Search results for: signal detection theory

Authors: Christopher E. A. Ramsey, Halia Valladares Montemayor

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This study examined whether the dissemination of information about the circular economy (CE) has any bearing on the likelihood of the implementation of its concepts on an individual basis. Specifically, the goal of this research study was to investigate the impact of consumer knowledge about the circular economy on their behavior in applying such concepts. Given that our current linear supply chains are unsustainable, it is of great importance that we understand what mechanisms are most effective in encouraging consumers to embrace CE. The theoretical framework employed was the theory of planned behavior (TPB). TPB, with its analysis of how attitude, subjective norms, and perceived behavioral control affect intention, provided an adequate model for testing the effects of increased information about the CE on the implementation of its recommendations. The empirical research consisted of a survey distributed among university students, faculty, and staff at a Canadian University in British Columbia.

Keywords: circular economy, consumer behavior, sustainability, theory of planned behavior

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Authors: Hamed Khezrzadeh

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Many investigations on the micromechanical structure of materials indicate that there exist fractal patterns at the micro scale in some of the main construction and industrial materials. A recently presented micro-fractal theory brings together the well-known periodic homogenization and the fractal geometry to construct an appropriate model for determination of the mechanical properties of particle reinforced composite materials. The proposed multi-step homogenization scheme considers the mechanical properties of different constituent phases in the composite together with the interaction between these phases throughout a step-by-step homogenization technique. In the proposed model the interaction of different phases is also investigated. By using this method the effect of fibers grading on the mechanical properties also could be studied. The theory outcomes are compared to the experimental data for different types of particle-reinforced composites which very good agreement with the experimental data is observed.

Keywords: fractal geometry, homogenization, micromehcanics, particulate composites

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Authors: Shimaa Holail, Tamer Saleh, Xiongwu Xiao

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Building change detection (BCD) from satellite imagery is an essential topic in urbanization monitoring, agricultural land management, and updating geospatial databases. Recently, methods for detecting changes based on deep learning have made significant progress and impressive results. However, it has the problem of being insensitive to changes in buildings with complex spectral differences, and the features being extracted are not discriminatory enough, resulting in incomplete buildings and irregular boundaries. To overcome these problems, we propose a dual Siamese network based on the Unet model with the addition of a deep supervision strategy (DS) in this paper. This network consists of a backbone (encoder) based on ImageNet pre-training, a fusion block, and feature pyramid networks (FPN) to enhance the step-by-step information of the changing regions and obtain a more accurate BCD map. To train the proposed method, we created a new dataset (EGY-BCD) of high-resolution and multi-temporal aerial images captured over New Cairo in Egypt to detect building changes for this purpose. The experimental results showed that the proposed method is effective and performs well with the EGY-BCD dataset regarding the overall accuracy, F1-score, and mIoU, which were 91.6 %, 80.1 %, and 73.5 %, respectively.

Keywords: building change detection, deep supervision, semantic segmentation, EGY-BCD dataset

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Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller

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Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.

Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation

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Authors: Mabel Usunobun Olanipekun, Henry Ogbemudia Omoregbee

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Anomalies such as water pipeline and hydraulic or petrochemical pipeline network leakages and bursts have significant implications for economic conditions and the environment. In order to ensure pipeline systems are reliable, they must be efficiently controlled. Wireless Sensor Networks (WSNs) have become a powerful network with critical infrastructure monitoring systems for water, oil and gas pipelines. The loss of water, oil and gas is inevitable and is strongly linked to financial costs and environmental problems, and its avoidance often leads to saving of economic resources. Substantial repair costs and the loss of precious natural resources are part of the financial impact of leaking pipes. Pipeline systems experts have implemented various methodologies in recent decades to identify and locate leakages in water, oil and gas supply networks. These methodologies include, among others, the use of acoustic sensors, measurements, abrupt statistical analysis etc. The issue of leak quantification is to estimate, given some observations about that network, the size and location of one or more leaks in a water pipeline network. In detecting background leakage, however, there is a greater uncertainty in using these methodologies since their output is not so reliable. In this work, we are presenting a scalable concept and simulation where a pressure-driven model (PDM) was used to determine water pipeline leakage in a system network. These pressure data were collected with the use of acoustic sensors located at various node points after a predetermined distance apart. We were able to determine with the use of correlation difference to determine the leakage point locally introduced at a predetermined point between two consecutive nodes, causing a substantial pressure difference between in a pipeline network. After de-noising the signal from the sensors at the nodes, we successfully obtained the exact point where we introduced the local leakage using the correlation difference model we developed.

Keywords: leakage detection, acoustic signals, pipeline network, correlation, wireless sensor networks (WSNs)

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Authors: Mohammad Ehsani, Iman Zarei, Soudabeh Moazemigoudarzi

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The aim of this study is to determine Pro-Environmental Behavioral Intention of Mountain Hikers to the Theory of Planned Behavior. According to many researchers nature-based recreation activities play a significant role in the tourism industry and have provided myriad opportunities for the protection of natural areas. It is essential to investigate individuals' behavior during such activities to avoid further damage to precious and dwindling natural resources. This study develops a robust model that provides a comprehensive understanding of the formation of pro-environmental behavioral intentions among climbers of Mount Damavand National Park in Iran. To this end, we combined the theory of planned behavior (TPB), value-belief-norm theory (VBN), and a hierarchical model of leisure constraints to predict individuals’ pro-environmental hiking behavior during outdoor recreation. It was used structural equation modeling to test the theoretical framework. A sample of 787 climbers was analyzed. Among the theory of planned behavior variables, perceived behavioral control showed the strongest association with behavioral intention (β = .57). This relationship indicates that if people feel they can have fewer negative impacts on national resources while hiking, it will result in more environmentally acceptable behavior. Subjective norms had a moderate positive impact on behavioral intention, indicating the importance of other people on the individual's behavior. Attitude had a small positive effect on intention. Ecological worldview positively influenced attitude and personal belief. Personal belief (awareness of consequences and ascribed responsibility) showed a positive association with TPB variables. Although the data showed a high average score in awareness of consequences (mean = 4.219 out of 5), evidence from Damavand Mount shows that there are many environmental issues that need addressing (e.g., vast amounts of garbage). National park managers need to make sure that their solutions result in awareness about proenvironmental behavior (PEB). Findings showed that negative relationship between constraints and all TPB predictors. Providing proper restrooms and parking spaces in campgrounds, strategies controlling limiting capacity and solutions for removing waste from high altitudes are helpful to decrease the negative impact of structural constraints. In order to address intrapersonal constraints, managers should provide opportunities to interest individuals in environmental activities, such as environmental celebrations or making documentaries about environmental issues. Moreover, promoting a culture of environmental protection in the Damavand Mount area would reduce interpersonal constraints. Overall, the proposed model improved the explanatory power of the TPB by predicting 64.7% of intention compared to the original TPB that accounted for 63.8% of the variance in intention.

Keywords: theory of planned behavior, pro-environmental behavior, national park, constraints

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Authors: Aymen Gammoudi, Hamza Labbaci, Nizar Messai, Yacine Sam

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Web Service Composition (Mash-up) has been considered as a new approach used to offer the user a set of Web Services responding to his request. These approaches can return a set of similar Mash-ups in a given context that makes users unable to select the perfect one. Recent approaches focus on computing the skyline over a set of Quality of Service (QoS) attributes. However, these approaches are not sufficient in a dynamic web service environment where the delivered QoS by a Web service is inherently uncertain. In this paper, we treat the problem of computing the skyline over a set of similar Mash-ups under certain dimension values. We generate dimensions for each Mash-up using aggregation operations applied to the QoS attributes. We then tackle the problem of computing the skyline under uncertain dimensions. We present each dimension value of mash-up using a frame of discernment and introduce the d-dominance using the Evidence Theory. Finally, we propose our experimental results that show both the effectiveness of the introduced skyline extensions and the efficiency of the proposed approaches.

Keywords: web services, uncertain QoS, mash-ups, uncertain dimensions, skyline, evidence theory, d-dominance

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Authors: Ovett Nwosimiri

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Historically the concept of race has played a significant part in the existence of African philosophy. Race, as part of the historical events, has been used as a reason for colonization. In recent years, there has been a numerous work on the concept of race. Some philosophers have devoted their time to the discourse of race and to understand the ascription of the race. These philosophers have dedicated their time and energy to the concept of race. Philosophers, like Joshua Glasgow, W. E. B. Du Bois, Lucius Outlaw, Kwame Anthony Appiah, Naomi Zack, Emmanuel C. Eze and many others took up the task to explain the concept of race, and also to explain in their view whether the concept of race should be conserved or eliminated. According to the eliminativists, the concept of race should be eliminated. According to the conservationists, the concept of race should be conserved. The aim of this paper is to look at the possibility of transcending the concept of race. In order to do this, the paper will briefly explain Joshua Glasgow’ idea theory of ‘racial reconstructionism’, and it will propose a theory of ‘racial transcendentalism’ as a way of transcending the concept of race. The paper will argue that we should see the concept of race as a concept that has a future beyond the mere meaning and ideas that call for its elimination or conservation.

Keywords: conservationists, eliminativists, race, transcending

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Authors: T. Zergoug, S. E. H. Abaidia, A. Nedjar, M. Y. Mokeddem

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Physical properties of uranium di-nitride (UN2) were investigated in detail using first principles calculations based on density functional theory. To treat the strong correlation effects caused by 5f Uranium valence electrons, on-site Coulomb interaction correction via the Hubbard-like term, U (DFT+U) was employed. The UN2 structural, mechanical and thermodynamic properties were calculated within DFT and Various U of DFT+U approach. The Perdew–Burke–Ernzerhof (PBE.5.2) version of the generalized gradient approximation (GGA) is used to describe the exchange-correlation with the projector-augmented wave (PAW) pseudo potentials. A comparative study shows that results are improved by using the Hubbard formalism for a certain U value correction like the structural parameter. For some physical properties the variation versus Hubbard U is strong like Young modulus but for others it is weakly noticeable such as the density of state (DOS) or bulk modulus. We noticed also that up from U=7.5 eV, elastic results become not conform to the cubic cell elastic criteria since the C44 values turn out to be negative.

Keywords: uranium diNitride, UN2, DFT+U, elastic properties

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Authors: Bakhtiar Ul Haq, R. Ahmed, A. Shaari, Mazmira Binti Mohamed, Nisar Ali

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The capability of exploiting the electronic charge and spin properties simultaneously in a single material has made diluted magnetic semiconductors (DMS) remarkable in the field of spintronics. We report the designing of DMS based on zinc-blend ZnO doped with Cr impurity. The full potential linearized augmented plane wave plus local orbital FP-L(APW+lo) method in density functional theory (DFT) has been adapted to carry out these investigations. For treatment of exchange and correlation energy, generalized gradient approximations have been used. Introducing Cr atoms in the matrix of ZnO has induced strong magnetic moment with ferromagnetic ordering at stable ground state. Cr:ZnO was found to favor the short range magnetic interaction that reflect the tendency of Cr clustering. The electronic structure of ZnO is strongly influenced in the presence of Cr impurity atoms where impurity bands appear in the band gap.

Keywords: ZnO, density functional theory, diluted agnetic semiconductors, ferromagnetic materials, FP-L(APW+lo)

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: Aleksander Nawrat, Karol Jędrasiak, Artur Ryt, Dawid Sobel

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The goal of the article is to present a novel Multimedia Firearms Training System. The system was developed in order to compensate for major problems of existing shooting training systems. The designed and implemented solution can be characterized by five major advantages: algorithm for automatic geometric calibration, algorithm of photometric recalibration, firearms hit point detection using thermal imaging camera, IR laser spot tracking algorithm for after action review analysis, and implementation of ballistics equations. The combination of the abovementioned advantages in a single multimedia firearms training system creates a comprehensive solution for detecting and tracking of the target point usable for shooting training systems and improving intervention tactics of uniformed services. The introduced algorithms of geometric and photometric recalibration allow the use of economically viable commercially available projectors for systems that require long and intensive use without most of the negative impacts on color mapping of existing multi-projector multimedia shooting range systems. The article presents the results of the developed algorithms and their application in real training systems.

Keywords: firearms shot detection, geometric recalibration, photometric recalibration, IR tracking algorithm, thermography, ballistics

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Authors: Asyraf Abdul Halim, Mohd Edil Abd Sukor, Obiyathulla Ismath Bacha

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This paper attempts to investigate the capital structure behavior of Shariah compliant firms of various levels as well those firms who are consistently Shariah non-compliant in Malaysia. The paper utilizes a unique dataset of firms of the heterogeneous level of Shariah-compliancy status over a 20 year period from the year 1997 to 2016. The paper focuses on the effects of dynamic forces behind capital structure variation such as the optimal capital structure behavior based on the trade-off, pecking order, market timing and firmly fixed effect models of capital structure. This study documents significant evidence in support of the trade-off theory with a high speed of adjustment (SOA) as well as for the time-invariant firm fixed effects across all Shariah compliance group.

Keywords: capital structure, market timing, trade-off theory, equity risk premium, Shariah-compliant firms

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Authors: Frederick M. Dumisani Xaba, Nokuthula G. Khanyile

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There is a growing demand for greater accountability, transparency and ethical conduct based on sound governance principles in the developing world. Funders, donors and sponsors are increasingly demanding more transparency, better value for money and adherence to good governance standards. The drive towards improved governance measures is largely influenced by the need to ‘plug the leaks’, deal with malfeasance, engender greater levels of accountability and good governance and to ultimately attract further funding or investment. This is the case with the Non-Profit Organizations (NPOs) in South Africa in general, and in the province of KwaZulu-Natal in particular. The paper draws from the good governance theory, stakeholder theory and systems thinking to critically examine the requirements for good governance for the NPO sector from a theoretical and legislative point and to systematically looks at the contours of governance currently among the NPOs. The paper did this through the rigorous examination of the vignettes of cases of governance among selected NPOs based in KwaZulu-Natal. The study used qualitative and quantitative research methodologies through document analysis, literature review, semi-structured interviews, focus groups and statistical analysis from the various primary and secondary sources. It found some good cases of good governance but also found frightening levels of poor governance. There was an exponential growth of NPOs registered during the period under review, equally so there was an increase in cases of non-compliance to good governance practices. NPOs operate in an increasingly complex environment. There is contestation for influence and access to resources. Stakeholder management is poorly conceptualized and executed. Recognizing that the NPO sector operates in an environment characterized by complexity, constant changes, unpredictability, contestation, diversity and divergent views of different stakeholders, there is a need to apply legislative and systems thinking approaches to strengthen governance to withstand this turbulence through a capacity development model that recognizes these contextual and environmental challenges.

Keywords: good governance, non-profit organizations, stakeholder theory, systems theory

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Authors: Sekkal Nawel, Mahammed Nadir

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The proliferation of online activities on Online Social Networks (OSNs) has captured significant user attention. However, this growth has been hindered by the emergence of fraudulent accounts that do not represent real individuals and violate privacy regulations within social network communities. Consequently, it is imperative to identify and remove these profiles to enhance the security of OSN users. In recent years, researchers have turned to machine learning (ML) to develop strategies and methods to tackle this issue. Numerous studies have been conducted in this field to compare various ML-based techniques. However, the existing literature still lacks a comprehensive examination, especially considering different OSN platforms. Additionally, the utilization of bio-inspired algorithms has been largely overlooked. Our study conducts an extensive comparison analysis of various fake profile detection techniques in online social networks. The results of our study indicate that supervised models, along with other machine learning techniques, as well as unsupervised models, are effective for detecting false profiles in social media. To achieve optimal results, we have incorporated six bio-inspired algorithms to enhance the performance of fake profile identification results.

Keywords: machine learning, bio-inspired algorithm, detection, fake profile, system, social network

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Authors: Fatemeh Safdari, Amirnaser Shamkhali, Gholamabbas Parsafar

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Carbon nanostructures are of great importance in academic research and industry, which can be mentioned to chemical sensors, catalytic processes, pharmaceutical and environmental issues. Common point in all of these applications is the occurrence of adsorption of molecules on these structures. Important carbon nanostructures in this case are mainly nanotubes and graphene. To modify pure graphene, recently, many experimental and theoretical studies have carried out to investigate of metal adsorption on graphene. In this work, the adsorption of CO molecules on pure graphene and on metal adatom on graphene surface has been simulated based on density functional theory (DFT). All calculations were performed by PBE functional and Troullier-Martins pseudopotentials. Density of states (DOS) for graphene-CO, graphen and CO around the Fermi energy has been moved and very small mixing occured which implies the physisorption of CO on the bare graphen surface. While, the results have showed that CO adsorption on transition-metal adatom on graphene surface is chemisorption.

Keywords: adsorption, density functional theory, graphene, metal adatom

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Authors: Gu Chun-Mei, Kung Mei-Juan

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The aim of this research is to examine (1) how a kindergarten teacher followed the scaffolding theory to inspire children’s interest in bicycling and (2) how these children had learned the skill of bicycling. Results revealed that: first of all, the teacher (1) used questions during the teaching process to stimulate the levels of children’s abilities; (2) provided follow-up thematic clues and hints which are based on children’s abilities (e.g., would not provide instructions and demonstrations except children continued failing to solve the current problems); (3) assisted only when children needed it. Furthermore, when children continued failing the task and being frustrated, instead of providing more concrete guidance, the teacher would utilize the following strategies: (1) postulating children’s thoughts; (2) encouraging children to feel the difficulties; (3) giving children opportunities to reflect on how to solve the problems. In sum, by raising questions, allowing children to implement by themselves for the first attempt, then inducing children to correct their actions, the teacher built a scaffold with thematic teaching to develop children’s potential on bicycling.

Keywords: thematic teaching, scaffold, zone of proximal development, children

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Authors: Rabia Munsaf Khan, Eshrat Fatima

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The analysis of the spatial extent and temporal change of vegetation cover using remotely sensed data is of critical importance to agricultural sciences. Pakistan, being an agricultural country depends on this resource as it makes 70% of the GDP. The case study is of Lal Suhanra National Park, which is not only the biggest forest reserve of Pakistan but also of Asia. The study is performed using different temporal images of Landsat. Also, the results of Landsat are cross-checked by using Sentinel-2 imagery as it has both higher spectral and spatial resolution. Vegetation can easily be detected using NDVI which is a common and widely used index. It is an important vegetation index, widely applied in research on global environmental and climatic change. The images are then classified to observe the change occurred over 15 years. Vegetation cover maps of 2000 and 2016 are used to generate the map of vegetation change detection for the respective years and to find out the changing pattern of vegetation cover. Also, the NDVI values aided in the detection of percentage decrease in vegetation cover. The study reveals that vegetation cover of the area has decreased significantly during the year 2000 and 2016.

Keywords: Landsat, normalized difference vegetation index (NDVI), sentinel 2, Greenland monitoring

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Authors: Abdulwahab Kammon, Tan Sheau Wei, Abdul Rahman Omar, Abdunaser Dayhum, Ibrahim Eldghayes, Monier Sharif

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Infectious bronchitis virus (IBV) is a very dynamic and evolving virus which causing major economic losses to the global poultry industry. Recently, the Libyan poultry industry faced severe outbreak of respiratory distress associated with high mortality and dramatic drop in egg production. Tracheal and cloacal swabs were analyzed for several poultry viruses. IBV was detected using SYBR Green I real-time PCR detection based on the nucleocapsid (N) gene. Sequence analysis of the partial N gene indicated high similarity (~ 94%) to IBV strain 3382/06 that was isolated from Taiwan. Even though the IBV strain 3382/06 is more similar to that of the Mass type H120, the isolate has been implicated associated with intertypic recombinant of 3 putative parental IBV strains namely H120, Taiwan strain 1171/92 and China strain CK/CH/LDL/97I. Complete sequencing and antigenicity studies of the Libya IBV strains are currently underway to determine the evolution of the virus and its importance in vaccine induced immunity. In this paper, we documented for the first time the presence of possibly variant IBV strain from Libya which required a dramatic change in the vaccination program.

Keywords: Libya, infectious bronchitis, molecular characterization, viruses, vaccine

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Authors: Somayeh Khanjani, Samaneh Nabavi, Shirin Jalili, Afshin Khara

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Fingerprints are area source of ubiquitous evidence and consequential for establishing identity. The detection and subsequent development of fingerprints are thus inevitable in criminal investigations. This becomes a difficult task in the case of certain extreme conditions like fire. A fire scene may be accidental or arson. The evidence subjected to fire is generally overlooked as there is a misconception that they are damaged. There are several scientific approaches to determine whether the fire was deliberate or not. In such as scenario, fingerprints may be most critical to link the perpetrator to the crime. The reason for this may be the destructive nature of fire. Fingerprints subjected to fire are exposed to high temperatures, soot deposition, electromagnetic radiation, and subsequent water force. It is believed that these phenomena damage the fingerprint. A novel fluorescent and a pre existing small particle reagent were investigated for the same. Zinc carbonates based fluorescent small particle reagent was capable of developing latent fingerprints exposed to a maximum temperature of 800 ̊C. Fluorescent SPR may prove very useful in such cases. Fluorescent SPR reagent based on zinc carbonate is a potential method for developing fingerprints from arson sites. The method is cost effective and non hazardous. This formulation is suitable for developing fingerprints exposed to fire/ arson.

Keywords: fingerprint, small particle reagent (SPR), arson, novel fluorescent

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Authors: Mohamed A. Alhammad, Hadia A. Abou-Donia, Mona H. Hashish, Mohamed N. Massoud

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Background: Rotavirus is the leading etiologic agent of severe diarrheal disease in infants and young children worldwide. The present study was aimed 1) to detect rotavirus infection as a cause of diarrhoea among children under 5 years of age using the two serological methods (ELISA and LA) and the PCR technique (2) to evaluate the three methodologies used for human RV detection in stool samples. Materials and Methods: This study was carried out on 247 children less than 5 years old, diagnosed clinically as acute gastroenteritis and attending Alexandria University Children Hospital at EL-Shatby. Rotavirus antigen was screened by ELISA and LA tests in all stool samples, whereas only 100 samples were subjected to RT-PCR method for detection of rotavirus RNA. Results: Out of the 247 studied cases with diarrhoea, rotavirus antigen was detected in 83 (33.6%) by ELISA and 73 (29.6%) by LA, while the 100 cases tested by RT-PCR showed that 44% of them had rotavirus RNA. Rotavirus diarrhoea was significantly presented with a marked seasonal peak during autumn and winter (61.4%). Conclusion: The present study confirms the huge burden of rotavirus as a major cause of acute diarrhoea in Egyptian infants and young children. It was concluded that; LA is equal in sensitivity to ELISA, ELISA is more specific than LA, and RT-PCR is more specific than ELISA and LA in diagnosis of rotavirus infection.

Keywords: rotavirus, diarrhea, immunoenzyme techniques, latex fixation tests, RT-PCR

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Authors: Brahim El Fadil

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The nature of science as a solution (NOS) to life problems is well established in school activities the world over. However, this study reveals the lack of representation of the NOS in science textbooks used in Quebec Province. A content analysis method was adopted to analyze the NOS in relation to optics knowledge and teaching-learning activities in Grade 9 science and technology textbooks and Grade 11 physics textbooks. The selected textbooks were approved and authorized by the Provincial Ministry of Education. Our analysis points out that most of these editions provided a poor representation of NOS. None of them indicates that scientific knowledge is subject to change, even though the history of optics reveals evolutionary and revolutionary changes. Moreover, the analysis shows that textbooks place little emphasis on the discussion of scientific laws and theories. Few of them argue that scientific inquiries are required to gain a deep understanding of scientific concepts. Moreover, they rarely present empirical evidence to support their arguments.

Keywords: nature of science, history of optics, geometrical theory of optics, wave theory of optics

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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Authors: Balaji Ganesh Rajagopal, Subramanian Appavu alias Balamurugan, Ayyalraj Midhun Kumar, Krishnan Nallaperumal

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Intelligent Transportation System is an Emerging area to solve multiple transportation problems. Several forms of inputs are needed in order to solve ITS problems. Advanced Traveler Information System (ATIS) is a core and important ITS area of this modern era. This involves travel time forecasting, efficient road map analysis and cost based path selection, Detection of the vehicle in the dynamic conditions and Traffic congestion state forecasting. This Article designs and provides an algorithm for traffic data generation which can be used for the above said ATIS application. By inputting the real world traffic situation in the form of video sequences, the algorithm determines the Traffic density in terms of congestion, number of vehicles in a given path which can be fed for various ATIS applications. The Algorithm deduces the key frame from the video sequences and follows the Blob detection, Identification and Tracking using connected components algorithm to determine the correlation between the vehicles moving in the real road scene.

Keywords: traffic transportation, traffic density estimation, blob identification and tracking, relative velocity of vehicles, correlation between vehicles

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Authors: Ashneel Ajay Singh, Anish Maharaj, Havish Naidu, Michelle Kumar

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Mangrove patches are the foundation species located in the estuarine land areas. These patches provide a nursery, food source and protection for numerous aquatic, intertidal and well as land-based organisms. Mangroves also help in coastal protection, maintain water clarity and are one of the biggest sinks for blue carbon sequestration. In the Pacific Island countries, numerous coastal communities have a heavy socioeconomic dependence on coastal resources and mangroves play a key ecological and economical role in structuring the availability of these resources. Fiji has a large mangrove patch located in the Votua area of the Ba province. Globally, mangrove population continues to decline with the changes in climatic conditions and anthropogenic activities. Baseline information through wetland maps and time series change are essential references for development of effective mangrove management plans. These maps reveal the status of the resource and the effects arising from anthropogenic activities and climate change. In this study, we used remote sensing and GIS tools for mapping and temporal change detection over a period of >20 years in Votua, Fiji using Landsat imagery. Landsat program started in 1972 initially as Earth Resources Technology Satellite. Since then it has acquired millions of images of Earth. This archive allows mapping of temporal changes in mangrove forests. Mangrove plants consisted of the species Rhizophora stylosa, Rhizophora samoensis, Bruguiera gymnorrhiza, Lumnitzera littorea, Heritiera littoralis, Excoecaria agallocha and Xylocarpus granatum. Change detection analysis revealed significant reduction in the mangrove patch over the years. This information serves as a baseline for the development and implementation of effective management plans for one of Fiji’s biggest mangrove patches.

Keywords: climate change, GIS, Landsat, mangrove, temporal change

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Authors: Jorge R. Santos, Pedro Sebastiao

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In recent years there has been a great growth in the use of drones, being used in several areas such as security, agriculture, or research. The existence of some systems that allow the remote control of drones is a reality; however, these systems are quite simple and directed to specific functionality. This paper proposes the development of a web platform made in Vue.js and Node.js to control, manage, and monitor drones in real time. Using a microservice architecture, the proposed project will be able to integrate algorithms that allow the optimization of processes. Communication with remote devices is suggested via HTTP through 3G, 4G, and 5G networks and can be done in real time or by scheduling routes. This paper addresses the case of forest fires as one of the services that could be included in a system similar to the one presented. The results obtained with the elaboration of this project were a success. The communication between the web platform and drones allowed its remote control and monitoring. The incorporation of the fire detection algorithm in the platform proved possible a real time analysis of the images captured by the drone without human intervention. The proposed system has proved to be an asset to the use of drones in fire detection. The architecture of the application developed allows other algorithms to be implemented, obtaining a more complex application with clear expansion.

Keywords: drone control, microservices, node.js, unmanned aerial vehicles, vue.js

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Authors: A. Jawahar

Abstract:

In this paper, the dependence of soliton pulses with respect to phase in a 10 Gbps, single channel, dispersion uncompensated telecommunication system was studied. The characteristic feature of periodic soliton interaction was noted at the Interaction point (I=6202.5Km) in one collision length of L=12405.1 Km. The interaction point is located for 10Gbps system with an initial relative spacing (qo) of soliton as 5.28 using Perturbation theory. It is shown that, when two in-phase solitons are launched, they interact at the point I=6202.5 Km, but the interaction could be restricted with introduction of different phase initially. When the phase of the input solitons increases, the deviation of soliton pulses at the I also increases. We have successfully demonstrated this effect in a telecommunication set-up in terms of Quality factor (Q), where the Q=0 for in-phase soliton. The Q was noted to be 125.9, 38.63, 47.53, 59.60, 161.37, and 78.04 for different phases such as 10o, 20o, 30o, 45o, 60o and 90o degrees respectively at Interaction point I.

Keywords: Soliton interaction, Initial relative spacing, phase, Perturbation theory and telecommunication system

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Authors: Karchung, S. Ruangsinchaiwanich

Abstract:

This paper presents open-loop vector control method of induction motor with space vector pulse width modulation (SVPWM) technique. Normally, the closed loop speed control is preferred and is believed to be more accurate. However, it requires a position sensor to track the rotor position which is not desirable to use it for certain workspace applications. This paper exhibits the performance of three-phase induction motor with the simplest control algorithm without the use of a position sensor nor an estimation block to estimate rotor position for sensorless control. The motor stator currents are measured and are transformed to synchronously rotating (d-q-axis) frame by use of Clarke and Park transformation. The actual control happens in this frame where the measured currents are compared with the reference currents. The error signal is fed to a conventional PI controller, and the corrected d-q voltage is generated. The controller outputs are transformed back to three phase voltages and are fed to SVPWM block which generates PWM signal for the voltage source inverter. The open loop vector control model along with SVPWM algorithm is modeled in MATLAB/Simulink software and is experimented and validated in TMS320F28335 DSP board.

Keywords: electric drive, induction motor, open-loop vector control, space vector pulse width modulation technique

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Authors: V. Naciti, L. Pulejo, F. Cesaroni

Abstract:

This study empirically analyzes whether the composition of the board of directors (BoD) enhances sustainability performance, in order to understand how the BoD contribute to the integration of Sustainable Development Goals (SDGs) in their businesses. Hypotheses are developed based on the agency theory and stakeholder theory. Using a system generalized method of the moment (SGMM) two-step estimator, with data from Sustainalytics and Compustat databases for 362 firms in six regions, we find that firms with more diversity on the board and a separation of chair and CEO roles have higher sustainability performance. Moreover, our findings provide that a higher number of independent directors is negatively associated with sustainability performance. This study contributes to the literature on corporate governance and the firm’s performance by demonstrating that the composition of the board of directors contributes to a better sustainability performance: by the implementation of a particular corporate governance mechanism, it is possible to integrate SDGs in the corporate strategy.

Keywords: sustainable development goals, corporate governance, board of directors, sustainability performance

Procedia PDF Downloads 166

Authors: Chinmay Shah

Abstract:

The project is all about development of a close loop traffic light control system using PLC (Programmable Logic Controller). This project is divided into two parts which are hardware and software. The hardware part for this project is a model of four way junction of a traffic light. Three indicator lamps (Red, Yellow and Green) are installed at each lane for represents as traffic light signal. This traffic control model is a replica of actuated traffic control. Actuated traffic control system is a close loop traffic control system which controls the timing of the indicator lamps depending on the fluidity of traffic for a particular lane. To make it autonomous, in each lane three IR sensors are placed which helps to sense the percentage of traffic present on any particular lane. The IR Sensors and Indicator lamps are connected to LG PLC XGB series. The PLC controls every signal which is coming from the inputs (IR Sensors) to software and display to the outputs (Indicator lamps). Default timing for the indicator lamps is 30 seconds for each lane. But depending on the percentage of traffic present, if the traffic is nearly 30-35%, green lamp will be on for 10 seconds, for 65-70% traffic it will be 20 seconds, for full 100% traffic it will be on for full 30 seconds. The software part that operates with LG PLC is “XG 5000” Programmer. Using this software, the ladder logic diagram is programmed to control the traffic light base on the flow chart. At the end of this project, the traffic light system is actuated successfully by PLC.

Keywords: close loop, IR sensor, PLC, light control system

Procedia PDF Downloads 551