Search results for: local stakeholders network

Authors: Hafida Ferfera-Harrar, Nacera Aiouaz, Nassima Dairi

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Super absorbents polymers received much attention and are used in many fields because of their superior characters to traditional absorbents, e.g., sponge and cotton. So, it is very important but challenging to prepare highly and fast-swelling super absorbents. A reliable, efficient and low-cost technique for removing heavy metal ions from waste water is the adsorption using bio-adsorbents obtained from biological materials, such as polysaccharides-based hydrogels super absorbents. In this study, novel multi-functional super absorbent composites type semi-interpenetrating polymer networks (Semi-IPNs) were prepared via graft polymerization of acrylamide onto chitosan backbone in presence of gelatin, CTS-g-PAAm/Ge, using potassium persulfate and N,N’ -methylenebisacrylamide as initiator and cross linker, respectively. These hydrogels were also partially hydrolyzed to achieve superabsorbents with ampholytic properties and uppermost swelling capacity. The formation of the grafted network was evidenced by Fourier Transform Infrared Spectroscopy (ATR-FTIR) and thermo gravimetric Analysis (TGA). The porous structures were observed by Scanning Electron Microscope (SEM). From TGA analysis, it was concluded that the incorporation of the Ge in the CTS-g-PAAm network has marginally affected its thermal stability. The effect of gelatin content on the swelling capacities of these super absorbent composites was examined in various media (distilled water, saline and pH-solutions).The water absorbency was enhanced by adding Ge in the network, where the optimum value was reached at 2 wt. % of Ge. Their hydrolysis has not only greatly optimized their absorption capacity but also improved the swelling kinetic. These materials have also showed reswelling ability. We believe that these super-absorbing materials would be very effective for the adsorption of harmful metal ions from waste water.

Keywords: chitosan, gelatin, superabsorbent, water absorbency

Procedia PDF Downloads 457

Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

Procedia PDF Downloads 70

Authors: V. V. Singh, Yusuf Ibrahim Gwanda, Rajesh Prasad

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In this paper, we focus on the reliability and performance analysis of Computer Centre (CC) at Yobe State University, Damaturu, Nigeria. The CC consists of three servers: one database mail server, one redundant and one for sharing with the client computers in the CC (called as a local server). Observing the different possibilities of the functioning of the CC, the analysis has been done to evaluate the various popular measures of reliability such as availability, reliability, mean time to failure (MTTF), profit analysis due to the operation of the system. The system can ultimately fail due to the failure of router, redundant server before repairing the mail server and switch failure. The system can also partially fail when a local server fails. The failed devices have restored according to Least Recently Used (LRU) techniques. The system can also fail entirely due to a cooling failure of the server, electricity failure or some natural calamity like earthquake, fire tsunami, etc. All the failure rates are assumed to be constant and follow exponential time distribution, while the repair follows two types of distributions: i.e. general and Gumbel-Hougaard family copula distribution.

Keywords: reliability, availability Gumbel-Hougaard family copula, MTTF, internet data centre

Procedia PDF Downloads 525

Authors: Marzieh Khezerloo, Lyazid Djenidi

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Owing to wide range of the micro-device applications, the problems of mixing at small scales is of significant interest. Also, because most of the processes produce heat, it is needed to develop and implement strategies for heat removal in these devices. There are many studies which focus on the effect of roughness or suction on heat transfer performance, separately, although it would be useful to take advantage of these two methods to improve heat transfer performance. Unfortunately, there is a gap in this area. The present numerical study is carried to investigate the combined effects of roughness and wall suction on heat transfer performance of a laminar channel flow; suction is applied on the top and back faces of the roughness element, respectively. The study is carried out for different Reynolds numbers, different suction rates, and various locations of suction area on the roughness. The flow is assumed two dimensional, incompressible, laminar, and steady state. The governing Navier-Stokes equations are solved using ANSYS-Fluent 18.2 software. The present results are tested against previous theoretical results. The results show that by adding suction, the local Nusselt number is enhanced in the channel. In addition, it is shown that by applying suction on the bottom section of the roughness back face, one can reduce the thickness of thermal boundary layer, which leads to an increase in local Nusselt number. This indicates that suction is an effective means for improving the heat transfer rate (suction by controls the thickness of thermal boundary layer). It is also shown that the size and intensity of vortical motion behind the roughness element, decreased with an increasing suction rate, which leads to higher local Nusselt number. So, it can be concluded that by using suction, strategically located on the roughness element, one can control both the recirculation region and the heat transfer rate. Further results will be presented at the conference for coefficient of drag and the effect of adding more roughness elements.

Keywords: heat transfer, laminar flow, numerical simulation, roughness, suction

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

Procedia PDF Downloads 116

Authors: M. Boudjerda, B. Touaibia, M. K. Mihoubi

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In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.

Keywords: water management, agricultural demand, dam and reservoir operation, Foum el-Gherza dam, dynamic programming, artificial neural network

Procedia PDF Downloads 110

Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

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Carefully scheduling the operations of pumps can be resulted to significant energy savings. Schedules can be defined either implicit, in terms of other elements of the network such as tank levels, or explicit by specifying the time during which each pump is on/off. In this study, two new explicit representations based on time-controlled triggers were analyzed, where the maximum number of pump switches was established beforehand, and the schedule may contain fewer switches than the maximum. The optimal operation of pumping stations was determined using a Jumping Particle Swarm Optimization (JPSO) algorithm to achieve the minimum energy cost. The model integrates JPSO optimizer and EPANET hydraulic network solver. The optimal pump operation schedule of VanZyl water distribution system was determined using the proposed model and compared with those from Genetic and Ant Colony algorithms. The results indicate that the proposed model utilizing the JPSP algorithm outperformed the others and is a versatile management model for the operation of real-world water distribution system.

Keywords: JPSO, operation, optimization, water distribution system

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Authors: Sofia Dokuka, Liz Lockhart, Alex Furman

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Organizational hierarchy, traditionally composed of individual contributors, middle management, and executives, is enhanced by the understanding of informal social roles. These roles, identified with organizational network analysis (ONA), might have an important effect on organizational functioning. In this paper, we identify three social roles – influencers, bridges, and soloists, and provide empirical analysis based on real-world organizational networks. Influencers are employees with broad networks and whose contacts also have rich networks. Influence is calculated using PageRank, initially proposed for measuring website importance, but now applied in various network settings, including social networks. Influencers, having high PageRank, become key players in shaping opinions and behaviors within an organization. Bridges serve as links between loosely connected groups within the organization. Bridges are identified using betweenness and Burt’s constraint. Betweenness quantifies a node's control over information flows by evaluating its role in the control over the shortest paths within the network. Burt's constraint measures the extent of interconnection among an individual's contacts. A high constraint value suggests fewer structural holes and lesser control over information flows, whereas a low value suggests the contrary. Soloists are individuals with fewer than 5 stable social contacts, potentially facing challenges due to reduced social interaction and hypothetical lack of feedback and communication. We considered social roles in the analysis of real-world organizations (N=1,060). Based on data from digital traces (Slack, corporate email and calendar) we reconstructed an organizational communication network and identified influencers, bridges and soloists. We also collected employee engagement data through an online survey. Among the top-5% of influencers, 10% are members of the Executive Team. 56% of the Executive Team members are part of the top influencers group. The same proportion of top influencers (10%) is individual contributors, accounting for just 0.6% of all individual contributors in the company. The majority of influencers (80%) are at the middle management level. Out of all middle managers, 19% hold the role of influencers. However, individual contributors represent a small proportion of influencers, and having information about these individuals who hold influential roles can be crucial for management in identifying high-potential talents. Among the bridges, 4% are members of the Executive Team, 16% are individual contributors, and 80% are middle management. Predominantly middle management acts as a bridge. Bridge positions of some members of the executive team might indicate potential micromanagement on the leader's part. Recognizing the individuals serving as bridges in an organization uncovers potential communication problems. The majority of soloists are individual contributors (96%), and 4% of soloists are from middle management. These managers might face communication difficulties. We found an association between being an influencer and attitude toward a company's direction. There is a statistically significant 20% higher perception that the company is headed in the right direction among influencers compared to non-influencers (p < 0.05, Mann-Whitney test). Taken together, we demonstrate that considering social roles in the company might indicate both positive and negative aspects of organizational functioning that should be considered in data-driven decision-making.

Keywords: organizational network analysis, social roles, influencer, bridge, soloist

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Authors: Diyaolu Babajide Olufemi, Oyerinde Oyewole Olusesan

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This study examined the effect of sex education training programs on the knowledge and practice of sexual risk behavior among secondary school adolescents in Ibadan North Local Government area of Oyo State. A total of 105 students were sampled from two schools in the Local Government area. Seventy students (70) constituted the experimental group while thirty-five (35) constituted the control group. Pretest-Posttest control group quasi-experimental design was adopted. A self-developed questionnaire was used to test participants’ knowledge and practice of sexual risk behavior before and after the training (α=.62, .82 and .74). Analysis indicated a significant effect of sex education training on participants’ knowledge and practice of sexual risk behavior, a significant gender difference in knowledge of sexual risk behavior but no significant age and gender difference in the practice of sexual risk behavior. It was thus concluded that sex education should be taught in schools and emphasized at homes with no age or gender restrictions.

Keywords: early adolescent, health risk, sexual risk behavior, sex education

Procedia PDF Downloads 136

Authors: Santhosh Kumar Sathi

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In India, Growth and spread of cities lead to the reduction of forests and green areas of the urban center with built structures. This is one of the reasons for increasing temperature about 2-5% in an urban environment and consequently also one of the key causes of urban heat island effects. Green roofs are one option that can reduce the negative impact of urban development providing numerous environmental benefits. In this paper, Vijayawada city is taken as case to study as it is experiencing rapid urbanization because of new capital Amaravati. That has resulted in remarkable urban heat island; which once recorded a highest temperature of 49°c. This paper focuses on the change in quality of the local environment with the introduction of green roofs. An in-depth study has to be carried out to understand the distribution of land surface temperature and land use of Vijayawada. Delineation of an area which has the highest temperature has been selected to adopt green roof retrofitting. Latest technologies of green roof retrofitting have to be implemented in the selected region. The results of the study indicate a significant temperature reduction in the local environment of that region, confirming the potential of green roofs as urban heat island mitigation strategy.

Keywords: energy consumption, green roofs, retrofitting, urban heat island

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Authors: Lyamine Guezouli, Kamel Barka, Zineb Seghir

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Wireless sensor and actor networks (WSANs) present a research challenge for different practice areas. Researchers are trying to optimize the use of such networks through their research work. This optimization is done on certain criteria, such as improving energy efficiency, exploiting node heterogeneity, self-adaptability and self-configuration. In this article, we present our proposal for BIFSA (Biologically-Inspired Framework for Wireless Sensor and Actor networks). Indeed, BIFSA is a middleware that addresses the key issues of wireless sensor and actor networks. BIFSA consists of two types of agents: sensor agents (SA) that operate at the sensor level to collect and transport data to actors and actor agents (AA) that operate at the actor level to transport data to base stations. Once the sensor agent arrives at the actor, it becomes an actor agent, which can exploit the resources of the actors and vice versa. BIFSA allows agents to evolve their genetic structures and adapt to the current network conditions. The simulation results show that BIFSA allows the agents to make better use of all the resources available in each type of node, which improves the performance of the network.

Keywords: wireless sensor and actor networks, self-management, genetic algorithm, agent.

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Authors: Hanadi Al-Mubaraki, Michael Busler

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Both in the developed and developing countries as well as Gulf Cooperation Council (GCC), the small and medium-sized enterprises (SMEs) proven to be main drivers of jobs creation and tools to accelerate economic development and economic diversification. This paper seeks to investigate and identify the strengths and weakness of SME as a veritable tool in economic development. A survey method was used to gather data from 171 SME from Gulf Cooperation Council (GCC). The research methodology uses a quantitative approach (survey) while data were collected with a structured questionnaire and analyzed with several descriptive statistics. The results of the study, therefore, will present sets of the strengths of SME in GCC such as 1) government supported local products (59%), 2) promoting SME local products rather than international products (47%), 3) reduce the legal and administrative procedures of SME establishment (46%) and weakness of SME in GCC such as: 1) lack of funding during the initial phase of the project (46%), 2) lack of liquidity during project continuity (39%), and 3) strong competition in the domestic and global market (38%). The study findings will be guidelines for academia and practitioners such as governments, policymakers, funded organizations, universities and strategic institutions for successful implementation.

Keywords: SME, economic development, GCC, strengths and weaknesses

Procedia PDF Downloads 144

Authors: Long Cheng, Tong He, Iraj Mantegh, Wen-Fang Xie

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Path planning is essential for UAVs (Unmanned Aerial Vehicle) with autonomous navigation in unknown environments. In this paper, an adaptive probabilistic sampling algorithm is proposed for the GPS-denied environment, which can be utilized for autonomous navigation system of multiple UAVs in a dynamically-changing structured environment. This method can be used for Unmanned Aircraft Systems Traffic Management (UTM) solutions and in autonomous urban aerial mobility, where a number of platforms are expected to share the airspace. A path network is initially built off line based on available environment map, and on-board sensors systems on the flying UAVs are used for continuous situational awareness and to inform the changes in the path network. Simulation results based on MATLAB and Gazebo in different scenarios and algorithms performance measurement show the high efficiency and accuracy of the proposed technique in unknown environments.

Keywords: path planning, adaptive probabilistic sampling, obstacle avoidance, multiple unmanned aerial vehicles, unknown environments

Procedia PDF Downloads 152

Authors: Mulu G. Gencha, Gebremedhin Simon, Menna Olango

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This study was conducted at Hawassa University (HwU) in the Southern Nation Nationalities Peoples Regional State (SNNPRS) of Ethiopia. The prime concern of this study was to examine the writing performances of experimental and control group students, perception of experimental group students, and subject instructors. The course was blended learning (BL). Blended learning is a hybrid of classroom and on-line learning. Participants were eighty students from the School of Computer Science. Forty students attended the BL delivery involved using Face-to-Face (FTF) and campus-based online instruction. All instructors, fifty, of School of Language and Communication Studies along with 10 FGD members participated in the study. The experimental group went to the computer lab two times a week for four months, March-June, 2012, using the local area network (LAN), and software (MOODLE) writing program. On the other hand, the control group, forty students, took the FTF writing course five times a week for four months in similar academic calendar. The three instruments, the attitude questionnaire, tests and FGD were designed to identify views of students, instructors, and FGD participants on BL. At the end of the study, students’ final course scores were evaluated. Data were analyzed using independent samples t-tests. A statistically, significant difference was found between the FTF and BL (p<0.05). The analysis showed that the BL group was more successful than the conventional group. Besides, both instructors and students had positive attitude towards BL. The final section of the thesis showed the potential benefits and challenges, considering the pedagogical implications for the BL, and recommended possible avenues for further works.

Keywords: blended learning, computer attitudes, computer usefulness, computer liking, computer confidence, computer phobia

Procedia PDF Downloads 407

Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

Procedia PDF Downloads 53

Authors: Chhabi Paudel

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The food and nutrition security of the people of the mountain of Karnali province of Nepal is dependent on traditional crop biodiversity. The altitude range of the study area is 1800 meters to 2700 meters above sea level. The climate is temperate to alpine. Farmers are adopting subsistent oriented diversified farming systems and selected crop species, cultivars, and local production systems by their own long adaptation mechanism. The major crop species are finger millet, proso millet, foxtail millet, potato, barley, wheat, mountain rice, buckwheat, Amaranths, medicinal plants, and many vegetable species. The genetic and varietal diversity of those underutilized indigenous crops is also very high, which has sustained farming even in uneven climatic events. Biodiversity provides production synergy, inputs, and other agro-ecological services for self-sustainability. But increase in human population and urban accessibility are seen as threats to biodiversity conservation. So integrated conservation measures are suggested, including agro-tourism and other monetary benefits to the farmers who conserve the local biodiversity.

Keywords: crop biodiversity, climate change, in-situ conservation, resilience, sustainability, agrotourism

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Authors: Kidist Mesfin Nguse

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Ethiopia is the second most densely populated nation in Africa, and about 121 million people as the 2022 Ethiopia population live report recorded. In recent years, the Ethiopian government (GOE) has been gradually growing its road network. With 138,127 kilometers (85,825 miles) of all-weather roads as of the end of 2018–19, Ethiopia possessed just 39% of the nation's necessary road network and lacked a well-organized system. The Ethiopian urban population report recorded that about 21% of the population lives in urban areas, and the high population, coupled with growth in various infrastructures, has led to the migration of the workforce from rural areas to cities across the country. In main roads, the heterogeneous traffic flow with various operational features makes it more unfavorable, causing frequent congestion in the stretch of road. The Level of Service (LOS), a qualitative measure of traffic, is categorized based on the operating conditions in the traffic stream. Determining the capacity and LOS for this city is very crucial as this affects the planning and design of traffic systems and their operation, and the allocation of route selection for infrastructure building projects to provide for a considerably good level of service.

Keywords: capacity, level of service, traffic volume, free flow speed

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Authors: L. J. de Bessa Neto, M. R. B. Guerra Vale, F. K. O. M. Varella Guerra

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In recent years, solar energy has established itself as one of the main sources of renewable energy, gaining a large space in electricity generation around the world. However, due to the low performance of photovoltaic panels, technologies need to be sought to maximize the production of electricity. In this regard, the present study aims to develop a prototype of solar tracker for didactics applications, controlled with the Arduino® platform, that enables the movement of photovoltaic plates in relation to the sun positions throughout the day through an electromechanical system, optimizing, thus, the efficiency of solar photovoltaic generation and improvements for the photovoltaic effect. The solar tracking technology developed in this work was presented of the shape oral and practical in two middle schools in the municipality of Mossoró/RN, being one of the public network and other of the private network, always keeping the average age of the students, in the case, around 16 years, contemplating an average of 60 students in each of the visits. Thus, it is concluded that the present study contributed substantially to the dissemination of knowledge concerning the photovoltaic solar generation, as well as the study of solar trackers, thus arousing the interest and curiosity of the students regarding the thematic approached.

Keywords: alternative energy, solar tracker, energy efficiency, photovoltaic panels

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Authors: Navneet Kaur, Amarpreet Singh

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In Vehicular Adhoc Networks, Data Dissemination is a challenging task. There are number of techniques, types and protocols available for disseminating the data but in order to preserve limited bandwidth and to disseminate maximum data over networks makes it more challenging. There are broadcasting, multicasting and geocasting based protocols. Multicasting based protocols are found to be best for conserving the bandwidth. One such protocol named BEAM exists that improves the performance of Vehicular Adhoc Networks by reducing the number of in-network message transactions and thereby efficiently utilizing the bandwidth during an emergency situation. But this protocol may result in multicar chain collision as there was no V2V communication. So, this paper proposes a new protocol named Enhanced Bandwidth Efficient Cluster Based Multicasting Protocol (EBECM) that will overcome the limitations of existing BEAM protocol. And Simulation results will show the improved performance of EBECM in terms of Routing overhead, throughput and PDR when compared with BEAM protocol.

Keywords: BEAM, data dissemination, emergency situation, vehicular adhoc network

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Authors: Muhammad Nasar-u-Minallah, Dagmar Haase, Salman Qureshi

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In a rapidly growing developing country cities are becoming more urbanized leading to modifications in urban climate. Rapid urbanization, especially unplanned urban land expansion, together with climate change has a profound impact on the urban settlement and urban thermal environment. Cities, particularly Pakistan are facing remarkably environmental issues and uneven development, and thus it is important to strengthen the investigation of urban environmental pressure brought by land-use changes and urbanization. The present study investigated the long term modification of the urban environment by urbanization utilizing Spatio-temporal dynamics of land-use change, urban population data, urban heat islands, monthly maximum, and minimum temperature of thirty years, multi remote sensing imageries, and spectral indices such as Normalized Difference Built-up Index and Normalized Difference Vegetation Index. The results indicate rapid growth in an urban built-up area and a reduction in vegetation cover in the last three decades (1990-2020). A positive correlation between urban heat islands and Normalized Difference Built-up Index, whereas a negative correlation between urban heat islands and the Normalized Difference Vegetation Index clearly shows how urbanization is affecting the local environment. The increase in air and land surface temperature temperatures is dangerous to human comfort. Practical approaches, such as increasing the urban green spaces and proper planning of the cities, have been suggested to help prevent further modification of the urban thermal environment by urbanization. The findings of this work are thus important for multi-sectorial use in the cities of Pakistan. By taking into consideration these results, the urban planners, decision-makers, and local government can make different policies to mitigate the urban land use impacts on the urban thermal environment in Pakistan.

Keywords: land use, urban environment, local climate, Lahore

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Authors: Luan Vardari, Dena Arapi Vardari

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The Balkan countries, known for their diverse landscapes and cultural heritage, face the dual challenge of promoting economic growth while addressing pressing environmental concerns. In recent years, the concept of green finance has emerged as a powerful tool to achieve sustainable development and mitigate the environmental impact of various sectors, including architecture. This extended abstract explores the untapped potential of green finance in architecture within the Balkan region and highlights its role in driving sustainable construction practices and fostering a greener future. The abstract begins by defining green finance and emphasizing its relevance in the context of the architectural sector in Balkan countries. It underlines the benefits of green finance, such as economic growth, environmental conservation, and social well-being. Integrating green finance into architectural projects is important as a means to achieve sustainable development goals while promoting financial viability. Also, delves into the current state of green building practices in the Balkan countries and identifies the need for financial support to further drive adoption. It explores the existing regulatory frameworks and policies that promote sustainable architecture and discusses how green finance can complement these initiatives. Unique challenges faced by Balkan countries are highlighted, along with the potential opportunities that green finance presents in overcoming these challenges. We highlight successful sustainable architectural projects in the region to showcase the practical application of green finance in the Balkans. These projects exemplify the effective utilization of green finance mechanisms, resulting in tangible economic and environmental impacts, including job creation, energy efficiency, and reduced carbon emissions. The abstract concludes by identifying replicable models and lessons learned from these projects that can serve as a blueprint for future sustainable architecture initiatives in the Balkans. The importance of collaboration and knowledge sharing among stakeholders is emphasized. Engaging architects, financial institutions, governments, and local communities is crucial to promoting green finance in architecture. The abstract suggests the establishment of knowledge exchange platforms and regional/international networks to foster collaboration and facilitate the sharing of expertise among Balkan countries.

Keywords: sustainable finance, renewable energy, Balkan region, investment opportunities, green infrastructure, ESG criteria, architecture

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Authors: Barry Aifesehi Aiworo, Henry Oriakhi

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This paper, examines the analysis of access pattern to school and travel risks among school children in Benin City, Edo State, Nigeria. The risk includes accident, molestation (sexually) and kidnapping. The objective of this paper are to examine the various means (modes) of transport to school; determine the type and incidences of risk experienced by school children in the study area; examine the risk incidences and ages of school children in the study area. Hypothesis which states that the types of risks encountered by school children are independent of means of transport was tested using the chi-square test (X2). A sampling ratio of twelve percent (12%) was taken from 396 schools in Benin City. By implication, 49 schools were randomly selected in Benin City for this research. A total of 42,053 students in the 49 schools constitute the sample frame for the research. Two percent (2%), 841 students were taken as the sample size. The use of stratified sampling method was applied by stratifying the study area (Benin City) into local governments- Egor, Ikpoba-Okha and Oredo. Thereafter, the lists of schools in the various local governments were obtained from the Ministry of Education before the schools for research were randomly chosen from each local government area. The analysis revealed that 6.7% of the total students interviewed have been involved in road accidents. 1.04% of the total respondents said at one time or the other that they have been kidnapped. Finally, the research found that travel is comparatively safe and believes this may be partly attributable to safer route to schools and school children being more familiar with the school journey. The research indicates that children aged between eleven and fifteen are most at risk of hit or knocked down on Benin City’s roads. These findings may help in planning and targeting road safety initiative (education, campaigns) in Benin City.

Keywords: accident, molestation (sexually), kidnapping, pedophile, pedestrian

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Authors: Darius Phiri, Moses Chibesa, Donald Zulu, Robby Kasubika

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In Zambia, wildlife is co-managed by Zambia Wildlife Authority (ZAWA) and the local communities by sharing management responsibilities and benefits derived from harvesting wildlife resources under a benefit sharing mechanism. Although the benefit sharing mechanism has been formulated under good principles, it is still facing numerous challenges. In response to these challenges, a study on the sustainability of ZAWA benefit sharing mechanism was carried out in order to assess its potential and continuity in line with community empowerment and wildlife resources management. Systematic sampling was used with a sampling intensity of 4% to administer three types of questionnaires to community members in Mumbwa Game Management Area (GMA), ZAWA officers, and to the Ministry of Tourism, Environment and Natural Resources (MTENR) staffs. The collected data was then analysed using SPSS version 16.5. The findings indicated that many people in the GMA do not participate fully because of lacking satisfactory benefits. However, the mechanism contribute to the community well-being and can still remain sustainable especially if measures to address the current challenges are put in place.

Keywords: benefit sharing, concessions, licenses, poaching, local communities, sustainability

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Authors: Arnon Medzini, Lilach Lev Ari

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Migration, the driving force behind increased urbanization, has made cities much more diverse places to live in. Nearly one-fifth of all migrants live in the world’s 20 largest cities. In many of these global cities, migrants constitute over a third of the population. Many of contemporary migrants are in fact ‘forced migrants,’ pushed from their countries of origin due to political or ethnic violence and persecution or natural disasters. During the past decade, massive numbers of labor migrants and asylum seekers have migrated from African countries to Israel via Egypt. Their motives for leaving their countries of origin include ongoing and bloody wars in the African continent as well as corruption, severe conditions of poverty and hunger, and economic and political disintegration. Most of the African migrants came to Israel from Eritrea and Sudan as they saw Israel the closest natural geographic asylum to Africa; soon they found their way to the metropolitan Tel-Aviv area. There they concentrated in poor neighborhoods located in the southern part of the city, where they live under conditions of crowding, poverty, and poor sanitation. Today around 45,000 African migrants reside in these neighborhoods, and yet there is no legal option for expelling them due to dangers they might face upon returning to their native lands. Migration of such magnitude to the weakened neighborhoods of south Tel-Aviv can lead to the destruction of physical, social and human infrastructures. The character of the neighborhoods is changing, and the local population is the main victim. These local residents must bear the brunt of the failure of both authorities and the government to handle the illegal inhabitants. The extremely crowded living conditions place a heavy burden on the dilapidated infrastructures in the weakened areas where the refugees live and increase the distress of the veteran residents of the neighborhoods. Some problems are economic and some stem from damage to the services the residents are entitled to, others from a drastic decline in their standard of living. Even the public parks no longer serve the purpose for which they were originally established—the well-being of the public and the neighborhood residents; they have become the main gathering place for the infiltrators and a center of crime and violence. Based on secondary data analysis (for example: The Israel’s Population, Immigration and Border Authority, the hotline for refugees and migrants), the objective of this presentation is to discuss the effects of forced migration to Tel Aviv on the following tensions: between the local population and the immigrants; between the local population and the state authorities, and between human rights groups vis-a-vis nationalist local organizations. We will also describe the changes which have taken place in the urban infrastructure of the city of Tel Aviv, and discuss the efficacy of various Israeli strategic trajectories when handling human problems arising in the marginal urban regions where the forced migrant population is concentrated.

Keywords: African asylum seekers, forced migrants, marginal urban regions, urban infrastructure

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Authors: Ali Oveysi Sarabi

Abstract:

The dimensions of nanostructures are in the range of inter-atomic spacing of the structures which makes them impossible to be modeled as a continuum. Nanoscale size-effects on vibration analysis of nanobeams embedded in an elastic medium is investigated using different types of beam theory. To this end, Eringen’s nonlocal elasticity is incorporated to various beam theories namely as Euler-Bernoulli beam theory (EBT), Timoshenko beam theory (TBT), Reddy beam theory (RBT), and Levinson beam theory (LBT). The surrounding elastic medium is simulated with both Winkler and Pasternak foundation models and the difference between them is studies. Explicit formulas are presented to obtain the natural frequencies of nanobeam corresponding to each nonlocal beam theory. Selected numerical results are given for different values of the non-local parameter, Winkler modulus parameter, Pasternak modulus parameter and aspect ratio of the beam that imply the effects of them, separately. It is observed that the values of natural frequency are strongly dependent on the stiffness of elastic medium and the value of the non-local parameter and these dependencies varies with the value of aspect ratio and mode number.

Keywords: nanobeams, free vibration, nonlocal elasticity, winkler foundation model, Pasternak foundation model, beam theories

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Authors: Thel Phyu Phyu Soe

Abstract:

Myanmar started its new political movement in 2011, opening up to trade, encouraging foreign investment, deepening its financial sectors. The tourism is one of the key sectors to make reform process from the perspective of green economy and green growth. The Inle Lake, second largest lake, famous for broad diversity of cultural and natural assets, become one of the country’s main tourism destination. In the study area, local livelihoods are based on a combination of farming (mainly floating garden) wage labor, tourism, and small business. But the Inle lake water body or water surface area decreased by 96.44 km² within 20 years, from 67.98 km² in 1990 to 56.63 km² in 2010. Floating garden cultivation (hydro phonic farm) is a distinguished characteristic of Inle Lake. Two adjacent villages (A and B) were selected to compare the relationship between tourism access and agricultural production. Ground truthing, focus group discussion, and in-depth questionnaires with floating gardeners were carried out. In A village, 57% of the respondents relied tourism as their major income sources, while almost all the households in B village relied floating gardens as major livelihood. Both satellite image interpretation and community studies highlighted that around 80% of the floating garden become fallow after severe drought in 2010 and easy income access to tourism related activities. The villagers can get 20-30 US$ for round trip guiding to major tourist attraction places.Even though tourism is the major livelihood options for the A village, the poorest households (less than 1500 US$ per year) are those who didn’t own transportation property for tourism related activities. In B village, more than 70% of the households relied floating gardens as their major income sources and less participated in tourism related activities because they don’t have motorboat stand connected to the major tourist attraction areas. Access to tourism related activities (having boat stand where they can guide tourists by boat and sell local products and souvenirs) have much impacted on changes in local people livelihood options. However, tourism may have impacts that are beneficial for one group of a society, but which are negative for another. Income inequality and negative impacts can only be managed effectively if they have been identified, measured and evaluated. The severe drought in 2010, instability of lake water level, high expenses for agriculture assisted the local people to participate in easy access tourism related activities.

Keywords: diminishing, floating garden, livelihood, tourism-related income

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Authors: Tamás Hartványi, Ferenc Tóth

Abstract:

European telecommunication distribution center performance is measured by service lead time and quality. Operation model is CTO (customized to order) namely, a high mix customization of telecommunication network equipment and parts. CTO operation contains material receiving, warehousing, network and server assembly to order and configure based on customer specifications. Variety of the product and orders does not support mass production structure. One of the success factors to satisfy customer is to have a proper aggregated planning method for the operation in order to have optimized human resources and highly efficient asset utilization. Research will investigate several methods and find proper way to have an order book simulation where practical optimization problem may contain thousands of variables and the simulation running times of developed algorithms were taken into account with high importance. There are two operation research models that were developed, customer demand is given in orders, no change over time, customer demands are given for product types, and changeover time is constant.

Keywords: CTO, aggregated planning, demand simulation, changeover time

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Authors: Huinan Zhang, Wenjie Jiang

Abstract:

Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Bikram Jung Kunwar, Pralhad Kunwor

Abstract:

The Community-Based Forest Management (CBFM) approach is often glorified as the best forest management alternatives in the developing countries. However, how the approach has been understood by the local user households, who implement it is remained unanswered for many planners, policy makers, and sometimes researcher as well. The study attempts to assess the understanding of ecology and economics of CBFM in Nepal, where community forest program has been implemented since the 1970s. In order to understand the impacts of the program, eight criteria and sixteen indicators for ecological conservation and similarly same number of criteria and indicators for socio-economic impacts of the program were designed and compared between before and after the program implementation. The community forestry program has positive effects in forest ecology conservation and at the same time rural livelihood improvement of local people. The study revealed that collective understanding of forest ecology and economics leads the CBFM approach towards the sustainability of the program in a win-win situation. The recommendations of the study are expected to be useful to natural resource managers, planners, and policy makers.

Keywords: community, forest management, ecology, economics, Nepal

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Authors: Hong Su, Qiuju Yan, Wei Du, En Hu, Zhaoyu Yang, Wei Zhang, Yusheng Li, Tao Tang, Wang yang, Shushan Zhao

Abstract:

Osteoarthritis (OA) is a severe chronic inflammatory disease. As the main active component of Astragalus mongholicus Bunge, a classic traditional ethnic herb, calycosin exhibits anti-inflammatory action and its mechanism of exact targets for OA have yet to be determined. In this study, we established an anterior cruciate ligament transection (ACLT) mouse model. Mice were randomized to sham, OA, and calycosin groups. Cartilage synthesis markers type II collagen (Col-2) and SRY-Box Transcription Factor 9 (Sox-9) increased significantly after calycosin gavage. While cartilage matrix degradation index cyclooxygenase-2 (COX-2), phosphor-epidermal growth factor receptor (p-EGFR), and matrix metalloproteinase-9 (MMP9) expression were decreased. With the help of network pharmacology and molecular docking, these results were confirmed in chondrocyte ATDC5 cells. Our results indicated that the calycosin treatment significantly improved cartilage damage, this was probably attributed to reversing the imbalance between chondrocyte synthesis and catabolism.

Keywords: calycosin, osteoarthritis, network pharmacology, molecular docking, inflammatory, cyclooxygenase 2

Procedia PDF Downloads 96