Search results for: social network dynamics

Authors: Divvela Vishnu Sai Kumar, Deepak Arora, Sheenu Rizvi

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Forecasting a cyclone through satellite images consists of the estimation of the intensity of the cyclone and predicting it before a cyclone comes. This research work can help people to take safety measures before the cyclone comes. The prediction of the intensity of a cyclone is very important to save lives and minimize the damage caused by cyclones. These cyclones are very costliest natural disasters that cause a lot of damage globally due to a lot of hazards. Authors have proposed five different CNN (Convolutional Neural Network) models that estimate the intensity of cyclones through INSAT-3D IR images. There are a lot of techniques that are used to estimate the intensity; the best model proposed by authors estimates intensity with a root mean squared error (RMSE) of 10.02 kts.

Keywords: estimating cyclone intensity, deep learning, convolution neural network, prediction models

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Authors: L. Totladze

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The role of financial sector in supporting economic growth and development is well acknowledged. The term spread (the difference between the yields on long-term and short-term Treasury securities) has been found useful for predicting economic variables as output growth, inflation, industrial production, consumption. The temp spread is one of the leading economic indicators according to NBER methodology. Leading economic indicators are widely used in forecasting of economic activity. Many empirical studies find that the term spread predicts future economic activity. The article shortly explains how the term spread might predict future economic activity. This paper analyses the dynamics of the spread between short and long-term interest rates in countries with transition economies. The research paper analyses term spread dynamics in Georgia and compare it with post-communist countries and transition economies spread dynamics. In Georgia, the banking sector plays an important and dominant role in the financial sector, especially with respect to the mobilization of savings and provision of credit and may impact on economic activity. For this purpose, we study the impact of the term spread on economic growth in Georgia.

Keywords: forecasting, leading economic indicators, term spread, transition economies

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Authors: Zohreh Moghaddas, Morteza Yazdani, Farhad Hosseinzadeh

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Nowadays, data envelopment analysis (DEA) models featuring network structures have gained widespread usage for evaluating the performance of production systems and activities (Decision-Making Units (DMUs)) across diverse fields. By examining the relationships between the internal stages of the network, these models offer valuable insights to managers and decision-makers regarding the performance of each stage and its impact on the overall network. To further empower system decision-makers, the inverse data envelopment analysis (IDEA) model has been introduced. This model allows the estimation of crucial information for estimating parameters while keeping the efficiency score unchanged or improved, enabling analysis of the sensitivity of system inputs or outputs according to managers' preferences. This empowers managers to apply their preferences and policies on resources, such as inputs and outputs, and analyze various aspects like production, resource allocation processes, and resource efficiency enhancement within the system. The results obtained can be instrumental in making informed decisions in the future. The top result of this study is an analysis of infeasibility and incorrect estimation that may arise in the theory and application of the inverse model of data envelopment analysis with network structures. By addressing these pitfalls, novel protocols are proposed to circumvent these shortcomings effectively. Subsequently, several theoretical and applied problems are examined and resolved through insightful case studies.

Keywords: inverse models of data envelopment analysis, series network, estimation of inputs and outputs, efficiency, resource allocation, sensitivity analysis, infeasibility

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Authors: Van-Thanh Ho, Jaiyoung Ryu

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In soft robotics, the optimization of fluid dynamics through pneumatic methods plays a pivotal role in enhancing operational efficiency and reducing energy loss. This is particularly crucial when replacing conventional techniques such as cable-driven electromechanical systems. The pneumatic model employed in this study represents a sophisticated framework designed to efficiently channel pressure from a high-pressure reservoir to various muscle locations on the robot's body. This intricate network involves a branching system of tubes. The study introduces a comprehensive pneumatic model, encompassing the components of a reservoir, tubes, and Pneumatically Actuated Muscles (PAM). The development of this model is rooted in the principles of shock tube theory. Notably, the study leverages experimental data to enhance the understanding of the interplay between the PAM structure and the surrounding fluid. This improved interactive approach involves the use of morphing motion, guided by a contraction function. The study's findings demonstrate a high degree of accuracy in predicting pressure distribution within the PAM. The model's predictive capabilities ensure that the error in comparison to experimental data remains below a threshold of 10%. Additionally, the research employs a machine learning model, specifically a surrogate model based on the Kriging method, to assess and quantify uncertainty factors related to the initial reservoir pressure and tube diameter. This comprehensive approach enhances our understanding of pneumatic soft robotics and its potential for improved operational efficiency.

Keywords: pneumatic artificial muscles, pressure drop, morhing motion, branched network, surrogate model

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Authors: Lata Shakya, Toshio Otsuki, Saori Imoto, Bijaya Krishna Shrestha, Umesh Bahadur Malla

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2015 Gorkha Nepal earthquake have damaged the human settlements in 14 districts of Nepal. Historic core areas of three principal cities namely Kathmandu, Lalitpur and Bhaktapur including numerous traditional ‘newari’ settlements in the peripheral areas have been either collapsed or severely damaged. Despite Government of Nepal and (international) non-government organisations’ attempt towards disaster risk management through the preparation of policies and guidelines and implementation of community-based activities, the recent ‘Gorkha’ earthquake has demonstrated the inadequate preparedness, poor implementation of a legal instrument, resource constraints, and managerial weakness. However, the social capital through community based institutions, self-help attitude, and community bond has helped a lot not only in rescue and relief operation but also in a post-disaster temporary shelter living thereby exhibiting the resilient power of the local community. Conducting a detailed case study of ‘Kaminani’ community with 42 houses at ward no. 16 of Bhaktapur municipality, this paper analyses the local community’s response and activities on the Gorkha earthquake in rescue and relief operation as well as in post disaster work. Leadership, the existence of internal/external aid, physical and human support are also analyzed. Social resource and networking are also explained through critical review of the existing community organisation and their activities. The research methodology includes literature review, field survey, and interview with community leaders and residents based on a semi-structured questionnaire. The study reveals that community carried their recovery process in four different phases: (i) management of emergency evacuation, (ii) constructing community owed temporary shelter for individuals, (iii) demolishing upper floors of the damaged houses, and (iv) planning for collaborative housing reconstruction. As territorial based organization, religion based agency and aim based institution exist in the survey area from pre-disaster time, it can be assumed that the community activists including leaders are well experienced to create aim-based group and manage teamwork to deal with various issues and problems collaboratively. Physical and human support including partial financial aid from external source as a result of community leader’s personal networking is extended to the community members. Thus, human/social resource and personal/social network play a crucial role in the recovery process. And to build such social capital, community should have potential from pre-disaster time.

Keywords: Gorkha Nepal earthquake, local community, recovery process, social resource, social network

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Authors: Cristian Pauna

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Trading the financial markets is a widespread activity today. A large number of investors, companies, public of private funds are buying and selling every day in order to make profit. Algorithmic trading is the prevalent method to make the trade decisions after the electronic trading release. The orders are sent almost instantly by computers using mathematical models. This paper will present a price prediction methodology based on a multi-dimensional neural network. Using the Fisher transform, the neural network will be instructed for a low-latency auto-adaptive process in order to predict the price evolution for the next period of time. The model is designed especially for algorithmic trading and uses the real-time price series. It was found that the characteristics of the Fisher function applied at the nodes scale level can generate reliable trading signals using the neural network methodology. After real time tests it was found that this method can be applied in any timeframe to trade the financial markets. The paper will also include the steps to implement the presented methodology into an automated trading system. Real trading results will be displayed and analyzed in order to qualify the model. As conclusion, the compared results will reveal that the neural network methodology applied together with the Fisher transform at the nodes level can generate a good price prediction and can build reliable trading signals for algorithmic trading.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, neural network

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Authors: Tesfaw Belayneh Abebe

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Integrating low-altitude earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs) within a non-terrestrial network (NTN) with the assistance of reconfigurable intelligent surfaces (RIS), we investigate the problem of how to enhance throughput through integrated LEO satellites and UAVs with the assistance of RIS. We propose a method to jointly optimize the associations with the LEO satellite, the 3D trajectory of the UAV, and the phase shifts of the RIS to maximize communication throughput for RIS-assisted integrated LEO satellite and UAV-enabled wireless communications, which is challenging due to the time-varying changes in the position of the LEO satellite, the high mobility of UAVs, an enormous number of possible control actions, and also the large number of RIS elements. Utilizing a multi-agent double deep Q-network (MADDQN), our approach dynamically adjusts LEO satellite association, UAV positioning, and RIS phase shifts. Simulation results demonstrate that our method significantly outperforms baseline strategies in maximizing throughput. Lastly, thanks to the integrated network and the RIS, the proposed scheme achieves up to 65.66x higher peak throughput and 25.09x higher worst-case throughput.

Keywords: integrating low-altitude earth orbit (LEO) satellites, unmanned aerial vehicles (UAVs) within a non-terrestrial network (NTN), reconfigurable intelligent surfaces (RIS), multi-agent double deep Q-network (MADDQN)

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Authors: Andra Blumberga, Uldis Bariss, Anna Kubule, Dagnija Blumberga

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European Union Energy Efficiency Directive provides a set of binding energy efficiency measures to reach. Each of the member states can use either energy efficiency obligation scheme or alternative policy measures or combination of both. Latvian government has decided to divide savings among obligation scheme (65%) and alternative measures (35%). This decision might lead to significant energy tariff increase hence impact on the national economy. To assess impact of alternative policy measures focusing on energy management scheme based on ISO 50001 and ability to decrease share of obligation scheme a System Dynamics modeling was used. Simulation results show that energy efficiency goal can be met with alternative policy measure to large energy consumers in industrial, tertiary and public sectors by applying the energy tax exemption for implementers of energy management system. A delay in applying alternative policy measures plays very important role in reaching the energy efficiency goal. One year delay in implementation of this policy measure reduces cumulative energy savings from 2016 to 2017 from 5200 GWh to 3000 GWh in 2020.

Keywords: system dynamics, energy efficiency, policy measure, energy management system, obligation scheme

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Authors: Semanur Savruk, Onur Akbatı

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Integration of various communication protocols into an automation system causes a rise in setup and maintenance cost and make to control network devices in difficulty. The gateway becomes necessary for reducing complexity in network topology. In this study, Modbus RTU/Modbus TCP industrial ethernet gateway design and implementation are presented with ARM embedded system and FreeRTOS real-time operating system. The Modbus gateway can perform communication with Modbus RTU and Modbus TCP devices over itself. Moreover, the gateway can be adjustable with the user-interface application or messaging interface. Conducted experiments and the results are presented in the paper. Eventually, the proposed system is a complete, low-cost, real-time, and user-friendly design for monitoring and setting devices and useful for meeting remote control purposes.

Keywords: gateway, industrial communication, modbus, network

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Authors: Apisaraporn Baicharoen, Prapasiri Pongprayoon

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Betaine aldehyde dehydrogenase 2 (BADH2) is an enzyme that inhibits the accumulation of 2-acetyl-1-pyrroline (2AP), a potent flavor compound in rice fragrance. BADH2 contains three domains (NAD-binding, substrate-binding, and oligomerization domains). It catalyzes the oxidation of amino aldehydes. The lack of BADH2 results in the formation of 2AP and consequently an increase in rice fragrance. To date, inadequate data on BADH2 structure and function are available. An insight into the nature of BADH2 can serve as one of key starting points for the production of high quality fragrant rice. In this study, we therefore constructed the homology model of BADH2 and employed 500-ns Molecular Dynamics simulations (MD) to primarily understand the structural and dynamic properties of BADH2. Initially, Ramachandran plot confirms the good quality of modeled protein structure. Principle Component Analysis (PCA) was also calculated to capture the protein dynamics. Among 3 domains, the results show that NAD binding site is found to be more flexible. Moreover, interactions from key amino acids (N162, E260, C294, and Y419) that are crucial for function are investigated.

Keywords: betaine aldehyde dehydrogenase 2, fragrant rice, homology modeling, molecular dynamics simulations

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Authors: Luna Moni Das

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This paper is an attempt to study the channel dynamics in the area bounded by the foothills of the eastern Himalayas in the north, the Brahmaputra in the south and southeast and eastern side and the Subansiri River in the west. There are many streams in this region and only a few are perennial. There are two major anabranches of the Brahmaputra called Kharkutia Xuti and Charikoria. All of these makes it a very dynamic area. The analysis done in this paper is based on the remote sensing data and mapping of the channel planforms in GIS environment. The temporal trend of the change in channel planform has been produced. This study shows that, during the period from 1973 to 2013, the streams/rivers originating in the north have experienced a reduction in the total length. The other most important result is that even though the western edge of Majuli Island is eroding faster there is a formation of a larger island in between Charikoria and Brahmaputra, that comprises of Majuli island and parts of Dhakuakhana subdivision of Lakhimpur District along the south of Charikoria river. The field study shows that the Kharkutia Xuti, that divides Majuli from Dhakuakhana, do not experience any flow from the Brahmaputra for the major portion of the year and Charikoria has developed as a major anabranch of the Brahmaputra.

Keywords: channel dynamics, Brahmaputra river, Majuli Island, sinuosity

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Authors: Lanlan Xiao, Yang Liu, Shuo Chen, Bingmei Fu

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Most cancer-related deaths are due to metastasis. Metastasis is a complex, multistep processes including the detachment of cancer cells from the primary tumor and the migration to distant targeted organs through blood and/or lymphatic circulations. During hematogenous metastasis, the emigration of tumor cells from the blood stream through the vascular wall into the tissue involves arrest in the microvasculature, adhesion to the endothelial cells forming the microvessel wall and transmigration to the tissue through the endothelial barrier termed as extravasation. The narrow slit between endothelial cells that line the microvessel wall is the principal pathway for tumor cell extravasation to the surrounding tissue. To understand this crucial step for tumor hematogenous metastasis, we used Dissipative Particle Dynamics method to investigate an individual cell passing through a narrow slit numerically. The cell membrane was simulated by a spring-based network model which can separate the internal cytoplasm and surrounding fluid. The effects of the cell elasticity, cell shape and cell surface area increase, and slit size on the cell transmigration through the slit were investigated. Under a fixed driven force, the cell with higher elasticity can be elongated more and pass faster through the slit. When the slit width decreases to 2/3 of the cell diameter, the spherical cell becomes jammed despite reducing its elasticity modulus by 10 times. However, transforming the cell from a spherical to ellipsoidal shape and increasing the cell surface area only by 3% can enable the cell to pass the narrow slit. Therefore the cell shape and surface area increase play a more important role than the cell elasticity in cell passing through the narrow slit. In addition, the simulation results indicate that the cell migration velocity decreases during entry but increases during exit of the slit, which is qualitatively in agreement with the experimental observation.

Keywords: dissipative particle dynamics, deformability, surface area increase, cell migration

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Authors: Gurmail Singh

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Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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Authors: Shokoufeh Monjezi Kouchak

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Cognitive radio network (CRN) is future network .Without this network wireless devices can’t work appropriately in the next decades. Today, wireless devices use static spectrum access methods and these methods don’t use spectrums optimum so we need use dynamic spectrum access methods to solve shortage spectrum challenge and CR is a great device for DSA but first of all its challenges should be solved .security is one of these challenges .In this paper we provided a survey about CR security. You can see this survey in tables 1 to 7 .After that we proposed a multi criteria authentication method in CRN. Our criteria in this method are: sensing results, following sending data rules, position of secondary users and no talk zone. Finally we compared our method with other authentication methods.

Keywords: authentication, cognitive radio, security, radio networks

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Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

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Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD

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Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

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In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

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Authors: Susan P. Teru, Jerome Nyameh

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Many contemporary organizations are placing a greater emphasis on business enterprise systems as a means of generating higher levels of economic development. Many business research and literature has also concur that enterprise drive economic development, giving little or no credit to social enterprise, whose profit is reinvest to the community development compare to the business enterprise that share their profit to shareholders. Economic development includes economic policies that affect the beneficiaries of the economic entity. We suggest that producing social enterprise increments may be best achieved by orienting social enterprise entrepreneurs system to promote economic development. To this end, we describe a new approach to the social enterprise process that includes social entrepreneur and the key drivers of economic development at each stage. We present a model of social enterprise that incorporates the main ideas of the paper and suggests a new perspective for thinking about how to foster and manage social enterprise to achieve high levels of economic development.

Keywords: social enterprise, economic development, Nigeria, business and management

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Authors: Mohammad Mehdizadeh, Sara Miri

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In today's world, competition is one of the essential components of different markets. Therefore, in addition to economic factors, social factors can also affect the development and prosperity of businesses. In this regard, social networks are of particular importance and play a critical role in the flourishing and development of Internet businesses. The purpose of this article is to investigate the effect of different social networks in promoting digital entrepreneurship. The research method is the descriptive survey. The results show that social networks have a positive and significant impact on digital entrepreneurship development. Among the social networks studied, Instagram and Facebook have the most positive effect on digital entrepreneurship.

Keywords: entrepreneurship, Facebook, Instagram, social media

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Authors: Manoj Kumar Dutta

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Wavelength division multiplexing (WDM) technology is the most promising technology for the proper utilization of huge raw bandwidth provided by an optical fiber. One of the key problems in implementing the all-optical WDM network is the packet contention. This problem can be solved by several different techniques. In time domain approach the packet contention can be reduced by incorporating fiber delay lines (FDLs) as optical buffer in the switch architecture. Different types of buffering architectures are reported in literatures. In the present paper a comparative performance analysis of three most popular FDL architectures are presented in order to obtain the best contention resolution performance. The analysis is further extended to consider the effect of different fiber non-linearities on the network performance.

Keywords: WDM network, contention resolution, optical buffering, non-linearity, throughput

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Authors: Kamel Allaw, Jocelyne Adjizian Gerard, Makram Chehayeb, Nada Badaro Saliba

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In developing countries, such as Lebanon, the demographic data are hardly available due to the absence of the mechanization of population system. The aim of this study is to evaluate, using only remote sensing data, the correlations between the number of population and the characteristics of roads network (length of primary roads, length of secondary roads, total length of roads, density and percentage of roads and the number of intersections). In order to find the influence of the different factors on the demographic data, we studied the degree of correlation between each factor and the number of population. The results of this study have shown a strong correlation between the number of population and the density of roads and the number of intersections.

Keywords: population, road network, statistical correlations, remote sensing

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Authors: Gunasekaran Raja, Ramkumar Jayaraman

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In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing

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Authors: Sheng-Tse Wu, Wu-Sung Yao

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In this paper, a drift assist control system is proposed for remote control (RC) cars to get the perfect drift angle. A steering servo control scheme is given powerfully to assist the drift driving. A gyroscope sensor is included to detect the machine's tail sliding and to achieve a better automatic counter-steering to prevent RC car from spinning. To analysis tire traction and vehicle dynamics is used to obtain the dynamic track of RC cars. It comes with a control gain to adjust counter-steering amount according to the sensor condition. An illustrated example of 1:10 RC drift car is given and the real-time control algorithm is realized by Arduino Uno.

Keywords: drift assist control system, remote control cars, gyroscope, vehicle dynamics

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Authors: Lim Teck Beng, Thiha Kyaw, Poh Boon Kiat, Lee Ngai Meng

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This work presents discussion on the possibility of merging two emerging technologies in microwave; wireless power transfer (WPT) and RF energy harvesting. The current state of art of the two technologies is discussed and the strength and weakness of the two technologies is also presented. The equivalent circuit of wireless power transfer is modeled and explained as how the range and efficiency can be further increased by controlling certain parameters in the receiver. The different techniques of harvesting the RF energy from the ambient are also extensive study. Last but not least, we demonstrate that a low power wireless sensor network (WSN) can be power up by RF energy harvesting. The WSN is designed to transmit every 3 minutes of information containing the temperature of the environment and also the voltage of the node. One thing worth mention is both the sensors that are used for measurement are also powering up by the RF energy harvesting system.

Keywords: energy harvesting, wireless power transfer, wireless sensor network and magnetic coupled resonator

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Authors: Homa Hedayat

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In the dynamic urban landscape of Toronto, the concept of belonging assumes paramount importance. As global challenges—such as the pandemic, financial instability, and geopolitical shifts—reshape our world, understanding how different generations of immigrants establish connections within this multicultural metropolis becomes increasingly vital. Our research delves into forming a sense of belonging in urban spaces, specifically focusing on the experiences of Iranian immigrants residing in Toronto. By examining their perceptions of public places, attachment to residential neighborhoods, and the impact of the urban environment, we contribute to a more holistic understanding of social sustainability and community well-being. We unravel the intricate interplay between individual characteristics, housing context, and neighborhood dynamics through qualitative interviews and a quantitative survey. This research presents a study of the perception of public places and sense of belonging in residential neighbourhoods by younger and older Iranian immigrants living in the Toronto metropolitan area. Few works in the existing literature have investigated the relationship immigrants develop with the shared spaces of the city and their residential environment and how that relationship can impact the development of a ‘sense of belonging’ in the city. Ultimately, our findings pave the way for inclusive and cohesive urban environments, fostering connections across generations and enhancing Toronto’s resilience and harmony. As Toronto continues to evolve, nurturing a sense of belonging becomes paramount. Our research emphasizes the importance of social cohesion and community well-being. By fostering connections across generations, we pave the way for a more resilient and harmonious city.

Keywords: sense of belonging, multigenerational, urban spaces, social sustainability

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Authors: Revalin Herdianto

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Recent climate changes increase uncertainties in vegetation conditions such as health and biomass globally and locally. The detection is, however, difficult due to the spatial and temporal scale of vegetation coverage. Due to unique vegetation response to its environmental conditions such as water availability, the interplay between vegetation dynamics and hydrologic conditions leave a signature in their feedback relationship. Vegetation indices (VI) depict vegetation biomass and photosynthetic capacity that indicate vegetation dynamics as a response to variables including hydrologic conditions and microclimate factors such as rainfall characteristics and land surface temperature (LST). It is hypothesized that the signature may be depicted by VI in its relationship with other variables. To study this signature, several catchments in Asia, Australia, and Indonesia were analysed to assess the variations in hydrologic characteristics with vegetation types. Methods used in this study includes geographic identification and pixel marking for studied catchments, analysing time series of VI and LST of the marked pixels, smoothing technique using Savitzky-Golay filter, which is effective for large area and extensive data. Time series of VI, LST, and rainfall from satellite and ground stations coupled with digital elevation models were analysed and presented. This study found that the hydrologic response of vegetation to rainfall variations may be shown in one hydrologic year, in which a drought event can be detected a year later as a suppressed growth. However, an annual rainfall of above average do not promote growth above average as shown by VI. This technique is found to be a robust and tractable approach for assessing catchment dynamics in changing climates.

Keywords: vegetation indices, land surface temperature, vegetation dynamics, catchment

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Authors: Jesus David Argueta Moreno, Justa Rufina Martel, Edith Gabriela Carrasco

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The Central American Coffee small, medium, and large corporations search for excellence, sustainability, and continuous improvement, triggers in a still unknown scale the Local expansion, crusading, and franchising strategies towards a more suitable commercial opportunity, where the dynamics of the Central American business displacement can be explained through the markets permeability traits. By considering the previously mentioned, the present study aims to evaluate the franchising potentialities offered by Central American Coffee business scenario, in order to explain dynamics of the business demography phenomena and its relevance on the Central American competitiveness landscape.

Keywords: competitiveness, franchising, business demography, Central American Coffee

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Authors: P. R. Dushantha Chaminda, Peng Kai

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In this review paper, we enclose the thought of wireless ad hoc networks and particularly mobile ad hoc network (MANET), their field of study, intention, concern, benefit and disadvantages, modifications, with relation of AODV routing protocol. Mobile computing is developing speedily with progression in wireless communications and wireless networking protocols. Making communication easy, we function most wireless network devices and sensor networks, movable, battery-powered, thus control on a highly constrained energy budget. However, progress in battery technology presents that only little improvements in battery volume can be expected in the near future. Moreover, recharging or substitution batteries is costly or unworkable, it is preferable to support energy waste level of devices low.

Keywords: wireless ad hoc network, energy efficient routing protocols, AODV, EOAODV, AODVEA, AODVM, AOMDV, FF-AOMDV, AOMR-LM

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Authors: Misagh Faezipour

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This paper explores the effects of screen time on children from a systems engineering perspective. We reviewed literature from several related works on the effects of screen time on children to explore all factors and interrelationships that would impact children that are subjected to using long screen times. Factors such as kids' age, parent attitudes, parent screen time influence, amount of time kids spend with technology, psychosocial and physical health outcomes, reduced mental imagery, problem-solving and adaptive thinking skills, obesity, unhealthy diet, depressive symptoms, health problems, disruption in sleep behavior, decrease in physical activities, problematic relationship with mothers, language, social, emotional delays, are examples of some factors that could be either a cause or effect of screen time. A systems engineering perspective is used to explore all the factors and factor relationships that were discovered through literature. A causal model is used to illustrate a graphical representation of these factors and their relationships. Through the causal model, the factors with the highest impacts can be realized. Future work would be to develop a system dynamics model to view the dynamic behavior of the relationships and observe the impact of changes in different factors in the model. The different changes on the input of the model, such as a healthier diet or obesity rate, would depict the effect of the screen time in the model and portray the effect on the children’s health and other factors that are important, which also works as a decision support tool.

Keywords: children, causal model, screen time, systems engineering, system dynamics

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Authors: John Pomerat, Aviv Segev

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Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.

Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning

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Authors: Yossiri Ariyakul, Piyakiat Insom, Poonyawat Sangiamkulthavorn, Takamichi Nakamoto

Abstract:

In this paper, the method of optimization algorithm for sensor network comprised of movable sensor nodes which can be used for odor source localization was proposed. A sensor node is composed of an odor sensor, an anemometer, and a wireless communication module. The odor intensity measured from the sensor nodes are sent to the processor to perform the localization based on optimization algorithm by which the odor source localization map is obtained as a result. The map can represent the exact position of the odor source or show the direction toward it remotely. The proposed method was experimentally validated by creating the odor source localization map using three, four, and five sensor nodes in which the accuracy to predict the position of the odor source can be observed.

Keywords: odor sensor, odor source localization, optimization, sensor network

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