Search results for: cognitive artificial intelligence

Authors: Ichiro Takahashi

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One conundrum that macroeconomic theory faces is to explain how an economy can revive from depression, in which the aggregate demand has fallen substantially below its productive capacity. This paper examines an autonomous stabilizing mechanism using an agent-based Wicksell-Keynes macroeconomic model. This paper focuses on the effects of the number of firms and the length of the gestation period for investment that are often assumed to be one in a mainstream macroeconomic model. The simulations found the virtual economy was highly unstable, or more precisely, collapsing when these parameters are fixed at one. This finding may even suggest us to question the legitimacy of these common assumptions. A perpetual decline in capital stock will eventually encourage investment if the capital stock is short-lived because an inactive investment will result in insufficient productive capacity. However, for an economy characterized by a roundabout production method, a gradual decline in productive capacity may not be able to fall below the aggregate demand that is also shrinking. Naturally, one would then ask if our economy cannot rely on an external stimulus such as population growth and technological progress to revive investment, what factors would provide such a buoyancy for stimulating investments? The current paper attempts to answer this question by employing the artificial macroeconomic model mentioned above. The baseline model has the following three features: (1) the multi-period gestation for investment, (2) a large number of heterogeneous firms, (3) demand-constrained firms. The instability is a consequence of the following dynamic interactions. (a) A multiple-period gestation period means that once a firm starts a new investment, it continues to invest over some subsequent periods. During these gestation periods, the excess demand created by the investing firm will spill over to ignite new investment of other firms that are supplying investment goods: the presence of multi-period gestation for investment provides a field for investment interactions. Conversely, the excess demand for investment goods tends to fade away before it develops into a full-fledged boom if the gestation period of investment is short. (b) A strong demand in the goods market tends to raise the price level, thereby lowering real wages. This reduction of real wages creates two opposing effects on the aggregate demand through the following two channels: (1) a reduction in the real labor income, and (2) an increase in the labor demand due to the principle of equality between the marginal labor productivity and real wage (referred as the Walrasian labor demand). If there is only a single firm, a lower real wage will increase its Walrasian labor demand, thereby an actual labor demand tends to be determined by the derived labor demand. Thus, the second positive effect would not work effectively. In contrast, for an economy with a large number of firms, Walrasian firms will increase employment. This interaction among heterogeneous firms is a key for stability. A single firm cannot expect the benefit of such an increased aggregate demand from other firms.

Keywords: agent-based macroeconomic model, business cycle, demand constraint, gestation period, representative agent model, stability

Procedia PDF Downloads 151

Authors: Yazan S. Khaled, Shazana Shamsuddin, Jim Tiernan, Mike McPherson, Thomas Hughes, Paul Millner, David G. Jayne

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Introduction: There is a need for real-time imaging of colorectal cancer (CRC) to allow tailored surgery to the disease stage. Fluorescence guided laparoscopic imaging of primary colorectal cancer and the draining lymphatics would potentially bring stratified surgery into clinical practice and realign future CRC management to the needs of patients. Fluorescent nanoparticles can offer many advantages in terms of intra-operative imaging and therapy (theranostic) in comparison with traditional soluble reagents. Nanoparticles can be functionalised with diverse reagents and then targeted to the correct tissue using an antibody or Affimer (artificial binding protein). We aimed to develop and test fluorescent silica nanoparticles and targeted against CRC using an anti-carcinoembryonic antigen (CEA) Affimer (Aff). Methods: Anti-CEA and control Myoglobin Affimer binders were subcloned into the expressing vector pET11 followed by transformation into BL21 Star™ (DE3) E.coli. The expression of Affimer binders was induced using 0.1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG). Cells were harvested, lysed and purified using nickle chelating affinity chromatography. The photosensitiser Foslip (soluble analogue of 5,10,15,20-Tetra(m-hydroxyphenyl) chlorin) was incorporated into the core of silica nanoparticles using water-in-oil microemulsion technique. Anti-CEA or control Affs were conjugated to silica nanoparticles surface using sulfosuccinimidyl-4-(N-maleimidomethyl) cyclohexane-1-carboxylate (sulfo SMCC) chemical linker. Binding of CEA-Aff or control nanoparticles to colorectal cancer cells (LoVo, LS174T and HC116) was quantified in vitro using confocal microscopy. Results: The molecular weights of the obtained band of Affimers were ~12.5KDa while the diameter of functionalised silica nanoparticles was ~80nm. CEA-Affimer targeted nanoparticles demonstrated 9.4, 5.8 and 2.5 fold greater fluorescence than control in, LoVo, LS174T and HCT116 cells respectively (p < 0.002) for the single slice analysis. A similar pattern of successful CEA-targeted fluorescence was observed in the maximum image projection analysis, with CEA-targeted nanoparticles demonstrating 4.1, 2.9 and 2.4 fold greater fluorescence than control particles in LoVo, LS174T, and HCT116 cells respectively (p < 0.0002). There was no significant difference in fluorescence for CEA-Affimer vs. CEA-Antibody targeted nanoparticles. Conclusion: We are the first to demonstrate that Foslip-doped silica nanoparticles conjugated to anti-CEA Affimers via SMCC allowed tumour cell-specific fluorescent targeting in vitro, and had shown sufficient promise to justify testing in an animal model of colorectal cancer. CEA-Affimer appears to be a suitable targeting molecule to replace CEA-Antibody. Targeted silica nanoparticles loaded with Foslip photosensitiser is now being optimised to drive photodynamic killing, via reactive oxygen generation.

Keywords: colorectal cancer, silica nanoparticles, Affimers, antibodies, imaging

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Authors: Francisca Alves, Diana Figueiredo, Paula Vagos, Luiza Lima, Maria do Céu Salvador, Daniel Rijo

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In recent years, Acceptance and Commitment Therapy (ACT) has been shown to be effective in the treatment of numerous anxiety disorders, including social anxiety disorder (SAD). However, limited evidence exists on its therapeutic gains for adolescents with SAD. The current work presents a weekly 10-session manualized online ACT approach to adolescent SAD, being the first study to do so in a clinical sample of adolescents. The intervention ACT@TeenSAD addresses the six proposed processes of psychological inflexibility (i.e., experiential avoidance, cognitive fusion, lack of values clarity, unworkable action, dominance of the conceptualized past and future, attachment to the conceptualized self) in social situations relevant to adolescents (e.g., doing a presentation). It is organized into four modules. The first module explores the role of psychological (in)flexibility in SAD (session 1 and 2), addressing psychoeducation (i.e., functioning of the mind) according to ACT, the development of an individualized model, and creative hopelessness. The second module focuses on the foundation of psychological flexibility (session 3, 4, and 5), specifically on the development and practice of strategies to promote clarification of values, contact with the present moment, the observing self, defusion, and acceptance. The third module encompasses psychological flexibility in action (sessions 6, 7, 8, and 9), encouraging committed action based on values in social situations relevant to the adolescents. The fourth modules’ focus is the revision of gains and relapse prevention (session 10). This intervention further includes two booster sessions after therapy has ended (3 and 6-month follow-up) that aim to review the continued practice of learned abilities and to plan for their future application to potentially anxious social events. As part of an ongoing clinical trial, the intervention will be assessed on its feasibility with adolescents diagnosed with SAD and on its therapeutic efficacy based on a longitudinal design including pretreatment, posttreatment, 3 and 6-month follow-up. If promising, findings may support the online delivery of ACT interventions for SAD, contributing to increased treatment availability to adolescents. This availability of an effective therapeutic approach will be helpful not only in relation to adolescents who face obstacles (e.g., distance) when attending to face-to-face sessions but also particularly to adolescents with SAD, who are usually more reluctant to look for specialized treatment in public or private health facilities.

Keywords: acceptance and commitment therapy, social anxiety disorder, adolescence, manualized online approach

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Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

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Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

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Authors: Onada Olawale Ahmed

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As the intensification of aquaculture production increases on global scale, the growing concern of fish farmers around the world is related to cost of fish production, where cost of feeding takes substantial percentage. Fishmeal (FM) is one of the most expensive ingredients, and its high dependence in aqua-feed production translates to high cost of feeding of stocked fish. However, to reach a sustainable aquaculture, new alternative protein sources including cheaper plant or animal origin proteins are needed to be introduced for stable aqua-feed production. Spirulina is a cyanobacterium that has good nutrient profile that could be useful in aquaculture. This review therefore emphasizes on the nutritional value of Spirulina as a potential replacement of FM in aqua-feed. Spirulina is a planktonic photosynthetic filamentous cyanobacterium that forms massive populations in tropical and subtropical bodies of water with high levels of carbonate and bicarbonate. Spirulina grows naturally in nutrient rich alkaline lake with water salinity ( > 30 g/l) and high pH (8.5–11.0). Its artificial production requires luminosity (photo-period 12/12, 4 luxes), temperature (30 °C), inoculum, water stirring device, dissolved solids (10–60 g/litre), pH (8.5– 10.5), good water quality, and macro and micronutrient presence (C, N, P, K, S, Mg, Na, Cl, Ca and Fe, Zn, Cu, Ni, Co, Se). Spirulina has also been reported to grow on agro-industrial waste such as sugar mill waste effluent, poultry industry waste, fertilizer factory waste, and urban waste and organic matter. Chemical composition of Spirulina indicates that it has high nutritional value due to its content of 55-70% protein, 14-19% soluble carbohydrate, high amount of polyunsaturated fatty acids (PUFAs), 1.5–2.0 percent of 5–6 percent total lipid, all the essential minerals are available in spirulina which contributes about 7 percent (average range 2.76–3.00 percent of total weight) under laboratory conditions, β-carotene, B-group vitamin, vitamin E, iron, potassium and chlorophyll are also available in spirulina. Spirulina protein has a balanced composition of amino acids with concentration of methionine, tryptophan and other amino acids almost similar to those of casein, although, this depends upon the culture media used. Positive effects of spirulina on growth, feed utilization and stress and disease resistance of cultured fish have been reported in earlier studies. Spirulina was reported to replace up to 40% of fishmeal protein in tilapia (Oreochromis mossambicus) diet and even higher replacement of fishmeal was possible in common carp (Cyprinus carpio), partial replacement of fish meal with spirulina in diets for parrot fish (Oplegnathus fasciatus) and Tilapia (Orechromis niloticus) has also been conducted. Spirulina have considerable potential for development, especially as a small-scale crop for nutritional enhancement and health improvement of fish. It is important therefore that more research needs to be conducted on its production, inclusion level in aqua-feed and its possible potential use of aquaculture.

Keywords: aquaculture, spirulina, fish nutrition, fish feed

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Authors: Meral Huri, Sedef Şahin

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Post-traumatic stress disorder (PTSD) is characterized by psychiatric symptoms and triggered by a terrifying experience which may immediately effect cognitive, affective, behavioral and social skills of the individual. One of the most common noncutaneous cancer among men is prostate cancer. The incidence of psychological stress is quite common in men with prostate cancer. The aim of the study was to explore the PTSD frequency among prostate cancer and define the relationship between occupational participation, coping skills and level of perceived social support among patients with prostate cancer. Forty patients diagnosed with prostate cancer were included in the study. After dividing the patients into two groups ( study/ control) according to type of tumor, we recorded their characteristics and evaluations differences. We evaluated the demographic information form, Structured Clinical Interview for DSM-IV (SCID- I)- Clinical Version for PTSD, Multidimensional Scale of Perceived Social Support, Styles of Coping Inventory and Canadian Occupational Performance Measure (COPM) before and after 1 month from surgery. The mean age of the study group (n:18) was 65.85.6 years (range: 61-79 years). The mean age of the control group (n: 22) was a little bit higher than the study group with mean age 71.3±6.9 years (range: 60-85 years). There was no statistically significant difference between the groups for age and the other characteristics. According to the results of the study, statistically significant difference was found between the level of PTSD of study and the control group. 22% of study group showed PTSD while 13% of the control group showed PTSD (r: 0.02, p<0.001). The scores of study group and control group showed statistically significant difference in five sub-categories of Styles of Coping Inventory. Patients with prostate cancer showed decreased scores in optimistic, seeking social supports and self-confident approach, while increased scores in helpless and submissive sub-categories than the control group (p<0.001). The scores of Multidimensional Scale of Perceived Social Supports of study group and control group showed statistically significant difference. The total perceived social supports score of the study group was 71.34 ± 0.75 while it was 75.34 ± 0.64 for the control group. Total and the sub-category scores of study group were statistically significant lower than the control group. According to COPM, mean scores of occupational participation of study group for occupational performance were 4.32±2.24 and 7.01±1.52 for the control group, respectively). Mean Satisfaction scores were 3,22±2.31 and 7.45±1.74 for the study and control group, respectively. The patients with prostate cancer and benign prostate hyperplasia (BPH) did not show any statistically difference in activity performance (r:0.87) while patients with prostate cancer showed statistically lower scores than the patients with BPH in activity satisfaction (r:0.02, p<0.001).Psycho-social occupational therapy interventions might help to decrease the prevalence of PTSD by increasing associated factors such as the social support perception, using coping skills and activity participation of patients with prostate cancer.

Keywords: activity performance, occupational therapy, posttraumatic stress disorder, prostate cancer

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Authors: Nirit Gavish, Rotem Halutz, Liad Neta

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Nowadays, chatbots are gaining more and more attention due to the advent of large language models. One of the important considerations in chatbot design is how to create an interface to achieve high user satisfaction, trust, and acceptance. Since WhatsApp conversations sometimes substitute for face-to-face communication, we studied whether WhatsAppization of the chatbot -making the conversation resemble a WhatsApp conversation more- will improve user satisfaction, trust, and acceptance, or whether the opposite will occur due to the Uncanny Valley (UV) effect. The task was a drive-sharing task, in which participants communicated with a textual chatbot via WhatsApp and could decide whether to participate in a ride to college with a driver suggested by the chatbot. WhatsAppization of the chatbot was done in two ways: By a dialog-style conversation (Dialog versus No Dialog), and by adding WhatsApp indicators – “Last Seen”, “Connected”, “Read Receipts”, and “Typing…” (Indicators versus No Indicators). Our 120 participants were randomly assigned to one of the four 2 by 2 design groups, with 30 participants in each. They interacted with the WhatsApp chatbot and then filled out a questionnaire. The results demonstrated that, as expected from the manipulation, the interaction with the chatbot was longer for the dialog condition compared to the no dialog. This extra interaction, however, did not lead to higher acceptance -quite the opposite, since participants in the dialog condition were less willing to implement the decision made at the end of the conversation with the chatbot and continue the interaction with the driver they chose. The results are even more striking when considering the Indicators condition. Both for the satisfaction measures and the trust measures, participants’ ratings were lower in the Indicators condition compared to the No Indicators. Participants in the Indicators condition felt that the ride search process was harder to operate, and slower (even though the actual interaction time was similar). They were less convinced that the chatbot suggested real trips and they trusted the person offering the ride and referred to them by the chatbot less. These effects were more evident for participants who preferred to share their rides using WhatsApp compared to participants who preferred chatbots for that purpose. Considering our findings, we can say that the WhatsAppization of the chatbot was detrimental. This is true for the both chatbot WhatsAppization methods – by making the conversation more a dialog and adding WhatsApp indicators. For the chosen drive-sharing task, the results were, in addition to lower satisfaction, less trust in the chatbot’s suggestion and even in the driver suggested by the chatbot, and lower willingness to actually undertake the suggested ride. In addition, it seems that the most problematic WhatsAppization method was using WhatsApp’s indicators during the interaction with the chatbot. The current study suggests that a conversation with an artificial agent should also not imitate a WhatsApp conversation very closely. With the proliferation of WhatsApp use, the emotional and social aspect of face-to face commination are moving to WhatsApp communication. Based on the current study’s findings, it is possible that the UV effect also occurs in WhatsAppization, and not only in humanization, of the chatbot, with a similar feeling of eeriness, and is more pronounced for people who prefer to use WhatsApp over chatbots. The current research can serve as a starting point to study the very interesting and important topic of chatbots WhatsAppization. More methods of WhatsAppization and other tasks could be the focus of further studies.

Keywords: chatbot, WhatsApp, humanization, Uncanny Valley, drive sharing

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Authors: Ferzat Anka

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Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

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Authors: Evgeni Baratashvili, Anzor Abralava, Rusudan Kutateladze, Nino Pailodze, Irma Makharashvili, Larisa Takalandze

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Sinergy as a neological term is reflected in modern sciences. It can be found in the various fields of science including the humanities and technical sciences. Among them are biology and medicine, philology, economy and etc. Synergy is the received surplus of marginal high total effect of the groups, consolidated by one common idea, received through endeavored applies of their combined tools, via obtained effect of the separate independent actions of the groups. In the conditions of market economy, according the terms of new communication terminology, synergy effects on management and marketing successfully as well as on purity defense of native language. The well-known scientist’s and public figure’s Academician I. Prangishvili’s works are especially valuable in this aspect. In our opinion the entropy research is linked to his name in our country. In modern economy, the current qualitative changes shows us that the most number of factors and issues have been regrouped. They have a great influence and even define the economic development. The declining abilities of traditional recourses of economic growth have been related on the use of their physical abilities and their moving closer to the edge. Also it is related on the reduced effectiveness, which at the same time increases the expenditures. This means that the leading must be the innovative process system of products and services in the economic growth model. In our opinion the above mentioned system is distinguished with the synergistic approach. It should be noted that the main components of the innovative system are technological, scientific and scientific-technical, social-organizational, managerial and cognitive changes. All of them are reflected on scientific works and inventions in the proper dosages, in know-how and material source. At any stage they create the reproduction cycle. The innovations are different from each other by technologies, origination, design, innovation and quality, subject-content structure, by the the spread of economic processes and the impact of the level of it’s distribution. We have presented a generalized statement of an innovative approach, which is not a single act of innovation but it is also targeted system of the development, implementation, reconciling-exploitation, production, diffusion and commercialization of news. The innovative approaches should be considered as the creation of news, in-depth process of creativity as an innovative alternative to the realization of innovative and entrepreneurial efforts and measures, in order to meet the requirements of the permanent process.

Keywords: economic development, leading process, neological term, synergy

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Authors: Likith Reddy Pinninti, Fredrik Ribsskog Staven, Leslie Robert Noble, Jorge Manuel de Oliveira Fernandes, Deepti Manjari Patel, Torstein Kristensen

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Understanding fish behavior is essential to improve animal welfare in aquaculture research. Behavioral traits can have a strong influence on fish health and habituation. To identify the genes and biological pathways responsible for lumpfish behavior, we performed an experiment to understand the interspecies relationship (mutualism) between the lumpfish and salmon. Also, we tested the correlation between the gene expression data vs. observational/physiological data to know the essential genes that trigger stress and swimming behavior in lumpfish. After the de novo assembly of the brain transcriptome, all the samples were individually mapped to the available lumpfish (Cyclopterus lumpus L.) primary genome assembly (fCycLum1.pri, GCF_009769545.1). Out of ~16749 genes expressed in brain samples, we found 267 genes to be statistically significant (P > 0.05) found only in odor and control (1), model and control (41) and salmon and control (225) groups. However, genes with |LogFC| ≥0.5 were found to be only eight; these are considered as differentially expressed genes (DEG’s). Though, we are unable to find the differential genes related to the behavioral traits from RNA-Seq data analysis. From the correlation analysis, between the gene expression data vs. observational/physiological data (serotonin (5HT), dopamine (DA), 3,4-Dihydroxyphenylacetic acid (DOPAC), 5-hydroxy indole acetic acid (5-HIAA), Noradrenaline (NORAD)). We found 2495 genes found to be significant (P > 0.05) and among these, 1587 genes are positively correlated with the Noradrenaline (NORAD) hormone group. This suggests that Noradrenaline is triggering the change in pigmentation and skin color in lumpfish. Genes related to behavioral traits like rhythmic, locomotory, feeding, visual, pigmentation, stress, response to other organisms, taxis, dopamine synthesis and other neurotransmitter synthesis-related genes were obtained from the correlation analysis. In KEGG pathway enrichment analysis, we find important pathways, like the calcium signaling pathway and adrenergic signaling in cardiomyocytes, both involved in cell signaling, behavior, emotion, and stress. Calcium is an essential signaling molecule in the brain cells; it could affect the behavior of fish. Our results suggest that changes in calcium homeostasis and adrenergic receptor binding activity lead to changes in fish behavior during stress.

Keywords: behavior, De novo, lumpfish, salmon

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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

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Authors: Fadwa Al Bawardi

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In March 2021, the Saudi Arabian Council of Ministers issued a decision to form a committee called the "Higher Committee for Research, Development and Innovation," a committee linked to the Council of Economic and Development Affairs, chaired by the Chairman of the Council of Economic and Development Affairs, and concerned with the development of the research, development and innovation sector in the Kingdom. In order to talk about the dimensions of this wonderful step, let us first try to answer the following questions. Is there a difference between creativity and innovation..? What are the factors of creativity in the individual. Are they mental genetic factors or are they factors that an individual acquires through learning..? The methodology included surveys that have been conducted on more than 500 individuals, males and females, between the ages of 18 till 60. And the answer is. "Creativity" is the creation of a new idea, while "Innovation" is the development of an already existing idea in a new, successful way. They are two sides of the same coin, as the "creative idea" needs to be developed and transformed into an "innovation" in order to achieve either strategic achievements at the level of countries and institutions to enhance organizational intelligence, or achievements at the level of individuals. For example, the beginning of smart phones was just a creative idea from IBM in 1994, but the actual successful innovation for the manufacture, development and marketing of these phones was through Apple later. Nor does creativity have to be hereditary. There are three basic factors for creativity: The first factor is "the presence of a challenge or an obstacle" that the individual faces and seeks thinking to find solutions to overcome, even if thinking requires a long time. The second factor is the "environment surrounding" of the individual, which includes science, training, experience gained, the ability to use techniques, as well as the ability to assess whether the idea is feasible or otherwise. To achieve this factor, the individual must be aware of own skills, strengths, hobbies, and aspects in which one can be creative, and the individual must also be self-confident and courageous enough to suggest those new ideas. The third factor is "Experience and the Ability to Accept Risk and Lack of Initial Success," and then learn from mistakes and try again tirelessly. There are some tools and techniques that help the individual to reach creative and innovative ideas, such as: Mind Maps tool, through which the available information is drawn by writing a short word for each piece of information and arranging all other relevant information through clear lines, which helps in logical thinking and correct vision. There is also a tool called "Flow Charts", which are graphics that show the sequence of data and expected results according to an ordered scenario of events and workflow steps, giving clarity to the ideas, their sequence, and what is expected of them. There are also other great tools such as the Six Hats tool, a useful tool to be applied by a group of people for effective planning and detailed logical thinking, and the Snowball tool. And all of them are tools that greatly help in organizing and arranging mental thoughts, and making the right decisions. It is also easy to learn, apply and use all those tools and techniques to reach creative and innovative solutions. The detailed figures and results of the conducted surveys are available upon request, with charts showing the %s based on gender, age groups, and job categories.

Keywords: innovation, creativity, factors, tools

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Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

Procedia PDF Downloads 181

Authors: Corbel Camille, Le Cerf Flora, Capriz Françoise, Vaillant-Ciszewicz Anne-Julie, Breaud Jean, Guerin Olivier, Corveleyn Xavier

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Background: The medical environment can generate stressful and anxiety-provoking situations for patients, particularly during painful care procedures for the older population. These stressful environments have deleterious effects on the quality of care and can even put the patient at risk and set the care team up for failure. The search for a solution is, therefore, imperative. The development of new technologies, such as virtual reality (VR), seems to be an answer to this problem. Objectives: The objective of this study is to compare the effects of virtual reality on pain and anxiety when caring for older hospitalized people with the effects of usual care. More precisely, different individual factors (age, cognitive level, individual preferences, etc.) and different virtual reality universes (personalized or non-personalized) are studied to understand the role of these factors in reducing pain and anxiety during care procedures. The aim of this study is to improve the quality of life of patients and caregivers in their work environment. Method: This mono-centered, randomized, controlled study was conducted from September 2023 to September 2024 on 120 participants recruited from the geriatric departments of the Cimiez Hospital, Nice, France. Participants are randomized into three groups: a control group, a personalized VR group and a non-personalized VR group. Each participant is followed during a painful care session. Data are collected before, during and after the care, using measures of pain (Algoplus and numerical scale) and anxiety (Hospital anxiety scale and numerical scale). Physiological assessments with an oximeter are also performed to collect both heart and respiratory rate measurements. The implementation of the care will be assessed among healthcare providers to evaluate its effects on the difficulty and fatigue associated with the care. Additionally, a questionnaire (System Usability Scale) will be administered at the conclusion of the study to determine the willingness of healthcare providers to integrate VR into their daily care practices. Result: The preliminary results indicate significant effects on anxiety (p=.001) and pain (p=<.001) following the VR intervention during care, as compared to the control group. Conclusion: The preliminary results suggest that VRI appears to be a suitable and effective method for reducing anxiety and pain among older hospitalized individuals compared with standard care. Finally, the experiences of healthcare professionals involved will also be considered to assess the impact of these interventions on working conditions and patient support.

Keywords: anxiety, care, pain, older adults, virtual reality

Procedia PDF Downloads 58

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

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

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

Procedia PDF Downloads 64

Authors: Chrysthia Papacleovoulou

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The era of de-regulation, off-shore and tax haven jurisdictions, and shelf companies has come to an end. The usage of complex corporate structures involving trust instruments, special purpose vehicles, holding-subsidiaries in offshore haven jurisdictions, and taking advantage of tax treaties is soaring. States which raced to introduce corporate friendly legislation, tax incentives, and creative international trust law in order to attract greater FDI are now faced with regulatory challenges and are forced to revisit the corporate form and its tax treatment. The fiduciary services industry, which dominated over the last 3 decades, is now striving to keep up with the new regulatory framework as a result of a number of European and international legislative measures. This article considers the challenges to the company and the corporate form as a result of the legislative measures on tax planning and tax avoidance, CRS reporting, FATCA, CFC rules, OECD’s BEPS, the EU Commission's new transparency rules for intermediaries that extends to tax advisors, accountants, banks & lawyers who design and promote tax planning schemes for their clients, new EU rules to block artificial tax arrangements and new transparency requirements for financial accounts, tax rulings and multinationals activities (DAC 6), G20's decision for a global 15% minimum corporate tax and banking regulation. As a result, states are found in a race of over-regulation and compliance. These legislative measures constitute a global up-side down tax-harmonisation. Through the adoption of the OECD’s BEPS, states agreed to an international collaboration to end tax avoidance and reform international taxation rules. Whilst the idea was to ensure that multinationals would pay their fair share of tax everywhere they operate, an indirect result of the aforementioned regulatory measures was to attack private clients-individuals who -over the past 3 decades- used the international tax system and jurisdictions such as Marshal Islands, Cayman Islands, British Virgin Islands, Bermuda, Seychelles, St. Vincent, Jersey, Guernsey, Liechtenstein, Monaco, Cyprus, and Malta, to name but a few, to engage in legitimate tax planning and tax avoidance. Companies can no longer maintain bank accounts without satisfying the real substance test. States override the incorporation doctrine theory and apply a real seat or real substance test in taxing companies and their activities, targeting even the beneficial owners personally with tax liability. Tax authorities in civil law jurisdictions lift the corporate veil through the public registries of UBO Registries and Trust Registries. As a result, the corporate form and the doctrine of limited liability are challenged in their core. Lastly, this article identifies the development of new instruments, such as funds and private placement insurance policies, and the trend of digital nomad workers. The baffling question is whether industry and states can meet somewhere in the middle and exit this over-regulation frenzy.

Keywords: company, regulation, TAX, corporate structure, trust vehicles, real seat

Procedia PDF Downloads 122

Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

Procedia PDF Downloads 150

Authors: Happy Kumar Das, Md. Shahriar Shafiq

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This paper portrays an assumed change in the primary teacher education program in Bangladesh. An initiative has been taken with a vision to ensure an integrated approach to developing trainee teachers’ knowledge and understanding about learning at a deeper level, and with that aim, the Diploma in Primary Education (DPEd) program replaces the Certificate-in-Education (C-in-Ed) program in Bangladeshi context for primary teachers. The stated professional values of the existing program such as ‘learner-centered’, ‘reflective’ approach to pedagogy tend to contradict the practice exemplified through the delivery mechanism. To address the challenges, through the main two components (i) Training Institute-based learning and (ii) School-based learning, the new program tends to cover knowledge and value that underpin the actual practice of teaching. These two components are given approximately equal weighting within the program in terms of both time, content and assessment as the integration seeks to combine theoretical knowledge with practical knowledge and vice versa. The curriculum emphasizes a balance between the taught modules and the components of the practicum. For example, the theories of formative and summative assessment techniques are elaborated through focused reflection on case studies as well as observation and teaching practice in the classroom. The key ideology that is reflected through this newly developed program is teacher’s belief in ‘holistic education’ that can lead to creating opportunities for skills development in all three (Cognitive, Social and Affective) domains simultaneously. The proposed teacher education program aims to address these areas of generic skill development alongside subject-specific learning outcomes. An exploratory study has been designed in this regard where 7 Primary Teachers’ Training Institutes (PTIs) in 7 divisions of Bangladesh was used for experimenting DPEd program. The analysis was done based on document analysis, periodical monitoring report and empirical data gathered from the experimental PTIs. The findings of the study revealed that the intervention brought positive change in teachers’ professional beliefs, attitude and skills along with improvement of school environment. Teachers in training schools work together for collective professional development where they support each other through lesson study, action research, reflective journals, group sharing and so on. Although the DPEd program addresses the above mentioned factors, one of the challenges of the proposed program is the issue of existing capacity and capabilities of the PTIs towards its effective implementation.

Keywords: Bangladesh, effective implementation, primary teacher education, reflective approach

Procedia PDF Downloads 203

Authors: Grant Bifolchi

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As global environmental problems continue to have highly adverse effects, finding long-term, sustainable solutions to combat ecological distress are of growing paramount concern. Ghost Gear—also known as abandoned, lost or otherwise discarded fishing gear (ALDFG) and derelict fishing gear (DFG)—represents one of the greatest threats to the world’s oceans, posing a significant hazard to human health, livelihoods, and global food security. In fact, according to the UN Food and Agriculture Organization (FAO), abandoned, lost and discarded fishing gear represents approximately 10% of marine debris by volume. Around the world, many governments, governmental and non-profit organizations are doing their best to manage the reporting and retrieval of nets, lines, ropes, traps, floats and more from their respective bodies of water. However, these organizations’ ability to effectively manage files and documents about the environmental problem further complicates matters. In Ghost Gear monitoring and management, organizations face additional complexities. Whether it’s data ingest, industry regulations and standards, garnering actionable insights into the location, security, and management of data, or the application of enforcement due to disparate data—all of these factors are placing massive strains on organizations struggling to save the planet from the dangers of Ghost Gear. In this 90-minute educational session, globally recognized Ghost Gear technology expert Grant Bifolchi CET, BBA, Bcom, will provide real-world insight into how governments currently manage Ghost Gear and the technology that can accelerate success in combatting ALDFG and DFG. In this session, attendees will learn how to: • Identify specific technologies to solve the ingest and management of Ghost Gear data categories, including type, geo-location, size, ownership, regional assignment, collection and disposal. • Provide enhanced access to authorities, fisheries, independent fishing vessels, individuals, etc., while securely controlling confidential and privileged data to globally recognized standards. • Create and maintain processing accuracy to effectively track ALDFG/DFG reporting progress—including acknowledging receipt of the report and sharing it with all pertinent stakeholders to ensure approvals are secured. • Enable and utilize Business Intelligence (BI) and Analytics to store and analyze data to optimize organizational performance, maintain anytime-visibility of report status, user accountability, scheduling, management, and foster governmental transparency. • Maintain Compliance Reporting through highly defined, detailed and automated reports—enabling all stakeholders to share critical insights with internal colleagues, regulatory agencies, and national and international partners.

Keywords: ghost gear, ALDFG, DFG, abandoned, lost or otherwise discarded fishing gear, data, technology

Procedia PDF Downloads 80

Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

Procedia PDF Downloads 129

Authors: S. Sabatino, V. Calderaro, V. Galdi, G. Graber, L. Ippolito

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Climate change is a rapidly growing global threat caused mainly by increased emissions of carbon dioxide (CO₂) into the atmosphere. These emissions come from multiple sources, including industry, power generation, and the transport sector. The need to tackle climate change and reduce CO₂ emissions is indisputable. A crucial solution to achieving decarbonization in the transport sector is the adoption of electric vehicles (EVs). These vehicles use lithium (Li-Ion) batteries as an energy source, making them extremely efficient and with low direct emissions. However, Li-Ion batteries are not without problems, including the risk of overheating and performance degradation. To ensure its safety and longevity, it is essential to use a battery management system (BMS). The BMS constantly monitors battery status, adjusts temperature and cell balance, ensuring optimal performance and preventing dangerous situations. From the monitoring carried out, it is also able to optimally manage the battery to increase its life. Among the parameters monitored by the BMS, the main ones are State of Charge (SoC), State of Health (SoH), and State of Power (SoP). The evaluation of these parameters can be carried out in two ways: offline, using benchtop batteries tested in the laboratory, or online, using batteries installed in moving vehicles. Online estimation is the preferred approach, as it relies on capturing real-time data from batteries while operating in real-life situations, such as in everyday EV use. Actual battery usage conditions are highly variable. Moving vehicles are exposed to a wide range of factors, including temperature variations, different driving styles, and complex charge/discharge cycles. This variability is difficult to replicate in a controlled laboratory environment and can greatly affect performance and battery life. Online estimation captures this variety of conditions, providing a more accurate assessment of battery behavior in real-world situations. In this article, a hybrid approach based on a neural network and a statistical method for real-time estimation of SoC, SoH, and SoP parameters of interest is proposed. These parameters are estimated from the analysis of a one-day driving profile of an electric vehicle, assumed to be divided into the following four phases: (i) Partial discharge (SoC 100% - SoC 50%), (ii) Partial discharge (SoC 50% - SoC 80%), (iii) Deep Discharge (SoC 80% - SoC 30%) (iv) Full charge (SoC 30% - SoC 100%). The neural network predicts the values of ohmic resistance and incremental capacity, while the statistical method is used to estimate the parameters of interest. This reduces the complexity of the model and improves its prediction accuracy. The effectiveness of the proposed model is evaluated by analyzing its performance in terms of square mean error (RMSE) and percentage error (MAPE) and comparing it with the reference method found in the literature.

Keywords: electric vehicle, Li-Ion battery, BMS, state-of-charge, state-of-health, state-of-power, artificial neural networks

Procedia PDF Downloads 50

Authors: Arif Tri Setyanto, Aditya Nanda Priyatama, Nugraha Arif Karyanta, Fadjri Kirana A., Afia Fitriani, Rini Setyowati, Moh.Abdul Hakim

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The Basic Health Research Report by the Ministry of Health (2018) shows an increase in the prevalence of mental health disorders in the adolescent and early adult age ranges. Supporting this finding, data on the psychological examination of the student health service unit at one State University recorded 115 cases of moderate and severe health problems in the period 2016 - 2019. More specifically, the highest number of cases was experienced by clients in the age range of 21-23 years or equivalent, with the mid-semester stage towards the end. Based on the distribution of cases experienced and the disorder becomes a psychological problem experienced by students. A total of 29% or the equivalent of 33 students experienced anxiety disorders, 25% or 29 students experienced problems ranging from mild to severe, as well as other classifications of disorders experienced, including adjustment disorders, family problems, academics, mood disorders, self-concept disorders, personality disorders, cognitive disorders, and others such as trauma and sexual disorders. Various mental health disorders have a significant impact on the academic life of students, such as low GPA, exceeding the limit in college, dropping out, disruption of social life on campus, to suicide. Based on literature reviews and best practices from universities in various countries, one of the effective ways to prevent and treat student mental health disorders is to implement a mental health monitoring system in universities. This study uses a participatory action research approach, with a sample of 423 from a total population of 32,112 students. The scale used in this study is the Beck Depression Inventory (BDI) to measure depression and the Taylor Minnesota Anxiety Scale (TMAS) to measure anxiety levels. This study aims to (1) develop a digital-based health monitoring system for students' mental health situations in the mental health category. , dangers, or those who have mental disorders, especially indications of symptoms of depression and anxiety disorders, and (2) implementing a mental health monitoring system in universities at the beginning and end of each semester. The results of the analysis show that from 423 respondents, the main problems faced by all coursework, such as thesis and academic assignments. Based on the scoring and categorization of the Beck Depression Inventory (BDI), 191 students experienced symptoms of depression. A total of 24.35%, or 103 students experienced mild depression, 14.42% (61 students) had moderate depression, and 6.38% (27 students) experienced severe or extreme depression. Furthermore, as many as 80.38% (340 students) experienced anxiety in the high category. This article will review this review of the student mental health service system on campus.

Keywords: monitoring system, mental health, psychological problems, students

Procedia PDF Downloads 94

Authors: Arun Perumbilavil Anand

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For the past few years, the state of Kerala has been witnessing a large inflow of migrant workers from other states of the country, which emerged as a result of demographic transition and Gulf emigration. The in-migration patterns in Kerala have changed over the time with the migrants having a higher residence history bringing their families to the state, thereby making the process more complicated and divergent in its approach. These developments have led to an increase in the young migrant population at least in some parts of the state, which has opened up doubts and questions related to their future in the host society. At this juncture, the study ponders into the factors that are associated with the assimilation and wellbeing of migrant children in the society of Kerala. As one of the objectives, the study also analyzed the influence and role played by the educational institutions (both public and private) in meeting the needs and aspirations of both the children and their parents. The study gains significance as it tries to identify various impediments that hinder the cognitive skill formation and behaviour patterns of the migrant children in the host society. Data and Methodology: The study is based on the primary data collected through a series of interviews and interactions held with parents, children, and teachers of different educational institutions, including both public and private. The primary survey also made use of research techniques like observation, in-depth interviews, and case study method. The study was conducted in schools in the Kanjikode area of the Palakkad district in Kerala. The findings of the study are on the basis of a survey conducted in four schools and 40 migrant children. Findings: The study found that majority of the children have wholly integrated and assimilated into the host society. The influence of the peer group was quite visible in giving stimulus to the assimilation process. Most of the children do not have any emotional or cultural sentiments attached to their state of origin, and they consider Kerala as their ‘home state’ and the local language (Malayalam) as their ‘mother tongue'. The study could also find that the existing education system in the host society fails to meet the needs and aspirations of migrants as well as that of their children. On a comparative scale, to some extent, private schools have succeeded in fulfiling the special requirements of the migrant children. An interesting point that the study could pinpoint at is that the children of the migrants show better health conditions and wellbeing than compared to the natives, which is usually addressed as an epidemiologic paradox. As a concluding remark, the study recommends the inclusion concept of inclusive education into the education system of the state with giving due emphasis on those who are at higher risk of being excluded or marginalized, along with fostering increased interaction between diverse groups.

Keywords: assimilation, Kerala, migrant children, well-being

Procedia PDF Downloads 156

Authors: E. Gaury, P. Mandausch, O. Picot, A. R. Thomas, L. Veisblat, L. Ralambozanany, C. Delsart

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In Dakar, demographic and spatial growth was accompanied by a 50% increase in household waste between 1988 and 2008 in the city. In addition, a change in the nature of household waste was observed between 1990 and 2007. The share of plastic increased by 15% between 2004 and 2007 in Dakar. Plastics represent the seventh category of household waste, the most produced per year in Senegal. The share of plastic in household and similar waste is 9% in Senegal. Waste management in the city of Dakar is a complex process involving a multitude of formal and informal actors with different perceptions and objectives. The objective of this study was to understand the motivations that could lead to sorting action, as well as the perception of plastic waste sorting within the Dakar population (households and institutions). The problematic of this study was as follows: what may be the factors playing a role in the sorting action? In an attempt to answer this, two approaches have been developed: (1) An exploratory qualitative study by semi-structured interviews with two groups of individuals concerned by the sorting of plastic waste: on the one hand, the experts in charge of waste management and on the other the households-producers of waste plastics. This study served as the basis for formulating the hypotheses and thus for the quantitative analysis. (2) A quantitative study using a questionnaire survey method among households producing plastic waste in order to test the previously formulated hypotheses. The objective was to have quantitative results representative of the population of Dakar in relation to the behavior and the process inherent in the adoption of the plastic waste sorting action. The exploratory study shows that the perception of state responsibility varies between institutions and households. Public institutions perceive this as a shared responsibility because the problem of plastic waste affects many sectors (health, environmental education, etc.). Their involvement is geared more towards raising awareness and educating young people. As state action is limited, the emergence of private companies in this sector seems logical as they are setting up collection networks to develop a recycling activity. The state plays a moral support role in these activities and encourages companies to do more. The study of the understanding of the action of sorting plastic waste by the population of Dakar through a quantitative analysis was able to demonstrate the attitudes and constraints inherent in the adoption of plastic waste sorting.Cognitive attitude, knowledge, and visible consequences have been shown to correlate positively with sorting behavior. Thus, it would seem that the population of Dakar is more sensitive to what they see and what they know to adopt sorting behavior.It has also been shown that the strongest constraints that could slow down sorting behavior were the complexity of the process, too much time and the lack of infrastructure in which to deposit plastic waste.

Keywords: behavior, Dakar, plastic waste, waste management

Procedia PDF Downloads 73

Authors: Baran Johansson

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This PhD dissertation aimed to explore children’s writing and reading in L1 (Persian) and L2 (Swedish). It adds new perspectives to reading and writing studies of bilingual biscriptal children with and without reading and writing difficulties (RWD). The study used standardised tests to examine linguistic and cognitive skills related to word reading and writing fluency in both languages. Furthermore, all participants produced two texts (one descriptive and one narrative) in each language. The writing processes and the writing product of these children were explored using logging methodologies (Eye and Pen) for both languages. Furthermore, this study investigated how two bilingual children with RWD presented themselves through writing across their languages. To my knowledge, studies utilizing standardised tests and logging tools to investigate bilingual children’s word reading and writing fluency across two different alphabetic scripts are scarce. There have been few studies analysing how bilingual children construct meaning in their writing, and none have focused on children who write in two different alphabetic scripts or those with RWD. Therefore, some aspects of the systemic functional linguistics (SFL) perspective were employed to examine how two participants with RWD created meaning in their written texts in each language. The results revealed that children with and without RWD had higher writing fluency in all measures (e.g. text lengths, writing speed) in their L2 compared to their L1. Word reading abilities in both languages were found to influence their writing fluency. The findings also showed that bilingual children without reading difficulties performed 1 standard deviation below the mean when reading words in Persian. However, their reading performance in Swedish aligned with the expected age norms, suggesting greater efficient in reading Swedish than in Persian. Furthermore, the results showed that the level of orthographic depth, consistency between graphemes and phonemes, and orthographic features can probably explain these differences across languages. The analysis of meaning-making indicated that the participants with RWD exhibited varying levels of difficulty, which influenced their knowledge and usage of writing across languages. For example, the participant with poor word recognition (PWR) presented himself similarly across genres, irrespective of the language in which he wrote. He employed the listing technique similarly across his L1 and L2. However, the participant with mixed reading difficulties (MRD) had difficulties with both transcription and text production. He produced spelling errors and frequently paused in both languages. He also struggled with word retrieval and producing coherent texts, consistent with studies of monolingual children with poor comprehension or with developmental language disorder. The results suggest that the mother tongue instruction provided to the participants has not been sufficient for them to become balanced biscriptal readers and writers in both languages. Therefore, increasing the number of hours dedicated to mother tongue instruction and motivating the children to participate in these classes could be potential strategies to address this issue.

Keywords: reading, writing, reading and writing difficulties, bilingual children, biscriptal

Procedia PDF Downloads 53

Authors: Nicolas Peyret, Sylvain Courtois, Gaël Chevallier

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This article outlines the development of the Project Based Learning (PBL) at the level of a last year’s Bachelor’s Degree. This form of pedagogy has for objective to allow a better involving of the students from the beginning of the module. The theoretical contributions are introduced during the project to solving a technological problem. The module in question is the module of mechanical dimensioning method of Supméca a French engineering school. This school issues a Master’s Degree. While the teaching methods used in primary and secondary education are frequently renewed in France at the instigation of teachers and inspectors, higher education remains relatively traditional in its practices. Recently, some colleagues have felt the need to put the application back at the heart of their theoretical teaching. This need is induced by the difficulty of covering all the knowledge deductively before its application. It is therefore tempting to make the students 'learn by doing', even if it doesn’t cover some parts of the theoretical knowledge. The other argument that supports this type of learning is the lack of motivation the students have for the magisterial courses. The role-play allowed scenarios favoring interaction between students and teachers… However, this pedagogical form known as 'pedagogy by project' is difficult to apply in the first years of university studies because of the low level of autonomy and individual responsibility that the students have. The question of what the student actually learns from the initial program as well as the evaluation of the competences acquired by the students in this type of pedagogy also remains an open problem. Thus we propose to add to the pedagogy by project format a regressive part of interventionism by the teacher based on pedagogy by example. This pedagogical scenario is based on the cognitive load theory and Bruner's constructivist theory. It has been built by relying on the six points of the encouragement process defined by Bruner, with a concrete objective, to allow the students to go beyond the basic skills of dimensioning and allow them to acquire the more global skills of engineering. The implementation of project-based teaching coupled with pedagogy by example makes it possible to compensate for the lack of experience and autonomy of first-year students, while at the same time involving them strongly in the first few minutes of the module. In this project, students have been confronted with the real dimensioning problems and are able to understand the links and influences between parameter variations and dimensioning, an objective that we did not reach in classical teaching. It is this form of pedagogy which allows to accelerate the mastery of basic skills and so spend more time on the engineer skills namely the convergence of each dimensioning in order to obtain a validated mechanism. A self-evaluation of the project skills acquired by the students will also be presented.

Keywords: Bruner's constructivist theory, mechanisms dimensioning, pedagogy by example, problem based learning

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Authors: Olga Maksakova

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A work with unconscious patients after acute brain damages besides special knowledge and practical skills of all the participants requires a very specific organization. A lot of said about team approach in neurorehabilitation, usually as for outpatient mode. Rehabilitologists deal with fixed patient problems or deficits (motion, speech, cognitive or emotional disorder). Team-building means superficial paradigm of management psychology. Linear mode of teamwork fits casual relationships there. Cases with deep altered states of consciousness (vegetative states, coma, and confusion) require non-linear mode of teamwork: recovery of consciousness might not be the goal due to phenomenon uncertainty. Rehabilitation team as Semi-open Complex System includes the patient as a part. Patient's response pattern becomes formed not only with brain deficits but questions-stimuli, context, and inquiring person. Teamwork is sourcing of phenomenology knowledge of patient's processes as Third-person approach is replaced with Second- and after First-person approaches. Here is a chance for real-time change. Patient’s contacts with his own body and outward things create a basement for restoration of consciousness. The most important condition is systematic feedbacks to any minimal movement or vegetative signal of the patient. Up to now, recovery work with the most severe contingent is carried out in the mode of passive physical interventions, while an effective rehabilitation team should include specially trained psychologists and psychotherapists. It is they who are able to create a network of feedbacks with the patient and inter-professional ones building up the team. Characteristics of ‘Team-Patient’ system (TPS) are energy, entropy, and complexity. Impairment of consciousness as the absence of linear contact appears together with a loss of essential functions (low energy), vegetative-visceral fits (excessive energy and low order), motor agitation (excessive energy and excessive order), etc. Techniques of teamwork are different in these cases for resulting optimization of the system condition. Directed regulation of the system complexity is one of the recovery tools. Different signs of awareness appear as a result of system self-organization. Joint meetings are an important part of teamwork. Regular or event-related discussions form the language of inter-professional communication, as well as the patient's shared mental model. Analysis of complex communication process in TPS may be useful for creation of the general theory of consciousness.

Keywords: rehabilitation team, urgent rehabilitation, severe brain damage, consciousness disorders, complex system theory

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Authors: Diamant Irene, Shklarnik Batya

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In on to its widespread effects on health and economic issues, Covid-19 shook the work and employment world. Among the prominent changes during the pandemic is the work-from-home trend, complete or partial, as part of social distancing. In fact, these changes accelerated an existing tendency of work flexibility already underway before the pandemic. Technology and means of advanced communications led to a re-assessment of “place of work” as a physical space in which work takes place. Today workers can remotely carry out meetings, manage projects, work in groups, and different research studies point to the fact that this type of work has no adverse effect on productivity. However, from the worker’s perspective, despite numerous advantages associated with work from home, such as convenience, flexibility, and autonomy, various drawbacks have been identified such as loneliness, reduction of commitment, home-work boundary erosion, all risk factors relating to the quality of life and burnout. Thus, a real need has arisen in exploring differences in work-from-home experiences and understanding the relationship between psychological characteristics and the prevalence of burnout. This understanding may be of significant value to organizations considering a future hybrid work model combining in-office and remote working. Based on Hobfoll’s Theory of Conservation of Resources, we hypothesized that burnout would mainly be found among workers whose physical remoteness from the workplace threatens or hinders their ability to retain significant individual resources. In the present study, we compared fully remote and partially remote workers (hybrid work), and we examined psychological characteristics and their connection to the formation of burnout. Based on the conceptualization of Place Attachment as the cognitive-emotional bond of an individual to a meaningful place and the need to maintain closeness to it, we assumed that individuals characterized with Place Attachment to the workplace would suffer more from burnout when working from home. We also assumed that extrovert individuals, characterized by the need of social interaction at the workplace and individuals with segmentationpreference – a need for separation between different life domains, would suffer more from burnout, especially among fully remote workers relative to partially remote workers. 194 workers, of which 111 worked from home in full and 83 worked partially from home, aged 19-53, from different sectors, were tested using an online questionnaire through social media. The results of the study supported our assumptions. The repercussions of these findings are discussed, relating to future occupational experience, with an emphasis on suitable occupational adjustment according to the psychological characteristics and needs of workers.

Keywords: working from home, burnout, place attachment, extraversion, segmentation preference, Covid-19

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Authors: Orhan Akınoğlu, Arif Çömek, Ersin Elmacı, Tuğba Gündoğdu

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The concept map is known to be a powerful tool to organize the ideas and concepts of an individuals’ mind. This tool is a kind of visual map that illustrates the relationships between the concepts of a certain subject. The effect of concept mapping on cognitive and affective qualities is one of the research topics among educational researchers for last decades. We educators want to utilize it both as an instructional tool or an assessment tool in classes. For that reason, this study aimed to determine the effect of concept mapping as a learning strategy in science classes on students’ academic achievement and attitude. The research employed a randomized pre-test post-test control group design. Data collected from 60 sixth grade students participated in the study from a randomly selected primary school in Turkey. Sixth-grade classes of the school were analyzed according to students’ academic achievement, science attitude, gender, mathematics, science courses grades, and their GPAs before the implementation. Two of the classes found to be equivalent (t=0,983, p>0,05) and one of them was defined as experimental and the other one control group randomly. During a 5-weeks period, the experimental group students (N=30) used the paper-based concept mapping method while the control group students (N=30) were taught with the traditional approach according to the science and technology education curriculum for light and sound subject. Both groups were taught by the same teacher who is experienced using concept mapping in science classes. Before the implementation, the teacher explained the theory of the concept maps and showed how to create paper-based concept mapping individually to the experimental group students for two hours. Then for two following hours she asked them to create some concept maps related to their former science subjects and gave them feedback by reviewing their concept maps to be sure that they can create during the implementation. The data were collected by science achievement test, science attitude scale and personal information form. Science achievement test and science attitude scale were implemented as pre-test and post-test while personal information form was implemented just as once. The reliability coefficient of the achievement test was KR20=0,76 and Cronbach’s Alpha of the attitude scale was 0,89. SPSS statistical software was used to analyze the data. According to the results, there was a statistically significant difference between the experimental and control group for academic achievement but not for attitude. The experimental group had significantly greater gains from academic achievement test than the control group (t=0,02, p<0,05). The findings showed that the paper-and-pencil concept mapping can be used as an effective method for students’ academic achievement in science classes. The results have implications for further researches.

Keywords: concept mapping, science education, constructivism, academic achievement, science attitude

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Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

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Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

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