Search results for: territorial information systems

Authors: Catherine Thompson, Maryam Jalali, Peter Hills

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The allocation of visual attention is critical when driving and anything that limits attention will have a detrimental impact on safety. Engaging in a secondary task reduces the amount of attention directed to the road because drivers allocate resources towards this task, leaving fewer resources to process driving-relevant information. Yet the dangers associated with a secondary task do not end when the driver returns their attention to the road. Instead, the attentional settings adopted to complete a secondary task may persist to the road, affecting attention, and therefore affecting driver performance. This 'attentional inertia' effect was investigated in the current work. Forty drivers searched for hazards in driving video clips while their eye-movements were recorded. At varying intervals they were instructed to attend to a secondary task displayed on a tablet situated to their left-hand side. The secondary task consisted of three separate computer games that induced horizontal, vertical, and random eye movements. Visual search and hazard detection in the driving clips were compared across the three conditions of the secondary task. Results showed that the layout of information in the secondary task, and therefore the allocation of attention in this task, had an impact on subsequent search in the driving clips. Vertically presented information reduced the wide horizontal spread of search usually associated with accurate driving and had a negative influence on the detection of hazards. The findings show the additional dangers of engaging in a secondary task while driving. The attentional inertia effect has significant implications for semi-autonomous and autonomous vehicles in which drivers have greater opportunity to direct their attention away from the driving task.

Keywords: attention, eye-movements, hazard perception, visual search

Procedia PDF Downloads 159

Authors: Rima A. Ajlouni

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The discovery of quasi-periodic structures in material science is revealing an exciting new class of symmetries, which has never been explored before. Due to their unique structural and visual properties, these symmetries are drawing interest from many scientific and design disciplines. Especially, in art and architecture, these symmetries can provide a rich source of geometry for exploring new patterns, forms, systems, and structures. However, the structural systems of these complicated symmetries are still posing a perplexing challenge. While much of their local order has been explored, the global governing system is still unresolved. Understanding their unique global long-range order is essential to their generation and application. The recent discovery of dodecagonal quasi-periodic patterns in historical Islamic architecture is generating a renewed interest into understanding the mathematical principles of traditional Islamic geometry. Astonishingly, many centuries before its description in the modern science, ancient artists, by using the most primitive tools (a compass and a straight edge), were able to construct patterns with quasi-periodic formations. These ancient patterns can be found all over the ancient Islamic world, many of which exhibit formations with 5, 8, 10 and 12 quasi-periodic symmetries. Based on the examination of these historical patterns and derived from the generating principles of Islamic geometry, a global multi-level structural model is presented that is able to describe the global long-range order of dodecagonal quasi-periodic formations in Islamic Architecture. Furthermore, this method is used to construct new quasi-periodic tiling systems as well as generating their deflation and inflation rules. This method can be used as a general guiding principle for constructing infinite patches of dodecagon-based quasi-periodic formations, without the need for local strategies (tiling, matching, grid, substitution, etc.) or complicated mathematics; providing an easy tool for scientists, mathematicians, teachers, designers and artists, to generate and study a wide range of dodecagonal quasi-periodic formations.

Keywords: dodecagonal, Islamic architecture, long-range order, quasi-periodi

Procedia PDF Downloads 398

Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

Procedia PDF Downloads 91

Authors: Romeo Botes, Imelda Smit

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In today’s modern age of technology vast amounts of data needs to be processed in real-time to keep users satisfied. This data comes from various sources and in many formats, including electronic and mobile devices such as GPRS modems and GPS devices. They make use of different protocols including TCP, UDP, and HTTP/s for data communication to web servers and eventually to users. The data obtained from these devices may provide valuable information to users, but are mostly in an unreadable format which needs to be processed to provide information and business intelligence. This data is not always current, it is mostly historical data. The data is not subject to implementation of consistency and redundancy measures as most other data usually is. Most important to the users is that the data are to be pre-processed in a readable format when it is entered into the database. To accomplish this, programmers build processing programs and scripts to decode and process the information stored in databases. Programmers make use of various techniques in such programs to accomplish this, but sometimes neglect the effect some of these techniques may have on database performance. One of the techniques generally used,is to pull data from the database server, process it and push it back to the database server in one single step. Since the processing of the data usually takes some time, it keeps the database busy and locked for the period of time that the processing takes place. Because of this, it decreases the overall performance of the database server and therefore the system’s performance. This paper follows on a paper discussing the performance increase that may be achieved by utilizing array lists along with a pull-process-push data processing technique split in three steps. The purpose of this paper is to expand the number of clients when comparing the two techniques to establish the impact it may have on performance of the CPU storage and processing time.

Keywords: performance measures, algorithm techniques, data processing, push data, process data, array list

Procedia PDF Downloads 237

Authors: Kalangi Rodrigo

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The term Neuroecology elucidates the study of customizable variation in cognition and the brain. Subject marked the birth since 1980s, when researches began to apply methods of comparative evolutionary biology to cognitive processes and the underlying neural mechanisms of cognition. In Archaeology and Anthropology, we observe behaviors such as social learning skills, innovative feeding and foraging, tool use and social manipulation to determine the cognitive processes of ancient mankind. Depending on the brainstem size was used as a control variable, and phylogeny was controlled using independent contrasts. Both disciplines need to enriched with comparative literature and neurological experimental, behavioral studies among tribal peoples as well as primate groups which will lead the research to a potential end. Neuroecology examines the relations between ecological selection pressure and mankind or sex differences in cognition and the brain. The goal of neuroecology is to understand how natural law acts on perception and its neural apparatus. Furthermore, neuroecology will eventually lead both principal disciplines to Ethology, where human behaviors and social management studies from a biological perspective. It can be either ethnoarchaeological or prehistoric. Archaeology should adopt general approach of neuroecology, phylogenetic comparative methods can be used in the field, and new findings on the cognitive mechanisms and brain structures involved mating systems, social organization, communication and foraging. The contribution of neuroecology to archaeology and anthropology is the information it provides on the selective pressures that have influenced the evolution of cognition and brain structure of the mankind. It will shed a new light to the path of evolutionary studies including behavioral ecology, primate archaeology and cognitive archaeology.

Keywords: Neuroecology, Archaeology, Brain Evolution, Cognitive Archaeology

Procedia PDF Downloads 116

Authors: Mohadese Oghbaee, Borna Firouzi

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The emergence of the Internet and more specifically the formation of social media has provided the ground for paying attention to new types of content dissemination. In recent years, Social media users share information, communicate with others, and exchange opinions on social events in this space. Many of the information published in this space are suspicious and produced with the intention of deceiving others. These contents are often called "fake news". Fake news, by disrupting the circulation of the concept and similar concepts such as fake news with correct information and misleading public opinion, has the ability to endanger the security of countries and deprive the audience of the basic right of free access to real information; Competing governments, opposition elements, profit-seeking individuals and even competing organizations, knowing about this capacity, act to distort and overturn the facts in the virtual space of the target countries and communities on a large scale and influence public opinion towards their goals. This process of extensive de-truthing of the information space of the societies has created a wave of harm and worries all over the world. The formation of these concerns has led to the opening of a new path of research for the timely containment and reduction of the destructive effects of fake news on public opinion. In addition, the expansion of this phenomenon has the potential to create serious and important problems for societies, and its impact on events such as the 2016 American elections, Brexit, 2017 French elections, 2019 Indian elections, etc., has caused concerns and led to the adoption of approaches It has been dealt with. In recent years, a simple look at the growth trend of research in "Scopus" shows an increasing increase in research with the keyword "false information", which reached its peak in 2020, namely 524 cases, reached, while in 2015, only 30 scientific-research contents were published in this field. Considering that one of the capabilities of social media is to create a context for the dissemination of news and information, both true and false, in this article, the classification of strategies for spreading fake news in social networks was investigated in social events. To achieve this goal, thematic analysis research method was chosen. In this way, an extensive library study was first conducted in global sources. Then, an in-depth interview was conducted with 18 well-known specialists and experts in the field of news and media in Iran. These experts were selected by purposeful sampling. Then by analyzing the data using the theme analysis method, strategies were obtained; The strategies achieved so far (research is in progress) include unrealistically strengthening/weakening the speed and content of the event, stimulating psycho-media movements, targeting emotional audiences such as women, teenagers and young people, strengthening public hatred, calling the reaction legitimate/illegitimate. events, incitement to physical conflict, simplification of violent protests and targeted publication of images and interviews were introduced.

Keywords: fake news, social network, social events, thematic analysis

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Authors: Nutthan Inkhong, Sutthiphong Ruangchante

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Chiang Rai province is located at the northern border of Thailand. Most of the geography there is the northern continental highlands, and the population has many types of inhabitants, including Thai people, immigrants and ethnic groups such as Akha, Lahu, Lisu, Yao, etc. Most of these ethnic groups migrated from neighbouring countries such as Myanmar, Laos, China, etc. and settled in the mountains. Each ethnic group has their unique traditions, culture, and ways of life, including the musical culture that the ancestors of each ethnic group brought with them. In the present, the Akha have the largest population in the region and still live together in numerous villages in many districts. Thus, Akha musical culture still appears in the community traditions and cultural events of Chiang Rai province regularly. This article presents the situations of Akha musical culture in the present and the predictions for the future. The study method involves the analysis of music information and the related social contexts, which were collected from the fieldwork of ethnomusicological methodology by in-depth interviews, observations, audio and visual recordings, and related documents. The results found that the important persons who are related with Akha musical culture include (1) a musical instrument maker (lives in Mae Chan district) who produces various Akha musical instruments, including gourd mouth organs, Akha drums, two-way flutes, three-hole flutes, Jew’s harps (the sound of teenage love), buffalo horns (the sound symbol of hunting) and bird call instruments (the imitation of bird sounds), (2) a folk philosopher (lives in Mae Pha Luang district) who can teach music to the new generation of Akha people as well as lecture and demonstrate music to academics and tourists, and (3) a community leader (lives in Mae Chan district) who conserves Akha performances, singing and music through various activities of the students in an informal school. Because of the changes to the social contexts and ways of life of the Akha people, such as the educational system, religion, social media, etc., including the popularity of both Thai and international popular music among the new generation of Akha people, changes to and the fading away of Akha musical culture in the future may likely occur. Therefore, the conservation and inheritance of Akha music is an issue that should be resolved quickly. This primary study leads to the next step of the ethnomusicological work and plays a part in preventing or reducing the problems impacting Akha musical culture survival by the recording of Akha music in all of its dimensions, such as producing musical instruments, playing musical instruments, analysis of tuning systems, recording Akha music as musical notation using symbols, researching related social contexts, etc. and the transcription of this information to create lessons that can be returned to the Akha community.

Keywords: Akha music, Chiang Rai, ethnic music in Thailand, ethnomusicology

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Authors: Hafiz Muhammad Tayyab Bhatti, Munazza Usmani

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One of nature's most destructive occurrences, floods do immense damage to communities and economic losses. Nigeria country, specifically southern Nigeria, is known for being prone to flooding. Even though periodic flooding occurs in Nigeria frequently, the floods of 2022 were the worst since those in 2012. Flood vulnerability analysis and mapping are still lacking in this region due to the very limited historical hydrological measurements and surveys on the effects of floods, which makes it difficult to develop and put into practice efficient flood protection measures. Remote sensing and Geographic Information Systems (GIS) are useful approaches to detecting, determining, and estimating the flood extent and its impacts. In this study, NOAA VIIR has been used to extract the flood extent using the flood water fraction data and afterward fused with GIS data for some zonal statistical analysis. The estimated possible flooding areas are validated using satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS). The goal is to map and studied flood extent, flood hazards, and their effects on the population, schools, and health facilities for each state of Nigeria. The resulting flood hazard maps show areas with high-risk levels clearly and serve as an important reference for planning and implementing future flood mitigation and control strategies. Overall, the study demonstrated the viability of using the chosen GIS and remote sensing approaches to detect possible risk regions to secure local populations and enhance disaster response capabilities during natural disasters.

Keywords: flood hazards, remote sensing, damage assessment, GIS, geospatial analysis

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Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

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Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

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Authors: Buse T. Aydın, Enver Ozdemir

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In this study, a double layer authentication scheme between the aircraft and the Air Traffic Control (ATC) tower is designed to prevent any unauthorized aircraft from introducing themselves as friends. The method is a combination of classical cryptographic methods and new generation physical layers. The first layer has employed the embedded key of the aircraft. The embedded key is assumed to installed during the construction of the utility. The other layer is a physical attribute (flight path, distance, etc.) between the aircraft and the ATC tower. We create a mathematical model so that two layers’ information is employed and an aircraft is authenticated as a friend or foe according to the accuracy of the results of the model. The results of the aircraft are compared with the results of the ATC tower and if the values found by the aircraft and ATC tower match within a certain error margin, we mark the aircraft as a friend. In this method, even if embedded key is captured by the enemy aircraft, without the information of the second layer, the enemy can easily be determined. Overall, in this work, we present a more reliable system by adding a physical layer in the authentication process.

Keywords: ADS-B, communication with physical layer security, cryptography, identification friend or foe

Procedia PDF Downloads 155

Authors: Pawan Kumar Sharma, J. Stephan Sampath Kumar, S. Anand, Chandana B. L.

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Protein is the major component for the success in culture of shrimp and fishes. Apparently, excess dietary protein is undesirable, as it not only enhances the production cost but also leads to water quality deterioration. A field survey was conducted with aqua farmers of Kerala, India, a leading state in coastal aquaculture, to assess the role of protein component in feed that can be efficiently and effectively managed for sustainable aquaculture. The study showed an average feed amount of 13.55 ± 2.16 tonnes per hectare was being used by the farmers of Kerala. The average feed cost percentage of Rs. 57.76 ± 13.46 /kg was invested for an average protein level of 36.26 % ± 0.082 in the feed and Rs.78.95 ± 3.086 per kilogram of feed was being paid by the farmers. Study revealed that replacement of fish meal and fish oil within shrimp aquafeeds with alternative protein, and lipid sources can only be achieved if changes are made in the basic shrimp culturing practices, such as closed farming system through water recycling or zero-water exchange, and by maximizing in-situ, floc and natural food production within the culture system. The upshot of such production systems is that imports of high-quality feed ingredients and aqua feeds can eventually be eliminated, and the utilization of locally available feed ingredients from agricultural by-products can be greatly improved and maximized. The promotion of closed shrimp production systems would also greatly reduce water use and increase shrimp production per unit area but would necessitate the continuous provision of electricity for aeration during production. Alternative energy sources such as solar power might be used, and resource poor farming communities should also explore wind energy for use. The study concluded that farm made feed and closed farming systems are essential for the sustainability and profitability of the aquaculture industry.

Keywords: aqua feeds, floc, fish meal, protein, zero-water exchange

Procedia PDF Downloads 138

Authors: Zohreh Moghaddas, Morteza Yazdani, Farhad Hosseinzadeh

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Nowadays, data envelopment analysis (DEA) models featuring network structures have gained widespread usage for evaluating the performance of production systems and activities (Decision-Making Units (DMUs)) across diverse fields. By examining the relationships between the internal stages of the network, these models offer valuable insights to managers and decision-makers regarding the performance of each stage and its impact on the overall network. To further empower system decision-makers, the inverse data envelopment analysis (IDEA) model has been introduced. This model allows the estimation of crucial information for estimating parameters while keeping the efficiency score unchanged or improved, enabling analysis of the sensitivity of system inputs or outputs according to managers' preferences. This empowers managers to apply their preferences and policies on resources, such as inputs and outputs, and analyze various aspects like production, resource allocation processes, and resource efficiency enhancement within the system. The results obtained can be instrumental in making informed decisions in the future. The top result of this study is an analysis of infeasibility and incorrect estimation that may arise in the theory and application of the inverse model of data envelopment analysis with network structures. By addressing these pitfalls, novel protocols are proposed to circumvent these shortcomings effectively. Subsequently, several theoretical and applied problems are examined and resolved through insightful case studies.

Keywords: inverse models of data envelopment analysis, series network, estimation of inputs and outputs, efficiency, resource allocation, sensitivity analysis, infeasibility

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Authors: Nicoleta Simona Vedeanu, Rares Stiufiuc, Dana Alina Magdas

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A detailed knowledge of the teeth structure is mandatory to understand and explain the defects and the dental pathology, but especially to take a correct decision regarding dental prophylaxis and treatment. The present work is an alternative study to the traditional investigation methods used in dentistry, a study based on the use of modern, sensitive physical methods to investigate human enamel and dentin. For the present study, several teeth collected from patients of different ages were used for structural and dietary investigation. The samples were investigated by Raman spectroscopy for the molecular structure analysis of dentin and enamel, atomic force microscopy (AFM) to view the dental topography at the micrometric size and mass spectrometry for isotopic ratios as a fingerprint of patients’ personal diet. The obtained Raman spectra and their interpretation are in good correlation with the literature and may give medical information by comparing affected dental structures with healthy ones. AFM technique gave us the possibility to study in details the dentin and enamel surface to collect information about dental hardness or dental structural changes. δ¹³C values obtained for the studied samples can be classified in C4 category specific to young people and children diet (sweets, cereals, juices, pastry). The methods used in this attempt furnished important information about dentin and enamel structure and dietary habits and each of the three proposed methods can be extended at a larger level in the study of the teeth structure.

Keywords: AFM, dentine, enamel, Raman spectroscopy

Procedia PDF Downloads 142

Authors: Vardan Melkonyan, Arman Azizyan, Astghik Boyajyan

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Virtual reality (VR) exposure therapy is a form of cognitive-behavioral therapy that uses immersive virtual environments to expose individuals to the feared stimuli or situations that trigger their phobia. VR exposure therapy has become an increasingly popular treatment for phobias, including fear of heights, public speaking, and flying, due to its ability to provide a controlled and safe environment for individuals to confront their fears while also allowing therapists to tailor the virtual exposure to the specific needs and goals of each individual. It is also a cost-effective and accessible treatment option, as it can be delivered remotely and does not require the use of drugs. Overall, VR exposure therapy has the potential to be a valuable tool for therapists in the treatment of phobias. But current methods may be improved by incorporating advanced technology such as photorealistic VR environments, tactile feedback suits, and responsive systems. The aim of this study was to identify the most effective approach for enhancing VR exposure therapy for the treatment of phobias. Photorealistic VR environments and stimuli can greatly enhance the effectiveness of VR exposure therapy for the treatment of phobias. By creating immersive, realistic virtual environments that closely mimic the real-life situations that trigger phobia responses, patients are able to more fully engage in the therapeutic process and confront their fears in a controlled and safe manner. This can help to reduce the severity of phobia symptoms and increase treatment outcomes. The use of tactile feedback suits and responsive systems can further enhance the VR exposure therapy experience by adding a physical element to the virtual environment. These suits, which can mimic the sensations of touch, pressure, and movement, allow patients to fully immerse themselves in the virtual world and feel as if they are physically present in the situation. This can help to increase the realism of the virtual environment and make it more effective in reducing phobia symptoms. Additionally, responsive systems can be used to trigger specific events or responses within the virtual environment based on the patient's actions, providing a more interactive and personalized treatment experience. A comprehensive literature review was conducted, including studies on VR exposure therapy for phobias and the use of advanced technology to enhance the therapy. Results indicate that incorporating these enhancements may significantly increase the effectiveness of VR exposure therapy for phobias. Further research is needed to fully understand the potential of these enhancements and to determine the optimal combination and implementation.

Keywords: virtual reality, mental health, phobias, fears, treatment, photorealistic, immersive, phobia

Procedia PDF Downloads 82

Authors: Anna Ouskova Leonteva, Michel Risser, Anne Jeannin-Girardon, Pierre Parrend, Pierre Collet

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This paper proposes an efficient optimization tool for an active magnetic regenerator (AMR) model, operating in two modes: magnetic refrigeration system (MRS) and thermo-magnetic generator (TMG). The aim of this optimizer is to improve the design of the AMR by applying a multi-physics multi-scales numerical model as a core of evaluation functions to achieve industrial requirements for refrigeration and energy conservation systems. Based on the multi-objective non-dominated sorting genetic algorithm 3 (NSGA3), it maximizes four different objectives: efficiency and power density for MRS and TMG. The main contribution of this work is in the simultaneously application of a CPU-parallel NSGA3 version to the AMR model in both modes for studying impact of control and design parameters on the performance. The parametric study of the optimization results are presented. The main conclusion is that the common (for TMG and MRS modes) optimal parameters can be found by the proposed tool.

Keywords: ecological refrigeration systems, active magnetic regenerator, thermo-magnetic generator, multi-objective evolutionary optimization, industrial optimization problem, real-world application

Procedia PDF Downloads 107

Authors: Malahat Rezaee, Mahiran Basri, Raja Noor Zaliha Raja Abdul Rahman, Abu Bakar Salleh

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Sodium diclofenac is one of the most commonly used drugs of nonsteroidal anti-inflammatory drugs (NSAIDs). It is especially effective in the controlling the severe conditions of inflammation and pain, musculoskeletal disorders, arthritis, and dysmenorrhea. Formulation as nanoemulsions is one of the nanoscience approaches that have been progressively considered in pharmaceutical science for transdermal delivery of drug. Nanoemulsions are a type of emulsion with particle sizes ranging from 20 nm to 200 nm. An emulsion is formed by the dispersion of one liquid, usually the oil phase in another immiscible liquid, water phase that is stabilized using surfactant. Palm kernel oil esters (PKOEs), in comparison to other oils; contain higher amounts of shorter chain esters, which suitable to be applied in micro and nanoemulsion systems as a carrier for actives, with excellent wetting behavior without the oily feeling. This research was aimed to study the effect of O/S ratio on stability and rheological behavior of sodium diclofenac loaded and unloaded palm kernel oil esters nanoemulsion systems. The effect of different O/S ratio of 0.25, 0.50, 0.75, 1.00 and 1.25 on stability of the drug-loaded and unloaded nanoemulsion formulations was evaluated by centrifugation, freeze-thaw cycle and storage stability tests. Lecithin and cremophor EL were used as surfactant. The stability of the prepared nanoemulsion formulations was assessed based on the change in zeta potential and droplet size as a function of time. Instability mechanisms including coalescence and Ostwald ripening for the nanoemulsion system were discussed. In comparison between drug-loaded and unloaded nanoemulsion formulations, drug-loaded formulations represented smaller particle size and higher stability. In addition, the O/S ratio of 0.5 was found to be the best ratio of oil and surfactant for production of a nanoemulsion with the highest stability. The effect of O/S ratio on rheological properties of drug-loaded and unloaded nanoemulsion systems was studied by plotting the flow curves of shear stress (τ) and viscosity (η) as a function of shear rate (γ). The data were fitted to the Power Law model. The results showed that all nanoemulsion formulations exhibited non-Newtonian flow behaviour by displaying shear thinning behaviour. Viscosity and yield stress were also evaluated. The nanoemulsion formulation with the O/S ratio of 0.5 represented higher viscosity and K values. In addition, the sodium diclofenac loaded formulations had more viscosity and higher yield stress than drug-unloaded formulations.

Keywords: nanoemulsions, palm kernel oil esters, sodium diclofenac, rheoligy, stability

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Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

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Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

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Authors: Valentina Narvaez Gaitan, Laura Valentina Rodriguez Leguizamon, Ruben Dario Hernandez B.

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This work describes a physiological signal emulation system that uses electromyography (EMG) signals obtained from muscle sensors in the first instance. These signals are used to extract their characteristics to model and emulate specific arm movements. The main objective of this effort is to develop a new biomedical software system capable of generating physiological signals through the use of embedded systems by establishing the characteristics of the acquired signals. The acquisition system used was Biosignals, which contains two EMG electrodes used to acquire signals from the forearm muscles placed on the extensor and flexor muscles. Processing algorithms were implemented to classify the signals generated by the arm muscles when performing specific movements such as wrist flexion extension, palmar grip, and wrist pronation-supination. Matlab software was used to condition and preprocess the signals for subsequent classification. Subsequently, the mathematical modeling of each signal is performed to be generated by the embedded system, with a validation of the accuracy of the obtained signal using the percentage of cross-correlation, obtaining a precision of 96%. The equations are then discretized to be emulated in the embedded system, obtaining a system capable of generating physiological signals according to the characteristics of medical analysis.

Keywords: classification, electromyography, embedded system, emulation, physiological signals

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Authors: M. Okeke, A. Blyth

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Industrial Control Systems (ICS) such as Supervisory Control And Data Acquisition (SCADA) can be seen in many different critical infrastructures, from nuclear management to utility, medical equipment, power, waste and engine management on ships and planes. The role SCADA plays in critical infrastructure has resulted in a call to secure them. Many lives depend on it for daily activities and the attack vectors are becoming more sophisticated. Hence, the security of ICS is vital as malfunction of it might result in huge risk. This paper describes how the application of Prey Predator (PP) approach in flocks of birds could enhance the detection of malicious activities on ICS. The PP approach explains how these animals in groups or flocks detect predators by following some simple rules. They are not necessarily very intelligent animals but their approach in solving complex issues such as detection through corporation, coordination and communication worth emulating. This paper will emulate flocking behavior seen in birds in detecting predators. The PP approach will adopt six nearest bird approach in detecting any predator. Their local and global bests are based on the individual detection as well as group detection. The PP algorithm was designed following MapReduce methodology that follows a Split Detection Convergence (SDC) approach.

Keywords: artificial life, industrial control system (ICS), IDS, prey predator (PP), SCADA, SDC

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Authors: Y. Laib Dit Leksir, S. Bouhouche

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Analysis and processing of data bases resulting from infrared thermal measurements made on the electrical installation requires the development of new tools in order to obtain correct and additional information to the visual inspections. Consequently, the methods based on the capture of infrared digital images show a great potential and are employed increasingly in various fields. Although, there is an enormous need for the development of effective techniques to analyse these data base in order to extract relevant information relating to the state of the equipments. Our goal consists in introducing recent techniques of modeling based on new methods, image and signal processing to develop mathematical models in this field. The aim of this work is to capture the anomalies existing in electrical equipments during an inspection of some machines using A40 Flir camera. After, we use binarisation techniques in order to select the region of interest and we make comparison between these methods of thermal images obtained to choose the best one.

Keywords: infrared thermography, defect detection, troubleshooting, electrical equipment

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Authors: S. M. Chabane sari S. Zargou, A.R. Senoudi, F. Benmouna

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Immobilization of nano particles (NPs) is the subject of numerous studies pertaining to the design of polymer nano composites, supported catalysts, bioactive colloidal crystals, inverse opals for novel optical materials, latex templated-hollow inorganic capsules, immunodiagnostic assays; “Pickering” emulsion polymerization for making latex particles and film-forming composites or Janus particles; chemo- and biosensors, tunable plasmonic nano structures, hybrid porous monoliths for separation science and technology, biocidal polymer/metal nano particle composite coatings, and so on. Particularly, in the recent years, the literature has witnessed an impressive progress of investigations on polymer coatings, grafts and particles as supports for anchoring nano particles. This is actually due to several factors: polymer chains are flexible and may contain a variety of functional groups that are able to efficiently immobilize nano particles and their precursors by dispersive or van der Waals, electrostatic, hydrogen or covalent bonds. We review methods to prepare polymer-immobilized nano particles through a plethora of strategies in view of developing systems for separation, sensing, extraction and catalysis. The emphasis is on methods to provide (i) polymer brushes and grafts; (ii) monoliths and porous polymer systems; (iii) natural polymers and (iv) conjugated polymers as platforms for anchoring nano particles. The latter range from soft bio macromolecular species (proteins, DNA) to metallic, C60, semiconductor and oxide nano particles; they can be attached through electrostatic interactions or covalent bonding. It is very clear that physicochemical properties of polymers (e.g. sensing and separation) are enhanced by anchored nano particles, while polymers provide excellent platforms for dispersing nano particles for e.g. high catalytic performances. We thus anticipate that the synergetic role of polymeric supports and anchored particles will increasingly be exploited in view of designing unique hybrid systems with unprecedented properties.

Keywords: gold, layer, polymer, macromolecular

Procedia PDF Downloads 388

Authors: Livia Calcagni

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Most of the largest cities in the world are located in areas that are vulnerable to coastal erosion and flooding, both linked to climate change and rising sea levels (RSL). Nevertheless, more and more people are moving to these vulnerable areas as cities keep growing. Architects, engineers and policy makers are called to rethink the way we live and to provide timely and adequate responses not only by investigating measures to improve the urban fabric, but also by developing strategies capable of planning change, exploring unusual and resilient frontiers of living, such as floating architecture. Since the beginning of the 21st century we have seen a dynamic growth of water-based architecture. At the same time, the shortage of land available for urban development also led to reclaim the seabed or to build floating structures. In light of these considerations, time is ripe to consider floating architecture not only as a full-fledged building typology but especially as a full-fledged adaptation solution for RSL. Currently, there is no global international legal framework for urban development on water and there is no structured performance based building design (PBBD) approach for floating architecture in most countries, let alone national regulatory systems. Thus, the research intends to identify the technological, morphological, functional, economic, managerial requirements that must be considered in a the development of the PBBD framework conceived as a meta-design tool. As it is expected that floating urban development is mostly likely to take place as extension of coastal areas, the needs and design criteria are definitely more similar to those of the urban environment than of the offshore industry. Therefor, the identification and categorization of parameters takes the urban-architectural guidelines and regulations as the starting point, taking the missing aspects, such as hydrodynamics, from the offshore and shipping regulatory frameworks. This study is carried out through an evidence-based assessment of performance guidelines and regulatory systems that are effective in different countries around the world addressing on-land and on-water architecture as well as offshore and shipping industries. It involves evidence-based research and logical argumentation methods. Overall, this paper highlights how inhabiting water is not only a viable response to the problem of RSL, thus a resilient frontier for urban development, but also a response to energy insecurity, clean water and food shortages, environmental concerns and urbanization, in line with Blue Economy principles and the Agenda 2030. Moreover, the discipline of architecture is presented as a fertile field for investigating solutions to cope with climate change and its effects on life safety and quality. Future research involves the development of a decision support system as an information tool to guide the user through the decision-making process, emphasizing the logical interaction between the different potential choices, based on the PBBD.

Keywords: adaptation measures, floating architecture, performance based building design, resilient architecture, rising sea levels

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Authors: Wan Nur'ashiqin Wan Mohamad, Zarina Othman, Mohd Azman Abas, Azizah Ya'acob, Rozmel Abdul Latiff

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Effective doctor-patient interaction is vital to both doctor and patient relationship. It is the cornerstone of good practice and an integral quality of a healthcare institution. This paper presented the hierarchy of the communication elements in doctor-patient interaction during medical consultations in a medical centre in Malaysia. This study adapted The Picker Patient Experience Questionnaire (2002) to obtain the information from patients. The questionnaire survey was responded by 100 patients between the ages of 20 and 50. Data collected were analysed using Rasch Measurement Model to yield the hierarchy of the communication elements in doctor-patient interaction. The findings showed that the three highest ranking on the doctor-patient interaction were doctor’s treatment, important information delivery and patient satisfaction of doctor’s responses. The results are valuable in developing the framework for communication ethics of doctors.

Keywords: communication elements, doctor-patient interaction, hierarchy, Rasch measurement model

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Authors: Jeewan Rai, Kinzang, Yeshi Jigme Choden

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Accumulation of dust on solar panels impacts the overall efficiency and the amount of energy it produces. Detecting and mitigating dust accumulation is, therefore, crucial for optimizing solar energy production. While various techniques exist for detecting dust to schedule cleaning, many of these methods use licensed software like MATLAB, which can be financially burdensome. This study proposes the use of a modified pre-trained ResNet-50 model architecture with an adjusted fully connected layer for binary classification. An experimental setup was installed utilizing a single 75 Wp panel with an inclination maintained at a 30-degree angle. The fine dirt particles were artificially introduced and datasets of images of clean and dusty panels were collected from five different sides were taken, to compensate for the surface reflectance from the PV panel due to camera angles. Those datasets were used to train and test the model, and the accuracy achieved was 90%. The model's ability to detect dust with minimal false positives ensures more efficient maintenance scheduling. This research demonstrates the potential of AI-driven dust detection systems to enhance the operational efficiency of solar PV installations.

Keywords: AI, dust detection, deep learning, image processing, ResNet-50, PV panels

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Authors: Djalal Boualili

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This article considers the problem of sizing prime movers for combined heating and power (CHP) systems operating at full load to satisfy a fraction of a facility's electric load, i.e. a base load. Prime mover sizing is examined using three criteria: operational cost, carbon dioxide emissions (CDE), and primary energy consumption (PEC). The sizing process leads to consider ratios of conversion factors applied to imported electricity to conversion factors applied to fuel consumed. These ratios are labelled RCost, R CDE, R PEC depending on whether the conversion factors are associated with operational cost, CDE, or PEC, respectively. Analytical results show that in order to achieve savings in operational cost, CDE, or PEC, the ratios must be larger than a unique constant R Min that only depends on the CHP components efficiencies. Savings in operational cost, CDE, or PEC due to CHP operation are explicitly formulated using simple equations. This facilitates the process of comparing the tradeoffs of optimizing the savings of one criterion over the other two – a task that has traditionally been accomplished through computer simulations. A hospital building, located in Chlef, Algeria, was used as an example to apply the methodology presented in this article.

Keywords: sizing, heating and power, ratios, energy consumption, carbon dioxide emissions

Procedia PDF Downloads 224

Authors: Angelis P. Barlampas

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Learning Objectives: The purpose of this study is to inform briefly the reader about the applications of AI in chest radiology. Background: Currently, there are 190 FDA-approved radiology AI applications, with 42 (22%) pertaining specifically to thoracic radiology. Imaging findings OR Procedure details Aids of AI in chest radiology1: Detects and segments pulmonary nodules. Subtracts bone to provide an unobstructed view of the underlying lung parenchyma and provides further information on nodule characteristics, such as nodule location, nodule two-dimensional size or three dimensional (3D) volume, change in nodule size over time, attenuation data (i.e., mean, minimum, and/or maximum Hounsfield units [HU]), morphological assessments, or combinations of the above. Reclassifies indeterminate pulmonary nodules into low or high risk with higher accuracy than conventional risk models. Detects pleural effusion . Differentiates tension pneumothorax from nontension pneumothorax. Detects cardiomegaly, calcification, consolidation, mediastinal widening, atelectasis, fibrosis and pneumoperitoneum. Localises automatically vertebrae segments, labels ribs and detects rib fractures. Measures the distance from the tube tip to the carina and localizes both endotracheal tubes and central vascular lines. Detects consolidation and progression of parenchymal diseases such as pulmonary fibrosis or chronic obstructive pulmonary disease (COPD).Can evaluate lobar volumes. Identifies and labels pulmonary bronchi and vasculature and quantifies air-trapping. Offers emphysema evaluation. Provides functional respiratory imaging, whereby high-resolution CT images are post-processed to quantify airflow by lung region and may be used to quantify key biomarkers such as airway resistance, air-trapping, ventilation mapping, lung and lobar volume, and blood vessel and airway volume. Assesses the lung parenchyma by way of density evaluation. Provides percentages of tissues within defined attenuation (HU) ranges besides furnishing automated lung segmentation and lung volume information. Improves image quality for noisy images with built-in denoising function. Detects emphysema, a common condition seen in patients with history of smoking and hyperdense or opacified regions, thereby aiding in the diagnosis of certain pathologies, such as COVID-19 pneumonia. It aids in cardiac segmentation and calcium detection, aorta segmentation and diameter measurements, and vertebral body segmentation and density measurements. Conclusion: The future is yet to come, but AI already is a helpful tool for the daily practice in radiology. It is assumed, that the continuing progression of the computerized systems and the improvements in software algorithms , will redder AI into the second hand of the radiologist.

Keywords: artificial intelligence, chest imaging, nodule detection, automated diagnoses

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Authors: Hala Zaghloul, Taymoor Nazmy

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One of the great challenges of the 21st century is to build a robot that can perceive and act within its environment and communicate with people, while also exhibiting the cognitive capabilities that lead to performance like that of people. The Pulse Coupled Neural Network, PCNN, is a relative new ANN model that derived from a neural mammal model with a great potential in the area of image processing as well as target recognition, feature extraction, speech recognition, combinatorial optimization, compressed encoding. PCNN has unique feature among other types of neural network, which make it a candid to be an important approach for perceiving in cognitive systems. This work show and emphasis on the potentials of PCNN to perform different tasks related to image processing. The main drawback or the obstacle that prevent the direct implementation of such technique, is the need to find away to control the PCNN parameters toward perform a specific task. This paper will evaluate the performance of PCNN standard model for processing images with different properties, and select the important parameters that give a significant result, also, the approaches towards find a way for the adaptation of the PCNN parameters to perform a specific task.

Keywords: cognitive system, image processing, segmentation, PCNN kernels

Procedia PDF Downloads 268

Authors: Figen Kadirgan, M. A. Neset Kadirgan, Gokcen A. Ciftcioglu

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Addressing food security and climate change challenges have to be done in an integrated manner. To increase food production and to reduce emissions intensity, thus contributing to mitigate climate change, food systems have to be more efficient in the use of resources. To ensure food security and adapt to climate change they have to become more resilient. The changes required in agricultural and food systems will require the creation of supporting institutions and enterprises to provide services and inputs to smallholders, fishermen and pastoralists, and transform and commercialize their production more efficiently. Thus there is continously growing need to switch to green economy where simultaneously causes reduction in carbon emissions and pollution, enhances energy and resource-use efficiency; and prevents the loss of biodiversity and ecosystem services. Smart Agriculture takes into account the four dimensions of food security, availability, accessibility, utilization, and stability. It is well known that, the increase in world population will strengthen the population-food imbalance. The emphasis on reduction of food losses makes a point on production, on farmers, on increasing productivity and income ensuring food security. Where also small farmers enhance their income and stabilize their budget. The use of solar drying for agricultural, marine or meat products is very important for preservation. Traditional sun drying is a relatively slow process where poor food quality is seen due to an infestation of insects, enzymatic reactions, microorganism growth and micotoxin development. In contrast, solar drying has a sound solution to all these negative effects of natural drying and artificial mechanical drying. The technical directions in the development of solar drying systems for agricultural products are compact collector design with high efficiency and low cost. In this study, using solar selective surface produced in Selektif Teknoloji Co. Inc. Ltd., solar dryers with high efficiency will be developed and a feasibility study will be realized.

Keywords: energy, renewable energy, solar collector, solar drying

Procedia PDF Downloads 220

Authors: Samuel Hyellamada Jerry

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This study focused on assessing conservation priorities within the Karlahi Forest Reserve of Fufore Local Government in Adamawa State. The main objective was to identify specific areas within the forest reserve that require immediate conservation attention. The research employed remote sensing and GIS techniques to achieve this goal. By overlaying the IDRIS Silva module results, a spatial distribution map was generated, highlighting the cumulative priority areas within and outside the forest. Among the total vegetated area of 26.38 km² in the Karlahi Forest Reserve, the analysis revealed that 16.16 km² were classified as high-priority conservation zones. Additionally, 4.59 km² and 5.63 km² were identified as medium and low-priority areas, respectively. In light of these findings, it is recommended that conservation efforts incorporate detailed land cover information and regular assessments of species diversity. Furthermore, strict adherence to national and state policies regarding forest reserves and parks is crucial for effective conservation management.

Keywords: priority, Karlahi, forest, reserve, IDRISI Silva, species diversity

Procedia PDF Downloads 140

Authors: Abdullah Al Mamun, Talal Alkharobi

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As data size is growing up, people are became more familiar to store big amount of secret information into cloud storage. Companies are always required to need transfer massive business files from one end to another. We are going to lose privacy if we transmit it as it is and continuing same scenario repeatedly without securing the communication mechanism means proper encryption. Although asymmetric key encryption solves the main problem of symmetric key encryption but it can only encrypt limited size of data which is inapplicable for large data encryption. In this paper we propose a probable approach of pretty good privacy for encrypt big data using both symmetric and asymmetric keys. Our goal is to achieve encrypt huge collection information and transmit it through a secure communication channel for committing the business and personal privacy. To justify our method an experimental dataset from three different platform is provided. We would like to show that our approach is working for massive size of various data efficiently and reliably.

Keywords: big data, cloud computing, cryptography, hadoop, public key

Procedia PDF Downloads 313