Search results for: social network ties
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13666

Search results for: social network ties

11986 Effect of Social Stress on Behavioural and Physiological Responses and its Assessment by non-Invasive Method in Zebu Cattle

Authors: Baishali Deb, Hari Om Pandey, Shrilla Elangbam, Mukesh Singh, Ayon Tarafdar, A. K. S. Tomar, A. K. Pandey, Triveni Dutt

Abstract:

The goal of the present investigation was to determine the impact of social stress on behavioural characteristics, physiological responses, and haemato-biochemical indicators under various social environments in Tharparkar cattle. Serum cortisol and faecal cortisol metabolites analysis were used to determine the stress level of Tharparkar cattle. Social isolation and social mixing were the two different social circumstances used to evaluate the animals. In both the experiments i.e., social isolation and social mixing, the lying period of animals decreased significantly (p<0.05) while standing period significantly (p<0.05) increased. Frequency and duration of activities like idling, walking, exploration, oral manipulation, and elimination increased significantly (p<0.05) in Tharparkar cattle after being subjected to social isolation and social mixing. Time spent in grooming (self-grooming and allo-grooming) in respect to social isolation significantly increased during isolation and post-reunion, whereas there was a significant (p<0.05) decline in the grooming behaviour especially allo-grooming during mixing of the animals. Feeding and rumination time also decreased significantly (p<0.05) in animals during both the experiments. Physiological parameters such as respiration rate, heart rate and pulse rate increased during the treatment periods. There was no significant difference in the haematological parameters for both the experiments. There was significant (p<0.05) increase in serum cortisol and faecal cortisol metabolites (FCM) concentration in animals subjected to social stress. Therefore, it can be concluded that social stress strongly impacts the behaviour and physiological parameters of the animals, causing stress and nervousness, proving that social stress is a valid psychological stress in animals. The higher concentration of FCM in Tharparkar cattle subjected to social stress, further supported by higher serum cortisol and behaviour manifestations, suggest that FCM could be used to assess stress response as a non-invasive method.

Keywords: social stress, fecal cortisol metabolites, non-invasive, animal welfare, behaviour

Procedia PDF Downloads 113
11985 Advancing Customer Service Management Platform: Case Study of Social Media Applications

Authors: Iseoluwa Bukunmi Kolawole, Omowunmi Precious Isreal

Abstract:

Social media has completely revolutionized the ways communication used to take place even a decade ago. It makes use of computer mediated technologies which helps in the creation of information and sharing. Social media may be defined as the production, consumption and exchange of information across platforms for social interaction. The social media has become a forum in which customer’s look for information about companies to do business with and request answers to questions about their products and services. Customer service may be termed as a process of ensuring customer’s satisfaction by meeting and exceeding their wants. In delivering excellent customer service, knowing customer’s expectations and where they are reaching out is important in meeting and exceeding customer’s want. Facebook is one of the most used social media platforms among others which also include Twitter, Instagram, Whatsapp and LinkedIn. This indicates customers are spending more time on social media platforms, therefore calls for improvement in customer service delivery over the social media pages. Millions of people channel their issues, complaints, complements and inquiries through social media. This study have being able to identify what social media customers want, their expectations and how they want to be responded to by brands and companies. However, the applied research methodology used in this paper was a mixed methods approach. The authors of d paper used qualitative method such as gathering critical views of experts on social media and customer relationship management to analyse the impacts of social media on customer's satisfaction through interviews. The authors also used quantitative such as online survey methods to address issues at different stages and to have insight about different aspects of the platforms i.e. customer’s and company’s perception about the effects of social media. Thereby exploring and gaining better understanding of how brands make use of social media as a customer relationship management tool. And an exploratory research approach strategy was applied analysing how companies need to create good customer support using social media in order to improve good customer service delivery, customer retention and referrals. Therefore many companies have preferred social media platform application as a medium of handling customer’s queries and ensuring their satisfaction, this is because social media tools are considered more transparent and effective in its operations when dealing with customer relationship management.

Keywords: brands, customer service, information, social media

Procedia PDF Downloads 268
11984 Systematic Examination of Methods Supporting the Social Innovation Process

Authors: Mariann Veresne Somosi, Zoltan Nagy, Krisztina Varga

Abstract:

Innovation is the key element of economic development and a key factor in social processes. Technical innovations can be identified as prerequisites and causes of social change and cannot be created without the renewal of society. The study of social innovation can be characterised as one of the significant research areas of our day. The study’s aim is to identify the process of social innovation, which can be defined by input, transformation, and output factors. This approach divides the social innovation process into three parts: situation analysis, implementation, follow-up. The methods associated with each stage of the process are illustrated by the chronological line of social innovation. In this study, we have sought to present methodologies that support long- and short-term decision-making that is easy to apply, have different complementary content, and are well visualised for different user groups. When applying the methods, the reference objects are different: county, district, settlement, specific organisation. The solution proposed by the study supports the development of a methodological combination adapted to different situations. Having reviewed metric and conceptualisation issues, we wanted to develop a methodological combination along with a change management logic suitable for structured support to the generation of social innovation in the case of a locality or a specific organisation. In addition to a theoretical summary, in the second part of the study, we want to give a non-exhaustive picture of the two counties located in the north-eastern part of Hungary through specific analyses and case descriptions.

Keywords: factors of social innovation, methodological combination, social innovation process, supporting decision-making

Procedia PDF Downloads 155
11983 On-Road Text Detection Platform for Driver Assistance Systems

Authors: Guezouli Larbi, Belkacem Soundes

Abstract:

The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.

Keywords: text detection, CNN, PZM, deep learning

Procedia PDF Downloads 83
11982 A Propose of Personnel Assessment Method Including a Two-Way Assessment for Evaluating Evaluators and Employees

Authors: Shunsuke Saito, Kazuho Yoshimoto, Shunichi Ohmori, Sirawadee Arunyanart

Abstract:

In this paper, we suggest a mechanism of assessment that rater and Ratee (or employees) to convince. There are many problems exist in the personnel assessment. In particular, we were focusing on the three. (1) Raters are not sufficiently recognized assessment point. (2) Ratee are not convinced by the mechanism of assessment. (3) Raters (or Evaluators) and ratees have empathy. We suggest 1: Setting of "understanding of the assessment points." 2: Setting of "relative assessment ability." 3: Proposal of two-way assessment mechanism to solve these problems. As a prerequisite, it is assumed that there are multiple raters. This is because has been a growing importance of multi-faceted assessment. In this model, it determines the weight of each assessment point evaluators by the degree of understanding and assessment ability of raters and ratee. We used the ANP (Analytic Network Process) is a theory that an extension of the decision-making technique AHP (Analytic Hierarchy Process). ANP can be to address the problem of forming a network and assessment of Two-Way is possible. We apply this technique personnel assessment, the weights of rater of each point can be reasonably determined. We suggest absolute assessment for Two-Way assessment by ANP. We have verified that the consent of the two approaches is higher than conventional mechanism. Also, human resources consultant we got a comment about the application of the practice.

Keywords: personnel evaluation, pairwise comparison, analytic network process (ANP), two-ways

Procedia PDF Downloads 382
11981 ZigBee Wireless Sensor Nodes with Hybrid Energy Storage System Based on Li-Ion Battery and Solar Energy Supply

Authors: Chia-Chi Chang, Chuan-Bi Lin, Chia-Min Chan

Abstract:

Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries. In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system.

Keywords: ZigBee, Li-ion battery, solar panel, CC2530

Procedia PDF Downloads 374
11980 Wavelet Based Residual Method of Detecting GSM Signal Strength Fading

Authors: Danladi Ali, Onah Festus Iloabuchi

Abstract:

In this paper, GSM signal strength was measured in order to detect the type of the signal fading phenomenon using one-dimensional multilevel wavelet residual method and neural network clustering to determine the average GSM signal strength received in the study area. The wavelet residual method predicted that the GSM signal experienced slow fading and attenuated with MSE of 3.875dB. The neural network clustering revealed that mostly -75dB, -85dB and -95dB were received. This means that the signal strength received in the study is a weak signal.

Keywords: one-dimensional multilevel wavelets, path loss, GSM signal strength, propagation, urban environment

Procedia PDF Downloads 338
11979 Design of Low Latency Multiport Network Router on Chip

Authors: P. G. Kaviya, B. Muthupandian, R. Ganesan

Abstract:

On-chip routers typically have buffers are used input or output ports for temporarily storing packets. The buffers are consuming some router area and power. The multiple queues in parallel as in VC router. While running a traffic trace, not all input ports have incoming packets needed to be transferred. Therefore large numbers of queues are empty and others are busy in the network. So the time consumption should be high for the high traffic. Therefore using a RoShaQ, minimize the buffer area and time The RoShaQ architecture was send the input packets are travel through the shared queues at low traffic. At high load traffic the input packets are bypasses the shared queues. So the power and area consumption was reduced. A parallel cross bar architecture is proposed in this project in order to reduce the power consumption. Also a new adaptive weighted routing algorithm for 8-port router architecture is proposed in order to decrease the delay of the network on chip router. The proposed system is simulated using Modelsim and synthesized using Xilinx Project Navigator.

Keywords: buffer, RoShaQ architecture, shared queue, VC router, weighted routing algorithm

Procedia PDF Downloads 542
11978 A Long Tail Study of eWOM Communities

Authors: M. Olmedilla, M. R. Martinez-Torres, S. L. Toral

Abstract:

Electronic Word-Of-Mouth (eWOM) communities represent today an important source of information in which more and more customers base their purchasing decisions. They include thousands of reviews concerning very different products and services posted by many individuals geographically distributed all over the world. Due to their massive audience, eWOM communities can help users to find the product they are looking for even if they are less popular or rare. This is known as the long tail effect, which leads to a larger number of lower-selling niche products. This paper analyzes the long tail effect in a well-known eWOM community and defines a tool for finding niche products unavailable through conventional channels.

Keywords: eWOM, online user reviews, long tail theory, product categorization, social network analysis

Procedia PDF Downloads 421
11977 Loading and Unloading Scheduling Problem in a Multiple-Multiple Logistics Network: Modelling and Solving

Authors: Yasin Tadayonrad

Abstract:

Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading /unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is loading/unloading capacity in each source/ destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming

Procedia PDF Downloads 91
11976 Neural Adaptive Controller for a Class of Nonlinear Pendulum Dynamical System

Authors: Mohammad Reza Rahimi Khoygani, Reza Ghasemi

Abstract:

In this paper, designing direct adaptive neural controller is applied for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) is used for the Neural network (NN). The adaptive neural controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are the merits of this paper. The promising performance of the proposed controllers investigates in simulation results.

Keywords: adaptive control, pendulum dynamical system, nonlinear control, adaptive neural controller, nonlinear dynamical, neural network, RBF, driven pendulum, position control

Procedia PDF Downloads 670
11975 The Driving Force for Taiwan Social Innovation Business Model Transformation: A Case Study of Social Innovation Internet Celebrity Training Project

Authors: Shih-Jie Ma, Jui-Hsu Hsiao, Ming-Ying Hsieh, Shin-Yan Yang, Chun-Han Yeh, Kuo-Chun Su

Abstract:

In Taiwan, social enterprises and non-profit organizations (NPOs) are not familiar with innovative business models, such as live streaming. In 2019, a brand new course called internet celebrity training project is introduced to them by the Social Innovation Lab. The Goal of this paper is to evaluate the effect of this project, to explore the role of new technology (internet live stream) in business process management (BPM), and to analyze how live stream programs can assist social enterprises in creating new business models. Social Innovation, with the purpose to solve social issues in innovative ways, is one of the most popular topics in the world. Social Innovation Lab was established in 2017 by Executive Yuan in Taiwan. The vision of Social Innovation Lab is to exploit technology, innovation and experimental methods to solve social issues, and to maximize the benefits from government investment. Social Innovation Lab aims at creating a platform for both supply and demand sides of social issues, to make social enterprises and start-ups communicate with each other, and to build an eco-system in which stakeholders can make a social impact. Social Innovation Lab keeps helping social enterprises and NPOs to gain better publicity and to enhance competitiveness by facilitating digital transformation. In this project, Social Innovation Lab exerted the influence of social media such as YouTube and Facebook, to make social enterprises and start-ups adjust their business models by using the live stream of social media, which becomes one of the tools to expand their market and diversify their sales channels. Internet live stream training courses were delivered in different regions of Taiwan in 2019, including Taitung, Taichung, Kaohsiung and Hualien. Through these courses, potential groups and enterprises were cultivated to become so-called internet celebrities. With their concern about social issues in mind, these internet celebrities know how to manipulate social media to make a social impact in different fields, such as aboriginal people, food and agriculture, LOHAS (Lifestyles of Health and Sustainability), environmental protection and senior citizens. Participants of live stream training courses in Taiwan are selected to take in-depth interviews and questionnaire surveys. Results indicate that the digital transformation process of social enterprises and NPOs can be successful by implementing business process reengineering, a significant change made by social innovation internet celebrities. Therefore, this project can be the new driving force to facilitate the business model transformation in Taiwan.

Keywords: business process management, digital transformation, live stream, social innovation

Procedia PDF Downloads 146
11974 Convolutional Neural Network and LSTM Applied to Abnormal Behaviour Detection from Highway Footage

Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

Abstract:

Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

Procedia PDF Downloads 166
11973 Embodied Spiritualities and Emerging Search for Social Transformation: An Embodied Ethnographic Study of Yoga Practices in Medellin, Colombia

Authors: Lina M. Vidal

Abstract:

This paper discusses yoga practices involvement in both self-transformation and social transformations by means of an embodied ethnographic approach to different initiatives for social change in Medellín. In the context of gradual popularization of embodied spiritualities, yoga practices have opened their way in calls for social change in a performative perspective which involves collective experiences, reflections and production of embodied knowledge. Through the reflection on bodily dimension and corporal experience, this ethnographic approach acknowledges inter-corporality and somatic modes of attention during observations and personal experiences. In social change initiatives that include yoga practices were identified transformations of common understanding on social issues such as it is produced by institutionalized education, health system and other fields of knowledge. This is clearly visible in yoga projects for children in vulnerable conditions, homeless people, prisoners, and young people recovering from drug addiction. These projects are often promoted by organizations and networks, which incorporate individual life stories into collective experiences. Dissemination of yoga is heading to a broad institutional and cultural legitimation of yoga and of spirituality that impact different fields of social work and everyday life in general. This way, yoga is becoming an embodied activist way of life and a legitimate field for social work.

Keywords: embodied ethnography, Medellin, social transformation, embodied spiritualities, yoga practices

Procedia PDF Downloads 188
11972 Museums and Corporate Social Responsibility: Environmental Impact and Strategies in Corporate Social Responsibility Policies

Authors: Nicola Urbino

Abstract:

The definition of corporate social responsibility policies is a central topic in contemporary museology, as the role of museums in developing social, cultural, and environmental impact strategies has become increasingly prominent. An overarching perspective in this domain can be provided by the publication of the primary tool for impact verification and reporting in the CSR field: the Social Report. The presentation, based on an international and national theoretical and regulatory assessment, focuses on the operational significance of structured social reporting for Italian museums. The study involves analyzing over 25 Social Reports from leading Italian museums over the past 5 years to assess their CSR practices, examining both the strengths and weaknesses, in order to offer a comprehensive overview of the phenomenon of social responsibility in the national context. Moreover, a benchmark will be done between the legislative framework and guidelines and the effective implementation of CSR policies and practices. That said, the contribution aims at analyzing the strategies of the main Italian museums regarding their environmental impact on the territory. Through the analysis of the Social Balance Sheets published by a group of museums from the north to the south of Italy, it will highlight the relations that museums have established over the years with the territory and the environment, their sensitivity to climate change, and the strategies proposed to mitigate their environmental impact. Starting from a general analysis, the paper will help to highlight best practices and management models to be followed for sustainable growth, analyzing best practice, case studies and strategies applied to the museological field.

Keywords: museums, social report, sustainable development, footprint

Procedia PDF Downloads 28
11971 Pose Normalization Network for Object Classification

Authors: Bingquan Shen

Abstract:

Convolutional Neural Networks (CNN) have demonstrated their effectiveness in synthesizing 3D views of object instances at various viewpoints. Given the problem where one have limited viewpoints of a particular object for classification, we present a pose normalization architecture to transform the object to existing viewpoints in the training dataset before classification to yield better classification performance. We have demonstrated that this Pose Normalization Network (PNN) can capture the style of the target object and is able to re-render it to a desired viewpoint. Moreover, we have shown that the PNN improves the classification result for the 3D chairs dataset and ShapeNet airplanes dataset when given only images at limited viewpoint, as compared to a CNN baseline.

Keywords: convolutional neural networks, object classification, pose normalization, viewpoint invariant

Procedia PDF Downloads 352
11970 Diffusion of Social Innovation in Thai Community Enterprises

Authors: Thanisa Sirithaporn

Abstract:

The study aims to examine the diffusion of social innovation among Thai Community Enterprises in conjunction with a singular case study of a medium-sized corporation that has successfully transitioned from a charitable foundation to a sustainable, profitable entity creating value for both shareholders and the communities in which it operates. It seeks to bridge the gap between different streams of aligned research in the fields of diffusion, social innovation, and community enterprises into a more cohesive conceptual framework and thus to better understand the historical and current impediments that have resulted in so many enterprises failing to be sustainable. The methodology is mixed and dual phased. The initial quantitative phase uses a questionnaire as the main research instrument distributed among community enterprises throughout Thailand which will provide the themes for the qualitative phase through semi-structured interviews with key stakeholders at a commercial enterprise actively engaged in social innovation. The findings seek to present a more comprehensive conceptual framework and actionable guidelines to aid community enterprises to develop social innovation in a sustainable manner that creates value to its beneficiaries.

Keywords: diffusion, community enterprises, social innovation, Thailand

Procedia PDF Downloads 133
11969 On the Implementation of The Pulse Coupled Neural Network (PCNN) in the Vision of Cognitive Systems

Authors: Hala Zaghloul, Taymoor Nazmy

Abstract:

One of the great challenges of the 21st century is to build a robot that can perceive and act within its environment and communicate with people, while also exhibiting the cognitive capabilities that lead to performance like that of people. The Pulse Coupled Neural Network, PCNN, is a relative new ANN model that derived from a neural mammal model with a great potential in the area of image processing as well as target recognition, feature extraction, speech recognition, combinatorial optimization, compressed encoding. PCNN has unique feature among other types of neural network, which make it a candid to be an important approach for perceiving in cognitive systems. This work show and emphasis on the potentials of PCNN to perform different tasks related to image processing. The main drawback or the obstacle that prevent the direct implementation of such technique, is the need to find away to control the PCNN parameters toward perform a specific task. This paper will evaluate the performance of PCNN standard model for processing images with different properties, and select the important parameters that give a significant result, also, the approaches towards find a way for the adaptation of the PCNN parameters to perform a specific task.

Keywords: cognitive system, image processing, segmentation, PCNN kernels

Procedia PDF Downloads 280
11968 Energy Efficient Clustering with Adaptive Particle Swarm Optimization

Authors: KumarShashvat, ArshpreetKaur, RajeshKumar, Raman Chadha

Abstract:

Wireless sensor networks have principal characteristic of having restricted energy and with limitation that energy of the nodes cannot be replenished. To increase the lifetime in this scenario WSN route for data transmission is opted such that utilization of energy along the selected route is negligible. For this energy efficient network, dandy infrastructure is needed because it impinges the network lifespan. Clustering is a technique in which nodes are grouped into disjoints and non–overlapping sets. In this technique data is collected at the cluster head. In this paper, Adaptive-PSO algorithm is proposed which forms energy aware clusters by minimizing the cost of locating the cluster head. The main concern is of the suitability of the swarms by adjusting the learning parameters of PSO. Particle Swarm Optimization converges quickly at the beginning stage of the search but during the course of time, it becomes stable and may be trapped in local optima. In suggested network model swarms are given the intelligence of the spiders which makes them capable enough to avoid earlier convergence and also help them to escape from the local optima. Comparison analysis with traditional PSO shows that new algorithm considerably enhances the performance where multi-dimensional functions are taken into consideration.

Keywords: Particle Swarm Optimization, adaptive – PSO, comparison between PSO and A-PSO, energy efficient clustering

Procedia PDF Downloads 246
11967 Comparative Study of Scheduling Algorithms for LTE Networks

Authors: Samia Dardouri, Ridha Bouallegue

Abstract:

Scheduling is the process of dynamically allocating physical resources to User Equipment (UE) based on scheduling algorithms implemented at the LTE base station. Various algorithms have been proposed by network researchers as the implementation of scheduling algorithm which represents an open issue in Long Term Evolution (LTE) standard. This paper makes an attempt to study and compare the performance of PF, MLWDF and EXP/PF scheduling algorithms. The evaluation is considered for a single cell with interference scenario for different flows such as Best effort, Video and VoIP in a pedestrian and vehicular environment using the LTE-Sim network simulator. The comparative study is conducted in terms of system throughput, fairness index, delay, packet loss ratio (PLR) and total cell spectral efficiency.

Keywords: LTE, multimedia flows, scheduling algorithms, mobile computing

Procedia PDF Downloads 383
11966 Educaton for Social Reconstruction: Impact of Social Terrorism on Women Education in Nigeria

Authors: Theresa Chinyere ONU

Abstract:

This paper examines the effect of social terrorism on education in Nigeria. The article looked into some prevailing conditions of international political unrest and insecurity. The fear and risk of these conditions to national security and the struggle for power establishment which has further intensified and taken the shape of terrorism has imposed devastating effects on the growth and prosperity of Nigeria; as traffic patterns get disturbed, hospitals and schools get dysfunctional. This has also affected the educational standard in Nigeria as parents are no longer comfortable in sending their children to schools in some states for the fear of terrorist attacks. The study emphasized the integrated the effort of the government management institutions.

Keywords: education, social terrorism, women, Nigeria

Procedia PDF Downloads 583
11965 Signal Strength Based Multipath Routing for Mobile Ad Hoc Networks

Authors: Chothmal

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In this paper, we present a route discovery process which uses the signal strength on a link as a parameter of its inclusion in the route discovery method. The proposed signal-to-interference and noise ratio (SINR) based multipath reactive routing protocol is named as SINR-MP protocol. The proposed SINR-MP routing protocols has two following two features: a) SINR-MP protocol selects routes based on the SINR of the links during the route discovery process therefore it select the routes which has long lifetime and low frame error rate for data transmission, and b) SINR-MP protocols route discovery process is multipath which discovers more than one SINR based route between a given source destination pair. The multiple routes selected by our SINR-MP protocol are node-disjoint in nature which increases their robustness against link failures, as failure of one route will not affect the other route. The secondary route is very useful in situations where the primary route is broken because we can now use the secondary route without causing a new route discovery process. Due to this, the network overhead caused by a route discovery process is avoided. This increases the network performance greatly. The proposed SINR-MP routing protocol is implemented in the trail version of network simulator called Qualnet.

Keywords: ad hoc networks, quality of service, video streaming, H.264/SVC, multiple routes, video traces

Procedia PDF Downloads 249
11964 Efficiency of Background Chlorine Residuals against Accidental Microbial Episode in Proto-Type Distribution Network (Rig) Using Central Composite Design (CCD)

Authors: Sajida Rasheed, Imran Hashmi, Luiza Campos, Qizhi Zhou, Kim Keu

Abstract:

A quadratic model (p ˂ 0.0001) was developed by using central composite design of 50 experimental runs (42 non-center + 8 center points) to assess efficiency of background chlorine residuals in combating accidental microbial episode in a prototype distribution network (DN) (rig). A known amount of background chlorine residuals were maintained in DN and a required number of bacteria, Escherichia coli K-12 strain were introduced by an injection port in the pipe loop system. Samples were taken at various time intervals at different pipe lengths. Spread plate count was performed to count bacterial number. The model developed was significant. With microbial concentration and time (p ˂ 0.0001), pipe length (p ˂ 0.022), background chlorine residuals (p ˂ 0.07) and time^2 (p ˂ 0.09) as significant factors. The ramp function of variables shows that at the microbial count of 10^6, at 0.76 L/min, and pipe length of 133 meters, a background residual chlorine 0.16 mg/L was enough for complete inactivation of microbial episode in approximately 18 minutes.

Keywords: central composite design (CCD), distribution network, Escherichia coli, residual chlorine

Procedia PDF Downloads 462
11963 An Analysis of Iranian Social Media Users’ Perceptions of Published Images of Coronavirus Deaths

Authors: Ali Gheshmi

Abstract:

The highest rate of death, after World War II, is due to the Coronavirus epidemic and more than 2 million people have died since the epidemic outbreak in December 2019, so the word “death” is one of the highest frequency words in social media; moreover, the use of social media has grown due to quarantine and successive restrictions and lockdowns. The most important aspects of the approach used by this study include the analysis of Iranian social media users’ reactions to the images of those who died due to Coronavirus, investigating if seeing such images via social media is effective on the users’ perception of the closeness of death, and evaluating the extent to which the fear of Coronavirus death is instrumental in persuading users to observe health protocols or causing mental problems in social media users. Since the goal of this study is to discover how social media users perceive and react to the images of people who died of Coronavirus, the cultural studies approach is used Receipt analysis method and in-depth interviews will be used for collecting data from Iranian users; also, snowball sampling is used in this study. The probable results would show that cyberspace users experience the closeness of “death” more than any time else and to cope with these annoying images, avoid viewing them or if they view, it will lead them to suffer from mental problems.

Keywords: death, receipt analysis method, mental health, social media, Covid-19

Procedia PDF Downloads 155
11962 An Energy-Balanced Clustering Method on Wireless Sensor Networks

Authors: Yu-Ting Tsai, Chiun-Chieh Hsu, Yu-Chun Chu

Abstract:

In recent years, due to the development of wireless network technology, many researchers have devoted to the study of wireless sensor networks. The applications of wireless sensor network mainly use the sensor nodes to collect the required information, and send the information back to the users. Since the sensed area is difficult to reach, there are many restrictions on the design of the sensor nodes, where the most important restriction is the limited energy of sensor nodes. Because of the limited energy, researchers proposed a number of ways to reduce energy consumption and balance the load of sensor nodes in order to increase the network lifetime. In this paper, we proposed the Energy-Balanced Clustering method with Auxiliary Members on Wireless Sensor Networks(EBCAM)based on the cluster routing. The main purpose is to balance the energy consumption on the sensed area and average the distribution of dead nodes in order to avoid excessive energy consumption because of the increasing in transmission distance. In addition, we use the residual energy and average energy consumption of the nodes within the cluster to choose the cluster heads, use the multi hop transmission method to deliver the data, and dynamically adjust the transmission radius according to the load conditions. Finally, we use the auxiliary cluster members to change the delivering path according to the residual energy of the cluster head in order to its load. Finally, we compare the proposed method with the related algorithms via simulated experiments and then analyze the results. It reveals that the proposed method outperforms other algorithms in the numbers of used rounds and the average energy consumption.

Keywords: auxiliary nodes, cluster, load balance, routing algorithm, wireless sensor network

Procedia PDF Downloads 274
11961 Designing Social Media into Higher Education Courses

Authors: Thapanee Seechaliao

Abstract:

This research paper presents guiding on how to design social media into higher education courses. The research methodology used a survey approach. The research instrument was a questionnaire about guiding on how to design social media into higher education courses. Thirty-one lecturers completed the questionnaire. The data were scored by frequency and percentage. The research results were the lecturers’ opinions concerning the designing social media into higher education courses as follows: 1) Lecturers deem that the most suitable learning theory is Collaborative Learning. 2) Lecturers consider that the most important learning and innovation Skill in the 21st century is communication and collaboration skills. 3) Lecturers think that the most suitable evaluation technique is authentic assessment. 4) Lecturers consider that the most appropriate portion used as blended learning should be 70% in the classroom setting and 30% online.

Keywords: instructional design, social media, courses, higher education

Procedia PDF Downloads 510
11960 Forecasting Performance Comparison of Autoregressive Fractional Integrated Moving Average and Jordan Recurrent Neural Network Models on the Turbidity of Stream Flows

Authors: Daniel Fulus Fom, Gau Patrick Damulak

Abstract:

In this study, the Autoregressive Fractional Integrated Moving Average (ARFIMA) and Jordan Recurrent Neural Network (JRNN) models were employed to model the forecasting performance of the daily turbidity flow of White Clay Creek (WCC). The two methods were applied to the log difference series of the daily turbidity flow series of WCC. The measurements of error employed to investigate the forecasting performance of the ARFIMA and JRNN models are the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The outcome of the investigation revealed that the forecasting performance of the JRNN technique is better than the forecasting performance of the ARFIMA technique in the mean square error sense. The results of the ARFIMA and JRNN models were obtained by the simulation of the models using MATLAB version 8.03. The significance of using the log difference series rather than the difference series is that the log difference series stabilizes the turbidity flow series than the difference series on the ARFIMA and JRNN.

Keywords: auto regressive, mean absolute error, neural network, root square mean error

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11959 National Image in the Age of Mass Self-Communication: An Analysis of Internet Users' Perception of Portugal

Authors: L. Godinho, N. Teixeira

Abstract:

Nowadays, massification of Internet access represents one of the major challenges to the traditional powers of the State, among which the power to control its external image. The virtual world has also sparked the interest of social sciences which consider it a new field of study, an immense open text where sense is expressed. In this paper, that immense text has been accessed to so as to understand the perception Internet users from all over the world have of Portugal. Ours is a quantitative and qualitative approach, as we have resorted to buzz, thematic and category analysis. The results confirm the predominance of sea stereotype in others' vision of the Portuguese people, and evidence that national image has adapted to network communication through processes of individuation and paganization.

Keywords: national image, internet, self-communication, perception

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11958 Social Entrepreneurship and Women: A Bibliometric Analysis

Authors: S. Jailapdeen

Abstract:

Social entrepreneurship (SE)plays a pivotal role in the country which can contribute to women’s empowerment by providing them employment opportunities. SE plays a vital role in improving the economic condition of women, with self-motivated women entrepreneurs engaging several of their community members in their enterprises. Social enterprises unearth women’s inherent ability to be engaged in jobs other than agricultural and allied fields for their livelihoods. This paper highlights the role of social entrepreneurship in socio-economic empowerment of women. The researcher performed a bibliographic analysis of previously published works from peer-reviewed journals. The results are presented in the form of descriptive findings and discussions. The paper concludes by setting an agenda for future researchers in this field.

Keywords: social entrepreneurship, women’s socio-economic empowerment, bibliometric analysis, agenda for future researchers

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11957 Pion/Muon Identification in a Nuclear Emulsion Cloud Chamber Using Neural Networks

Authors: Kais Manai

Abstract:

The main part of this work focuses on the study of pion/muon separation at low energy using a nuclear Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The work consists of two parts: particle reconstruction algorithm and a Neural Network that assigns to each reconstructed particle the probability to be a muon or a pion. The pion/muon separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data. The algorithm allows to achieve a 60% muon identification efficiency with a pion misidentification smaller than 3%.

Keywords: nuclear emulsion, particle identification, tracking, neural network

Procedia PDF Downloads 506