Search results for: oriented network

Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

Procedia PDF Downloads 130

Authors: Hanna Mamo Ergando

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Climate change is already having a severe influence on agriculture, affecting crop yields, the nutritional content of main grains, and livestock productivity. Significant adaptation investments will be necessary to sustain existing yields and enhance production and food quality to fulfill demand. Climate-smart agriculture (CSA) provides numerous potentials in this regard, combining a focus on enhancing agricultural output and incomes while also strengthening resilience and responding to climate change. To improve agriculture production and productivity, the Ethiopian government has adopted and implemented a series of strategies, including the recent agricultural cluster farming that is practiced as an effort to change, improve, and transform subsistence farming to modern, productive, market-oriented, and climate-smart approach through farmers production cluster. Besides, greater attention and focus have been given to wheat production and productivity by the government, and wheat is the major crop grown in cluster farming. Therefore, the objective of this assessment was to examine various opportunities and challenges farmers face in a cluster farming system. A qualitative research approach was used to generate primary and secondary data. Respondents were chosen using the purposeful sampling technique. Accordingly, experts from the Federal Ministry of Agriculture, the Ethiopian Agricultural Transformation Institute, the Ethiopian Agricultural Research Institute, and the Ethiopian Environment Protection Authority were interviewed. The assessment result revealed that farming in clusters is an economically viable technique for sustaining small, resource-limited, and socially disadvantaged farmers' agricultural businesses. The method assists farmers in consolidating their products and delivering them in bulk to save on transportation costs while increasing income. Smallholders' negotiating power has improved as a result of cluster membership, as has knowledge and information spillover. The key challenges, on the other hand, were identified as a lack of timely provision of modern inputs, insufficient access to credit services, conflict of interest in crop selection, and a lack of output market for agro-processing firms. Furthermore, farmers in the cluster farming approach grow wheat year after year without crop rotation or diversification techniques. Mono-cropping has disadvantages because it raises the likelihood of disease and insect outbreaks. This practice may result in long-term consequences, including soil degradation, reduced biodiversity, and economic risk for farmers. Therefore, the government must devote more resources to addressing the issue of environmental sustainability. Farmers' access to complementary services that promote production and marketing efficiencies through infrastructure and institutional services has to be improved. In general, the assessment begins with some hint that leads to a deeper study into the efficiency of the strategy implementation, upholding existing policy, and scaling up good practices in a sustainable and environmentally viable manner.

Keywords: cluster farming, smallholder farmers, wheat, challenges, opportunities

Procedia PDF Downloads 217

Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

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Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: cycle consistency, deformable multimodal image registration, deep learning, GAN

Procedia PDF Downloads 131

Authors: Yibeltal Chanie Manie, Zebider Asire Munyelet

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5G and 6G technology offers enhanced quality of service with high data transmission rates, which necessitates the implementation of the Internet of Things (IoT) in 5G/6G architecture. In this paper, we proposed the integration of free space optical communication (FSO) with fiber sensor networks for IoT applications. Recently, free-space optical communications (FSO) are gaining popularity as an effective alternative technology to the limited availability of radio frequency (RF) spectrum. FSO is gaining popularity due to flexibility, high achievable optical bandwidth, and low power consumption in several applications of communications, such as disaster recovery, last-mile connectivity, drones, surveillance, backhaul, and satellite communications. Hence, high-speed FSO is an optimal choice for wireless networks to satisfy the full potential of 5G/6G technology, offering 100 Gbit/s or more speed in IoT applications. Moreover, machine learning must be integrated into the design, planning, and optimization of future optical wireless communication networks in order to actualize this vision of intelligent processing and operation. In addition, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. Moreover, we proposed deep learning techniques to estimate the strain changes and peak wavelength of multiple Fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment.

Keywords: optical sensor, artificial Intelligence, Internet of Things, free-space optics

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Authors: Yumei Han, Ling Li, Naiqing Song, Xiaoping Yang, Yuping Han

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Educational think tank is agreeably regarded as significant part of a nation’s soft power to promote the scientific and democratic level of educational policy making, and it plays critical role of bridging educational research in higher institutions and educational policy making. This study explores the concept, functions and significance of educational think tank in China, and conceptualizes a three dimensional framework to analyze the approaches of transforming research-based higher institutions into effective educational think tanks to serve educational policy making in the nation wide. Since 2014, the Ministry of Education P.R. China has been promoting the strategy of developing new type of educational think tanks in higher institutions, and such a strategy has been put into the agenda for the 13th Five Year Plan for National Education Development released in 2017.In such context, increasing scholars conduct studies to put forth strategies of promoting the development and transformation of new educational think tanks to serve educational policy making process. Based on literature synthesis, policy text analysis, and analysis of theories about policy making process and relationship between educational research and policy-making, this study constructed a three dimensional conceptual framework to address the following questions: (a) what are the new features of educational think tanks in the new era comparing traditional think tanks, (b) what are the functional objectives of the new educational think tanks, (c) what are the organizational patterns and mechanism of the new educational think tanks, (d) in what approaches traditional research-based higher institutions can be developed or transformed into think tanks to effectively serve the educational policy making process. The authors adopted case study approach on five influential education policy study centers affiliated with top higher institutions in China and applied the three dimensional conceptual framework to analyze their functional objectives, organizational patterns as well as their academic pathways that researchers use to contribute to the development of think tanks to serve education policy making process.Data was mainly collected through interviews with center administrators, leading researchers and academic leaders in the institutions. Findings show that: (a) higher institution based think tanks mainly function for multi-level objectives, providing evidence, theoretical foundations, strategies, or evaluation feedbacks for critical problem solving or policy-making on the national, provincial, and city/county level; (b) higher institution based think tanks organize various types of research programs for different time spans to serve different phases of policy planning, decision making, and policy implementation; (c) in order to transform research-based higher institutions into educational think tanks, the institutions must promote paradigm shift that promotes issue-oriented field studies, large data mining and analysis, empirical studies, and trans-disciplinary research collaborations; and (d) the five cases showed distinguished features in their way of constructing think tanks, and yet they also exposed obstacles and challenges such as independency of the think tanks, the discourse shift from academic papers to consultancy report for policy makers, weakness in empirical research methods, lack of experience in trans-disciplinary collaboration. The authors finally put forth implications for think tank construction in China and abroad.

Keywords: education policy-making, educational research, educational think tank, higher institution

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Authors: Abdulkader Helwan

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Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

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Authors: Tariq Mahmood, Faiza Lehrasab, Faraz Akrim, Muhammad Sajid nadeem, Muhammad Mushtaq, Unza waqar, Ayesha Sheraz, Shaista Andleeb

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Brown bear (Ursus arctos), a member of the family Ursidae, is distributed in a wide range of habitats in North America, Europe and Asia. Suspectedly, the global distribution range of brown bears is decreasing at the moment due to various factors. The carnivore species is categorized as ‘Least Concern’ globally by the IUCN Red List of Threatened Species. However, there are some fragmented, small populations that are on the verge of extinction, as is in Pakistan, where the species is listed as ‘Critically Endangered’, with a declining population trend. Importantly, the global historical distribution range of brown bears is undocumented. Therefore, in the current study, we reconstructed and estimated the historical distribution range of brown bears using QGIS software and also analyzed the network of protected areas in the past and current ranges of the species. Results showed that brown bear was more widely distributed in historic times, encompassing 52.6 million km² area as compared to their current distribution of 38.8 million km², resulting in a total range contraction of up to approximately 28 %. In the past, a total of N = 62,234 protected Areas, covering approximately 3.89 million km² were present in the distribution range of the species, while now a total of N= 33,313 Protected Areas, covering approximately 2.75 million km² area, are present in the current distribution range of the brown bear. The brown bear distribution range in the protected areas has also contracted by 1.15 million km² and the total percentage reduction of PAs is 29%.

Keywords: brown bear, historic distribution, range contraction, protected areas

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Authors: Foluke E. Sola-Ojo, Ibraheem A. Abubakar, Semiu F. Bello, Isiaka H. Fatima, Sule Bisola, Adesina M. Olusegun, Adeniyi C. Adeola

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The domesticated pigeon, Columba livia domestica, has many valuable characteristics, including high nutritional value and fast growth rate. There is a lack of information on its genetic diversity in Nigeria; thus, the genetic variability in mitochondrial cytochrome oxidase subunit I (COI) sequences of 150 domestic pigeons from four different locations was examined. Three haplotypes (HT) were identified in Nigerian populations; the most common haplotype, HT1, was shared with wild and domestic pigeons from Europe, America, and Asia, while HT2 and HT3 were unique to Nigeria. The overall haplotype diversity was 0.052± 0.025, and nucleotide diversity was 0.026± 0.068 across the four investigated populations. The phylogenetic tree showed significant clustering and genetic relationship of Nigerian domestic pigeons with other global pigeons. The median-joining network showed a star-like pattern suggesting population expansion. AMOVA results indicated that genetic variations in Nigerian pigeons mainly occurred within populations (99.93%), while the Neutrality tests results suggested that the Nigerian domestic pigeons’ population experienced recent expansion. This study showed a low genetic diversity and population differentiation among Nigerian domestic pigeons consistent with a relatively conservative COI sequence with few polymorphic sites. Furthermore, the COI gene could serve as a candidate molecular marker to investigate the genetic diversity and origin of pigeon species. The current data is insufficient for further conclusions; therefore, more research evidence from multiple molecular markers is required.

Keywords: Nigeria pigeon, COI, genetic diversity, genetic variation, conservation

Procedia PDF Downloads 193

Authors: Aisultan Shoiynbek, Darkhan Kuanyshbay, Paulo Menezes, Akbayan Bekarystankyzy, Assylbek Mukhametzhanov, Temirlan Shoiynbek

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Speech emotion recognition (SER) has received increasing research interest in recent years. It is a common practice to utilize emotional speech collected under controlled conditions recorded by actors imitating and artificially producing emotions in front of a microphone. There are four issues related to that approach: emotions are not natural, meaning that machines are learning to recognize fake emotions; emotions are very limited in quantity and poor in variety of speaking; there is some language dependency in SER; consequently, each time researchers want to start work with SER, they need to find a good emotional database in their language. This paper proposes an approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describes the sequence of actions involved in the proposed approach. One of the first objectives in the sequence of actions is the speech detection issue. The paper provides a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To investigate the working capacity of the developed model, an analysis of speech detection and extraction from real tasks has been performed.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: Veronika Zivicova, Petr Broz, Zdenek Fik, Alzbeta Mifkova, Jan Plzak, Zdenek Cada, Herbert Kaltner, Jana Fialova Kucerova, Hans-Joachim Gabius, Karel Smetana Jr.

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The possibility to determine genome-wide expression profiles of cells and tissues opens a new level of analysis in the quest to define dysregulation in malignancy and thus identify new tumor markers. Toward this long-term aim, we here address two issues on this level for head and neck cancer specimen: i) defining profiles in different regions, i.e. the tumor, the transition zone and normal control and ii) comparing complete data sets for seven individual patients. Special focus in the flanking immunohistochemical part is given to adhesion/growth-regulatory galectins that upregulate chemo- and cytokine expression in an NF-κB-dependent manner, to these regulators and to markers of differentiation, i.e. keratins. The detailed listing of up- and down-regulations, also available in printed form (1), not only served to unveil new candidates for testing as marker but also let the impact of the tumor in the transition zone become apparent. The extent of interindividual variation raises a strong cautionary note on assuming uniformity of regulatory events, to be noted when considering therapeutic implications. Thus, a combination of test targets (and a network analysis for galectins and their downstream effectors) is (are) advised prior to reaching conclusions on further perspectives.

Keywords: galectins, genome scale sequencing, squamous cell carcinoma, transition zone

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Authors: G. Shahzadi, A. Soulaimani

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This research work aims to identify the physical parameters of the constitutive soil model in the design of a rockfill dam by inverse analysis. The best parameters of the constitutive soil model, are those that minimize the objective function, defined as the difference between the measured and numerical results. The Finite Element code (Plaxis) has been utilized for numerical simulation. Polynomial and neural network-based response surfaces have been generated to analyze the relationship between soil parameters and displacements. The performance of surrogate models has been analyzed and compared by evaluating the root mean square error. A comparative study has been done based on objective functions and optimization techniques. Objective functions are categorized by considering measured data with and without uncertainty in instruments, defined by the least square method, which estimates the norm between the predicted displacements and the measured values. Hydro Quebec provided data sets for the measured values of the Romaine-2 dam. Stochastic optimization, an approach that can overcome local minima, and solve non-convex and non-differentiable problems with ease, is used to obtain an optimum value. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) are compared for the minimization problem, although all these techniques take time to converge to an optimum value; however, PSO provided the better convergence and best soil parameters. Overall, parameter identification analysis could be effectively used for the rockfill dam application and has the potential to become a valuable tool for geotechnical engineers for assessing dam performance and dam safety.

Keywords: Rockfill dam, parameter identification, stochastic analysis, regression, PLAXIS

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Authors: Deng Tingting

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The coordinated and integrated development of regions is an inevitable requirement for China to move towards high-quality, sustainable development. As one of the regions with the best economic foundation and the strongest economic strength in western China, it is a typical area with national importance and strong network connection characteristics in terms of the comprehensive effect of linking the inland hinterland and connecting the western and national urban networks. The integrated development of the Chengdu-Chongqing economic circle is of great strategic significance for the rapid and high-quality development of the western region. In the context of new urbanization, this paper takes 16 urban units within the economic circle as the research object, based on the 5-year panel data of population, regional economy, and spatial construction and development from 2016 to 2020, using the entropy method and Theil index to analyze the three target layers, and cause analysis. The research shows that there are temporal and spatial differences in the Chengdu-Chongqing economic circle, and there are significant differences between the core city and the surrounding cities. Therefore, by reforming and innovating the regional coordinated development mechanism, breaking administrative barriers, and strengthening the "polar nucleus" radiation function to release the driving force for economic development, especially in the gully areas of economic development belts, not only promote the coordinated development of internal regions but also promote the coordinated and sustainable development of the western region and take a high-quality development path.

Keywords: Chengdu-Chongqing economic circle, new urbanization, coordinated regional development, Theil Index

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Authors: Syed Jawad Hussain, Abir Touati, Farid Touati

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Free-Space Optics (FSO) is a wireless technology that enables the optical transmission of data though the air. FSO is emerging as a promising alternative or complementary technology to fiber optic and wireless radio-frequency (RF) links due to its high-bandwidth, robustness to EMI, and operation in unregulated spectrum. These systems are envisioned to be an essential part of future generation heterogeneous communication networks. Despite the vibrant advantages of FSO technology and the variety of its applications, its widespread adoption has been hampered by rather disappointing link reliability for long-range links due to atmospheric turbulence-induced fading and sensitivity to detrimental climate conditions. Qatar, with modest cloud coverage, high concentrations of airborne dust and high relative humidity particularly lies in virtually rainless sunny belt with a typical daily average solar radiation exceeding 6 kWh/m2 and 80-90% clear skies throughout the year. The specific objective of this work is to study for the first time in Qatar the effect of solar irradiation on the deliverability of the FSO Link. In order to analyze the transport media, we have ported Embedded Linux kernel on Field Programmable Gate Array (FPGA) and designed a network sniffer application that can run into FPGA. We installed new FSO terminals and configure and align them successively. In the reporting period, we carry out measurement and relate them to weather conditions.

Keywords: free space optics, solar irradiation, field programmable gate array, FSO outage

Procedia PDF Downloads 360

Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

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Authors: Pankhudi Khandelwal

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The revenue models of digital giants such as Facebook and Google, use targeted advertising for revenues. Such a model requires huge amounts of consumer data. While the data protection law deals with the protection of personal data, however, this data is acquired by the companies on the basis of consent, performance of a contract, or legitimate interests. This paper analyses the role that competition law can play in evading these loopholes for the protection of data and privacy of online consumers. Digital markets have certain distinctive features such as network effects and feedback loop, which gives incumbents of these markets a first-mover advantage. This creates a situation where the winner takes it all, thus creating entry barriers and concentration in the market. It has been also seen that this dominant position is then used by the undertakings for leveraging in other markets. This can be harmful to the consumers in form of less privacy, less choice, and stifling innovation, as seen in the cases of Facebook Cambridge Analytica, Google Shopping, and Google Android. Therefore, the article aims to provide a legal framework wherein the data protection law and competition law can come together to provide a balance in regulating digital markets. The issue has become more relevant in light of the Facebook decision by German competition authority, where it was held that Facebook had abused its dominant position by not complying with data protection rules, which constituted an exploitative practice. The paper looks into the jurisdictional boundaries that the data protection and competition authorities can work from and suggests ex ante regulation through data protection law and ex post regulation through competition law. It further suggests a change in the consumer welfare standard where harm to privacy should be considered as an indicator of low quality.

Keywords: data protection, dominance, ex ante regulation, ex post regulation

Procedia PDF Downloads 179

Authors: Jamaiah H. Yahaya, Aziz Deraman, Abdul Razak Hamdan, Yusmadi Yah Jusoh

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One of the most essential issues in software products is to maintain it relevancy to the dynamics of the user’s requirements and expectation. Many studies have been carried out in quality aspect of software products to overcome these problems. Previous software quality assessment models and metrics have been introduced with strengths and limitations. In order to enhance the assurance and buoyancy of the software products, certification models have been introduced and developed. From our previous experiences in certification exercises and case studies collaborating with several agencies in Malaysia, the requirements for user based software certification approach is identified and demanded. The emergence of social network applications, the new development approach such as agile method and other varieties of software in the market have led to the domination of users over the software. As software become more accessible to the public through internet applications, users are becoming more critical in the quality of the services provided by the software. There are several categories of users in web-based systems with different interests and perspectives. The classifications and metrics are identified through brain storming approach with includes researchers, users and experts in this area. The new paradigm in software quality assessment is the main focus in our research. This paper discusses the classifications of users in web-based software system assessment and their associated factors and metrics for quality measurement. The quality model is derived based on IEEE structure and FCM model. The developments are beneficial and valuable to overcome the constraints and improve the application of software certification model in future.

Keywords: software certification model, user centric approach, software quality factors, metrics and measurements, web-based system

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Authors: Sanjivrao Katakam, Thanumoorthi I., Antony Gerald, Ratan Kulkarni, Shaju Nair

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With increasing energy costs and its impact on the business, sustainability today has evolved from a social expectation to an economic imperative. Therefore, finding methods to reduce cost has become a critical directive for Industry leaders. Effective energy management is the only way to cut costs. However, Energy Management has been a challenge because it requires a change in old habits and legacy systems followed for decades. Today exorbitant levels of energy and operational data is being captured and stored by Industries, but they are unable to convert these structured and unstructured data sets into meaningful business intelligence. It must be noted that for quick decisions, organizations must learn to cope with large volumes of operational data in different formats. Energy analytics not only helps in extracting inferences from these data sets, but also is instrumental in transformation from old approaches of energy management to new. This in turn assists in effective decision making for implementation. It is the requirement of organizations to have an established corporate strategy for reducing operational costs through visibility and optimization of energy usage. Energy analytics play a key role in optimization of operations. The paper describes how today energy data analytics is extensively used in different scenarios like reducing operational costs, predicting energy demands, optimizing network efficiency, asset maintenance, improving customer insights and device data insights. The paper also highlights how analytics helps transform insights obtained from energy data into sustainable solutions. The paper utilizes data from an array of segments such as retail, transportation, and water sectors.

Keywords: energy analytics, energy management, operational data, business intelligence, optimization

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

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Authors: Penrug Pengsombut, Worawut Hamarn, Teerawuth Suwannasri, Kittiphong Songrukkiat, Kanatip Ratanachoo

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PTT Public Company Limited or simply PTT has played an important role in strengthening national energy security of the Kingdom of Thailand by transporting natural gas to customers in power, industrial and commercial sectors since 1981. PTT has been constructing and operating natural gas pipeline system of over 4,500-km network length both onshore and offshore laid through different area classifications i.e., marine, forest, agriculture, rural, urban, and city areas. During project development phase, an Environmental Impact Assessment (EIA) is conducted and submitted to the Office of Natural Resources and Environmental Policy and Planning (ONEP) for approval before project construction commencement. Knowledge and experiences gained and revealed from EIA in the past projects definitely are developed to further advance EIA study process for newly 5th Transmission Natural Gas Pipeline Project (5TP) with approximately 415 kilometers length. The preferred pipeline route is selected and justified by SMARTi map, an advance digital one-map platform with consists of multiple layers geographic and environmental information. Sensitive area impact focus (SAIF) is a practicable impact assessment methodology which appropriate for a particular long distance infrastructure project such as 5TP. An environmental modeling simulation is adopted into SAIF methodology for impact quantified in all sensitive areas whereas other area along pipeline right-of-ways is typically assessed as an impact representative. Resulting time and cost deduction is beneficial to project for early start.

Keywords: environmental impact assessment, EIA, natural gas pipeline, sensitive area impact focus, SAIF

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Authors: Swadha Singh

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International Solar Alliance is the foremost treaty-based global organization concerned with tapping the potential of sun-abundant nations between the Tropics of Cancer and Capricorn and enables co-operation among them. As a founding member of the International Solar Alliance, India exhibits its positioning as an upcoming leader in clean energy. India has set ambitious goals and targets to expand the share of solar in its energy mix and is playing a proactive role both at the regional and global levels. ISA aims to serve multiple goals- bring about scale commercialization of solar power, boost domestic manufacturing, and leverage solar diplomacy in African countries, amongst others. Against this backdrop, this paper attempts to examine the ways in which ISA as an intergovernmental organization under Indian leadership can leverage the cause of clean energy (solar) diplomacy and effectively shape partnerships and collaborations with other developing countries in terms of sharing solar technology, capacity building, risk mitigation, mobilizing financial investment and providing an aggregate market. A more specific focus of ISA is on the developing countries, which in the absence of a collective, are constrained by technology and capital scarcity, despite being naturally endowed with solar resources. Solar rich but finance-constrained economies face political risk, foreign exchange risk, and off-taker risk. Scholars argue that aligning India’s climate change discourse and growth prospects in its engagements, collaborations, and partnerships at the bilateral, multilateral and regional level can help promote trade, attract investments, and promote resilient energy transition both in India and in partner countries. For developing countries, coming together in an action-oriented way on issues of climate and clean energy is particularly important since it is developing and underdeveloped countries that face multiple and coalescing challenges such as the adverse impact of climate change, uneven and low access to reliable energy, and pressing employment needs. Investing in green recovery is agreed to be an assured way to create resilient value chains, create sustainable livelihoods, and help mitigate climate threats. If India is able to ‘green its growth’ process, it holds the potential to emerge as a climate leader internationally. It can use its experience in the renewable sector to guide other developing countries in balancing multiple similar objectives of development, energy security, and sustainability. The challenges underlying solar expansion in India have lessons to offer other developing countries, giving India an opportunity to assume a leadership role in solar diplomacy and expand its geopolitical influence through inter-governmental organizations such as ISA. It is noted that India has limited capacity to directly provide financial funds and support and is not a leading manufacturer of cheap solar equipment, as does China; however, India can nonetheless leverage its large domestic market to scale up the commercialization of solar power and offer insights and learnings to similarly placed abundant solar countries. The paper examines the potential of and limits placed on India’s solar diplomacy.

Keywords: climate diplomacy, energy security, solar diplomacy, renewable energy

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Authors: V. Jagadeesh, K. Venkata Subbaiah, P. Govinda Rao

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This paper explaining about the significance of information technology tools and software packages in supply chain management (SCM) in order to manage the entire supply chain. Managing materials flow and financial flow and information flow effectively and efficiently with the aid of information technology tools and packages in order to deliver right quantity with right quality of goods at right time by using right methods and technology. Information technology plays a vital role in streamlining the sales forecasting and demand planning and Inventory control and transportation in supply networks and finally deals with production planning and scheduling. It achieves the objectives by streamlining the business process and integrates within the enterprise and its extended enterprise. SCM starts with customer and it involves sequence of activities from customer, retailer, distributor, manufacturer and supplier within the supply chain framework. It is the process of integrating demand planning and supply network planning and production planning and control. Forecasting indicates the direction for planning raw materials in order to meet the production planning requirements. Inventory control and transportation planning allocate the optimal or economic order quantity by utilizing shortest possible routes to deliver the goods to the customer. Production planning and control utilize the optimal resources mix in order to meet the capacity requirement planning. The above operations can be achieved by using appropriate information technology tools and software packages for the supply chain management.

Keywords: supply chain management, information technology, business process, extended enterprise

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Authors: M. Zayoud, S. Oueida, S. Ionescu, P. AbiChar

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Background: Wireless sensor network is encompassed of diversified tools of information technology, which is widely applied in a range of domains, including military surveillance, weather forecasting, and earthquake forecasting. Strengthened grounds are always developed for wireless sensor networks, which usually emerges security issues during professional application. Thus, essential technological tools are necessary to be assessed for secure aggregation of data. Moreover, such practices have to be incorporated in the healthcare practices that shall be serving in the best of the mutual interest Objective: Aggregation of encrypted data has been assessed through homomorphic stream cipher to assure its effectiveness along with providing the optimum solutions to the field of healthcare. Methods: An experimental design has been incorporated, which utilized newly developed cipher along with CPU-constrained devices. Modular additions have also been employed to evaluate the nature of aggregated data. The processes of homomorphic stream cipher have been highlighted through different sensors and modular additions. Results: Homomorphic stream cipher has been recognized as simple and secure process, which has allowed efficient aggregation of encrypted data. In addition, the application has led its way to the improvisation of the healthcare practices. Statistical values can be easily computed through the aggregation on the basis of selected cipher. Sensed data in accordance with variance, mean, and standard deviation has also been computed through the selected tool. Conclusion: It can be concluded that homomorphic stream cipher can be an ideal tool for appropriate aggregation of data. Alongside, it shall also provide the best solutions to the healthcare sector.

Keywords: aggregation, cipher, homomorphic stream, encryption

Procedia PDF Downloads 259

Authors: Ebrahim Panah, Muhammad Yasir Babar

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Thanks to the development of online technology and social networks, people are able to communicate as well as learn. WhatsApp is a popular social network which is growingly gaining popularity. This app can be used for communication as well as education. It can be used for instructor-learner, learner-learner, and learner-content interactions; however, very little knowledge is available on these potentials of WhatsApp. The current study was undertaken to investigate university students’ perceptions of WhatsApp used as a tool for instructor-learner dialogue, learner-content dialogue, and learner-learner dialogue. The study adopted a survey approach and distributed the questionnaire developed by Google Forms to 54 (11 males and 43 females) university students. The obtained data were analyzed using SPSS version 20. The result of data analysis indicates that students have positive attitudes towards WhatsApp as a tool for Instructor-Learner Dialogue: it easy to reach the lecturer (4.07), the instructor gives me valuable feedback on my assignment (4.02), the instructor is supportive during course discussion and offers continuous support with the class (4.00). Learner-Content Dialogue: WhatsApp allows me to academically engage with lecturers anytime, anywhere (4.00), it helps to send graphics such as pictures or charts directly to the students (3.98), it also provides out of class, extra learning materials and homework (3.96), and Learner-Learner Dialogue: WhatsApp is a good tool for sharing knowledge with others (4.09), WhatsApp allows me to academically engage with peers anytime, anywhere (4.07), and we can interact with others through the use of group discussion (4.02). It was also found that there are significant positive correlations between students’ perceptions of Instructor-Learner Dialogue (ILD), Learner-Content Dialogue (LCD), Learner-Learner Dialogue (LLD) and WhatsApp Application in classroom. The findings of the study have implications for lectures, policy makers and curriculum developers.

Keywords: instructor-learner dialogue, learners-contents dialogue, learner-learner dialogue, whatsapp application

Procedia PDF Downloads 158

Authors: Abdul Rahmat

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Community-based education in the economic empowerment of the family is an attempt to accelerate human development index (HDI) Dumbo Kingdom District of Gorontalo economics (purchasing power) program developed in this activity is the manufacture of functional skills shredded fish, fish balls, fish nuggets, chips anchovies, and corn sticks fish. The target audience of this activity is fishing se mothers subdistrict Dumbo Kingdom include Talumolo Village, Village Botu, Kampung Bugis Village, Village North and Sub Leato South Leato that each village is represented by 20 participants so totaling 100 participants. Time activities beginning in October s/d November 2014 held once a week on every Saturday at 9.00 s/d 13:00/14:00. From the results of the learning process of testing the skills of functional skills of making shredded fish, fish balls, fish nuggets, chips anchovies, fish and corn sticks residents have additional knowledge and experience are: 1) Order the concept include: nutrient content, processing food with fish raw materials , variations in taste, packaging, pricing and marketing sales. 2) Products made: in accordance with the wishes of the residents learned that estimated Eligible selling, product packaging logo creation, preparation and realization of the establishment of Business Study Group (KBU) and pioneered the marketing network with restaurant, store / shop staple food vendors that are around CLC.

Keywords: community development, functional skills, gender, HDI

Procedia PDF Downloads 312

Authors: Raheel Shakoor Siddiqui, Sanjay Narayana Murthy, Manikandar Srinivas Cheruvu, Kash Akhtar

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Major trauma is a dynamic public health epidemic that is continuously evolving. Major trauma care services rely on multi-disciplinary team input involving highly trained pre and in-hospital critical care teams. Pre-hospital critical care teams (PHCCTs), major trauma centres (MTCs), trauma units, and rehabilitation facilities all form an efficient and organised trauma system. England comprises 27 MTCs funded by the National Health Service (NHS). Major trauma care entails enhanced resuscitation protocols coupled with the expertise of dedicated trauma teams and rapid radiological imaging to improve trauma outcomes. Literature reports a change in the demographic of major trauma as elderly patients (silver trauma) with injuries sustained from a fall of 2 metres or less commonly present to services. Evidence of an increasing population age with multiple comorbidities necessitates treatment within the first hour of injury (golden hour) to improve trauma survival outcomes. Staffing and funding pressures within the NHS have subsequently led to a shortfall of available physician-led PHCCTs. Thus, there is a strong emphasis on targeted research and funding to appropriately deploy resources to deprived areas. This review article will discuss the current English trauma system whilst critically appraising present challenges, identifying insufficiencies, and recommending aims for an improved future trauma system in England.

Keywords: trauma, orthopaedics, major trauma, trauma system, trauma network

Procedia PDF Downloads 186

Authors: Dorit Olenik-Shemesh, Tali Heiman

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The rapid increase in the massive use of the internet in recent yearshas led to an increase in the prevalence of a phenomenon called 'Problematic Internet use' (PIU), an emerging, growing health problem, especially during adolescents, that poses a challenge for mental health research and practitioners. Problematic Internet use (PIU) is defined as an excessive overuse of the internet, including an inability to control time spent on the internet, cognitivepreoccupation with the Internet, and continued use in spite of the adverse consequences, which may lead to psychological, social, and academic difficulties in one's life and daily functioning. However, little is known about the nature of the nexusbetween PIU and subjective well-being among adolescents. The main purpose of the current study was to explore in depth the network of connections between PIU, sense of well-being, and fourpersonal-emotional factors (resilience, self-control, depressive mood, and loneliness) that may mediate these relationships. A total sample of 433 adolescents, 214 (49.4%) girls and 219 (50.6%) boys between the ages of 12–17 (mean = 14.9, SD = 2.16), completed self-reportquestionnaires relating to the study variables. In line with the hypothesis, analysis of a Structural Equation modeling (SEM) revealed the main following results: high levels of PIU predicted low levels of well-being among adolescents. In addition, low levels of resilience and high levels of depressivemood (together), as well as low levels of self control and high levels of depressivemood (together), as well as low levels of resilience and high levels of loneliness, mediated the relationships between PIU and well-being. In general, girls were found to be higher in PIU and inresilience than boys. The study results revealed specific implications for developing intervention programs for adolescents in the context of PIU; aiming at more balanced adjusted use of the Internet along withpreventingthe decrease in well being.

Keywords: probelmatic inetrent Use, well-being, adolescents, SEM model

Procedia PDF Downloads 167

Authors: Hui Luo, Zhenhong Li, Zhen Dong

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The analysis of multi-temporal InSAR (MTInSAR) such as persistent scatterer (PS) and small baseline subset (SBAS) techniques usually relies on temporal/spatial phase unwrapping (PU). Unfortunately, it always fails to unwrap the phase for two reasons: 1) spatial phase jump between adjacent pixels larger than π, such as layover and high discontinuous terrain; 2) temporal phase discontinuities such as time varied atmospheric delay. To overcome these limitations, a least-square based PU method is introduced in this paper, which incorporates baseline-combination interferograms and adjacent phase gradient network. Firstly, permanent scatterers (PS) are selected for study. Starting with the linear baseline-combination method, we obtain equivalent 'small baseline inteferograms' to limit the spatial phase difference. Then, phase different has been conducted between connected PSs (connected by a specific networking rule) to suppress the spatial correlated phase errors such as atmospheric artifact. After that, interval phase difference along arcs can be computed by least square method and followed by an outlier detector to remove the arcs with phase ambiguities. Then, the unwrapped phase can be obtained by spatial integration. The proposed method is tested on real data of TerraSAR-X, and the results are also compared with the ones obtained by StaMPS(a software package with 3D PU capabilities). By comparison, it shows that the proposed method can successfully unwrap the interferograms in urban areas even when high discontinuities exist, while StaMPS fails. At last, precise DEM errors can be got according to the unwrapped interferograms.

Keywords: phase unwrapping, time series, InSAR, urban areas

Procedia PDF Downloads 147

Authors: Meenu Kaushik, Ayon K. Bandhoyadhayay, Lalit M. Joshi

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Inductive output tubes (IOTs) are widely used as microwave power amplifiers for broadcast and scientific applications. It is capable of amplifying radio frequency (RF) power with very good efficiency. Its compactness, reliability, high efficiency, high linearity and low operating cost make this device suitable for various applications. The device consists of an integrated structure of electron gun and RF cavity, collector and focusing structure. The working principle of IOT is a combination of triode and klystron. The cathode lies in the electron gun produces a stream of electrons. A control grid is placed in close proximity to the cathode. Basically, the input part of IOT is the integrated structure of gridded electron gun which acts as an input cavity thereby providing the interaction gap where the input RF signal is applied to make it interact with the produced electron beam for supporting the amplification phenomena. The paper presents the design, fabrication and testing of a radial re-entrant cavity for implementing in the input structure of IOT at 350 MHz operating frequency. The model’s suitability has been discussed and a generalized mathematical relation has been introduced for getting the proper transverse magnetic (TM) resonating mode in the radial narrow gap RF cavities. The structural modeling has been carried out in CST and SUPERFISH codes. The cavity is fabricated with the Aluminum material and the RF characterization is done using vector network analyzer (VNA) and the results are presented for the resonant frequency peaks obtained in VNA.

Keywords: inductive output tubes, IOT, radial cavity, coaxial cavity, particle accelerators

Procedia PDF Downloads 122

Authors: Arvind Srivastav, Tarun Kanti Bhattacharyya

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The north-eastern, Himalayan, and Eastern Ghats Belt of India comprise of earthquake-prone, remote, and hilly terrains. Earthquakes have caused enormous damages in these regions in the past. A wireless sensor network based earthquake early warning system (EEWS) is being developed to mitigate the damages caused by earthquakes. It consists of sensor nodes, distributed over the region, that perform majority voting of the output of the seismic sensors in the vicinity, and relay a message to a base station to alert the residents when an earthquake is detected. At the heart of the EEWS is a low-power two-stage seismic sensor that continuously tracks seismic events from incoming three-axis accelerometer signal at the first-stage, and, in the presence of a seismic event, triggers the second-stage P-wave detector that detects the onset of P-wave in an earthquake event. The parameters of the P-wave detector have been optimized for minimizing detection time and maximizing the accuracy of detection.Working of the sensor scheme has been verified with seven earthquakes data retrieved from IRIS. In all test cases, the scheme detected the onset of P-wave accurately. Also, it has been established that the P-wave onset detection time reduces linearly with the sampling rate. It has been verified with test data; the detection time for data sampled at 10Hz was around 2 seconds which reduced to 0.3 second for the data sampled at 100Hz.

Keywords: earthquake early warning system, EEWS, STA/LTA, polarization, wavelet, event detector, P-wave detector

Procedia PDF Downloads 174

Authors: L. Spitaleri, C. M. A. Gangemi, R. Purrello, G. Nicotra, G. Trusso Sfrazzetto, G. Casella, M. Casarin, A. Gulino

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Hybrid molecular–nanoparticle materials, obtained with a bottom-up approach, are suitable for the fabrication of functional nanostructures showing structural control and well-defined properties, i.e., optical, electronic or catalytic properties, in the perspective of applications in different fields of nanotechnology. Gold nanoparticles (Au NPs) exhibit important chemical, electronic and optical properties due to their size, shape and electronic structures. In fact, Au NPs containing no more than 30-40 atoms are only luminescent because they can be considered as large molecules with discrete energy levels, while nano-sized Au NPs only show the surface plasmon resonance. Hence, it appears that gold nanoparticles can alternatively be luminescent or plasmonic, and this represents a severe constraint for their use as an optical material. The aim of this work was the fabrication of nanoscale assembly of Au NPs covalently anchored to each other by means of novel bi-functional porphyrin molecules that work as bridges between different gold nanoparticles. This functional architecture shows a strong surface plasmon due to the Au nanoparticles and a strong luminescence signal coming from porphyrin molecules, thus, behaving like an artificial organized plasmonic and fluorescent network. The self-assembly geometry of this porphyrin on the Au NPs was studied by investigation of the conformational properties of the porphyrin derivative at the DFT level. The morphology, electronic structure and optical properties of the conjugated Au NPs – porphyrin system were investigated by TEM, XPS, UV–vis and Luminescence. The present nanostructures can be used for plasmon-enhanced fluorescence, photocatalysis, nonlinear optics, etc., under atmospheric conditions since our system is not reactive to air nor water and does not need to be stored in a vacuum or inert gas.

Keywords: gold nanoparticle, porphyrin, surface plasmon resonance, luminescence, nanostructures

Procedia PDF Downloads 153