Search results for: case citation network

Authors: Tom Hickey

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It is difficult to conceive of a case that might more starkly bring the arguments concerning judicial review to the fore than State (Ryan) v Lennon. Small wonder that it has attracted so much scholarly attention, although the fact that almost all of it has been in an Irish setting is perhaps surprising, given the illustrative value of the case in respect of a philosophical quandary that continues to command attention in all developed constitutional democracies. Should judges have power to invalidate legislation? This article revisits Ryan v Lennon with an eye on the importance of the idea of “democracy” in the case. It assesses the meaning of democracy: what its purpose might be and what practical implications might follow, specifically in respect of judicial review. Based on this assessment, it argues for a particular institutional model for the vindication of constitutional rights. In the context of calls for the drafting of a new constitution for Ireland, however forlorn these calls might be for the moment, it makes a broad and general case for the abandonment of judicial supremacy and for the taking up of a model in which judges have a constrained rights reviewing role that informs a more robust role that legislators would play, thereby enhancing the quality of the control that citizens have over their own laws. The article is in three parts. Part I assesses the exercise of judicial power over legislation in Ireland, with the primary emphasis on Ryan v Lennon. It considers the role played by the idea of democracy in that case and relates it to certain apparently intractable dilemmas that emerged in later Irish constitutional jurisprudence. Part II considers the concept of democracy more generally, with an eye on overall implications for judicial power. It argues for an account of democracy based on the idea of equally shared popular control over government. Part III assesses how this understanding might inform a new constitutional arrangement in the Irish setting for the vindication of fundamental rights.

Keywords: constitutional rights, democracy as popular control, Ireland, judicial power, republican theory, Ryan v Lennon

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Authors: István Fekete, Imre Berki, Áron Béni, Katalin Juhos, Marianna Makádi, Zsolt Kotroczó

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The average annual precipitation significantly influences the moisture content of the soils and, through this, the decomposition of the organic substances in the soils, the leaching of nutrients from the soils, and the pH of the soils. Climate change, together with the lengthening of the vegetation period and the increasing CO₂ level, can increase the amount of biomass that is formed. Degradation processes, which accelerate as the temperature increases and slow down due to the drying climate, and the change in the degree of leaching can cancel out or strengthen each other's effects. In the course of our research, we looked for oak forests with climate-zonal soils where the geological, geographical and ecological background conditions are as similar as possible, apart from the different annual precipitation averages and the differences that can arise from them. We examined 5 dry and 5 humid Hungarian oak soils. Climate change affects the soils of drier and wetter forests differently. The aim of our research was to compare the content of carbon, nitrogen and some other nutrients, as well as the pH of the soils of humid and dry forests. Showing the effects of the drier climate on the tested soil parameters. In the case of the examined forest soils, we found a significant difference between the soils of dry and humid forests: in the case of the annual average precipitation values (p≥ 0.0001, for dry forest soils: 564±5.2 mm; for humid forest soils: 716±3.8 mm) for pH (p= 0.0004, for dry forest soils: 5.49±0.16; for wet forest soils: 5.36±0.21); for C content (p= 0.0054, for dry forest soils: 6.92%±0.59; for humid forest soils 3.09%±0.24), for N content (p= 0.0022, dry forest in the case of soils: 0.44%±0.047; in the case of humid forest soils: 0.23%±0.013), for the K content (p=0.0017, in the case of dry forest soils: 5684±732 (mg/kg); in the case of humid forest soils 2169±196 (mg/kg)), for the Ca content (p= 0.0096, for dry forest soils: 8207±2118 (mg/kg); for wet forest soils 957±320 (mg/kg)). No significant difference was found in the case of Mg. In a wetter environment, especially if the moisture content of the soil is also optimal for the decomposing organisms during the growing season, the decomposition of organic residues accelerates, and the processes of leaching from the soil are also intensified. The different intensity of the leaching processes is also well reflected in the quantitative differences of Ca and K, and in connection with these, it is also reflected in the difference in pH values. The differences in the C and N content can be explained by differences in the intensity of the decomposition processes. In addition to warming, drying is expected in a significant part of Hungary due to climate change. Thus, the comparison of the soils of dry and humid forests allows us to predict the subsequent changes in the case of the examined parameters.

Keywords: soil nutrients, precipitation difference, climate change, organic matter decomposition, leaching

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Authors: Rana I. Abdulghani, Amera I. Melhum

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With the abnormal growth of the usage of computers over networks and under the consideration or agreement of most of the computer security experts who said that the goal of building a secure system is never achieved effectively, all these points led to the design of the intrusion detection systems(IDS). This research adopts a comparison between two techniques for network intrusion detection, The first one used the (Particles Swarm Optimization) that fall within the field (Swarm Intelligence). In this Act, the algorithm Enhanced for the purpose of obtaining the minimum error rate by amending the cluster centers when better fitness function is found through the training stages. Results show that this modification gives more efficient exploration of the original algorithm. The second algorithm used a (Back propagation NN) algorithm. Finally a comparison between the results of two methods used were based on (NSL_KDD) data sets for the construction and evaluation of intrusion detection systems. This research is only interested in clustering the two categories (Normal and Abnormal) for the given connection records. Practices experiments result in intrude detection rate (99.183818%) for EPSO and intrude detection rate (69.446416%) for BP neural network.

Keywords: IDS, SI, BP, NSL_KDD, PSO

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Authors: Vaishnavi Shivde, Shrishti Sinha, Trapti Mishra

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Traffic light detection from a moving vehicle is an important technology both for driver safety assistance functions as well as for autonomous driving in the city. This paper proposed a deep-learning-based traffic light recognition method that consists of a pixel-wise image segmentation technique and a fully convolutional network i.e., UNET architecture. This paper has used a method for detecting the position and recognizing the state of the traffic lights in video sequences is presented and evaluated using Traffic Light Dataset which contains masked traffic light image data. The first stage is the detection, which is accomplished through image processing (image segmentation) techniques such as image cropping, color transformation, segmentation of possible traffic lights. The second stage is the recognition, which means identifying the color of the traffic light or knowing the state of traffic light which is achieved by using a Convolutional Neural Network (UNET architecture).

Keywords: traffic light detection, image segmentation, machine learning, classification, convolutional neural networks

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Authors: Vivek Ku, A. K. Janmeja, D. Aggarwal, R. Gupta

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Purpose: Pulmonary rehabilitation plays a key role in management of chronic lung diseases. However, pulmonary rehabilitation is an underused modality in the management of interstitial lung disease (ILD). This is because limited information is available in literature and no data is available from India on this issue so far. The study was carried out to evaluate the role of pulmonary rehabilitation on respiratory parameters in ILD patients. Methods: The present study was a prospective randomized non-blind case control study. Total of 40 ILD patients were randomized into 2 groups of 20 patients each viz ‘pulmonary rehabilitation group’ and ‘control group’. Pulmonary rehabilitation group underwent 8 weeks pulmonary rehabilitation (PR) along with medical management as per guidelines and the control group was advised only medical management. Results: Mean age in case group was 59.15 ± 10.39 years and in control group was 62.10 ± 14.54 years. The case and the control groups were matched for age and sex. Mean MRC grading at the end of 8 weeks showed significant improvement in the case group as compared to control group (p= 0.011 vs p = 0.655). Similarly, mean St. George Respiratory Questionnaire (SGRQ) score also showed significant improvement in pulmonary rehabilitation group at the end of the study (p= 0.001 vs p= 0.492). However, FEV1 and FVC had no significant change in the case and control group. Similarly, blood gases also did not show any significant difference in the group. Conclusion: Pulmonary rehabilitation improves breathlessness and thereby improves quality of life in the patients suffering from ILD. However, the pulmonary function values and blood gases are unaffected by pulmonary rehabilitation. Clinical Implications: Further large scale multicentre study is needed to ascertain the association.

Keywords: ILD, pulmonary rehabilitation, quality of life, pulmonary functions

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Authors: Minjung Park, Sangmi Chai, Myoung Jun Lee

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Since there are growing concerns on online privacy, enterprises could involve various personal privacy infringements cases resulting legal causations. For companies that are involving online business, it is important for them to pay extra attentions to protect users’ privacy. If firms can aware consequences from possible online privacy invasion cases, they can more actively prevent future online privacy infringements. This study attempts to predict the probability of ruling types caused by various invasion cases under U.S Personal Privacy Act. More specifically, this research explores online privacy invasion cases which was sentenced guilty to identify types of criminal punishments such as penalty, imprisonment, probation as well as compensation in civil cases. Based on the 853 U.S judicial cases ranged from January, 2000 to May, 2016, which related on data privacy, this research examines the relationship between personal information infringements cases and adjudications. Upon analysis results of 41,724 words extracted from 853 regal cases, this study examined online users’ privacy invasion cases to predict the probability of conviction for a firm as an offender in both of criminal and civil law. This research specifically examines that a cause of privacy infringements and a judgment type, whether it leads a civil or criminal liability, from U.S court. This study applies network text analysis (NTA) for data analysis, which is regarded as a useful method to discover embedded social trends within texts. According to our research results, certain online privacy infringement cases caused by online spamming and adware have a high possibility that firms are liable in the case. Our research results provide meaningful insights to academia as well as industry. First, our study is providing a new insight by applying Big Data analytics to legal cases so that it can predict the cause of invasions and legal consequences. Since there are few researches applying big data analytics in the domain of law, specifically in online privacy, this study suggests new area that future studies can explore. Secondly, this study reflects social influences, such as a development of privacy invasion technologies and changes of users’ level of awareness of online privacy on judicial cases analysis by adopting NTA method. Our research results indicate that firms need to improve technical and managerial systems to protect users’ online privacy to avoid negative legal consequences.

Keywords: network text analysis, online privacy invasions, personal information infringements, predicting judgements

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Authors: Justin Reverdi, Sixin Zhang, Serge Gratton, Said Aoues, Thomas Pellegrini

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In Vapor Cycle Systems, the flow sensor plays a key role in different monitoring and control purposes. However, physical sensors can be expensive, inaccurate, heavy, cumbersome, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor based on other standard sensors is a good alternative. In this paper, a data-driven model using a Convolutional Neural Network is proposed to estimate the flow of the compressor. To fit the model to our dataset, we tested different loss functions. We show in our application that a Dynamic Time Warping based loss function called DILATE leads to better dynamical performance than the vanilla mean squared error (MSE) loss function. DILATE allows choosing a trade-off between static and dynamic performance.

Keywords: deep learning, dynamic time warping, vapor cycle system, virtual sensor

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Authors: Elisa Esposito, Johannes C. Jansen, Loredana Dellamuzia, Ugo Moretti, Lidietta Giorno

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The reduction of CO₂ emission into the atmosphere as a result of human activity is one of the most important environmental challenges to face in the next decennia. Emission of CO₂, related to the use of fossil fuels, is believed to be one of the main causes of global warming and climate change. In this scenario, the production of biomethane from organic waste, as a renewable energy source, is one of the most promising strategies to reduce fossil fuel consumption and greenhouse gas emission. Unfortunately, biogas upgrading still produces the greenhouse gas CO₂ as a waste product. Therefore, this work presents a case study on biogas upgrading, aimed at the simultaneous purification of methane and CO₂ via different steps, including CO₂/methane separation by polymeric membranes. The original objective of the project was the biogas upgrading to distribution grid quality methane, but the innovative aspect of this case study is the further purification of the captured CO₂, transforming it from a useless by-product to a pure gas with food-grade quality, suitable for commercial application in the food and beverage industry. The study was performed on a pilot plant constructed by Tecno Project Industriale Srl (TPI) Italy. This is a model of one of the largest biogas production and purification plants. The full-scale anaerobic digestion plant (Montello Spa, North Italy), has a digestive capacity of 400.000 ton of biomass/year and can treat 6.250 m3/hour of biogas from FORSU (organic fraction of solid urban waste). The entire upgrading process consists of a number of purifications steps: 1. Dehydration of the raw biogas by condensation. 2. Removal of trace impurities such as H₂S via absorption. 3.Separation of CO₂ and methane via a membrane separation process. 4. Removal of trace impurities from CO₂. The gas separation with polymeric membranes guarantees complete simultaneous removal of microorganisms. The chemical purity of the different process streams was analysed by a certified laboratory and was compared with the guidelines of the European Industrial Gases Association and the International Society of Beverage Technologists (EIGA/ISBT) for CO₂ used in the food industry. The microbiological purity was compared with the limit values defined in the European Collaborative Action. With a purity of 96-99 vol%, the purified methane respects the legal requirements for the household network. At the same time, the CO₂ reaches a purity of > 98.1% before, and 99.9% after the final distillation process. According to the EIGA/ISBT guidelines, the CO₂ proves to be chemically and microbiologically sufficiently pure to be suitable for food-grade applications.

Keywords: biogas, CO₂ separation, CO2 utilization, CO₂ food grade

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Authors: Shen Jian, Hu Jie, Qi Jin, Liu Wei Jie, Chen Ji Yi, Peng Ying Hong

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In order to settle the problem of acquiring case in biological related to design problems, a biometrics instance acquisition method based on text mining is presented. Through the construction of corpus text vector space and knowledge mining, the feature selection, similarity measure and case retrieval method of text in the field of biology are studied. First, we establish a vector space model of the corpus in the biological field and complete the preprocessing steps. Then, the corpus is retrieved by using the vector space model combined with the functional keywords to obtain the biological domain examples related to the design problems. Finally, we verify the validity of this method by taking the example of text.

Keywords: text mining, vector space model, feature selection, biologically inspired design

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Authors: Chenlu Zhang, Wanni Zhang, Florian Schaule

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Indoor environment in office buildings directly affects comfort, productivity, health, and well-being of building occupants. Wireless environmental sensor networks have been deployed in many modern offices to monitor and control the indoor environments. However, indoor environmental variables are not strong enough predictors of comfort and productivity levels of every occupant due to personal differences, both physiologically and psychologically. This study proposes human-centric sensor networks that integrate wireless environmental sensors, body area network sensors and participatory sensing technologies to collect data from both environment and human and support building operations. The sensor networks have been tested in one small-size and one medium-size office rooms with 22 participants for five months. Indoor environmental data (e.g., air temperature and relative humidity), physiological data (e.g., skin temperature and Galvani skin response), and physiological responses (e.g., comfort and self-reported productivity levels) were obtained from each participant and his/her workplace. The data results show that: (1) participants have different physiological and physiological responses in the same environmental conditions; (2) physiological variables are more effective predictors of comfort and productivity levels than environmental variables. These results indicate that the human-centric sensor networks can support human-centric building control and improve comfort and productivity in offices.

Keywords: body area network, comfort and productivity, human-centric sensors, internet of things, participatory sensing

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Authors: Cecilia Teljas

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Many government agencies use social media to supplement their traditional communication channels. Government agencies are typically risk-averse, which makes social media practices problematic. However, this case study of the social media use of the Swedish social insurance agency shows considerable bi-directional communication between the agency and the public. On one hand, the agency’s aims, strategies, ways of working and experiences related to its social media communication practice are analyzed. On the other hand, the communication by both the agency and the public is studied on one of the agency’s Facebook pages. The results showed that it is possible for an agency to provide relevant and accurate information in real-time in social media if identifying and addressing different segments separately. Furthermore, as a result of context adaption this communication was rather informal and the practice can be considered to manifest positive democratic effects due to the increased availability and inclusion.

Keywords: e-government, social media, case study, discourse analysis

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Authors: Rula Al Azawi, Abobaker Shafi

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The purpose of this paper is to use gamification technology in the mobile computing course to increase students motivation and engagement. The game applied to be designed by students focusing also to design educational game for children with age six years. This game will teach the students how to learn in a fun way. Our case study is implemented at Gulf College which is affiliated with Staffordshire University-UK. Our game design was applied to teach students Android Studio software by designing an educational game. Our goal with gamification is to improve student attendance, increase student engagement, problem solving and user stratification. Finally, we describe the findings and results of our case study. The data analysis and evaluation are based on students feedback, staff feedback and the final marking grades for the students.

Keywords: gamification, educational game, android studio software, students motivation and engagement

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Authors: Chuanbo Xu, Xinying Li, Gejirifu De, Yunna Wu

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Energy Internet (EI) is a new form that deeply integrates the Internet and the entire energy process from production to consumption. The assessment of energy efficient performance is of vital importance for the long-term sustainable development of EI project. Although the newly proposed fuzzy integrated cloud evaluation algorithm considers the randomness of uncertainty, it relies too much on the experience and knowledge of experts. Fortunately, the enrichment of EI data has enabled the utilization of data-driven methods. Therefore, the main purpose of this work is to assess the energy efficient of park-level EI by using a combination of a data-driven method with the fuzzy integrated cloud evaluation algorithm. Firstly, the indicators for the energy efficient are identified through literature review. Secondly, the artificial neural network (ANN)-based data-driven method is employed to cluster the values of indicators. Thirdly, the energy efficient of EI project is calculated through the fuzzy integrated cloud evaluation algorithm. Finally, the applicability of the proposed method is demonstrated by a case study.

Keywords: energy efficient, energy internet, data-driven, fuzzy integrated evaluation, cloud model

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Authors: Ilef Ketata, Mohamed Khalil Baazaoui, Robert Fromm, Ahmad Fakhfakh, Faouzi Derbel

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The integration of wireless communication, e. g. in real-or quasi-real-time applications, is related to many challenges such as energy consumption, communication range, latency, quality of service, and reliability. To minimize the latency without increasing energy consumption, wake-up receiver (WuRx) nodes have been introduced in recent works. Low-noise amplifiers (LNAs) are introduced to improve the WuRx sensitivity but increase the supply current severely. Different WuRx approaches exist with always-on, power-gated, or duty-cycled receiver designs. This paper presents a comparative study for improving communication range and decreasing the energy consumption of wireless sensor nodes.

Keywords: wireless sensor network, wake-up receiver, duty-cycled, low-noise amplifier, envelope detector, range study

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Authors: Atiya Khan

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Recent research on the condition of school education in India has reaffirmed the importance of quality teacher professional development, especially in light of the rapid changes in teaching methods, learning theories, curriculum, and major shifts in information and technology that education systems are experiencing around the world. However, the quality of programs of teacher professional development in India is often uneven, in some cases non-existing. The educational authorities in India have long recognized this and have developed a range of programs to assist in-service teacher education. But, these programs have been mostly inadequate at improving the quality of teachers in India. Policy literature and reports indicate that the unevenness of these programs and more generally the lack of quality teacher professional development in India are due to factors such as a large number of teachers, budgetary constraints, top-down decision making, teacher overload, lack of infrastructure, and little or no follow-up. The disparity between the government stated goals for quality teacher professional development in India and its inability to meet the learning needs of teachers suggests that new interventions are needed. The realization that globalization has brought about an increase in the social, cultural, political and economic interconnectedness between countries has also given rise to transnational opportunities for education systems, such as India’s, aiming to build their capacity to support teacher professional development. Moreover, new developments in communication technologies seem to present a plausible means of achieving high-quality professional development for teachers through the creation of social learning spaces, such as transnational learning networks. This case study investigates the potential of one such transnational learning network to support the quality of teacher professional development in India, namely the Australia-Asia BRIDGE School Partnerships Project. It explores the participation of some fifteen teachers and their principals from BRIDGE participating schools in Delhi region of India; focusing on their professional development expectations from the BRIDGE program and account for their experiences in the program, in order to determine the program’s potential for the professional development of teachers in this study.

Keywords: case study, Australia-Asia BRIDGE Project, teacher professional development, transnational learning networks

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Authors: Anil Kumar Pandey

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A compact planar monopole antenna with dual-band operation suitable for wireless local area network (WLAN) application is presented in this paper. The antenna occupies an overall area of 18 ×12 mm². The antenna is fed by a coplanar waveguide (CPW) transmission line and it combines two folded strips, which radiates at 2.4 and 5.2 GHz. In the proposed antenna, by optimally selecting the antenna dimensions, dual-band resonant modes with a much wider impedance matching at the higher band can be produced. Prototypes of the obtained optimized design have been simulated using EM solver. The simulated results explore good dual-band operation with -10 dB impedance bandwidths of 50 MHz and 2400 MHz at bands of 2.4 and 5.2 GHz, respectively, which cover the 2.4/5.2/5.8 GHz WLAN operating bands. Good antenna performances such as radiation patterns and antenna gains over the operating bands have also been observed. The antenna with a compact size of 18×12×1.6 mm³ is designed on an FR4 substrate with a dielectric constant of 4.4.

Keywords: CPW antenna, dual-band, electromagnetic simulation, wireless local area network (WLAN)

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Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Aradhna Pandarum

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South Africa is experiencing an exponential growth of distributed solar PV installations. This is due to various factors with the predominant one being increasing electricity tariffs along with decreasing installation costs, resulting in attractive business cases to some end-users. Despite there being a variety of economic and environmental advantages associated with the installation of PV, their potential impact on distribution grids has yet to be thoroughly investigated. This is especially true since the locations of these units cannot be controlled by Network Service Providers (NSPs) and their output power is stochastic and non-dispatchable. This report details two case studies that were completed to determine the possible voltage and technical losses impact of increasing PV penetration in the Northern Cape of South Africa. Some major impacts considered for the simulations were ramping of PV generation due to intermittency caused by moving clouds, the size and overall hosting capacity and the location of the systems. The main finding is that the technical impact is different on a constrained feeder vs a non-constrained feeder. The acceptable PV penetration level is much lower for a constrained feeder than a non-constrained feeder, depending on where the systems are located.

Keywords: medium voltage networks, power system losses, power system voltage, solar photovoltaic

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Authors: Daniel Olshansky, Ramiro Rodrıguez Colmeiro

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Relay Mining presents a scalable solution employing probabilistic mechanisms and crypto-economic incentives to estimate RPC volume usage, facilitating decentralized multitenant rate limiting. Network traffic from individual applications can be concurrently serviced by multiple RPC service providers, with costs, rewards, and rate limiting governed by a native cryptocurrency on a distributed ledger. Building upon established research in token bucket algorithms and distributed rate-limiting penalty models, our approach harnesses a feedback loop control mechanism to adjust the difficulty of mining relay rewards, dynamically scaling with network usage growth. By leveraging crypto-economic incentives, we reduce coordination overhead costs and introduce a mechanism for providing RPC services that are both geopolitically and geographically distributed.

Keywords: remote procedure call, crypto-economic, commit-reveal, decentralization, scalability, blockchain, rate limiting, token bucket

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Authors: Amin Ranjbar, Amir Arsalan Jalili Zolfaghari, Amir Abolfazl Suratgar, Mehrdad Khajavi

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This paper describes two stages of learning-based fault detection procedure in alternators. The procedure consists of three states of machine condition namely shortened brush, high impedance relay and maintaining a healthy condition in the alternator. The fault detection algorithm uses Wigner-Ville distribution as a feature extractor and also appropriate feature classifier. In this work, ANN (Artificial Neural Network) and also SVM (support vector machine) were compared to determine more suitable performance evaluated by the mean squared of errors criteria. Modules work together to detect possible faulty conditions of machines working. To test the method performance, a signal database is prepared by making different conditions on a laboratory setup. Therefore, it seems by implementing this method, satisfactory results are achieved.

Keywords: alternator, artificial neural network, support vector machine, time-frequency analysis, Wigner-Ville distribution

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Authors: Joshua Midha

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The basis for information campaigns and behavioral interventions has long reigned as a tactic. From the Soviet-era propaganda machines to the opinion hijacks in Iran, these measures are now commonplace and are used for dissemination and disassembly. However, the use of these tools for strategic diffusion, specifically in a counter-terrorism setting, has only been explored on the surface. This paper aims to introduce a larger conceptual portion of guided information campaigns into preexisting terror cells and situations. It provides an alternative, low-risk intervention platform for future military strategy. This paper highlights a theoretical framework to lay out the foundationary details and explanations for behavioral interventions and moves into using a case study to highlight the possibility of implementation. It details strategies, resources, circumstances, and risk factors for intervention. It also sets an expanding foundation for offensive PsyOps and argues for tactical diffusion of information to battle extremist sentiment. The two larger frameworks touch on the internal spread of information within terror cells and external political sway, thus charting a larger holistic purpose of strategic operations.

Keywords: terrorism, behavioral intervention, propaganda, SNA, extremism

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Authors: Mingxi Xiao

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Children’s experiences in the early years build and shape the brain. The early years learning environment plays a significantly important role in children’s development. A well-constructed environment will facilitate children’s physical and mental well-being. This case study used an early learning centre in Australia called SDN Hurstville as an example, describing the learning environment in the centre, as well as analyzing the functions of the affordances. In addition, this report talks about the sustainability of learning in the centre, and how the environment supports cultural diversity and indigenous learning. The early years for children are significant. Different elements in the early childhood centre should work together to help children develop better. This case study found that the natural environment and the artificial environment are both critical to children; only when they work together can children have better development in physical and mental well-being and have a sense of belonging when playing and learning in the centre.

Keywords: early childhood center, early childhood education, learning environment, Australia

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Authors: Valentina Dotto

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Climate change cases used to take the form of statutory disputes rather than constitutional or common law disputes. This changed in 2015, with the Urgenda Climate case in the Netherlands (Urgenda Foundation v. The State of the Netherlands, C/09/456689/HAZA 13-1396) and, the Juliana case in the U.S. (United States v. U.S. District Court for District of Oregon, 17-71692, 9th Cir.). The two cases represent a new type of climate litigation, the claims brought against the federal government were in fact grounded in constitutional rights. The complaints used the Doctrine of Public Trust as a cornerstone for the lawsuits asserting that government's actions against climate change failed to protect essential public trust resources; thus, violating a generation's constitutional rights to life, liberty, and property. The Public Trust Doctrine –a quintessentially American legal concept-, reserved to the States by virtue of the 9th and 10th amendment of the federal Constitution, gives them considerable jurisdiction over natural resources and has been refined by a number of Supreme Court rulings. The Juliana case exemplifies the Doctrine’s evolutionary nature because it attempts to apply it to the federal government, and establish a right to a climate system capable of sustaining human life as a fundamental right protected by a substantive due process. Furthermore, the flexibility of the Doctrine makes it permissible to be applied to a variety of different legal systems as in the Urgenda case. At the very heart of the lawsuits stands the question of who owns the Earth resources and, to what extent the general public can claim the services that the Earth provides as common property. By employing the widest possible definition of the Doctrine of Public Trust these lawsuits tried to redefine environmental resources as a collective right of all people. By doing case analysis, the paper explores how these cases can contribute to widening the public access to information and broadening the public voice in decision making as well as providing a precedent to equal access in seeking justice and redress from environmental failures.

Keywords: climate change, doctrine of public trust, environmental democracy, Juliana case, Urgenda climate case

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Authors: Svenja Pieritz, Jakab Pilaszanovich

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Collaborative Problem Solving (CPS) is recognized as being one of the most important skills of the 21st century with having a potential impact on education, job selection, and collaborative systems design. Therefore, CPS has been adopted in several standardized tests, including the Programme for International Student Assessment (PISA) in 2015. A significant challenge of evaluating CPS is the underlying interplay of cognitive and social skills, which requires a more holistic assessment. However, the majority of the existing tests are using a questionnaire-based assessment, which oversimplifies this interplay and undermines ecological validity. Two major difficulties were identified: Firstly, the creation of a controllable, real-time environment allowing natural behaviors and communication between at least two people. Secondly, the development of an appropriate method to collect and synthesize both cognitive and social metrics of collaboration. This paper proposes a more holistic and automated approach to the assessment of CPS. To address these two difficulties, a multiplayer problem-solving game called Sea of Light was developed: An environment allowing students to deploy a variety of measurable collaborative strategies. This controlled environment enables researchers to monitor behavior through the analysis of game actions and chat. The according solution for the statistical model is a combined approach of Natural Language Processing (NLP) and Bayesian network analysis. Social exchanges via the in-game chat are analyzed through NLP and fed into the Bayesian network along with other game actions. This Bayesian network synthesizes evidence to track and update different subdimensions of CPS. Major findings focus on the correlations between the evidences collected through in- game actions, the participants’ chat features and the CPS self- evaluation metrics. These results give an indication of which game mechanics can best describe CPS evaluation. Overall, Sea of Light gives test administrators control over different problem-solving scenarios and difficulties while keeping the student engaged. It enables a more complete assessment based on complex, socio-cognitive information on actions and communication. This tool permits further investigations of the effects of group constellations and personality in collaborative problem-solving.

Keywords: bayesian network, collaborative problem solving, game-based assessment, natural language processing

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Authors: Murray Matarab Konzang

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Lae Port Development Project, Four Lane Highway and other development in the extraction industry which have direct road link to Lae City are predicted to have significant impact on its road network system. This paper evaluates Lae roads improvement program with forecast on planning, economic and the installation of bypasses to ease congestion, effective and convenient transport service for bulk goods and reduce travel time. Land-use transportation study and plans for local area traffic management scheme will be considered. City roads are faced with increased number of traffic and some inadequate road pavement width, poor transport plans, and facilities to meet this transportation demand. Lae also has drainage system which might not hold a 100 year flood. Proper evaluation, plan, design and intersection analysis is needed to evaluate road network system thus recommend improvement and estimate future growth. Repetitive and cyclic loading by heavy commercial vehicles with different axle configurations apply on the flexible pavement which weakens and tear the pavement surface thus small cracks occur. Rain water seeps through and overtime it creates potholes. Effective planning starts from experimental research and appropriate design standards to enable firm embankment, proper drains and quality pavement material. This paper will address traffic problems as well as road pavement, capacities of intersections, and pedestrian flow during peak hours. The outcome of this research will be to identify heavily trafficked road sections and recommend treatments to reduce traffic congestions, road classification, and proposal for bypass routes and improvement. First part of this study will describe transport or traffic related problems within the city. Second part would be to identify challenges imposed by traffic and road related problems and thirdly to recommend solutions after the analyzing traffic data that will indicate current capacities of road intersections and finally recommended treatment for improvement and future growth.

Keywords: Lae, road network, highway, vehicle traffic, planning

Procedia PDF Downloads 358

Authors: G. Levacic, A. Zupan

Abstract:

Application of new technological solutions and installation of new elements into the network requires special attention when investigating its interaction with the existing power system. Special attention needs to be devoted to the occurrence of harmonic resonance. Sources of increasing harmonic penetration could be wind power plants, Flexible Alternating Current Transmission System (FACTS) devices, underground and submarine cable installations etc. Calculation in frequency domain with various software, for example, the software for power systems transients EMTP-RV presents one of the most common ways to obtain the harmonic impedance of the system. Along calculations in frequency domain, such software allows performing of different type of calculations as well as steady-state domain. This paper describes a power system modeling with software EMTP-RV based on data from SCADA/EMS system. The power flow results on 220 kV and 400 kV voltage levels retrieved from EMTP-RV are verified by comparing with power flow results from power transmissions system planning software PSS/E. The determination of the harmonic impedance for the case of remote power plant connection with cable up to 2500 Hz is presented as an example of calculations in frequency domain.

Keywords: power system modeling, frequency domain, steady state, EMTP-RV, PSS/E

Procedia PDF Downloads 322

Authors: Oyebade K. Oyedotun

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The cardiotocogram is a technical recording of the heartbeat rate and uterine contractions of a fetus during pregnancy. During pregnancy, several complications can occur to both the mother and the fetus; hence it is very crucial that medical experts are able to find technical means to check the healthiness of the mother and especially the fetus. It is very important that the fetus develops as expected in stages during the pregnancy period; however, the task of monitoring the health status of the fetus is not that which is easily achieved as the fetus is not wholly physically available to medical experts for inspection. Hence, doctors have to resort to some other tests that can give an indication of the status of the fetus. One of such diagnostic test is to obtain cardiotocograms of the fetus. From the analysis of the cardiotocograms, medical experts can determine the status of the fetus, and therefore necessary medical interventions. Generally, medical experts classify examined cardiotocograms into ‘normal’, ‘suspect’, or ‘pathological’. This work presents an artificial neural network based decision support system which can filter cardiotocograms data, producing the corresponding statuses of the fetuses. The capability of artificial neural network to explore the cardiotocogram data and learn features that distinguish one class from the others has been exploited in this research. In this research, feedforward and radial basis neural networks were trained on a publicly available database to classify the processed cardiotocogram data into one of the three classes: ‘normal’, ‘suspect’, or ‘pathological’. Classification accuracies of 87.8% and 89.2% were achieved during the test phase of the trained network for the feedforward and radial basis neural networks respectively. It is the hope that while the system described in this work may not be a complete replacement for a medical expert in fetus status evaluation, it can significantly reinforce the confidence in medical diagnosis reached by experts.

Keywords: decision support, cardiotocogram, classification, neural networks

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Authors: Noor Farizah Ibrahim, Christopher Durugbo

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This study aims to investigate how the Twittersphere reacted during the recent historical event of robotic landing on a comet. The news is about Philae, a robotic lander from European Space Agency (ESA), which successfully made the first-ever rendezvous and touchdown of its kind on a nucleus comet on November 12, 2014. In order to understand how Twitter is practically used in spreading messages on historical events, we conducted an analysis of one-week tweet feeds that contain the #CometLanding hashtag. We studied the trends of tweets, the diffusion of the information and the characteristics of the social network created. The results indicated that the use of Twitter as a platform enables online communities to engage and spread the historical event through social media network (e.g. tweets, retweets, mentions and replies). In addition, it was found that comprehensible and understandable hashtags could influence users to follow the same tweet stream compared to other laborious hashtags which were difficult to understand by users in online communities.

Keywords: diffusion of information, hashtag, social media, Twitter

Procedia PDF Downloads 325

Authors: Chiao-Cheng Huang, Pei-Te Chiueh, Ya-Hsuan Liou

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Chromium-contaminated wastewater from electroplating industrial activity has been a long-standing environmental issue, as it can degrade surface water quality and is harmful to soil ecosystems. The traditional method of treating chromium-contaminated wastewater has been to use chemical coagulation processes. However, this method consumes large amounts of chemicals such as sulfuric acid, sodium hydroxide, and sodium bicarbonate in order to remove chromium. However, a series of new methods for treating chromium-containing wastewater have been developed. This study aimed to compare the environmental impact of four different lab scale chromium removal processes: 1.) chemical coagulation process (the most common and traditional method), in which sodium metabisulfite was used as reductant, 2.) electrochemical process using two steel sheets as electrodes, 3.) reduction by iron-copper bimetallic powder, and 4.) photocatalysis process by TiO2. Each process was run in the lab, and was able to achieve 100% removal of chromium in solution. Then a Life Cycle Assessment (LCA) study was conducted based on the experimental data obtained from four different case studies to identify the environmentally preferable alternative to treat chromium wastewater. The model used for calculating the environmental impact was TRACi, and the system scope includes the production phase and use phase of chemicals and electricity consumed by the chromium removal processes, as well as the final disposal of chromium containing sludge. The functional unit chosen in this study was the removal of 1 mg of chromium. Solution volume of each case study was adjusted to 1 L in advance and the chemicals and energy consumed were proportionally adjusted. The emissions and resources consumed were identified and characterized into 15 categories of midpoint impacts. The impact assessment results show that the human ecotoxicity category accounts for 55 % of environmental impact in Case 1, which can be attributed to the sulfuric acid used for pH adjustment. In Case 2, production of steel sheet electrodes is an energy-intensive process, thus contributed to 20 % of environmental impact. In Case 3, sodium bicarbonate is used as an anti-corrosion additive, which results mainly in 1.02E-05 Comparative Toxicity Unit (CTU) in the human toxicity category and 0.54E-05 (CTU) in acidification of air. In Case 4, electricity consumption for power supply of UV lamp gives 5.25E-05 (CTU) in human toxicity category, 1.15E-05 (kg Neq) in eutrophication. In conclusion, Case 3 and Case 4 have higher environmental impacts than Case 1 and Case 2, which can be attributed mostly to higher energy and chemical consumption, leading to high impacts in the global warming and ecotoxicity categories.

Keywords: chromium, lab scale, life cycle assessment, wastewater

Procedia PDF Downloads 265

Authors: Minna Chang

Abstract:

Introduction: M. pneumoniae is a respiratory pathogen, which commonly causes upper and lower respiratory infections. It primarily affects children and young adults. Respiratory symptoms are well recognized, but extrapulmonary involvement is also common. Other systems that have been implicated in the disease include: skin, mucus membranes, central, peripheral nervous systems, cardiovascular, haematological, renal, and musculoskeletal systems. Here, we report a case of an otherwise healthy, young female with M. pneumonia, who presented with right upper quadrant abdominal pain. Case presentation: a healthy 25-year-old female was referred to A&E by her general practitioner, after presenting with fever, malaise, and right upper quadrant pain. M. pneumoniae was confirmed retrospectively by serology. The patient made a full recovery after a six-day course of doxycycline 100mg. Conclusion: M. pneumonia is a well-established cause of respiratory infections in children and young adults. Febrile illness with multisystem involvement, even in the absence of respiratory symptoms, should raise suspicion of M. pneumoniae infection in healthy, young adults. Our case illustrates the multi-system involvement of M. pneumoniae, which was initially missed, due to paucity of respiratory symptoms at presentation.

Keywords: infectious diseases, mycoplasma pneumoniae, respiratory infections, extra-pulmonary manifestations

Procedia PDF Downloads 143