Comparative Performance Analysis of Wireless Communication Protocols for Inte...chokrio
The systems based on intelligent sensors are currently expanding, due to theirs functions and theirs performances of intelligence: transmitting and receiving data in real-time, computation and processing algorithms, metrology remote, diagnostics, automation and storage measurements…The radio frequency wireless communication with its multitude offers a better solution for data traffic in this kind of systems. The mains objectives of this paper is to present a solution of the problem related to the selection criteria of a better wireless communication technology face up to the constraints imposed by the intended application and the evaluation of its key features. The comparison between the different wireless technologies (Wi-Fi, Wi-Max, UWB, Bluetooth, ZigBee, ZigBeeIP, GSM/GPRS) focuses on their performance which depends on the areas of utilization. Furthermore, it shows the limits of their characteristics. Study findings can be used by the developers/ engineers to deduce the optimal mode to integrate and to operate a system that guarantees quality of communication, minimizing energy consumption, reducing the implementation cost and avoiding time constraints.
Implementation of Wireless Communication using Adaptive Beamforming of Smart ...IOSR Journals
Abstract : As the growing demand for mobile communications is constantly increasing, the need for better coverage, improved capacity, and higher transmission quality rises. Thus, a more efficient use of the radio spectrum is required. A smart antenna system is capable of efficiently utilizing the radio spectrum and is an effective solution to the present wireless system problems while achieving reliable and robust high-speed, high-data-rate transmission. Smart antenna technology offer significantly improved solution to reduce interference level and improve system capacity. Smart antenna technology attempts to address this problem via advanced signal processing technology called beamforming. Adaptive beamforming is used for enhancing a desired signal while suppressing noise and interference at the output of an array of sensors. , in this paper work, a robust adaptive beamforming algorithm using smart antenna base station system, is to investigated its performance in presence of multipath components and multiple users .The capability of smart antenna and adaptive antenna easily employable to cognitive radio and OFDM system. Keywords - Smart/adaptive antenna, beamforming, DSP, OFDM
Exploring the Advantages of Dual-Band Antenna | GQ ResearchGQ Research
In this article, we explore the intricacies of dual-band antennas, their applications, and the impact they have on enhancing connectivity in diverse environments.
Impact of Next Generation Cognitive Radio Network on the Wireless Green Eco s...ijeei-iaes
Land mobile communication is burdened with typical propagation constraints due to the channel characteristics in radio systems.Also,the propagation characteristics vary form place to place and also as the mobile unit moves,from time to time.Hence,the tramsmission path between transmitter and receiver varies from simple direct LOS to the one which is severely obstructed by buildings, foliage and terrain. Multipath propagation and shadow fading effects affect the signal strength of an arbitrary Transmitter-Receiver due to the rapid fluctuations in the phase and amplitude of signal which also determines the average power over an area of tens or hundreds of meters. Shadowing introduces additional fluctuations, so the received local mean power varies around the area –mean. The present paper deals with the performance analysis of impact of next generation wireless cognitive radio network on wireless green eco system through signal and interference level based k coverage probability under the shadow fading effects.
K Coverage Probability of 5G Wireless Cognitive Radio Network under Shadow Fa...ijeei-iaes
Land mobile communication is burdened with typical propagation constraints due to the channel characteristics in radio systems.Also,the propagation characteristics vary form place to place and also as the mobile unit moves,from time to time.Hence,the tramsmission path between transmitter and receiver varies from simple direct LOS to the one which is severely obstructed by buildings,foliage and terrain.Multipath propagation and shadow fading effects affect the signal strength of an arbitrary Transmitter-Receiver due to the rapid fluctuations in the phase and amplitude of signal which also determines the average power over an area of tens or hundreds of meters.Shadowing introduces additional fluctuations,so the received local mean power varies around the area –mean.The present section deals with the performance analysis of fifth generation wireless cognitive radio network on the basis of signal and interference level based k coverage probability under the shadow fading effects.
Exploring the Dynamics of Transmission Characteristics and their Applications...GQ Research
Transmission characteristics refer to the unique attributes and behaviors exhibited by signals as they propagate through transmission mediums, such as cables, optical fibers, or wireless channels.
Comparative Performance Analysis of Wireless Communication Protocols for Inte...chokrio
The systems based on intelligent sensors are currently expanding, due to theirs functions and theirs performances of intelligence: transmitting and receiving data in real-time, computation and processing algorithms, metrology remote, diagnostics, automation and storage measurements…The radio frequency wireless communication with its multitude offers a better solution for data traffic in this kind of systems. The mains objectives of this paper is to present a solution of the problem related to the selection criteria of a better wireless communication technology face up to the constraints imposed by the intended application and the evaluation of its key features. The comparison between the different wireless technologies (Wi-Fi, Wi-Max, UWB, Bluetooth, ZigBee, ZigBeeIP, GSM/GPRS) focuses on their performance which depends on the areas of utilization. Furthermore, it shows the limits of their characteristics. Study findings can be used by the developers/ engineers to deduce the optimal mode to integrate and to operate a system that guarantees quality of communication, minimizing energy consumption, reducing the implementation cost and avoiding time constraints.
Implementation of Wireless Communication using Adaptive Beamforming of Smart ...IOSR Journals
Abstract : As the growing demand for mobile communications is constantly increasing, the need for better coverage, improved capacity, and higher transmission quality rises. Thus, a more efficient use of the radio spectrum is required. A smart antenna system is capable of efficiently utilizing the radio spectrum and is an effective solution to the present wireless system problems while achieving reliable and robust high-speed, high-data-rate transmission. Smart antenna technology offer significantly improved solution to reduce interference level and improve system capacity. Smart antenna technology attempts to address this problem via advanced signal processing technology called beamforming. Adaptive beamforming is used for enhancing a desired signal while suppressing noise and interference at the output of an array of sensors. , in this paper work, a robust adaptive beamforming algorithm using smart antenna base station system, is to investigated its performance in presence of multipath components and multiple users .The capability of smart antenna and adaptive antenna easily employable to cognitive radio and OFDM system. Keywords - Smart/adaptive antenna, beamforming, DSP, OFDM
Exploring the Advantages of Dual-Band Antenna | GQ ResearchGQ Research
In this article, we explore the intricacies of dual-band antennas, their applications, and the impact they have on enhancing connectivity in diverse environments.
Impact of Next Generation Cognitive Radio Network on the Wireless Green Eco s...ijeei-iaes
Land mobile communication is burdened with typical propagation constraints due to the channel characteristics in radio systems.Also,the propagation characteristics vary form place to place and also as the mobile unit moves,from time to time.Hence,the tramsmission path between transmitter and receiver varies from simple direct LOS to the one which is severely obstructed by buildings, foliage and terrain. Multipath propagation and shadow fading effects affect the signal strength of an arbitrary Transmitter-Receiver due to the rapid fluctuations in the phase and amplitude of signal which also determines the average power over an area of tens or hundreds of meters. Shadowing introduces additional fluctuations, so the received local mean power varies around the area –mean. The present paper deals with the performance analysis of impact of next generation wireless cognitive radio network on wireless green eco system through signal and interference level based k coverage probability under the shadow fading effects.
K Coverage Probability of 5G Wireless Cognitive Radio Network under Shadow Fa...ijeei-iaes
Land mobile communication is burdened with typical propagation constraints due to the channel characteristics in radio systems.Also,the propagation characteristics vary form place to place and also as the mobile unit moves,from time to time.Hence,the tramsmission path between transmitter and receiver varies from simple direct LOS to the one which is severely obstructed by buildings,foliage and terrain.Multipath propagation and shadow fading effects affect the signal strength of an arbitrary Transmitter-Receiver due to the rapid fluctuations in the phase and amplitude of signal which also determines the average power over an area of tens or hundreds of meters.Shadowing introduces additional fluctuations,so the received local mean power varies around the area –mean.The present section deals with the performance analysis of fifth generation wireless cognitive radio network on the basis of signal and interference level based k coverage probability under the shadow fading effects.
Exploring the Dynamics of Transmission Characteristics and their Applications...GQ Research
Transmission characteristics refer to the unique attributes and behaviors exhibited by signals as they propagate through transmission mediums, such as cables, optical fibers, or wireless channels.
Mobile Ad hoc Networks (MANETs) have drawn considerable attentions of the researchers for the last few years. MANETs, consisting of mobile nodes, are self-organizing and self-configuring and hence can be deployed without any infrastructure support. MANETs also have some limitations including short-life, unreliability, scalability, latency, high interference, and limited resources. In order to overcome these limitations many innovations and researches have been done in this field. Incorporating smart antenn system with the mobile nodes is one of them. It has been shown in the literatures that smart antenna can improve network capacity, increase network lifetime, reduce delay, and improve scalability by using directional radiation pattern. But, there are some unsolvedissues too. Smart antenna requires a large
number of antenna elements that a resource constraint mobile node can hardly handle. Hence, one major
design issue is to achieve a desired radiation pattern by using minimum number of antenna elements. Another important issue is the arrangement of antenna elements. Antenna elements can be arranged in linear, planar, and circular manners. In this paper we have addressed these issues. We have proposed a window based smart antenna design for MANETs. Our target is to improve the routing performance of
MANETs. We have shown that by using appropriate window function a desired radiation pattern can be achieved with a minimum number of antenna elements.
Machine learning based lightweight interference mitigation scheme for wireles...TELKOMNIKA JOURNAL
The interference issue is most vibrant on low-powered networks like wireless sensor network (WSN). In some cases, the heavy interference on WSN from different technologies and devices result in life threatening situations. In this paper, a machine learning (ML) based lightweight interference mitigation scheme for WSN is proposed. The scheme detects and identifies heterogeneous interference like Wifi, bluetooth and microwave oven using a lightweight feature extraction method and ML lightweight decision tree. It also provides WSN an adaptive interference mitigation solution by helping to choose packet scheduling, Acknowledgement (ACK)-retransmission or channel switching as the best countermeasure. The scheme is simulated with test data to evaluate the accuracy performance and the memory consumption. Evaluation of the proposed scheme’s memory profile shows a 14% memory saving compared to a fast fourier transform (FFT) based periodicity estimation technique and 3% less memory compared to logistic regression-based ML model, hence proving the scheme is lightweight. The validation test shows the scheme has a high accuracy at 95.24%. It shows a precision of 100% in detecting WiFi and microwave oven interference while a 90% precision in detecting bluetooth interference.
Optimal Operating Performances of Wireless Protocols for Intelligent Sensors ...chokrio
The systems based on intelligent sensors are currently expanding, due to theirs functions and theirs performances of intelligence: transmitting and receiving data in real-time, computation and processing algorithms, metrology remote, diagnostics, automation and storage measurements…The radio frequency wireless communication with its multitude offers a better solution for data traffic in this kind of systems. The mains objectives of this paper is to present a solution of the problem related to the selection criteria of a better wireless communication technology face up to the constraints imposed by the intended application and the evaluation of its key features. The comparison between the different wire-less technologies (Wi-Fi, Wi-Max, UWB, Bluetooth, ZigBee, ZigBeeIP, GSM/GPRS) focuses on their performance which depends on the areas of utilization. Furthermore, it shows the limits of their characteristics. Study findings can be used by the developers/ engineers to deduce the optimal mode to integrate and to operate a system that guarantees quality of communication, minimizing energy consumption, reducing the implementation cost and avoiding time con-straints.
Smart Antenna Report for third year Electronics and Communication Students .
Smart Antenna is a really nice topic to discover and present for third year students of electronics and communication engineering branch. So this Report covers it all .
A novel frequency reconfigurable antenna for smart grid applications in TV w...IJECEIAES
This paper presents the design and analysis of a frequency reconfigurable, aperture coupled rectangular patch antenna for use in smart grid applications in TV white space bands. The proposed antenna model has been realized on multi-substrate layers of Polylactic acid (PLA) material (εr=2.65, tanδ=0.003) with a ground plane sandwiched in between them. An aperture has been made in the ground plane for coupling energy to the patch. The overall system dimensions are 270×270 mm. The feature of frequency reconfigurability has been achieved by incorporating a switch and varying the reactance of the feed line on the bottom substrate. A rectangular slot on the long feed line improves impedance matching. The ON and OFF states of the switch provide two operating frequency bands namely 630.13 to 636.7 MHz and 619.16 to 625.3 MHz respectively. The proposed aperture coupled reconfigurable system operates with a maximum gain of 6.4 dB and average efficiency of 78.5% in both bands. The measured results are satisfactory and the proposed antenna will be suitable for operation in the smart grid environment.
Cognitive Radio (CR) is an adaptive, intelligent radio and network technology that can automatically detect available channels in a wireless spectrum and change transmission parameters enabling more communications to run concurrently and also improve radio operating behavior.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Wideband Sensing for Cognitive Radio Systems in Heterogeneous Next Generation...CSCJournals
Mobile Next Generation Network (MNGN) is characterized as heterogeneous network where variety of access technologies are meant to coexist. Decisions on choosing an air interface that meets a particular need at a particular time will be shifted from the network’s side to (a more intelligent) user’s side. On top of that network operators and regularities have come to the realization that assigned spectrum bands are not utilized as they should be. Cognitive radio stands out as a candidate technology to address many emerging issues in MNGN such as capacity, quality of service and spectral efficiency. As a transmission strategy, cognitive radio systems depend greatly on sensing the radio environment. In this paper, we present a novel approach for interference characterization in cognitive radio networks based on wideband chirp signal. The results presented show that improved sensing accuracy is maintained at tolerable system complexity.
Chapter 1 AI is used in Customer Relationship Management (CRM):.pptxfilembarketema
Certainly! Here are some examples of how AI is used in Customer Relationship Management (CRM):
Chatbots: AI-powered chatbots are used in CRM systems to provide automated customer support and assistance. Chatbots can handle a wide range of customer inquiries, answer frequently asked questions, and provide relevant information in real-time. They can engage in natural language conversations, understand customer intent, and provide personalized recommendations or solutions.
Sentiment Analysis: AI algorithms can analyze customer interactions, such as emails, social media posts, and chat transcripts, to determine customer sentiment and emotions. Sentiment analysis helps CRM systems understand customer satisfaction levels, identify potential issues or concerns, and take proactive measures to address them.
Personalization: AI enables CRM systems to deliver personalized experiences to customers. By analyzing customer data, purchase history, browsing behavior, and preferences, AI algorithms can generate personalized product recommendations, targeted marketing campaigns, and customized offers to enhance customer engagement and satisfaction.
Lead Scoring and Qualification: AI can assist in lead scoring and qualification processes. By analyzing historical data and customer behavior patterns, AI algorithms can predict the likelihood of a lead converting into a customer. This helps sales teams prioritize their efforts and allocate resources effectively to high-potential leads, improving conversion rates and sales efficiency.
Predictive Analytics: AI algorithms can analyze customer data and historical patterns to make predictions about customer behavior, such as likelihood to churn or cross-sell/up-sell opportunities. These predictions help CRM systems identify the most effective strategies for customer retention and revenue growth.
Voice and Speech Analytics: AI-powered voice and speech analytics tools can analyze customer calls and extract valuable insights. These tools can identify keywords, sentiment, and speech patterns to understand customer needs, identify common issues, and provide feedback for agent training and process improvement.
Social Media Monitoring: AI algorithms can monitor social media platforms to track brand mentions, customer feedback, and sentiment. This helps CRM systems identify customer concerns, engage in social listening, and respond promptly to customer queries or complaints, improving overall customer satisfaction and brand reputation.
Customer Segmentation: AI can assist in segmenting customers based on various criteria, such as demographics, purchase history, interests, and behavior. This enables CRM systems to tailor marketing campaigns, promotions, and communication strategies to specific customer segments, improving targeting and response rates.
Customer Lifetime Value (CLV) Prediction: This helps CRM
Welcome to International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Cognitive Radio : Emerging Business Toward an Efficiently Smart Era of ICTNurmaya Widuri
Cognitive Radio is a hot issue in wireless technology. This is ultimately new wave of how radio technolgy communicate through spectrum effeciency. Furthermore, this new big thing bring a new wave of future ICT business lanscape toward efficiently smart era of ICT.
Ports and Terminal Operations Market Forecast 2024-2031 | GQ ResearchGQ Research
The Global Ports and Terminal Operations Market size was USD 4.5 trillion in 2023 and is projected to reach USD 7.8 trillion by 2031, with a CAGR of 6.7% during the forecast period.
Air Handling Units: Components, Applications, Benefits | GQ ResearchGQ Research
In this comprehensive guide, we delve into the fundamentals, components, operation, applications, and benefits of Air handling units, shedding light on their significance in modern building design and HVAC engineering.
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Mobile Ad hoc Networks (MANETs) have drawn considerable attentions of the researchers for the last few years. MANETs, consisting of mobile nodes, are self-organizing and self-configuring and hence can be deployed without any infrastructure support. MANETs also have some limitations including short-life, unreliability, scalability, latency, high interference, and limited resources. In order to overcome these limitations many innovations and researches have been done in this field. Incorporating smart antenn system with the mobile nodes is one of them. It has been shown in the literatures that smart antenna can improve network capacity, increase network lifetime, reduce delay, and improve scalability by using directional radiation pattern. But, there are some unsolvedissues too. Smart antenna requires a large
number of antenna elements that a resource constraint mobile node can hardly handle. Hence, one major
design issue is to achieve a desired radiation pattern by using minimum number of antenna elements. Another important issue is the arrangement of antenna elements. Antenna elements can be arranged in linear, planar, and circular manners. In this paper we have addressed these issues. We have proposed a window based smart antenna design for MANETs. Our target is to improve the routing performance of
MANETs. We have shown that by using appropriate window function a desired radiation pattern can be achieved with a minimum number of antenna elements.
Machine learning based lightweight interference mitigation scheme for wireles...TELKOMNIKA JOURNAL
The interference issue is most vibrant on low-powered networks like wireless sensor network (WSN). In some cases, the heavy interference on WSN from different technologies and devices result in life threatening situations. In this paper, a machine learning (ML) based lightweight interference mitigation scheme for WSN is proposed. The scheme detects and identifies heterogeneous interference like Wifi, bluetooth and microwave oven using a lightweight feature extraction method and ML lightweight decision tree. It also provides WSN an adaptive interference mitigation solution by helping to choose packet scheduling, Acknowledgement (ACK)-retransmission or channel switching as the best countermeasure. The scheme is simulated with test data to evaluate the accuracy performance and the memory consumption. Evaluation of the proposed scheme’s memory profile shows a 14% memory saving compared to a fast fourier transform (FFT) based periodicity estimation technique and 3% less memory compared to logistic regression-based ML model, hence proving the scheme is lightweight. The validation test shows the scheme has a high accuracy at 95.24%. It shows a precision of 100% in detecting WiFi and microwave oven interference while a 90% precision in detecting bluetooth interference.
Optimal Operating Performances of Wireless Protocols for Intelligent Sensors ...chokrio
The systems based on intelligent sensors are currently expanding, due to theirs functions and theirs performances of intelligence: transmitting and receiving data in real-time, computation and processing algorithms, metrology remote, diagnostics, automation and storage measurements…The radio frequency wireless communication with its multitude offers a better solution for data traffic in this kind of systems. The mains objectives of this paper is to present a solution of the problem related to the selection criteria of a better wireless communication technology face up to the constraints imposed by the intended application and the evaluation of its key features. The comparison between the different wire-less technologies (Wi-Fi, Wi-Max, UWB, Bluetooth, ZigBee, ZigBeeIP, GSM/GPRS) focuses on their performance which depends on the areas of utilization. Furthermore, it shows the limits of their characteristics. Study findings can be used by the developers/ engineers to deduce the optimal mode to integrate and to operate a system that guarantees quality of communication, minimizing energy consumption, reducing the implementation cost and avoiding time con-straints.
Smart Antenna Report for third year Electronics and Communication Students .
Smart Antenna is a really nice topic to discover and present for third year students of electronics and communication engineering branch. So this Report covers it all .
A novel frequency reconfigurable antenna for smart grid applications in TV w...IJECEIAES
This paper presents the design and analysis of a frequency reconfigurable, aperture coupled rectangular patch antenna for use in smart grid applications in TV white space bands. The proposed antenna model has been realized on multi-substrate layers of Polylactic acid (PLA) material (εr=2.65, tanδ=0.003) with a ground plane sandwiched in between them. An aperture has been made in the ground plane for coupling energy to the patch. The overall system dimensions are 270×270 mm. The feature of frequency reconfigurability has been achieved by incorporating a switch and varying the reactance of the feed line on the bottom substrate. A rectangular slot on the long feed line improves impedance matching. The ON and OFF states of the switch provide two operating frequency bands namely 630.13 to 636.7 MHz and 619.16 to 625.3 MHz respectively. The proposed aperture coupled reconfigurable system operates with a maximum gain of 6.4 dB and average efficiency of 78.5% in both bands. The measured results are satisfactory and the proposed antenna will be suitable for operation in the smart grid environment.
Cognitive Radio (CR) is an adaptive, intelligent radio and network technology that can automatically detect available channels in a wireless spectrum and change transmission parameters enabling more communications to run concurrently and also improve radio operating behavior.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Wideband Sensing for Cognitive Radio Systems in Heterogeneous Next Generation...CSCJournals
Mobile Next Generation Network (MNGN) is characterized as heterogeneous network where variety of access technologies are meant to coexist. Decisions on choosing an air interface that meets a particular need at a particular time will be shifted from the network’s side to (a more intelligent) user’s side. On top of that network operators and regularities have come to the realization that assigned spectrum bands are not utilized as they should be. Cognitive radio stands out as a candidate technology to address many emerging issues in MNGN such as capacity, quality of service and spectral efficiency. As a transmission strategy, cognitive radio systems depend greatly on sensing the radio environment. In this paper, we present a novel approach for interference characterization in cognitive radio networks based on wideband chirp signal. The results presented show that improved sensing accuracy is maintained at tolerable system complexity.
Chapter 1 AI is used in Customer Relationship Management (CRM):.pptxfilembarketema
Certainly! Here are some examples of how AI is used in Customer Relationship Management (CRM):
Chatbots: AI-powered chatbots are used in CRM systems to provide automated customer support and assistance. Chatbots can handle a wide range of customer inquiries, answer frequently asked questions, and provide relevant information in real-time. They can engage in natural language conversations, understand customer intent, and provide personalized recommendations or solutions.
Sentiment Analysis: AI algorithms can analyze customer interactions, such as emails, social media posts, and chat transcripts, to determine customer sentiment and emotions. Sentiment analysis helps CRM systems understand customer satisfaction levels, identify potential issues or concerns, and take proactive measures to address them.
Personalization: AI enables CRM systems to deliver personalized experiences to customers. By analyzing customer data, purchase history, browsing behavior, and preferences, AI algorithms can generate personalized product recommendations, targeted marketing campaigns, and customized offers to enhance customer engagement and satisfaction.
Lead Scoring and Qualification: AI can assist in lead scoring and qualification processes. By analyzing historical data and customer behavior patterns, AI algorithms can predict the likelihood of a lead converting into a customer. This helps sales teams prioritize their efforts and allocate resources effectively to high-potential leads, improving conversion rates and sales efficiency.
Predictive Analytics: AI algorithms can analyze customer data and historical patterns to make predictions about customer behavior, such as likelihood to churn or cross-sell/up-sell opportunities. These predictions help CRM systems identify the most effective strategies for customer retention and revenue growth.
Voice and Speech Analytics: AI-powered voice and speech analytics tools can analyze customer calls and extract valuable insights. These tools can identify keywords, sentiment, and speech patterns to understand customer needs, identify common issues, and provide feedback for agent training and process improvement.
Social Media Monitoring: AI algorithms can monitor social media platforms to track brand mentions, customer feedback, and sentiment. This helps CRM systems identify customer concerns, engage in social listening, and respond promptly to customer queries or complaints, improving overall customer satisfaction and brand reputation.
Customer Segmentation: AI can assist in segmenting customers based on various criteria, such as demographics, purchase history, interests, and behavior. This enables CRM systems to tailor marketing campaigns, promotions, and communication strategies to specific customer segments, improving targeting and response rates.
Customer Lifetime Value (CLV) Prediction: This helps CRM
Welcome to International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Cognitive Radio : Emerging Business Toward an Efficiently Smart Era of ICTNurmaya Widuri
Cognitive Radio is a hot issue in wireless technology. This is ultimately new wave of how radio technolgy communicate through spectrum effeciency. Furthermore, this new big thing bring a new wave of future ICT business lanscape toward efficiently smart era of ICT.
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JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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Send an interactive Slack channel message (using buttons)
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In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
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Charlie Greenberg, Host
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Essentials of Automations: Optimizing FME Workflows with Parameters
Anti-Jamming Antenna: Principles, Applications, Advancements, Future Trends and Challenges | GQ Research
1. Anti-Jamming Antenna: Securing
Communication In An Interference-Prone World
(Source – Hexagon US Federal)
In our increasingly connected world, reliable and secure communication is paramount.
However, the proliferation of electronic devices and wireless networks has also led to a rise
in signal interference and jamming attempts. Anti-jamming antennas have emerged as a
critical technology to counteract these threats, ensuring the integrity and availability of
communication systems in diverse environments. In this comprehensive guide, we delve into
the principles, applications, and advancements in anti-jamming antenna technology.
They are designed to mitigate the effects of intentional or unintentional interference on
wireless communication systems. Signal jamming, often employed by adversaries to disrupt
communication, can target a wide range of frequencies and transmission protocols, posing
significant challenges to military, civilian, and commercial networks. Anti-jamming antennas
employ various techniques, such as spatial filtering, frequency hopping, and polarization
diversity, to enhance signal resilience and combat interference.
Principles of Anti-Jamming Antennas:
a. Spatial Filtering:
Spatial filtering techniques involve the use of multiple antenna elements to selectively
receive desired signals while rejecting interference from unwanted directions.
Directional antennas, such as phased array antennas and adaptive nulling antennas, can
dynamically adjust their beam patterns to nullify jamming signals while maintaining the
reception of legitimate signals.
2. b. Frequency Hopping:
Frequency-hopping spread spectrum (FHSS) techniques involve rapidly changing the
transmission frequency over a wide spectrum to evade jamming attempts.
Antennas equipped with FHSS capabilities can synchronize frequency hopping patterns
between transmitters and receivers, making it difficult for adversaries to disrupt
communication.
c. Polarization Diversity:
Polarization diversity exploits the orthogonal polarization properties of electromagnetic
waves to improve signal robustness against interference.
By transmitting and receiving signals in multiple polarization states simultaneously,
antennas can mitigate the effects of polarization-dependent jamming techniques.
Applications of Anti-Jamming Antennas:
(Source – GPS World)
a. Military Communication:
Anti-jamming antennas play a critical role in military communication systems, where
secure and reliable communication is essential for mission success.
Military-grade antennas are designed to withstand electronic warfare threats, including
jamming, spoofing, and interception, while maintaining continuous connectivity in hostile
environments.
b. Civilian Navigation:
Global navigation satellite systems (GNSS), such as GPS, GLONASS, and Galileo, rely
on precise timing and positioning information for a wide range of civilian applications.
Anti-jamming antennas are deployed in GNSS receivers to mitigate the effects of
deliberate or unintentional interference, ensuring accurate navigation and timing
synchronization in urban, rural, and maritime environments.
c. Commercial Communication:
3. Commercial wireless networks, including cellular, Wi-Fi, and Bluetooth systems, are
susceptible to interference from neighboring devices, environmental factors, and malicious
attacks.
Antennas integrated into consumer electronics and infrastructure components help
maintain signal quality, coverage, and throughput in congested and high-interference
environments.
Advancements in Anti-Jamming Antenna Technology:
(Source – GQ Research)
a. Adaptive Beamforming:
Adaptive beamforming algorithms enable antennas to dynamically adjust their radiation
patterns in response to changing interference conditions.
Machine learning and artificial intelligence techniques are increasingly being applied to
optimize beamforming parameters and enhance signal discrimination and resilience.
b. Cognitive Radio:
Cognitive radio systems leverage spectrum sensing and dynamic spectrum access
techniques to opportunistically utilize available frequency bands and avoid congested or
jammed channels.
Antennas equipped with cognitive radio capabilities can autonomously detect and adapt to
interference sources, ensuring uninterrupted communication in dynamic RF environments.
c. Software-Defined Radio (SDR):
Software-defined radio platforms enable flexible and reconfigurable signal processing and
modulation schemes, facilitating rapid deployment of anti-jamming techniques.
SDR-based antennas offer scalability, interoperability, and compatibility with emerging
wireless standards and protocols, making them ideal for next-generation communication
systems.
Future Trends and Challenges:
4. As wireless communication technologies continue to evolve, antennas will play a pivotal
role in safeguarding communication networks against emerging threats and vulnerabilities.
Future research and development efforts will focus on improving the efficiency, agility,
and resilience of antenna systems through advances in materials, components, and signal-
processing algorithms.
Addressing regulatory, ethical, and privacy concerns associated with anti-jamming
technologies will be essential to ensure responsible deployment and usage in civilian and
commercial applications.
Integration with Satellite Communication:
Antennas are increasingly being integrated into satellite communication systems to
enhance signal resilience and mitigate interference from ground-based and space-based
jamming sources.
Satellite terminals equipped with anti-jamming capabilities can maintain connectivity and
data transmission integrity in contested electromagnetic environments, supporting critical
applications such as military communications, remote sensing, and satellite navigation.
Cybersecurity Considerations:
(Source – IARE)
As communication networks become more interconnected and reliant on digital
infrastructure, cybersecurity emerges as a critical consideration for antenna systems.
Secure authentication, encryption, and intrusion detection mechanisms are essential to
prevent unauthorized access, manipulation, or disruption of antenna functionality by
malicious actors.
Cross-Domain Integration:
Anti-jamming antenna technology is increasingly being integrated across multiple
domains, including air, land, sea, and space, to provide comprehensive protection against
jamming threats.
5. Cross-domain anti-jamming solutions enable seamless communication interoperability and
coordination between disparate platforms and systems, enhancing situational awareness
and mission effectiveness in complex operational environments.
Miniaturization and Low-Power Design:
Advances in miniaturization and low-power design enable the development of compact,
lightweight, and energy-efficient antenna solutions suitable for portable and mobile
applications.
Miniaturized antennas find applications in unmanned aerial vehicles (UAVs), wearable
devices, and IoT sensors, where space, weight, and power constraints are critical
considerations.
Standardization and Interoperability:
Standardization efforts led by industry consortia, regulatory bodies, and standards
organizations are essential to ensure interoperability and compatibility between antenna
systems from different manufacturers.
Common interfaces, protocols, and performance metrics facilitate seamless integration,
deployment, and operation of antennas in heterogeneous communication environments,
promoting ecosystem growth and innovation.
Conclusion:
Anti-jamming antennas represent a critical line of defense against signal interference and
jamming threats in modern communication systems. By leveraging advanced signal
processing techniques, adaptive beamforming algorithms, and cognitive radio capabilities,
these antennas enable secure, reliable, and resilient communication in diverse environments.
As the demand for secure wireless connectivity continues to grow, ongoing research and
innovation in anti-jamming antenna technology will be essential to address emerging threats,
safeguard critical infrastructure, and ensure the integrity of communication networks
worldwide.