensive rail traffic, the available time slots for maintenance and repair works are extremely short and are often distributed throughout the day. To identify efficient working periods, a first concept of a Bayesian network is introduced and is integrated into the extended RCPSP with pre-emptive and non-pre-emptive tasks. Thereby, the Bayesian network is used to calculate the probability of a maintenance task to be processed during a specific period of the shift. Focusing on the domain of maintenance of the railway infrastructure in metropolitan areas as the most unproductive implementation process at construction site, the paper illustrates how the extended RCPSP can be applied for maintenance planning support. A multi-criteria evolutionary algorithm with a problem representation is introduced which is capable of revising technician-task allocations, whereas the duration of the task may be stochastic. The approach uses a novel activity list representation to ensure easily describable and modifiable elements which can be converted into detailed shift schedules. Thereby, the main objective is to develop a shift plan which maximizes the utilization of each technician due to a minimization of the waiting times caused by rail traffic. The results of the already implemented core algorithm illustrate a fast convergence towards an optimal team composition for a shift, an efficient sequence of tasks and a high probability of the subsequent implementation due to the stochastic durations of the tasks. In the paper, the algorithm for the extended RCPSP is analyzed in experimental evaluation using real-world example problems with various size, resource complexity, tightness and so forth.

Keywords: maintenance management, scheduling, resource constrained project scheduling problem, genetic algorithms

Procedia PDF Downloads 227

Authors: Mona Alyedreessy

Abstract:

This study, which is based on a qualitative study sample of thirty-four British converts from different ages, ethnicities, social classes, areas and religious backgrounds in London, investigates the common challenges, problems and abuse in the name of Islam that many British female Muslim converts experienced during their time as Muslims, which caused them to leave the faith. It is an important study, as it creates an awareness of the weaknesses found in western Muslim societies and in various Islamic educational programs that causes people to leave Islam and contribute towards its negative reputation in the media. The women in this study shared common problems regarding gender and racial discrimination, identity development, feminism, marriage, parenting, Muslim culture, isolation, extremism, belonging and practising Islam in both Muslim and non-Muslim societies with differing sacrifices and consequences that caused them to de-convert. The study argues that many of the personal, religious and social problems female Muslim converts experience are due to a lack of knowledge about Islam and their rights as Muslim women, which often results in them being vulnerable and influenced by the opinions, attitudes and actions of uneducated, abusive, non-practising and extremist Muslims. For example, it was found that young female converts in particular were often taken advantage of and manipulated into believing that many negative actions displayed by patriarchal Muslim husbands were a part of Islam. This created much confusion, especially when their husbands used specific Quran texts and Hadiths to justify their abuse, authority and attitudes that made them miserable. As a result and based on the positive experiences of some converts, the study found that obtaining a broad Islamic education that started with an intimate study of the Prophet Muhammad’s biography alongside being guided by the teachings of western Muslim scholars contributed greatly towards a more enjoyable conversion journey, as women were able to identify and avoid problematic Muslims and abuse in the name of Islam. This in turn helped to create a healthier family unit and Muslim society. Those who enjoyed being Muslims were able to create a balanced western Muslim identity by negotiating and applying their own morals and western values to their understanding of The Prophet’s biography and The Quran and integrated Islamic values into their own secular western environments that were free from foreign cultural practices. The outcomes of the study also highlight some effective modern approaches to da’wah based on the teachings of The Prophet Mohammad and other prophets for young Arab and Asian Muslims who marry, study and live among non-Muslims and converts.

Keywords: abuse, apostasy, converts, Muslims

Procedia PDF Downloads 225

Authors: Sean Griffiths

Abstract:

Introduction: This paper examines the expression of ‘objectivity’ in architecture in the context of the post-war rejection of this concept. It aims to re-examine the question in light of the assault on truth characterizing contemporary culture and of the unassailable truth of the climate emergency. The paper analyses the search for objective truth as it was prosecuted in the Modern Movement in the early 20th century, looking at the extent to which this quest was successful in contributing to the development of a radically new, politically-informed architecture and the extent to which its particular interpretation of objectivity, limited that development. The paper studies the influence of the Vienna Circle philosophers Rudolph Carnap and Otto Neurath on the pedagogy of the Bauhaus and the architecture of the Neue Sachlichkeit in Germany. Their logical positivism sought to determine objective truths through empirical analysis, expressed in an austere formal language as part of a ‘scientific world conception’ which would overcome metaphysics and unverifiable mystification. These ideas, and the concurrent prioritizing of measurement as the determinant of environmental quality, became key influences in the socially-driven architecture constructed in the 1920s and 30s by Bauhaus architects in numerous German Cities. Methodology: The paper reviews the history of the early Modern Movement and summarizes accounts of the relationship between the Vienna Circle and the Bauhaus. It looks at key differences in the approaches Neurath and Carnap took to the achievement of their shared philosophical and political aims. It analyses how the adoption of Carnap’s foundationalism influenced the architectural language of modern architecture and compares, through a close reading of the structure of Neurath’s ‘protocol sentences,’ the latter’s alternative approach, speculating on the possibility that its adoption offered a different direction of travel for Modern Architecture. Findings: The paper finds that the adoption of Carnap’s foundationalism, while helping Modern Architecture forge a new visual language, ultimately limited its development and is implicated in its failure to escape the very metaphysics against which it had set itself. It speculates that Neurath’s relational language-based approach to the issue of establishing objectivity has its architectural corollary in the process of revision and renovation that offers new ways an ‘objective’ language of architecture might be developed in a manner that is more responsive to our present-day crisis. Conclusion: The philosophical principles of the Vienna Circle and the architects of the Modern Movement had much in common. Both contributed to radical historical departures which sought to instantiate a world scientific conception in their respective fields, which would attempt to banish mystification and metaphysics and would align itself with socialism. However, in adopting Carnap’s foundationalism as the theoretical basis for the new architecture, Modern Architecture not only failed to escape metaphysics but arguably closed off new avenues of development to itself. The adoption of Neurath’s more open-ended and interactive approach to objectivity offers possibilities for new conceptions of the expression of objectivity in architecture that might be more tailored to the multiple crises we face today.

Keywords: Bauhaus, logical positivism, Neue Sachlichkeit, rationalism, Vienna Circle

Procedia PDF Downloads 74

Authors: Despoina Mouratidis, Katia Lida Kermanidis

Abstract:

Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

Procedia PDF Downloads 123

Authors: Ashley Hobson, Ashley Efaw

Abstract:

Professionalism is an essential skill for clinicians, particularly for Occupational Therapy Providers (OTPs). The World Federation of Occupational Therapy (WFOT) Guiding Principles for Ethical Occupational Therapy and American Occupational Therapy Association (AOTA) Code of Ethics establishes expectations for professionalism among OTPs, emphasizing its importance in the field. However, the teaching and assessment of professionalism vary across OTP programs. The flexibility provided by the country standards allows programs to determine their own approaches to meeting these standards, resulting in inconsistency. Educators in both academic and fieldwork settings face challenges in objectively assessing and providing feedback on student professionalism. Although they observe instances of unprofessional behavior, there is no standardized assessment measure to evaluate professionalism in OTP students. While most students are committed to learning and applying professionalism skills, they enter OTP programs with varying levels of proficiency in this area. Consequently, they lack a uniform understanding of professionalism and lack an objective means to self-assess their current skills and identify areas for growth. It is crucial to explicitly teach professionalism, have students to self-assess their professionalism skills, and have OTP educators assess student professionalism. This approach is necessary for fostering students' professionalism journeys. Traditionally, there has been no objective way for students to self-assess their professionalism or for educators to provide objective assessments and feedback. To establish a uniform approach to professionalism, the authors incorporated professionalism content into our curriculum. Utilizing an operational definition of professionalism, the authors integrated professionalism into didactic, fieldwork, and capstone courses. The complexity of the content and the professionalism skills expected of students increase each year to ensure students graduate with the skills to practice in accordance with the WFOT Guiding Principles for Ethical Occupational Therapy Practice and AOTA Code of Ethics. Two professionalism assessments were developed based on the expectations outlined in the both documents. The Professionalism Self-Assessment allows students to evaluate their professionalism, reflect on their performance, and set goals. The Professionalism Assessment for Educators is a modified version of the same tool designed for educators. The purpose of this workshop is to provide educators with a framework and tools for assessing student professionalism. The authors discuss how to integrate professionalism content into OTP curriculum and utilize professionalism assessments to provide constructive feedback and equitable learning opportunities for OTP students in academic, fieldwork, and capstone settings. By adopting these strategies, educators can enhance the development of professionalism among OTP students, ensuring they are well-prepared to meet the demands of the profession.

Keywords: professionalism, assessments, student learning, student preparedness, ethical practice

Procedia PDF Downloads 32

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

Abstract:

Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

Procedia PDF Downloads 67

Authors: P. Cavlan, B. Kırmızıgil

Abstract:

Introduction: Each exercise in suspension exercises offer the use of gravity and body weight; and is thought to develop the equilibrium, flexibility and body stability necessary for daily life activities and sports, in addition to creating the correct functional force. Suspension exercises based on body weight focus the human body as an integrated system. Total Resistance Exercises (TRX) suspension training that physiotherapists, athletic health clinics, exercise centers of hospitals and chiropractic clinics now use for rehabilitation purposes. The purpose of this study is to investigate and compare the effects of TRX suspension exercises on physical performance in healthy individuals. Method: Healthy subjects divided into two groups; the study group and the control group with 40 individuals for each, between ages 20 to 45 with similar gender distributions. Study group had 2 sessions of suspension exercises per week for 8 weeks and control group had no exercises during this period. All the participants were given explosive strength, flexibility, strength and endurance tests before and after the 8 week period. The tests used for evaluation were respectively; standing long jump test and single leg (left and right) long jump tests, sit and reach test, sit up and back extension tests. Results: In the study group a statistically significant difference was found between prior- and final-tests in all evaluations, including explosive strength, flexibility, core strength and endurance of the group performing TRX exercises. These values were higher than the control groups’ values. The final test results were found to be statistically different between the study and control groups. Study group showed development in all values. Conclusions: In this study, which was conducted with the aim of investigating and comparing the effects of TRX suspension exercises on physical performance, the results of the prior-tests of both groups were similar. There was no significant difference between the prior and the final values in the control group. It was observed that in the study group, explosive strength, flexibility, strength, and endurance development was achieved after 8 weeks. According to these results, it was shown that TRX suspension exercise program improved explosive strength, flexibility, especially core strength and endurance; therefore the physical performance. Based on the results of our study, it was determined that the physical performance, an indispensable requirement of our life, was developed by the TRX suspension system. We concluded that TRX suspension exercises can be used to improve the explosive strength and flexibility in healthy individuals, as well as developing the muscle strength and endurance of the core region. The specific investigations could be done in this area so that programs that emphasize the TRX's physical performance features could be created.

Keywords: core strength, endurance, explosive strength, flexibility, physical performance, suspension exercises

Procedia PDF Downloads 164

Authors: Pooria Norouzi, Nicholas Tsang, Adam van der Goes, Joseph Yu, Douglas Zheng, Sirine Maleej

Abstract:

In this study, virtual meters will be designed and used for energy balance measurements of an air handling unit (AHU). The method aims to replace traditional physical sensors in heating, ventilation, and air conditioning (HVAC) systems with simulated virtual meters. Due to the inability to manage and monitor these systems, many HVAC systems have a high level of inefficiency and energy wastage. Virtual meters are implemented and applied in an actual HVAC system, and the result confirms the practicality of mathematical sensors for alternative energy measurement. While most residential buildings and offices are commonly not equipped with advanced sensors, adding, exploiting, and monitoring sensors and measurement devices in the existing systems can cost thousands of dollars. The first purpose of this study is to provide an energy consumption rate based on available sensors and without any physical energy meters. It proves the performance of virtual meters in HVAC systems as reliable measurement devices. To demonstrate this concept, mathematical models are created for AHU-07, located in building NE01 of the British Columbia Institute of Technology (BCIT) Burnaby campus. The models will be created and integrated with the system’s historical data and physical spot measurements. The actual measurements will be investigated to prove the models' accuracy. Based on preliminary analysis, the resulting mathematical models are successful in plotting energy consumption patterns, and it is concluded confidently that the results of the virtual meter will be close to the results that physical meters could achieve. In the second part of this study, the use of virtual meters is further assisted by artificial intelligence (AI) in the HVAC systems of building to improve energy management and efficiency. By the data mining approach, virtual meters’ data is recorded as historical data, and HVAC system energy consumption prediction is also implemented in order to harness great energy savings and manage the demand and supply chain effectively. Energy prediction can lead to energy-saving strategies and considerations that can open a window in predictive control in order to reach lower energy consumption. To solve these challenges, the energy prediction could optimize the HVAC system and automates energy consumption to capture savings. This study also investigates AI solutions possibility for autonomous HVAC efficiency that will allow quick and efficient response to energy consumption and cost spikes in the energy market.

Keywords: virtual meters, HVAC, artificial intelligence, energy consumption prediction

Procedia PDF Downloads 99

Authors: Abdul Rahman Hamdan

Abstract:

The Fourth Industrial Revolution (4IR) has brought unprecedented technological advancements that have disrupted many industries worldwide. In keeping up with the technological advances and rapid disruption by the introduction of many technological advancements brought forth by the 4IR, the use of technology road mapping has emerged as one of the critical tools for organizations to leverage. Technology road mapping can be used by many companies to guide them to become more adaptable and anticipate future transformation and innovation, and avoid being redundant or irrelevant due to the rapid changes in technological advancement. This research paper provides a comprehensive analysis of technology road mapping within the context of the 4IR. The objectives of the paper are to provide companies with practical insights and a strategic framework of technology road mapping for them to navigate the fast-changing nature of the 4IR. This study also contributes to the understanding and practice of technology road mapping in the 4IR and, at the same time, provides organizations with the necessary tools and critical insight to navigate the 4IR transformation by leveraging technology road mapping. Based on the literature review and case studies, the study analyses key principles, methodologies, and best practices in technology road mapping and integrates them with the unique characteristics and challenges of the 4IR. The research paper gives the background of the fourth industrial revolution. It explores the disruptive potential of technologies in the 4IR and the critical need for technology road mapping that consists of strategic planning and foresight to remain competitive and relevant in the 4IR era. It also highlights the importance of technology road mapping as an organisation’s proactive approach to align the organisation’s objectives and resources to their technology and product development in meeting the fast-evolving technological 4IR landscape. The paper also includes the theoretical foundations of technology road mapping and examines various methodological approaches, and identifies external stakeholders in the process, such as external experts, stakeholders, collaborative platforms, and cross-functional teams to ensure an integrated and robust technological roadmap for the organisation. Moreover, this study presents a comprehensive framework for technology road mapping in the 4IR by incorporating key elements and processes such as technology assessment, competitive intelligence, risk analysis, and resource allocation. It provides a framework for implementing technology road mapping from strategic planning, goal setting, and technology scanning to road mapping visualisation, implementation planning, monitoring, and evaluation. In addition, the study also addresses the challenges and limitations related to technology roadmapping in 4IR, including the gap analysis. In conclusion of the study, the study will propose a set of practical recommendations for organizations that intend to leverage technology road mapping as a strategic tool in the 4IR in driving innovation and becoming competitive in the current and future ecosystem.

Keywords: technology management, technology road mapping, technology transfer, technology planning

Procedia PDF Downloads 63