Search results for: sexual and gender based violence (SGBV)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30322

Search results for: sexual and gender based violence (SGBV)

22102 Mapping and Measuring the Vulnerability Level of the Belawan District Community in Encountering the Rob Flood Disaster

Authors: Dessy Pinem, Rahmadian Sembiring, Adanil Bushra

Abstract:

Medan Belawan is one of the subdistricts of 21 districts in Medan. Medan Belawan Sub-district is directly adjacent to the Malacca Strait in the North. Due to its direct border with the Malacca Strait, the problem in this sub-district, which has continued for many years, is a flood of rob. In 2015, rob floods inundated Sicanang urban village, Belawan I urban village, Belawan Bahagia urban village and Bagan Deli village. The extent of inundation in the flood of rob that occurred in September 2015 reached 540, 938 ha. Rob flood is a phenomenon where the sea water is overflowing into the mainland. Rob floods can also be interpreted as a puddle of water on the coastal land that occurs when the tidal waters. So this phenomenon will inundate parts of the coastal plain or lower place of high tide sea level. Rob flood is a daily disaster faced by the residents in the district of Medan Belawan. Rob floods can happen every month and last for a week. The flood is not only the residents' houses, the flood also soaked the main road to Belawan Port reaching 50 cm. To deal with the problems caused by the flood and to prepare coastal communities to face the character of coastal areas, it is necessary to know the vulnerability of the people who are always the victims of the rob flood. Are the people of Medan Belawan sub-district, especially in the flood-affected villages, able to cope with the consequences of the floods? To answer this question, it is necessary to assess the vulnerability of the Belawan District community in the face of the flood disaster. This research is descriptive, qualitative and quantitative. Data were collected by observation, interview and questionnaires in 4 urban villages often affected by rob flood. The vulnerabilities measured are physical, economic, social, environmental, organizational and motivational vulnerabilities. For vulnerability in the physical field, the data collected is the distance of the building, floor area ratio, drainage, and building materials. For economic vulnerability, data collected are income, employment, building ownership, and insurance ownership. For the vulnerability in the social field, the data collected is education, number of family members, children, the elderly, gender, training for disasters, and how to dispose of waste. For the vulnerability in the field of organizational data collected is the existence of organizations that advocate for the victims, their policies and laws governing the handling of tidal flooding. The motivational vulnerability is seen from the information center or question and answer about the rob flood, and the existence of an evacuation plan or path to avoid disaster or reduce the victim. The results of this study indicate that most people in Medan Belawan sub-district have a high-level vulnerability in physical, economic, social, environmental, organizational and motivational fields. They have no access to economic empowerment, no insurance, no motivation to solve problems and only hope to the government, not to have organizations that support and defend them, and have physical buildings that are easily destroyed by rob floods.

Keywords: disaster, rob flood, Medan Belawan, vulnerability

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22101 Reinforced Concrete Box Girder Bridge Hinge Replacement and Horizontal and Vertical Earthquake Restrainers

Authors: Kumars ZandParsa, Quynh Nguyen, Hadi Moradi

Abstract:

There are old cast-in-place concrete box girder bridges in California with inter-span hinges that are designed based on old earthquake codes. Hinge removal is part of the bridges’ earthquake retrofitting project, and hinges were removed and replaced with modified hinges per new earthquake codes. The span that has a hinge is divided into short and long cantilevers in which the short cantilever supports the long cantilever. In the recent bridge hinge replacement, the length of the short and long cantilevers were 20ft and 80ft, respectively. The seat in the new design is wider than the old design, and the horizontal and vertical movements of the deck at the hinge location must be computed to check if restraints are needed. In this paper, besides considering the conventional reinforced concrete box girder bridges, the hinge removal operations, along with the response spectrum analysis based on the El Centro 1940 earthquake, will be presented to verify if vertical and horizontal restrainers are needed.

Keywords: hinge replacement, restrainers, vertical earthquake, response spectrum analysis

Procedia PDF Downloads 571
22100 Glucose Monitoring System Using Machine Learning Algorithms

Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

Abstract:

The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

Procedia PDF Downloads 196
22099 Cinema Reception in a Digital World: A Study of Cinema Audiences in India

Authors: Sanjay Ranade

Abstract:

Traditional film theory assumes the cinema audience in a darkened room where cinema is projected on to a white screen, and the audience suspends their sense of reality. Shifts in audiences due to changes in cultural tastes or trends have been studied for decades. In the past two decades, however, the audience, especially the youth, has shifted to digital media for the consumption of cinema. As a result, not only are audiences watching cinema on different devices, they are also consuming cinema in places and ways never imagined before. Public transport often crowded to the brim with a lot of ambient content, and a variety of workplaces have become sites for cinema viewing. Cinema is watched piecemeal and at different times of the day. Audiences use devices such as mobile phones and tablets to watch cinema. The cinema viewing experience is getting redesigned by the user. The emerging design allows the spectator to not only consume images and narratives but also produce, reproduce, and manipulate existing images and narratives, thereby participating in the process and influencing it. Spectatorship studies stress on the importance of subjectivity when dealing with the structure of the film text and the cultural and psychological implications in the engagement between the spectator and the film text. Indian cinema has been booming and contributing to global movie production significantly. In 2005 film production was 1000 films a year and doubled to 2000 by 2016. Digital technology helped push this growth in 2012. Film studies in India have had a decided Euro-American bias. The studies have chiefly analysed the content for ideological leanings or myth or as reflections of society, societal changes, or articulation of identity or presented retrospectives of directors, actors, music directors, etc. The one factor relegated to the background has been the spectator. If they have been addressed, they are treated as a collective of class or gender. India has a performative tradition going back several centuries. How Indians receive cinema is an important aspect to study with respect to film studies. This exploratory and descriptive study looked at 162 young media students studying cinema at the undergraduate and postgraduate levels. The students, speaking as many as 20 languages amongst them, were drawn from across the country’s media schools. The study looked at nine film societies registered with the Federation of Film Societies of India. A structured questionnaire was made and distributed online through media teachers for the students. The film societies were approached through the regional office of the FFSI in Mumbai. Lastly, group discussions were held in Mumbai with students and teachers of media. A group consisted of between five and twelve student participants, along with one or two teachers. All the respondents looked at themselves as spectators and shared their experiences of spectators of cinema, providing a very rich insight into Indian conditions of viewing cinema and challenges for cinema ahead.

Keywords: audience, digital, film studies, reception, reception spectatorship

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22098 Design of Nanoreinforced Polyacrylamide-Based Hybrid Hydrogels for Bone Tissue Engineering

Authors: Anuj Kumar, Kummara M. Rao, Sung S. Han

Abstract:

Bone tissue engineering has emerged as a potentially alternative method for localized bone defects or diseases, congenital deformation, and surgical reconstruction. The designing and the fabrication of the ideal scaffold is a great challenge, in restoring of the damaged bone tissues via cell attachment, proliferation, and differentiation under three-dimensional (3D) biological micro-/nano-environment. In this case, hydrogel system composed of high hydrophilic 3D polymeric-network that is able to mimic some of the functional physical and chemical properties of the extracellular matrix (ECM) and possibly may provide a suitable 3D micro-/nano-environment (i.e., resemblance of native bone tissues). Thus, this proposed hydrogel system is highly permeable and facilitates the transport of the nutrients and metabolites. However, the use of hydrogels in bone tissue engineering is limited because of their low mechanical properties (toughness and stiffness) that continue to posing challenges in designing and fabrication of tough and stiff hydrogels along with improved bioactive properties. For this purpose, in our lab, polyacrylamide-based hybrid hydrogels were synthesized by involving sodium alginate, cellulose nanocrystals and silica-based glass using one-step free-radical polymerization. The results showed good in vitro apatite-forming ability (biomineralization) and improved mechanical properties (under compression in the form of strength and stiffness in both wet and dry conditions), and in vitro osteoblastic (MC3T3-E1 cells) cytocompatibility. For in vitro cytocompatibility assessment, both qualitative (attachment and spreading of cells using FESEM) and quantitative (cell viability and proliferation using MTT assay) analyses were performed. The obtained hybrid hydrogels may potentially be used in bone tissue engineering applications after establishment of in vivo characterization.

Keywords: bone tissue engineering, cellulose nanocrystals, hydrogels, polyacrylamide, sodium alginate

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22097 CNN-Based Compressor Mass Flow Estimator in Industrial Aircraft Vapor Cycle System

Authors: Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini

Abstract:

In vapor cycle systems, the mass flow sensor plays a key role for different monitoring and control purposes. However, physical sensors can be inaccurate, heavy, cumbersome, expensive, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor, based on other standard sensors, is a good alternative. This paper has two main objectives. Firstly, a data-driven model using a convolutional neural network is proposed to estimate the mass flow of the compressor. We show that it significantly outperforms the standard polynomial regression model (thermodynamic maps) in terms of the standard MSE metric and engineer performance metrics. Secondly, a semi-automatic segmentation method is proposed to compute the engineer performance metrics for real datasets, as the standard MSE metric may pose risks in analyzing the dynamic behavior of vapor cycle systems.

Keywords: deep learning, convolutional neural network, vapor cycle system, virtual sensor

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22096 Reservoir Fluids: Occurrence, Classification, and Modeling

Authors: Ahmed El-Banbi

Abstract:

Several PVT models exist to represent how PVT properties are handled in sub-surface and surface engineering calculations for oil and gas production. The most commonly used models include black oil, modified black oil (MBO), and compositional models. These models are used in calculations that allow engineers to optimize and forecast well and reservoir performance (e.g., reservoir simulation calculations, material balance, nodal analysis, surface facilities, etc.). The choice of which model is dependent on fluid type and the production process (e.g., depletion, water injection, gas injection, etc.). Based on close to 2,000 reservoir fluid samples collected from different basins and locations, this paper presents some conclusions on the occurrence of reservoir fluids. It also reviews the common methods used to classify reservoir fluid types. Based on new criteria related to the production behavior of different fluids and economic considerations, an updated classification of reservoir fluid types is presented in the paper. Recommendations on the use of different PVT models to simulate the behavior of different reservoir fluid types are discussed. Each PVT model requirement is highlighted. Available methods for the calculation of PVT properties from each model are also discussed. Practical recommendations and tips on how to control the calculations to achieve the most accurate results are given.

Keywords: PVT models, fluid types, PVT properties, fluids classification

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22095 Comparison of Direction of Arrival Estimation Method for Drone Based on Phased Microphone Array

Authors: Jiwon Lee, Yeong-Ju Go, Jong-Soo Choi

Abstract:

Drones were first developed for military use and were used in World War 1. But recently drones have been used in a variety of fields. Several companies actively utilize drone technology to strengthen their services, and in agriculture, drones are used for crop monitoring and sowing. Other people use drones for hobby activities such as photography. However, as the range of use of drones expands rapidly, problems caused by drones such as improperly flying, privacy and terrorism are also increasing. As the need for monitoring and tracking of drones increases, researches are progressing accordingly. The drone detection system estimates the position of the drone using the physical phenomena that occur when the drones fly. The drone detection system measures being developed utilize many approaches, such as radar, infrared camera, and acoustic detection systems. Among the various drone detection system, the acoustic detection system is advantageous in that the microphone array system is small, inexpensive, and easy to operate than other systems. In this paper, the acoustic signal is acquired by using minimum microphone when drone is flying, and direction of drone is estimated. When estimating the Direction of Arrival(DOA), there is a method of calculating the DOA based on the Time Difference of Arrival(TDOA) and a method of calculating the DOA based on the beamforming. The TDOA technique requires less number of microphones than the beamforming technique, but is weak in noisy environments and can only estimate the DOA of a single source. The beamforming technique requires more microphones than the TDOA technique. However, it is strong against the noisy environment and it is possible to simultaneously estimate the DOA of several drones. When estimating the DOA using acoustic signals emitted from the drone, it is impossible to measure the position of the drone, and only the direction can be estimated. To overcome this problem, in this work we show how to estimate the position of drones by arranging multiple microphone arrays. The microphone array used in the experiments was four tetrahedral microphones. We simulated the performance of each DOA algorithm and demonstrated the simulation results through experiments.

Keywords: acoustic sensing, direction of arrival, drone detection, microphone array

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22094 Villar Settlement Farm School for the Aetas: Assimilation through American Colonial Education in Zambales, Philippines

Authors: Julian E. Abuso, Alberto T. Paala Jr.

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The creation of settlement farm schools at the outset of American colonization of the Philippines was not a matter of accident; rather, their establishment was a major component of a grand plan on public education based on the benevolent assimilation policy of the United States. This argument is illustrated by the case of Villar Settlement Farm School, a school for the Aetas as a non-Christian tribal community in 1907. The study aims to: (1) identify and describe the antecedents for the establishment of Settlement Farm School, (2) explicate the cultural conflicts encountered by Aetas in school, (3) appraise the consequences of education as acculturation among Aeta population. The study made use of the following: historical data based on primary and secondary sources and life histories from primary informants. The Settlement Farm School for the Aetas was borne out of the American’s change in policy from military to civilian authority, recognition of education as a tool for benevolent assimilation. The narratives of informants manifested resistance to certain aspects of the educational process.

Keywords: settlement farm school Aetas, tribe, colonial education, Aeta, non-Christian tribal community

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22093 Using Variation Theory in a Design-based Approach to Improve Learning Outcomes of Teachers Use of Video and Live Experiments in Swedish Upper Secondary School

Authors: Andreas Johansson

Abstract:

Conceptual understanding needs to be grounded on observation of physical phenomena, experiences or metaphors. Observation of physical phenomena using demonstration experiments has a long tradition within physics education and students need to develop mental models to relate the observations to concepts from scientific theories. This study investigates how live and video experiments involving an acoustic trap to visualize particle-field interaction, field properties and particle properties can help develop students' mental models and how they can be used differently to realize their potential as teaching tools. Initially, they were treated as analogs and the lesson designs were kept identical. With a design-based approach, the experimental and video designs, as well as best practices for a respective teaching tool, were then developed in iterations. Variation theory was used as a theoretical framework to analyze the planned respective realized pattern of variation and invariance in order to explain learning outcomes as measured by a pre-posttest consisting of conceptual multiple-choice questions inspired by the Force Concept Inventory and the Force and Motion Conceptual Evaluation. Interviews with students and teachers were used to inform the design of experiments and videos in each iteration. The lesson designs and the live and video experiments has been developed to help teachers improve student learning and make school physics more interesting by involving experimental setups that usually are out of reach and to bridge the gap between what happens in classrooms and in science research. As students’ conceptual knowledge also rises their interest in physics the aim is to increase their chances of pursuing careers within science, technology, engineering or mathematics.

Keywords: acoustic trap, design-based research, experiments, variation theory

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22092 Genetic Algorithm Based Node Fault Detection and Recovery in Distributed Sensor Networks

Authors: N. Nalini, Lokesh B. Bhajantri

Abstract:

In Distributed Sensor Networks, the sensor nodes are prone to failure due to energy depletion and some other reasons. In this regard, fault tolerance of network is essential in distributed sensor environment. Energy efficiency, network or topology control and fault-tolerance are the most important issues in the development of next-generation Distributed Sensor Networks (DSNs). This paper proposes a node fault detection and recovery using Genetic Algorithm (GA) in DSN when some of the sensor nodes are faulty. The main objective of this work is to provide fault tolerance mechanism which is energy efficient and responsive to network using GA, which is used to detect the faulty nodes in the network based on the energy depletion of node and link failure between nodes. The proposed fault detection model is used to detect faults at node level and network level faults (link failure and packet error). Finally, the performance parameters for the proposed scheme are evaluated.

Keywords: distributed sensor networks, genetic algorithm, fault detection and recovery, information technology

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22091 Using Group Concept Mapping to Identify a Pharmacy-Based Trigger Tool to Detect Adverse Drug Events

Authors: Rodchares Hanrinth, Theerapong Srisil, Peeraya Sriphong, Pawich Paktipat

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The trigger tool is the low-cost, low-tech method to detect adverse events through clues called triggers. The Institute for Healthcare Improvement (IHI) has developed the Global Trigger Tool for measuring and preventing adverse events. However, this tool is not specific for detecting adverse drug events. The pharmacy-based trigger tool is needed to detect adverse drug events (ADEs). Group concept mapping is an effective method for conceptualizing various ideas from diverse stakeholders. This technique was used to identify a pharmacy-based trigger to detect adverse drug events (ADEs). The aim of this study was to involve the pharmacists in conceptualizing, developing, and prioritizing a feasible trigger tool to detect adverse drug events in a provincial hospital, the northeastern part of Thailand. The study was conducted during the 6-month period between April 1 and September 30, 2017. Study participants involved 20 pharmacists (17 hospital pharmacists and 3 pharmacy lecturers) engaging in three concept mapping workshops. In this meeting, the concept mapping technique created by Trochim, a highly constructed qualitative group technic for idea generating and sharing, was used to produce and construct participants' views on what triggers were potential to detect ADEs. During the workshops, participants (n = 20) were asked to individually rate the feasibility and potentiality of each trigger and to group them into relevant categories to enable multidimensional scaling and hierarchical cluster analysis. The outputs of analysis included the trigger list, cluster list, point map, point rating map, cluster map, and cluster rating map. The three workshops together resulted in 21 different triggers that were structured in a framework forming 5 clusters: drug allergy, drugs induced diseases, dosage adjustment in renal diseases, potassium concerning, and drug overdose. The first cluster is drug allergy such as the doctor’s orders for dexamethasone injection combined with chlorpheniramine injection. Later, the diagnosis of drug-induced hepatitis in a patient taking anti-tuberculosis drugs is one trigger in the ‘drugs induced diseases’ cluster. Then, for the third cluster, the doctor’s orders for enalapril combined with ibuprofen in a patient with chronic kidney disease is the example of a trigger. The doctor’s orders for digoxin in a patient with hypokalemia is a trigger in a cluster. Finally, the doctor’s orders for naloxone with narcotic overdose was classified as a trigger in a cluster. This study generated triggers that are similar to some of IHI Global trigger tool, especially in the medication module such as drug allergy and drug overdose. However, there are some specific aspects of this tool, including drug-induced diseases, dosage adjustment in renal diseases, and potassium concerning which do not contain in any trigger tools. The pharmacy-based trigger tool is suitable for pharmacists in hospitals to detect potential adverse drug events using clues of triggers.

Keywords: adverse drug events, concept mapping, hospital, pharmacy-based trigger tool

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22090 Student Perceptions of Defense Acquisition University Courses: An Explanatory Data Collection Approach

Authors: Melissa C. LaDuke

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The overarching purpose of this study was to determine the relationship between the current format of online delivery for Defense Acquisition University (DAU) courses and Air Force Acquisition (AFA) personnel participation. AFA personnel (hereafter named “student”) were particularly of interest, as they have been mandated to take anywhere from 3 to 30 online courses to earn various DAU specialization certifications. Participants in this qualitative case study were AFA personnel who pursued DAU certifications in science and technology management, program/contract management, and other related fields. Air Force personnel were interviewed about their experiences with online courses. The data gathered were analyzed and grouped into 12 major themes. The themes tied into the theoretical framework and spoke to either teacher-centered or student-centered educational practices within Defense Acquisitions University. Based on the results of the data analysis, various factors contributed to student perceptions of DAU courses, including the online course construct and relevance to their job. The analysis also found students want to learn the information presented but would like to be able to apply the information learned in meaningful ways.

Keywords: educational theory, computer-based training, interview, student perceptions, online course design, teacher positionality

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22089 Mediation Models in Triadic Relationships: Illness Narratives and Medical Education

Authors: Yoko Yamada, Chizumi Yamada

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Narrative psychology is based on the dialogical relationship between self and other. The dialogue can consist of divided, competitive, or opposite communication between self and other. We constructed models of coexistent dialogue in which self and other were positioned side by side and communicated sympathetically. We propose new mediation models for narrative relationships. The mediation models are based on triadic relationships that incorporate a medium or a mediator along with self and other. We constructed three types of mediation model. In the first type, called the “Joint Attention Model”, self and other are positioned side by side and share attention with the medium. In the second type, the “Triangle Model”, an agent mediates between self and other. In the third type, the “Caring Model”, a caregiver stands beside the communication between self and other. We apply the three models to the illness narratives of medical professionals and patients. As these groups have different views and experiences of disease or illness, triadic mediation facilitates the ability to see things from the other person’s perspective and to bridge differences in people’s experiences and feelings. These models would be useful for medical education in various situations, such as in considering the relationships between senior and junior doctors and between old and young patients.

Keywords: illness narrative, mediation, psychology, model, medical education

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22088 Enhancing Early Detection of Coronary Heart Disease Through Cloud-Based AI and Novel Simulation Techniques

Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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22087 Cluster-Based Exploration of System Readiness Levels: Mathematical Properties of Interfaces

Authors: Justin Fu, Thomas Mazzuchi, Shahram Sarkani

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A key factor in technological immaturity in defense weapons acquisition is lack of understanding critical integrations at the subsystem and component level. To address this shortfall, recent research in integration readiness level (IRL) combines with technology readiness level (TRL) to form a system readiness level (SRL). SRL can be enriched with more robust quantitative methods to provide the program manager a useful tool prior to committing to major weapons acquisition programs. This research harnesses previous mathematical models based on graph theory, Petri nets, and tropical algebra and proposes a modification of the desirable SRL mathematical properties such that a tightly integrated (multitude of interfaces) subsystem can display a lower SRL than an inherently less coupled subsystem. The synthesis of these methods informs an improved decision tool for the program manager to commit to expensive technology development. This research ties the separately developed manufacturing readiness level (MRL) into the network representation of the system and addresses shortfalls in previous frameworks, including the lack of integration weighting and the over-importance of a single extremely immature component. Tropical algebra (based on the minimum of a set of TRLs or IRLs) allows one low IRL or TRL value to diminish the SRL of the entire system, which may not be reflective of actuality if that component is not critical or tightly coupled. Integration connections can be weighted according to importance and readiness levels are modified to be a cardinal scale (based on an analytic hierarchy process). Integration arcs’ importance are dependent on the connected nodes and the additional integrations arcs connected to those nodes. Lack of integration is not represented by zero, but by a perfect integration maturity value. Naturally, the importance (or weight) of such an arc would be zero. To further explore the impact of grouping subsystems, a multi-objective genetic algorithm is then used to find various clusters or communities that can be optimized for the most representative subsystem SRL. This novel calculation is then benchmarked through simulation and using past defense acquisition program data, focusing on the newly introduced Middle Tier of Acquisition (rapidly field prototypes). The model remains a relatively simple, accessible tool, but at higher fidelity and validated with past data for the program manager to decide major defense acquisition program milestones.

Keywords: readiness, maturity, system, integration

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22086 Mapping Vulnerabilities: A Social and Political Study of Disasters in Eastern Himalayas, Region of Darjeeling

Authors: Shailendra M. Pradhan, Upendra M. Pradhan

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Disasters are perennial features of human civilization. The recurring earthquakes, floods, cyclones, among others, that result in massive loss of lives and devastation, is a grim reminder of the fact that, despite all our success stories of development, and progress in science and technology, human society is perennially at risk to disasters. The apparent threat of climate change and global warming only severe our disaster risks. Darjeeling hills, situated along Eastern Himalayan region of India, and famous for its three Ts – tea, tourism and toy-train – is also equally notorious for its disasters. The recurring landslides and earthquakes, the cyclone Aila, and the Ambootia landslides, considered as the largest landslide in Asia, are strong evidence of the vulnerability of Darjeeling hills to natural disasters. Given its geographical location along the Hindu-Kush Himalayas, the region is marked by rugged topography, geo-physically unstable structure, high-seismicity, and fragile landscape, making it prone to disasters of different kinds and magnitudes. Most of the studies on disasters in Darjeeling hills are, however, scientific and geographical in orientation that focuses on the underlying geological and physical processes to the neglect of social and political conditions. This has created a tendency among the researchers and policy-makers to endorse and promote a particular type of discourse that does not consider the social and political aspects of disasters in Darjeeling hills. Disaster, this paper argues, is a complex phenomenon, and a result of diverse factors, both physical and human. The hazards caused by the physical and geological agents, and the vulnerabilities produced and rooted in political, economic, social and cultural structures of a society, together result in disasters. In this sense, disasters are as much a result of political and economic conditions as it is of physical environment. The human aspect of disasters, therefore, compels us to address intricating social and political challenges that ultimately determine our resilience and vulnerability to disasters. Set within the above milieu, the aims of the paper are twofold: a) to provide a political and sociological account of disasters in Darjeeling hills; and, b) to identify and address the root causes of its vulnerabilities to disasters. In situating disasters in Darjeeling Hills, the paper adopts the Pressure and Release Model (PAR) that provides a theoretical insight into the study of social and political aspects of disasters, and to examine myriads of other related issues therein. The PAR model conceptualises risk as a complex combination of vulnerabilities, on the one hand, and hazards, on the other. Disasters, within the PAR framework, occur when hazards interact with vulnerabilities. The root causes of vulnerability, in turn, could be traced to social and political structures such as legal definitions of rights, gender relations, and other ideological structures and processes. In this way, the PAR model helps the present study to identify and unpack the root causes of vulnerabilities and disasters in Darjeeling hills that have largely remained neglected in dominant discourses, thereby providing a more nuanced and sociologically sensitive understanding of disasters.

Keywords: Darjeeling, disasters, PAR, vulnerabilities

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22085 The Univalence Principle: Equivalent Mathematical Structures Are Indistinguishable

Authors: Michael Shulman, Paige North, Benedikt Ahrens, Dmitris Tsementzis

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The Univalence Principle is the statement that equivalent mathematical structures are indistinguishable. We prove a general version of this principle that applies to all set-based, categorical, and higher-categorical structures defined in a non-algebraic and space-based style, as well as models of higher-order theories such as topological spaces. In particular, we formulate a general definition of indiscernibility for objects of any such structure, and a corresponding univalence condition that generalizes Rezk’s completeness condition for Segal spaces and ensures that all equivalences of structures are levelwise equivalences. Our work builds on Makkai’s First-Order Logic with Dependent Sorts, but is expressed in Voevodsky’s Univalent Foundations (UF), extending previous work on the Structure Identity Principle and univalent categories in UF. This enables indistinguishability to be expressed simply as identification, and yields a formal theory that is interpretable in classical homotopy theory, but also in other higher topos models. It follows that Univalent Foundations is a fully equivalence-invariant foundation for higher-categorical mathematics, as intended by Voevodsky.

Keywords: category theory, higher structures, inverse category, univalence

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22084 Leveraging Multimodal Neuroimaging Techniques to in vivo Address Compensatory and Disintegration Patterns in Neurodegenerative Disorders: Evidence from Cortico-Cerebellar Connections in Multiple Sclerosis

Authors: Efstratios Karavasilis, Foteini Christidi, Georgios Velonakis, Agapi Plousi, Kalliopi Platoni, Nikolaos Kelekis, Ioannis Evdokimidis, Efstathios Efstathopoulos

Abstract:

Introduction: Advanced structural and functional neuroimaging techniques contribute to the study of anatomical and functional brain connectivity and its role in the pathophysiology and symptoms’ heterogeneity in several neurodegenerative disorders, including multiple sclerosis (MS). Aim: In the present study, we applied multiparametric neuroimaging techniques to investigate the structural and functional cortico-cerebellar changes in MS patients. Material: We included 51 MS patients (28 with clinically isolated syndrome [CIS], 31 with relapsing-remitting MS [RRMS]) and 51 age- and gender-matched healthy controls (HC) who underwent MRI in a 3.0T MRI scanner. Methodology: The acquisition protocol included high-resolution 3D T1 weighted, diffusion-weighted imaging and echo planar imaging sequences for the analysis of volumetric, tractography and functional resting state data, respectively. We performed between-group comparisons (CIS, RRMS, HC) using CAT12 and CONN16 MATLAB toolboxes for the analysis of volumetric (cerebellar gray matter density) and functional (cortico-cerebellar resting-state functional connectivity) data, respectively. Brainance suite was used for the analysis of tractography data (cortico-cerebellar white matter integrity; fractional anisotropy [FA]; axial and radial diffusivity [AD; RD]) to reconstruct the cerebellum tracts. Results: Patients with CIS did not show significant gray matter (GM) density differences compared with HC. However, they showed decreased FA and increased diffusivity measures in cortico-cerebellar tracts, and increased cortico-cerebellar functional connectivity. Patients with RRMS showed decreased GM density in cerebellar regions, decreased FA and increased diffusivity measures in cortico-cerebellar WM tracts, as well as a pattern of increased and mostly decreased functional cortico-cerebellar connectivity compared to HC. The comparison between CIS and RRMS patients revealed significant GM density difference, reduced FA and increased diffusivity measures in WM cortico-cerebellar tracts and increased/decreased functional connectivity. The identification of decreased WM integrity and increased functional cortico-cerebellar connectivity without GM changes in CIS and the pattern of decreased GM density decreased WM integrity and mostly decreased functional connectivity in RRMS patients emphasizes the role of compensatory mechanisms in early disease stages and the disintegration of structural and functional networks with disease progression. Conclusions: In conclusion, our study highlights the added value of multimodal neuroimaging techniques for the in vivo investigation of cortico-cerebellar brain changes in neurodegenerative disorders. An extension and future opportunity to leverage multimodal neuroimaging data inevitably remain the integration of such data in the recently-applied mathematical approaches of machine learning algorithms to more accurately classify and predict patients’ disease course.

Keywords: advanced neuroimaging techniques, cerebellum, MRI, multiple sclerosis

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22083 New Highly-Scalable Carbon Nanotube-Reinforced Glasses and Ceramics

Authors: Konstantinos G. Dassios, Guillaume Bonnefont, Gilbert Fantozzi, Theodore E. Matikas, Costas Galiotis

Abstract:

We report herein the development and preliminary mechanical characterization of fully-dense multi-wall carbon nanotube (MWCNT)-reinforced ceramics and glasses based on a completely new methodology termed High Shear Compaction (HSC). The tubes are introduced and bound to the matrix grains by aid of polymeric binders to form flexible green bodies which are sintered and densified by spark plasma sintering to unprecedentedly high densities of 100% of the pure-matrix value. The strategy was validated across a PyrexTM glass / MWCNT composite while no identifiable factors limit application to other types of matrices. Non-destructive evaluation, based on ultrasonics, of the dynamic mechanical properties of the materials including elastic, shear and bulk modulus as well as Poisson’s ratio showed optimum property improvement at 0.5 %wt tube loading while evidence of nanoscale-specific energy dissipative characteristics acting complementary to nanotube bridging and pull-out indicate a high potential in a wide range of reinforcing and multifunctional applications.

Keywords: ceramic matrix composites, carbon nanotubes, toughening, ultrasonics

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22082 Human Action Retrieval System Using Features Weight Updating Based Relevance Feedback Approach

Authors: Munaf Rashid

Abstract:

For content-based human action retrieval systems, search accuracy is often inferior because of the following two reasons 1) global information pertaining to videos is totally ignored, only low level motion descriptors are considered as a significant feature to match the similarity between query and database videos, and 2) the semantic gap between the high level user concept and low level visual features. Hence, in this paper, we propose a method that will address these two issues and in doing so, this paper contributes in two ways. Firstly, we introduce a method that uses both global and local information in one framework for an action retrieval task. Secondly, to minimize the semantic gap, a user concept is involved by incorporating features weight updating (FWU) Relevance Feedback (RF) approach. We use statistical characteristics to dynamically update weights of the feature descriptors so that after every RF iteration feature space is modified accordingly. For testing and validation purpose two human action recognition datasets have been utilized, namely Weizmann and UCF. Results show that even with a number of visual challenges the proposed approach performs well.

Keywords: relevance feedback (RF), action retrieval, semantic gap, feature descriptor, codebook

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22081 Remote Criminal Proceedings as Implication to Rethink the Principles of Criminal Procedure

Authors: Inga Žukovaitė

Abstract:

This paper aims to present postdoc research on remote criminal proceedings in court. In this period, when most countries have introduced the possibility of remote criminal proceedings in their procedural laws, it is not only possible to identify the weaknesses and strengths of the legal regulation but also assess the effectiveness of the instrument used and to develop an approach to the process. The example of some countries (for example, Italy) shows, on the one hand, that criminal procedure, based on orality and immediacy, does not lend itself to easy modifications that pose even a slight threat of devaluation of these principles in a society with well-established traditions of this procedure. On the other hand, such strong opposition and criticism make us ask whether we are facing the possibility of rethinking the traditional ways to understand the safeguards in order to preserve their essence without devaluing their traditional package but looking for new components to replace or compensate for the so-called “loss” of safeguards. The reflection on technological progress in the field of criminal procedural law indicates the need to rethink, on the basis of fundamental procedural principles, the safeguards that can replace or compensate for those that are in crisis as a result of the intervention of technological progress. Discussions in academic doctrine on the impact of technological interventions on the proceedings as such or on the limits of such interventions refer to the principles of criminal procedure as to a point of reference. In the context of the inferiority of technology, scholarly debate still addresses the issue of whether the court will not gradually become a mere site for the exercise of penal power with the resultant consequences – the deformation of the procedure itself as a physical ritual. In this context, this work seeks to illustrate the relationship between remote criminal proceedings in court and the principle of immediacy, the concept of which is based on the application of different models of criminal procedure (inquisitorial and adversarial), the aim is to assess the challenges posed for legal regulation by the interaction of technological progress with the principles of criminal procedure. The main hypothesis to be tested is that the adoption of remote proceedings is directly linked to the prevailing model of criminal procedure, arguing that the more principles of the inquisitorial model are applied to the criminal process, the more remote criminal trial is acceptable, and conversely, the more the criminal process is based on an adversarial model, more the remote criminal process is seen as incompatible with the principle of immediacy. In order to achieve this goal, the following tasks are set: to identify whether there is a difference in assessing remote proceedings with the immediacy principle between the adversarial model and the inquisitorial model, to analyse the main aspects of the regulation of remote criminal proceedings based on the examples of different countries (for example Lithuania, Italy, etc.).

Keywords: remote criminal proceedings, principle of orality, principle of immediacy, adversarial model inquisitorial model

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22080 Production of Poly-β-Hydroxybutyrate (PHB) by a Thermophilic Strain of Bacillus and Pseudomonas Species

Authors: Patience Orobosa Olajide

Abstract:

Five hydrocarbon degrading bacterial strains isolated from contaminated environment were investigated with respect to polyhydroxybutyrate (PHB) biosynthesis. Screening for bioplastic production was done on assay mineral salts agar medium containing 0.2% poly (3-hydroxybutyrate) as the sole carbon source. Two of the test bacteria were positive for PHB biosynthesis and were identified based on gram staining, biochemical tests, 16S rRNA gene sequence analysis as Pseudomonas aeruginosa and Bacillus licheniformis which grew at 37 and up to 65 °C respectively, thus suggesting the later to be thermotolerant. In this study, the effects of different carbon and nitrogen sources on PHB production in these strains were investigated. Maximum PHB production was obtained in 48 hr for the two strains and amounted to yields of 72.86 and 62.22 percentages for Bacillus licheniformis and Pseudomonas aeruginosa respectively. In these strains, glycine was the most efficient carbon sources for the production of PHB compared with other carbon (glucose, lactose, sucrose, Arabinose) and nitrogen (L- glycine, L-cysteine, DL-Tryptophan, and Potassium Nitrate) sources. The screening of microbial strains for industrial PHB production should be based on several factors including the cell’s capability to mineralize an inexpensive substrate, rate of growth and the extent of polymer accumulation.

Keywords: bacteria, poly-3-hydroxybutyrate (PHB), hydrocarbon, thermotolerant

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22079 Two Component Source Apportionment Based on Absorption and Size Distribution Measurement

Authors: Tibor Ajtai, Noémi Utry, Máté Pintér, Gábor Szabó, Zoltán Bozóki

Abstract:

Beyond its climate and health related issues ambient light absorbing carbonaceous particulate matter (LAC) has also become a great scientific interest in terms of its regulations recently. It has been experimentally demonstrated in recent studies, that LAC is dominantly composed of traffic and wood burning aerosol particularly under wintertime urban conditions, when the photochemical and biological activities are negligible. Several methods have been introduced to quantitatively apportion aerosol fractions emitted by wood burning and traffic but most of them require costly and time consuming off-line chemical analysis. As opposed to chemical features, the microphysical properties of airborne particles such as optical absorption and size distribution can be easily measured on-line, with high accuracy and sensitivity, especially under highly polluted urban conditions. Recently a new method has been proposed for the apportionment of wood burning and traffic aerosols based on the spectral dependence of their absorption quantified by the Aerosol Angström Exponent (AAE). In this approach the absorption coefficient is deduced from transmission measurement on a filter accumulated aerosol sample and the conversion factor between the measured optical absorption and the corresponding mass concentration (the specific absorption cross section) are determined by on-site chemical analysis. The recently developed multi-wavelength photoacoustic instruments provide novel, in-situ approach towards the reliable and quantitative characterization of carbonaceous particulate matter. Therefore, it also opens up novel possibilities on the source apportionment through the measurement of light absorption. In this study, we demonstrate an in-situ spectral characterization method of the ambient carbon fraction based on light absorption and size distribution measurements using our state-of-the-art multi-wavelength photoacoustic instrument (4λ-PAS) and Single Mobility Particle Sizer (SMPS) The carbonaceous particulate selective source apportionment study was performed for ambient particulate matter in the city center of Szeged, Hungary where the dominance of traffic and wood burning aerosol has been experimentally demonstrated earlier. The proposed model is based on the parallel, in-situ measurement of optical absorption and size distribution. AAEff and AAEwb were deduced from the measured data using the defined correlation between the AOC(1064nm)/AOC(266nm) and N100/N20 ratios. σff(λ) and σwb(λ) were determined with the help of the independently measured temporal mass concentrations in the PM1 mode. Furthermore, the proposed optical source apportionment is based on the assumption that the light absorbing fraction of PM is exclusively related to traffic and wood burning. This assumption is indirectly confirmed here by the fact that the measured size distribution is composed of two unimodal size distributions identified to correspond to traffic and wood burning aerosols. The method offers the possibility of replacing laborious chemical analysis with simple in-situ measurement of aerosol size distribution data. The results by the proposed novel optical absorption based source apportionment method prove its applicability whenever measurements are performed at an urban site where traffic and wood burning are the dominant carbonaceous sources of emission.

Keywords: absorption, size distribution, source apportionment, wood burning, traffic aerosol

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22078 Role-Governed Categorization and Category Learning as a Result from Structural Alignment: The RoleMap Model

Authors: Yolina A. Petrova, Georgi I. Petkov

Abstract:

The paper presents a symbolic model for category learning and categorization (called RoleMap). Unlike the other models which implement learning in a separate working mode, role-governed category learning and categorization emerge in RoleMap while it does its usual reasoning. The model is based on several basic mechanisms known as reflecting the sub-processes of analogy-making. It steps on the assumption that in their everyday life people constantly compare what they experience and what they know. Various commonalities between the incoming information (current experience) and the stored one (long-term memory) emerge from those comparisons. Some of those commonalities are considered to be highly important, and they are transformed into concepts for further use. This process denotes the category learning. When there is missing knowledge in the incoming information (i.e. the perceived object is still not recognized), the model makes anticipations about what is missing, based on the similar episodes from its long-term memory. Various such anticipations may emerge for different reasons. However, with time only one of them wins and is transformed into a category member. This process denotes the act of categorization.

Keywords: analogy-making, categorization, category learning, cognitive modeling, role-governed categories

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22077 An Automatic Model Transformation Methodology Based on Semantic and Syntactic Comparisons and the Granularity Issue Involved

Authors: Tiexin Wang, Sebastien Truptil, Frederick Benaben

Abstract:

Model transformation, as a pivotal aspect of Model-driven engineering, attracts more and more attentions both from researchers and practitioners. Many domains (enterprise engineering, software engineering, knowledge engineering, etc.) use model transformation principles and practices to serve to their domain specific problems; furthermore, model transformation could also be used to fulfill the gap between different domains: by sharing and exchanging knowledge. Since model transformation has been widely used, there comes new requirement on it: effectively and efficiently define the transformation process and reduce manual effort that involved in. This paper presents an automatic model transformation methodology based on semantic and syntactic comparisons, and focuses particularly on granularity issue that existed in transformation process. Comparing to the traditional model transformation methodologies, this methodology serves to a general purpose: cross-domain methodology. Semantic and syntactic checking measurements are combined into a refined transformation process, which solves the granularity issue. Moreover, semantic and syntactic comparisons are supported by software tool; manual effort is replaced in this way.

Keywords: automatic model transformation, granularity issue, model-driven engineering, semantic and syntactic comparisons

Procedia PDF Downloads 387
22076 The Link Between Collaboration Interactions and Team Creativity Among Nursing Student Teams in Taiwan: A Moderated Mediation Model

Authors: Hsing Yuan Liu

Abstract:

Background: Considerable theoretical and empirical work has identified a relationship between collaboration interactions and creativity in an organizational context. The mechanisms underlying this link, however, are not well understood in healthcare education. Objectives: The aims of this study were to explore the impact of collaboration interactions on team creativity and its underlying mechanism and to verify a moderated mediation model. Design, setting, and participants: This study utilized a cross-sectional, quantitative, descriptive design. The survey data were collected from 177 nursing students who enrolled in 18-week capstone courses of small interdisciplinary groups collaborating to design healthcare products in Taiwan during 2018 and 2019. Methods: Questionnaires assessed the nursing students' perceptions about their teams' swift trust (of cognition- and affect-based), conflicts (of task, process, and relationship), interaction behaviors (constructive controversy, helping behaviors, and spontaneous communication), and creativity. This study used descriptive statistics to compare demographics, swift trust scores, conflict scores, interaction behavior scores, and creativity scores for interdisciplinary teams. Data were analyzed using Pearson’s correlation coefficient and simple and hierarchical multiple regression models. Results: Pearson’s correlation analysis showed the cognition-based team swift trust was positively correlated with team creativity. The mediation model indicated constructive controversy fully mediated the effect of cognition-based team swift trust on student teams’ creativity. The moderated mediation model indicated that task conflict negatively moderates the mediating effect of the constructive controversy on the link between cognition-based team swift trust and team creativity. Conclusion: Our findings suggest nursing student teams’ interaction behaviors and task conflict are crucial mediating and moderated mediation variables on the relationship between collaboration interactions and team creativity, respectively. The empirical data confirms the validity of our proposed moderated mediation models of team creativity. Therefore, this study's validated moderated mediation model could provide guidance for nursing educators to improve collaboration interaction outcomes and creativity on nursing student teams.

Keywords: team swift trust, team conflict, team interaction behavior, moderated mediating effects, interdisciplinary education, nursing students

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22075 Modeling of the Mechanism of Ion Channel Opening of the Visual Receptor's Rod on the Light and Allosteric Effect of Rhodopsin in the Phosphorylation Process

Authors: N. S. Vassilieva-Vashakmadze, R. A. Gakhokidze, I. M. Khachatryan

Abstract:

In the first part of the paper it is shown that both the depolarization of the cytoplasmic membrane of rods observed in invertebrates and hyperpolarization characteristic of vertebrates on the light may activate the functioning of ion (Na+) channels of cytoplasmic membrane of rods and thus provide the emergence of nerve impulse and its transfer to the neighboring neuron etc. In the second part, using the quantum mechanical program for modeling of the molecular processes, we got a clear picture demonstrating the effect of charged phosphate groups on the protein components of α-helical subunits of the visual rhodopsin receptor. The analysis shows that the phosphorylation of terminal amino acid of seventh α-helical subunits of the visual rhodopsin causes a redistribution of electron density on the atoms, i.e. polarization of subunits, also the changing the configuration of the nuclear subsystem, which corresponds to the deformation process in the molecule. Based on the use of models it can be concluded that this system has an internal relationship between polarization and deformation processes that indicates on the allosteric effect. The allosteric effect is based on quantum-mechanical principle of the self-consistency of the molecules.

Keywords: membrane potential, ion channels, visual rhodopsin, allosteric effect

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22074 Constructing the Joint Mean-Variance Regions for Univariate and Bivariate Normal Distributions: Approach Based on the Measure of Cumulative Distribution Functions

Authors: Valerii Dashuk

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The usage of the confidence intervals in economics and econometrics is widespread. To be able to investigate a random variable more thoroughly, joint tests are applied. One of such examples is joint mean-variance test. A new approach for testing such hypotheses and constructing confidence sets is introduced. Exploring both the value of the random variable and its deviation with the help of this technique allows checking simultaneously the shift and the probability of that shift (i.e., portfolio risks). Another application is based on the normal distribution, which is fully defined by mean and variance, therefore could be tested using the introduced approach. This method is based on the difference of probability density functions. The starting point is two sets of normal distribution parameters that should be compared (whether they may be considered as identical with given significance level). Then the absolute difference in probabilities at each 'point' of the domain of these distributions is calculated. This measure is transformed to a function of cumulative distribution functions and compared to the critical values. Critical values table was designed from the simulations. The approach was compared with the other techniques for the univariate case. It differs qualitatively and quantitatively in easiness of implementation, computation speed, accuracy of the critical region (theoretical vs. real significance level). Stable results when working with outliers and non-normal distributions, as well as scaling possibilities, are also strong sides of the method. The main advantage of this approach is the possibility to extend it to infinite-dimension case, which was not possible in the most of the previous works. At the moment expansion to 2-dimensional state is done and it allows to test jointly up to 5 parameters. Therefore the derived technique is equivalent to classic tests in standard situations but gives more efficient alternatives in nonstandard problems and on big amounts of data.

Keywords: confidence set, cumulative distribution function, hypotheses testing, normal distribution, probability density function

Procedia PDF Downloads 172
22073 Road Maintenance Management Decision System Using Multi-Criteria and Geographical Information System for Takoradi Roads, Ghana

Authors: Eric Mensah, Carlos Mensah

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The road maintenance backlogs created as a result of deferred maintenance especially in developing countries has caused considerable deterioration of many road assets. This is usually due to difficulties encountered in selecting and prioritising maintainable roads based on objective criteria rather than some political or other less important criteria. In order to ensure judicious use of limited resources for road maintenance, five factors were identified as the most important criteria for road management within the study area. This was based on the judgements of 40 experts. The results were further used to develop weightings using the Multi-Criteria Decision Process (MCDP) to analyse and select road alternatives according to maintenance goal. Using Geographical Information Systems (GIS), maintainable roads were grouped using the Jenk’s natural breaks to allow for further prioritised in order of importance for display on a dashboard of maps, charts, and tables. This reduces the problems of subjective maintenance and road selections, thereby reducing wastage of resources and easing the maintenance process through an object organised spatial decision support system.

Keywords: decision support, geographical information systems, multi-criteria decision process, weighted sum

Procedia PDF Downloads 370