Search results for: heterogeneous combat network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5774

Search results for: heterogeneous combat network

2114 Effective Scheduling of Hybrid Reconfigurable Microgrids Considering High Penetration of Renewable Sources

Authors: Abdollah Kavousi Fard

Abstract:

This paper addresses the optimal scheduling of hybrid reconfigurable microgrids considering hybrid electric vehicle charging demands. A stochastic framework based on unscented transform to model the high uncertainties of renewable energy sources including wind turbine and photovoltaic panels, as well as the hybrid electric vehicles’ charging demand. In order to get to the optimal scheduling, the network reconfiguration is employed as an effective tool for changing the power supply path and avoiding possible congestions. The simulation results are analyzed and discussed in three different scenarios including coordinated, uncoordinated and smart charging demand of hybrid electric vehicles. A typical grid-connected microgrid is employed to show the satisfying performance of the proposed method.

Keywords: microgrid, renewable energy sources, reconfiguration, optimization

Procedia PDF Downloads 272
2113 Investigating the Factors Affecting Generalization of Deep Learning Models for Plant Disease Detection

Authors: Praveen S. Muthukumarana, Achala C. Aponso

Abstract:

A large percentage of global crop harvest is lost due to crop diseases. Timely identification and treatment of crop diseases is difficult in many developing nations due to insufficient trained professionals in the field of agriculture. Many crop diseases can be accurately diagnosed by visual symptoms. In the past decade, deep learning has been successfully utilized in domains such as healthcare but adoption in agriculture for plant disease detection is rare. The literature shows that models trained with popular datasets such as PlantVillage does not generalize well on real world images. This paper attempts to find out how to make plant disease identification models that generalize well with real world images.

Keywords: agriculture, convolutional neural network, deep learning, plant disease classification, plant disease detection, plant disease diagnosis

Procedia PDF Downloads 146
2112 Pharmacovigilance in Hospitals: Retrospective Study at the Pharmacovigilance Service of UHE-Oran, Algeria

Authors: Nadjet Mekaouche, Hanane Zitouni, Fatma Boudia, Habiba Fetati, A. Saleh, A. Lardjam, H. Geniaux, A. Coubret, H. Toumi

Abstract:

Medicines have undeniably played a major role in prolonging shelf life and improving quality. The absolute efficacy of the drug remains a lever for innovation, its benefit/risk balance is not always assured and it does not always have the expected effects. Prior to marketing, knowledge about adverse drug reactions is incomplete. Once on the market, phase IV drug studies begin. For years, the drug was prescribed with less care to a large number of very heterogeneous patients and often in combination with other drugs. It is at this point that previously unknown adverse effects may appear, hence the need for the implementation of a pharmacovigilance system. Pharmacovigilance represents all methods for detecting, evaluating, informing and preventing the risks of adverse drug reactions. The most severe adverse events occur frequently in hospital and that a significant proportion of adverse events result in hospitalizations. In addition, the consequences of hospital adverse events in terms of length of stay, mortality and costs are considerable. It, therefore, appears necessary to develop ‘hospital pharmacovigilance’ aimed at reducing the incidence of adverse reactions in hospitals. The most widely used monitoring method in pharmacovigilance is spontaneous notification. However, underreporting of adverse drug reactions is common in many countries and is a major obstacle to pharmacovigilance assessment. It is in this context that this study aims to describe the experience of the pharmacovigilance service at the University Hospital of Oran (EHUO). This is a retrospective study extending from 2011 to 2017, carried out on archived records of declarations collected at the level of the EHUO Pharmacovigilance Department. Reporting was collected by two methods: ‘spontaneous notification’ and ‘active pharmacovigilance’ targeting certain clinical services. We counted 217 statements. It involved 56% female patients and 46% male patients. Age ranged from 5 to 78 years with an average of 46 years. The most common adverse reaction was drug toxidermy. For the drugs in question, they were essentially according to the ATC classification of anti-infectives followed by anticancer drugs. As regards the evolution of declarations by year, a low rate of notification was noted in 2011. That is why we decided to set up an active approach at the level of some services where a resident of reference attended the staffs every week. This has resulted in an increase in the number of reports. The declarations came essentially from the services where the active approach was installed. This highlights the need for ongoing communication between all relevant health actors to stimulate reporting and secure drug treatments.

Keywords: adverse drug reactions, hospital, pharmacovigilance, spontaneous notification

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2111 Mathematical Modeling for Diabetes Prediction: A Neuro-Fuzzy Approach

Authors: Vijay Kr. Yadav, Nilam Rathi

Abstract:

Accurate prediction of glucose level for diabetes mellitus is required to avoid affecting the functioning of major organs of human body. This study describes the fundamental assumptions and two different methodologies of the Blood glucose prediction. First is based on the back-propagation algorithm of Artificial Neural Network (ANN), and second is based on the Neuro-Fuzzy technique, called Fuzzy Inference System (FIS). Errors between proposed methods further discussed through various statistical methods such as mean square error (MSE), normalised mean absolute error (NMAE). The main objective of present study is to develop mathematical model for blood glucose prediction before 12 hours advanced using data set of three patients for 60 days. The comparative studies of the accuracy with other existing models are also made with same data set.

Keywords: back-propagation, diabetes mellitus, fuzzy inference system, neuro-fuzzy

Procedia PDF Downloads 259
2110 Identification of Breast Anomalies Based on Deep Convolutional Neural Networks and K-Nearest Neighbors

Authors: Ayyaz Hussain, Tariq Sadad

Abstract:

Breast cancer (BC) is one of the widespread ailments among females globally. The early prognosis of BC can decrease the mortality rate. Exact findings of benign tumors can avoid unnecessary biopsies and further treatments of patients under investigation. However, due to variations in images, it is a tough job to isolate cancerous cases from normal and benign ones. The machine learning technique is widely employed in the classification of BC pattern and prognosis. In this research, a deep convolution neural network (DCNN) called AlexNet architecture is employed to get more discriminative features from breast tissues. To achieve higher accuracy, K-nearest neighbor (KNN) classifiers are employed as a substitute for the softmax layer in deep learning. The proposed model is tested on a widely used breast image database called MIAS dataset for experimental purposes and achieved 99% accuracy.

Keywords: breast cancer, DCNN, KNN, mammography

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2109 Mean Monthly Rainfall Prediction at Benina Station Using Artificial Neural Networks

Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

Procedia PDF Downloads 489
2108 A Multilevel Authentication Protocol: MAP in VANET for Human Safety

Authors: N. Meddeb, A. M. Makhlouf, M. A. Ben Ayed

Abstract:

Due to the real-time requirement of message in Vehicular Ad hoc NETworks (VANET), it is necessary to authenticate vehicles to achieve security, efficiency, and conditional privacy-preserving. Privacy is of utmost relevance in VANETs. For this reason, we have proposed a new protocol called ‘Multilevel Authentication Protocol’ (MAP) that considers different vehicle categories. The proposed protocol is based on our Multilevel Authentication protocol for Vehicular networks (MAVnet). But the MAP leads to human safety, where the priority is given to the ambulance vehicles. For evaluation, we used the Java language to develop a demo application and deployed it on the Network Security Simulation (Nessi2). Compared with existing authentication protocols, MAP markedly enhance the communication overhead and decreases the delay of exchanging messages while preserving conditional privacy.

Keywords: Vehicular Ad hoc NETworks (VANET), vehicle categories, safety, databases, privacy, authentication, throughput, delay

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2107 Optimization and Operation of Charging and Discharging Stations for Hybrid Cars and their Effects on the Electricity Distribution Network

Authors: Ali Heydarimoghim

Abstract:

In this paper, the optimal placement of charging and discharging stations is done to determine the location and capacity of the stations, reducing the cost of electric vehicle owners' losses, reducing the cost of distribution system losses, and reducing the costs associated with the stations. Also, observing the permissible limits of the bus voltage and the capacity of the stations and their distance are considered as constraints of the problem. Given the traffic situation in different areas of a city, we estimate the amount of energy required to charge and the amount of energy provided to discharge electric vehicles in each area. We then introduce the electricity distribution system of the city in question. Following are the scenarios for introducing the problem and introducing the objective and constraint functions. Finally, the simulation results for different scenarios are compared.

Keywords: charging & discharging stations, hybrid vehicles, optimization, replacement

Procedia PDF Downloads 139
2106 Synthesis of a Hybrid Material (PVA/SiO₂/TiO₂) by Sol-Gel Method

Authors: Gueridi Bachir, Dadache Derradji, Rouabah Farid

Abstract:

This work is focused on the preparation and characterization of poly (vinyl alcohol)/silica gel/Nano-TiO₂, and the study of titanium dioxide (TiO₂) nanoparticles 1% on the properties of poly (vinyl alcohol) (PVA)/silica films. Fourier transform infrared (FT-IR), water contact angle, ultraviolet-visible spectrometry (UV-VIS)) were used to characterize the hybrid films obtained. The PVA/SiO₂/Nano-TiO₂ films were successfully synthesized. Owing to the FT-IR Analysis, the chemical bonds have clearly shown that the PVA backbone is linked to the (SiO₂-TiO₂) network. UV-VIS tests indicated that the hybrid films' UV shielding properties were drastically enhanced as a result of the addition of TiO₂. The water contact angle results revealed that TiO₂ nanoparticles used as a doping compound possess an important influence on the hydrophilicity of PVA/SiO₂ as thin films.

Keywords: sol-gel method, hybrid materials, PVA/SIO₂/TiO₂, spectroscopical characterization

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2105 A Reasoning Method of Cyber-Attack Attribution Based on Threat Intelligence

Authors: Li Qiang, Yang Ze-Ming, Liu Bao-Xu, Jiang Zheng-Wei

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With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain and evidence chain of cyber-attack on threat intelligence platform through data calculation, analysis and reasoning. Then, we used a number of cyber-attack events which we have observed and analyzed to test the reasoning method and demo system, the result of testing indicates that the reasoning method can provide certain help in cyber-attack attribution.

Keywords: reasoning, Bayesian networks, cyber-attack attribution, Kill Chain, threat intelligence

Procedia PDF Downloads 452
2104 Analytical Study of Data Mining Techniques for Software Quality Assurance

Authors: Mariam Bibi, Rubab Mehboob, Mehreen Sirshar

Abstract:

Satisfying the customer requirements is the ultimate goal of producing or developing any product. The quality of the product is decided on the bases of the level of customer satisfaction. There are different techniques which have been reported during the survey which enhance the quality of the product through software defect prediction and by locating the missing software requirements. Some mining techniques were proposed to assess the individual performance indicators in collaborative environment to reduce errors at individual level. The basic intention is to produce a product with zero or few defects thereby producing a best product quality wise. In the analysis of survey the techniques like Genetic algorithm, artificial neural network, classification and clustering techniques and decision tree are studied. After analysis it has been discovered that these techniques contributed much to the improvement and enhancement of the quality of the product.

Keywords: data mining, defect prediction, missing requirements, software quality

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2103 Analyzing the Characteristics and Shifting Patterns of Creative Hubs in Bandung

Authors: Fajar Ajie Setiawan, Ratu Azima Mayangsari, Bunga Aprilia

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The emergence of creative hubs around the world, including in Bandung, was primarily driven by the needs of collaborative-innovative spaces for creative industry activities such as the Maker Movement and the Coworking Movement. These activities pose challenges for identification and formulation of sets of indicators for modeling creative hubs in Bandung to help stakeholders in formulating strategies. This study intends to identify their characteristics. This research was conducted using a qualitative approach comparing three concepts of creative hub categorization and integrating them into a single instrument to analyze 12 selected creative hubs. Our results showed three new functions of creative hubs in Bandung: (1) cultural, (2) retail business, and (3) community network. Results also suggest that creative hubs in Bandung are commonly established for networking and community activities. Another result shows that there was a shifting pattern of creative hubs before the 2000s and after the 2000s, which also creates a hybrid group of creative hubs.

Keywords: creative industry, creative hubs, Ngariung, Bandung

Procedia PDF Downloads 178
2102 Using Self Organizing Feature Maps for Classification in RGB Images

Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

Abstract:

Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feed-forward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on self organizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: classification, SOFM algorithm, neural network, neighborhood, RGB image

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2101 The Structure of Invariant Manifolds after a Supercritical Hamiltonian Hopf Bifurcation

Authors: Matthaios Katsanikas

Abstract:

We study the structure of the invariant manifolds of complex unstable periodic orbits of a family of periodic orbits, in a 3D autonomous Hamiltonian system of galactic type, after a transition of this family from stability to complex instability (Hamiltonian Hopf bifurcation). We consider the case of a supercritical Hamiltonian Hopf bifurcation. The invariant manifolds of complex unstable periodic orbits have two kinds of structures. The first kind is represented by a disk confined structure on the 4D space of section. The second kind is represented by a complicated central tube structure that is associated with an extended network of tube structures, strips and flat structures of sheet type on the 4D space of section.

Keywords: dynamical systems, galactic dynamics, chaos, phase space

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2100 Azolla Pinnata as Promising Source for Animal Feed in India: An Experimental Study to Evaluate the Nutrient Enhancement Result of Feed

Authors: Roshni Raha, Karthikeyan S.

Abstract:

The world's largest livestock population resides in India. Existing strategies must be modified to increase the production of livestock and their by-products in order to meet the demands of the growing human population. Even though India leads the world in both milk production and the number of cows, average production is not very healthy and productive. This may be due to the animals' poor nutrition caused by a chronic under-availability of high-quality fodder and feed. This article explores Azolla pinnata to be a promising source to produce high-quality unconventional feed and fodder for effective livestock production and good quality breeding in India. This article is an exploratory study using a literature survey and experimentation analysis. In the realm of agri-biotechnology, azolla sp gained attention for helping farmers achieve sustainability, having minimal land requirements, and serving as a feed element that doesn't compete with human food sources. It has high methionine content, which is a good source of protein. It can be easily digested as the lignin content is low. It has high antioxidants and vitamins like beta carotene, vitamin A, and vitamin B12. Using this concept, the paper aims to investigate and develop a model of using azolla plants as a novel, high-potential feed source to combat the problems of low production and poor quality of animals in India. A representative sample of animal feed is collected where azolla is added. The sample is ground into a fine powder using mortar. PITC (phenylisothiocyanate) is added to derivatize the amino acids. The sample is analyzed using HPLC (High-Performance Liquid Chromatography) to measure the amino acids and monitor the protein content of the sample feed. The amino acid measurements from HPLC are converted to milligrams per gram of protein using the method of amino acid profiling via a set of calculations. The amino acid profile data is then obtained to validate the proximate results of nutrient enhancement of the composition of azolla in the sample. Based on the proximate composition of azolla meal, the enhancement results shown were higher compared to the standard values of normal fodder supplements indicating the feed to be much richer and denser in nutrient supply. Thus azolla fed sample proved to be a promising source for animal fodder. This would in turn lead to higher production and a good breed of animals that would help to meet the economic demands of the growing Indian population. Azolla plants have no side effects and can be considered as safe and effective to be immersed in the animal feed. One area of future research could begin with the upstream scaling strategy of azolla plants in India. This could involve introducing several bioreactor types for its commercial production. Since azolla sp has been proved in this paper as a promising source for high quality animal feed and fodder, large scale production of azolla plants will help to make the process much quicker, more efficient and easily accessible. Labor expenses will also be reduced by employing bioreactors for large-scale manufacturing.

Keywords: azolla, fodder, nutrient, protein

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2099 Further Analysis of Global Robust Stability of Neural Networks with Multiple Time Delays

Authors: Sabri Arik

Abstract:

In this paper, we study the global asymptotic robust stability of delayed neural networks with norm-bounded uncertainties. By employing the Lyapunov stability theory and Homeomorphic mapping theorem, we derive some new types of sufficient conditions ensuring the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slopebounded activation functions. An important aspect of our results is their low computational complexity as the reported results can be verified by checking some properties symmetric matrices associated with the uncertainty sets of network parameters. The obtained results are shown to be generalization of some of the previously published corresponding results. Some comparative numerical examples are also constructed to compare our results with some closely related existing literature results.

Keywords: neural networks, delayed systems, lyapunov functionals, stability analysis

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2098 Comparative Analysis of Universal Filtered Multi Carrier and Filtered Orthogonal Frequency Division Multiplexing Systems for Wireless Communications

Authors: Raja Rajeswari K

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Orthogonal Frequency Division Multiplexing (OFDM), a multi Carrier transmission technique that has been used in implementing the majority of wireless applications like Wireless Network Protocol Standards (like IEEE 802.11a, IEEE 802.11n), in telecommunications (like LTE, LTE-Advanced) and also in Digital Audio & Video Broadcast standards. The latest research and development in the area of orthogonal frequency division multiplexing, Universal Filtered Multi Carrier (UFMC) & Filtered OFDM (F-OFDM) has attracted lots of attention for wideband wireless communications. In this paper UFMC & F-OFDM system are implemented and comparative analysis are carried out in terms of M-ary QAM modulation scheme over Dolph-chebyshev filter & rectangular window filter and to estimate Bit Error Rate (BER) over Rayleigh fading channel.

Keywords: UFMC, F-OFDM, BER, M-ary QAM

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2097 Intelligent Adaptive Learning in a Changing Environment

Authors: G. Valentis, Q. Berthelot

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Nowadays the trend to develop ever more intelligent and autonomous systems often takes its inspiration in the living beings on Earth. Some simple isolated systems are able, once brought together, to form a strong and reliable system. When trying to adapt the idea to man-made systems it is not possible to include in their program everything the system may encounter during its life cycle. It is, thus, necessary to make the system able to take decisions based on other criteria such as its past experience, i.e. to make the system learn on its own. However, at some point the acquired knowledge depends also on environment. So the question is: if system environment is modified, how could the system respond to it quickly and appropriately enough? Here, starting from reinforcement learning to rate its decisions, and using adaptive learning algorithms for gain and loss reward, the system is made able to respond to changing environment and to adapt its knowledge as time passes. Application is made to a robot finding an exit in a labyrinth.

Keywords: reinforcement learning, neural network, autonomous systems, adaptive learning, changing environment

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2096 The Dark History of American Psychiatry: Racism and Ethical Provider Responsibility

Authors: Mary Katherine Hoth

Abstract:

Despite racial and ethnic disparities in American psychiatry being well-documented, there remains an apathetic attitude among nurses and providers within the field to engage in active antiracism and provide equitable, recovery-oriented care. It is insufficient to be a “colorblind” nurse or provider and state that call care provided is identical for every patient. Maintaining an attitude of “colorblindness” perpetuates the racism prevalent throughout healthcare and leads to negative patient outcomes. The purpose of this literature review is to highlight the how the historical beginnings of psychiatry have evolved into the disparities seen in today’s practice, as well as to provide some insight on methods that providers and nurses can employ to actively participate in challenging these racial disparities. Background The application of psychiatric medicine to White people versus Black, Indigenous, and other People of Color has been distinctly different as a direct result of chattel slavery and the development of pseudoscience “diagnoses” in the 19th century. This weaponization of the mental health of Black people continues to this day. Population The populations discussed are Black, Indigenous, and other People of Color, with a primary focus on Black people’s experiences with their mental health and the field of psychiatry. Methods A literature review was conducted using CINAHL, EBSCO, MEDLINE, and PubMed databases with the following terms: psychiatry, mental health, racism, substance use, suicide, trauma-informed care, disparities and recovery-oriented care. Articles were further filtered based on meeting the criteria of peer-reviewed, full-text availability, written in English, and published between 2018 and 2023. Findings Black patients are more likely to be diagnosed with psychotic disorders and prescribed antipsychotic medications compared to White patients who were more often diagnosed with mood disorders and prescribed antidepressants. This same disparity is also seen in children and adolescents, where Black children are more likely to be diagnosed with behavior problems such as Oppositional Defiant Disorder (ODD) and White children with the same presentation are more likely to be diagnosed with Attention Hyperactivity Disorder. Medications advertisements for antipsychotics like Haldol as recent as 1974 portrayed a Black man, labeled as “agitated” and “aggressive”, a trope we still see today in police violence cases. The majority of nursing and medical school programs do not provide education on racism and how to actively combat it in practice, leaving many healthcare professionals acutely uneducated and unaware of their own biases and racism, as well as structural and institutional racism. Conclusions Racism will continue to grow wherever it is given time, space, and energy. Providers and nurses have an ethical obligation to educate themselves, actively deconstruct their personal racism and bias, and continuously engage in active antiracism by dismantling racism wherever it is encountered, be it structural, institutional, or scientific racism. Agents of change at the patient care level not only improve the outcomes of Black patients, but it will also lead the way in ensuring Black, Indigenous, and other People of Color are included in research of methods and medications in psychiatry in the future.

Keywords: disparities, psychiatry, racism, recovery-oriented care, trauma-informed care

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2095 Predicting Mobile Payment System Adoption in Nigeria: An Empirical Analysis

Authors: Aminu Hamza

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This study examines the factors that play vital role in the adoption of mobile payment system among consumers in Nigeria. Technology Acceptance Model (TAM) was used with two additional variables to form the conceptual model. The study was conducted in three Universities in Kano state, Nigeria. Convenience sampling method was used with a total valid 202 respondents which involved the students of Bayero University Kano (BUK), Northwest University, and Kano University of Science and Technology (KUST) Wudil, Kano, Nigeria. Results of the regression analysis revealed that Perceived ease of use (PEOU) and Perceived usefulness (PU) have significant and positive correlation with the behavioral intention to adopt mobile payment system. The findings of this study would be useful to the policy makers Central Bank of Nigeria (CBN), mobile network operators and providers of the services.

Keywords: mobile payment system, Nigeria, technology adoption, technology acceptance model

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2094 Analysis of Electricity Demand at Household Level Using Leap Model in Balochistan, Pakistan

Authors: Sheikh Saeed Ahmad

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Electricity is vital for any state’s development that needs policy for planning the power network extension. This study is about simulation modeling for electricity in Balochistan province. Baseline data of electricity consumption was used of year 2004 and projected with the help of LEAP model up to subsequent 30 years. Three scenarios were created to run software. One scenario was baseline and other two were alternative or green scenarios i.e. solar and wind energy scenarios. Present study revealed that Balochistan has much greater potential for solar and wind energy for electricity production. By adopting these alternative energy forms, Balochistan can save energy in future nearly 23 and 48% by incorporating solar and wind power respectively. Thus, the study suggests to government planners, an aspect of integrating renewable sources in power system for ensuring sustainable development and growth.

Keywords: demand and supply, LEAP, solar energy, wind energy, households

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2093 Recovering Trust in Institutions through Networked Governance: An Analytical Approach via the Study of the Provincial Government of Gipuzkoa

Authors: Xabier Barandiaran, Igone Guerra

Abstract:

The economic and financial crisis that hit European countries in 2008 revealed the inability of governments to respond unilaterally to the so-called “wicked” problems that affect our societies. Closely linked to this, the increasing disaffection of citizens towards politics has resulted in growing distrust of the citizenry not only in the institutions in general but also in the political system, in particular. Precisely, these two factors provoked the action of the local government of Gipuzkoa (Basque Country) to move from old ways of “doing politics” to a new way of “thinking politics” based on a collaborative approach, in which innovative modes of public decision making are prominent. In this context, in 2015, the initiative Etorkizuna Eraikiz (Building the Future), a contemporary form of networked governance, was launched by the Provincial Government. The paper focuses on the Etorkizuna Eraikiz initiative, a sound commitment from a local government to build jointly with the citizens the future of the territory. This paper will present preliminary results obtained from three different experiences of co-creation developed within Etorkizuna Eraikiz in which the formulation of networked governance is a mandatory pre-requisite. These experiences show how the network building approach among the different agents of the territory as well as the co-creation of public policies is the cornerstone of this challenging mission. Through the analysis of the information and documentation gathered during the four years of Etorkizuna-Eraikiz, and, specifically by delving into the strategy promoted by the initiative, some emerging analytical conclusions resulting from the promotion of this collaborative culture will be presented. For example, some preliminary results have shown a significant positive relationship between shared leadership and the formulation of the public good. In the period 2016-2018, a total of 73 projects were launched and funding by the Provincial Government of Gipuzkoa within the Etorkizuna Eraikiz initiative, that indicates greater engagement of the citizenry in the process of policy-making and therefore improving, somehow, the quality of the public policies. These statements have been supported by the last survey about the perspectives of the citizens toward politics and policies. Some of the more prominent results show us that there is still a high level of distrust in Politics (78,9% of respondents) but a greater trust in institutions such the Political Government of Gipuzkoa (40,8% of respondents declared as “good” the performance of this provincial institution). Regarding the Etorkizuna Eraikiz Initiative, it is being more readily recognized by citizens over this period of time (25,4% of the respondents in June 2018 agreed to know about the initiative giving it a mark of 5,89 ) and thus build trust and a sense of ownership. Although, there is a clear requirement for further research on the linkages between collaborative governance and level of trust, the paper, based on these findings, will provide some managerial and theoretical implications for collaborative governance in the territory.

Keywords: network governance, collaborative governance, public sector innovation, citizen participation, trust

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2092 Poly(Methyl Methacrylate)/Graphene Microparticles Having a Core/Shell Structure Prepared with Carboxylated Graphene as a Pickering Stabilizer

Authors: Gansukh Erdenedelger, Doljinsuren Sukhbaatar, Trung Dung Dao, Byeong-Kyu Lee, Han Mo Jeong

Abstract:

Two kinds of carboxylated thermally reduced graphenes (C-TRGs) having different lateral sizes are examined as a Pickering stabilizer in the suspension polymerization of methyl methacrylate. The size and the shape of the prepared composite particles are irregular due to agglomeration, more evidently when the larger C-TRG is used. In addition, C-TRG is distributed not only on the surface but also inside the composite particles. It indicates that the C-TRG alone is not a stable Pickering agent. However, a very small dosage of acrylic acid remedies all these issues, because acrylic acid interacts with C-TRG and synergizes the stabilizing effect. The compression molded composite of the core/shell poly(methyl methacrylate)/C-TRG particles exhibits a very low percolation threshold of electrical conductivity of 0.03 vol%. It demonstrates that the C-TRG shells of the composite particles effectively form a segregated conductive network throughout the composite.

Keywords: pickering, graphene, polymerization, PMMA

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2091 Deficient Multisensory Integration with Concomitant Resting-State Connectivity in Adult Attention Deficit/Hyperactivity Disorder (ADHD)

Authors: Marcel Schulze, Behrem Aslan, Silke Lux, Alexandra Philipsen

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Objective: Patients with Attention Deficit/Hyperactivity Disorder (ADHD) often report that they are being flooded by sensory impressions. Studies investigating sensory processing show hypersensitivity for sensory inputs across the senses in children and adults with ADHD. Especially the auditory modality is affected by deficient acoustical inhibition and modulation of signals. While studying unimodal signal-processing is relevant and well-suited in a controlled laboratory environment, everyday life situations occur multimodal. A complex interplay of the senses is necessary to form a unified percept. In order to achieve this, the unimodal sensory modalities are bound together in a process called multisensory integration (MI). In the current study we investigate MI in an adult ADHD sample using the McGurk-effect – a well-known illusion where incongruent speech like phonemes lead in case of successful integration to a new perceived phoneme via late top-down attentional allocation . In ADHD neuronal dysregulation at rest e.g., aberrant within or between network functional connectivity may also account for difficulties in integrating across the senses. Therefore, the current study includes resting-state functional connectivity to investigate a possible relation of deficient network connectivity and the ability of stimulus integration. Method: Twenty-five ADHD patients (6 females, age: 30.08 (SD:9,3) years) and twenty-four healthy controls (9 females; age: 26.88 (SD: 6.3) years) were recruited. MI was examined using the McGurk effect, where - in case of successful MI - incongruent speech-like phonemes between visual and auditory modality are leading to a perception of a new phoneme. Mann-Whitney-U test was applied to assess statistical differences between groups. Echo-planar imaging-resting-state functional MRI was acquired on a 3.0 Tesla Siemens Magnetom MR scanner. A seed-to-voxel analysis was realized using the CONN toolbox. Results: Susceptibility to McGurk was significantly lowered for ADHD patients (ADHDMdn:5.83%, ControlsMdn:44.2%, U= 160.5, p=0.022, r=-0.34). When ADHD patients integrated phonemes, reaction times were significantly longer (ADHDMdn:1260ms, ControlsMdn:582ms, U=41.0, p<.000, r= -0.56). In functional connectivity medio temporal gyrus (seed) was negatively associated with primary auditory cortex, inferior frontal gyrus, precentral gyrus, and fusiform gyrus. Conclusion: MI seems to be deficient for ADHD patients for stimuli that need top-down attentional allocation. This finding is supported by stronger functional connectivity from unimodal sensory areas to polymodal, MI convergence zones for complex stimuli in ADHD patients.

Keywords: attention-deficit hyperactivity disorder, audiovisual integration, McGurk-effect, resting-state functional connectivity

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2090 Radar Signal Detection Using Neural Networks in Log-Normal Clutter for Multiple Targets Situations

Authors: Boudemagh Naime

Abstract:

Automatic radar detection requires some methods of adapting to variations in the background clutter in order to control their false alarm rate. The problem becomes more complicated in non-Gaussian environment. In fact, the conventional approach in real time applications requires a complex statistical modeling and much computational operations. To overcome these constraints, we propose another approach based on artificial neural network (ANN-CMLD-CFAR) using a Back Propagation (BP) training algorithm. The considered environment follows a log-normal distribution in the presence of multiple Rayleigh-targets. To evaluate the performances of the considered detector, several situations, such as scale parameter and the number of interferes targets, have been investigated. The simulation results show that the ANN-CMLD-CFAR processor outperforms the conventional statistical one.

Keywords: radat detection, ANN-CMLD-CFAR, log-normal clutter, statistical modelling

Procedia PDF Downloads 365
2089 Solving Directional Overcurrent Relay Coordination Problem Using Artificial Bees Colony

Authors: M. H. Hussain, I. Musirin, A. F. Abidin, S. R. A. Rahim

Abstract:

This paper presents the implementation of Artificial Bees Colony (ABC) algorithm in solving Directional OverCurrent Relays (DOCRs) coordination problem for near-end faults occurring in fixed network topology. The coordination optimization of DOCRs is formulated as linear programming (LP) problem. The objective function is introduced to minimize the operating time of the associated relay which depends on the time multiplier setting. The proposed technique is to taken as a technique for comparison purpose in order to highlight its superiority. The proposed algorithms have been tested successfully on 8 bus test system. The simulation results demonstrated that the ABC algorithm which has been proved to have good search ability is capable in dealing with constraint optimization problems.

Keywords: artificial bees colony, directional overcurrent relay coordination problem, relay settings, time multiplier setting

Procedia PDF Downloads 330
2088 Impact of Work and Family Conflict on Employee Self Esteem

Authors: Romana P. Khokhar

Abstract:

The purpose of this study was to explore the impact of work-family conflict on self-esteem. On the basis of the literature reviewed, it was hypothesized that 1) work-family conflict has an impact on self- esteem, 2). There would be a gender difference on the variable of work family conflict. Data for this study was taken from a sample of 70 employees within the banking industry since this industry is generally associated with higher levels of work-family conflict. Statistical tests performed were regression and t-test. Self-esteem was assessed with the 10-item Rosenberg Self-Esteem Scale (RSE; Rosenberg, 1965) and Work-Family Conflict Scale (WFCS; Netemeyer, R. G., Boles, J. S., & McMurrian, R. 1996) was used to assess the level of work –family conflict. The results indicated that an increase in work-family conflict resulted in lower self-esteem due to the various pressures evidenced in a complicated network of direct and indirect influences. It was also determined that there is less effect of work-family conflict on the female workers, as opposed to the male population, leading to the conclusion that in the case of the female workers the impact on self-esteem was not significant.

Keywords: work and family conflict, self-esteem, employee

Procedia PDF Downloads 499
2087 Semiconductor Properties of Natural Phosphate Application to Photodegradation of Basic Dyes in Single and Binary Systems

Authors: Y. Roumila, D. Meziani, R. Bagtache, K. Abdmeziem, M. Trari

Abstract:

Heterogeneous photocatalysis over semiconductors has proved its effectiveness in the treatment of wastewaters since it works under soft conditions. It has emerged as a promising technique, giving rise to less toxic effluents and offering the opportunity of using sunlight as a sustainable and renewable source of energy. Many compounds have been used as photocatalysts. Though synthesized ones are intensively used, they remain expensive, and their synthesis involves special conditions. We thus thought of implementing a natural material, a phosphate ore, due to its low cost and great availability. Our work is devoted to the removal of hazardous organic pollutants, which cause several environmental problems and health risks. Among them, dye pollutants occupy a large place. This work relates to the study of the photodegradation of methyl violet (MV) and rhodamine B (RhB), in single and binary systems, under UV light and sunlight irradiation. Methyl violet is a triarylmethane dye, while RhB is a heteropolyaromatic dye belonging to the Xanthene family. In the first part of this work, the natural compound was characterized using several physicochemical and photo-electrochemical (PEC) techniques: X-Ray diffraction, chemical, and thermal analyses scanning electron microscopy, UV-Vis diffuse reflectance measurements, and FTIR spectroscopy. The electrochemical and photoelectrochemical studies were performed with a Voltalab PGZ 301 potentiostat/galvanostat at room temperature. The structure of the phosphate material was well characterized. The photo-electrochemical (PEC) properties are crucial for drawing the energy band diagram, in order to suggest the formation of radicals and the reactions involved in the dyes photo-oxidation mechanism. The PEC characterization of the natural phosphate was investigated in neutral solution (Na₂SO₄, 0.5 M). The study revealed the semiconducting behavior of the phosphate rock. Indeed, the thermal evolution of the electrical conductivity was well fitted by an exponential type law, and the electrical conductivity increases with raising the temperature. The Mott–Schottky plot and current-potential J(V) curves recorded in the dark and under illumination clearly indicate n-type behavior. From the results of photocatalysis, in single solutions, the changes in MV and RhB absorbance in the function of time show that practically all of the MV was removed after 240 mn irradiation. For RhB, the complete degradation was achieved after 330 mn. This is due to its complex and resistant structure. In binary systems, it is only after 120 mn that RhB begins to be slowly removed, while about 60% of MV is already degraded. Once nearly all of the content of MV in the solution has disappeared (after about 250 mn), the remaining RhB is degraded rapidly. This behaviour is different from that observed in single solutions where both dyes are degraded since the first minutes of irradiation.

Keywords: environment, organic pollutant, phosphate ore, photodegradation

Procedia PDF Downloads 132
2086 A Design for Supply Chain Model by Integrated Evaluation of Design Value and Supply Chain Cost

Authors: Yuan-Jye Tseng, Jia-Shu Li

Abstract:

To design a product with the given product requirement and design objective, there can be alternative ways to propose the detailed design specifications of the product. In the design modeling stage, alternative design cases with detailed specifications can be modeled to fulfill the product requirement and design objective. Therefore, in the design evaluation stage, it is required to perform an evaluation of the alternative design cases for deciding the final design. The purpose of this research is to develop a product evaluation model for evaluating the alternative design cases by integrated evaluating the criteria of functional design, Kansei design, and design for supply chain. The criteria in the functional design group include primary function, expansion function, improved function, and new function. The criteria in the Kansei group include geometric shape, dimension, surface finish, and layout. The criteria in the design for supply chain group include material, manufacturing process, assembly, and supply chain operation. From the point of view of value and cost, the criteria in the functional design group and Kansei design group represent the design value of the product. The criteria in the design for supply chain group represent the supply chain and manufacturing cost of the product. It is required to evaluate the design value and the supply chain cost to determine the final design. For the purpose of evaluating the criteria in the three criteria groups, a fuzzy analytic network process (FANP) method is presented to evaluate a weighted index by calculating the total relational values among the three groups. A method using the technique for order preference by similarity to ideal solution (TOPSIS) is used to compare and rank the design alternative cases according to the weighted index using the total relational values of the criteria. The final decision of a design case can be determined by using the ordered ranking. For example, the design case with the top ranking can be selected as the final design case. Based on the criteria in the evaluation, the design objective can be achieved with a combined and weighted effect of the design value and manufacturing cost. An example product is demonstrated and illustrated in the presentation. It shows that the design evaluation model is useful for integrated evaluation of functional design, Kansei design, and design for supply chain to determine the best design case and achieve the design objective.

Keywords: design for supply chain, design evaluation, functional design, Kansei design, fuzzy analytic network process, technique for order preference by similarity to ideal solution

Procedia PDF Downloads 318
2085 Multi-Period Supply Chain Design under Uncertainty

Authors: Amir Azaron

Abstract:

In this research, a stochastic programming approach is developed for designing supply chains with uncertain parameters. Demands and selling prices of products at markets are considered as the uncertain parameters. The proposed mathematical model will be multi-period two-stage stochastic programming, which takes into account the selection of retailer sites, suppliers, production levels, inventory levels, transportation modes to be used for shipping goods, and shipping quantities among the entities of the supply chain network. The objective function is to maximize the chain’s net present value. In order to maximize the chain’s NPV, the sum of first-stage investment costs on retailers, and the expected second-stage processing, inventory-holding and transportation costs should be kept as low as possible over multiple periods. The effects of supply uncertainty where suppliers are unreliable will also be investigated on the efficiency of the supply chain.

Keywords: supply chain management, stochastic programming, multiobjective programming, inventory control

Procedia PDF Downloads 296