This document proposes a deep learning model for detecting and identifying cyber attacks in wireless networks. The model uses an autoencoder and random forest classifier to extract features from network data and classify behaviors as malicious or benign. The model was evaluated on the NSL KDD Cup dataset and achieved an accuracy of 82% in detecting attacks. Key aspects of the model include using a non-symmetric deep autoencoder for feature extraction and dimensionality reduction, identifying and removing low frequency attacks from the data, and evaluating performance metrics like detection rate and precision.
This document discusses using a dual head cluster approach in a hierarchical cooperative intrusion detection system (IDS) to provide secure mobile ad hoc networks (MANETs). The proposed system uses two head nodes per cluster to detect intrusions through signature analysis or anomaly-based detection. Anomaly-based detection monitors network activities to detect deviations from normal behavior that could indicate intrusions, including new attacks not detectable by signature analysis. The system is designed and evaluated using the NS2 simulator to detect anomalies like black hole, denial of service, and flood attacks to form a more stable and secure network.
The document discusses security issues with 4G networks. It first provides an overview of 4G network architecture, including the IP Multimedia Subsystem security architecture and next generation network security architecture. It then discusses eight security dimensions for 4G networks: access control, authentication, non-repudiation, data confidentiality, communication security, data integrity, availability, and privacy. Finally, it outlines some specific security issues with 4G, including physical layer issues, WiMAX MAC layer issues, denial of service attacks, and Wi-Fi security issues.
Classification Rule Discovery Using Ant-Miner Algorithm: An Application Of N...
This document summarizes an algorithm called Ant-Miner that uses ant colony optimization to discover classification rules for network intrusion detection. Ant-Miner works by having artificial ants explore paths in a data structure representing the classification problem to discover rules. As more ants take the same path, the path is reinforced through pheromone updating, eventually leading to the discovery of classification rules. The authors apply Ant-Miner to a standard intrusion detection dataset and find it outperforms other classification methods in terms of accuracy and classification rate.
Multi-stage secure clusterhead selection using discrete rule-set against unkn...IJECEIAES
The document discusses a proposed multi-stage secure clusterhead selection technique for wireless sensor networks using a discrete rule-set. The technique aims to securely select clusterheads during the data aggregation process and learn the nature of communications to gain knowledge about adversary intensity. It constructs primary and secondary rule-sets to filter and select secure clusterheads based on energy, neighbors, vulnerability, vicinity and distance from adversaries. Simulation results using MEMSIC sensor nodes showed the proposed approach reduces energy consumption and improves data delivery compared to existing methods.
A Survey on Data Intrusion schemes used in MANETIRJET Journal
The document discusses data intrusion schemes used in mobile ad hoc networks (MANETs). It reviews common problems with data intrusion in MANETs due to their dynamic architecture and limited resources. Several proposed intrusion detection schemes are described, including distributed and cooperative schemes, specification-based schemes, and the proposed Random Walker Detection method. The proposed method aims to efficiently detect intrusions by deploying detection engines at each node and excluding detection engines from random walkers to reduce detection latency. It is described as working on three network layers and using advanced encryption standards to securely detect and route around malicious nodes.
IRJET- Heterogeneous Network Based Intrusion Detection System in Mobile Ad Ho...IRJET Journal
The document proposes a heterogeneous network based intrusion detection system for mobile ad hoc networks. It describes a probabilistic model that uses cooperation between intrusion detection systems among neighboring nodes to reduce their individual active time and conserve energy. Specifically, it proposes using a Heterogeneous Least Degree K method (HLDK) where each node determines the minimum monitoring probability in the network based on the degrees of its neighbors. This approach aims to achieve energy efficiency while maintaining a desired security level in heterogeneous networks consisting of nodes with varying capabilities. Simulation results show that using HLDK can significantly reduce the energy consumption and computational cost of running intrusion detection systems on nodes compared to having them active at all times.
This document discusses using a dual head cluster approach in a hierarchical cooperative intrusion detection system (IDS) to provide secure mobile ad hoc networks (MANETs). The proposed system uses two head nodes per cluster to detect intrusions through signature analysis or anomaly-based detection. Anomaly-based detection monitors network activities to detect deviations from normal behavior that could indicate intrusions, including new attacks not detectable by signature analysis. The system is designed and evaluated using the NS2 simulator to detect anomalies like black hole, denial of service, and flood attacks to form a more stable and secure network.
The document discusses security issues with 4G networks. It first provides an overview of 4G network architecture, including the IP Multimedia Subsystem security architecture and next generation network security architecture. It then discusses eight security dimensions for 4G networks: access control, authentication, non-repudiation, data confidentiality, communication security, data integrity, availability, and privacy. Finally, it outlines some specific security issues with 4G, including physical layer issues, WiMAX MAC layer issues, denial of service attacks, and Wi-Fi security issues.
Classification Rule Discovery Using Ant-Miner Algorithm: An Application Of N...IJMER
This document summarizes an algorithm called Ant-Miner that uses ant colony optimization to discover classification rules for network intrusion detection. Ant-Miner works by having artificial ants explore paths in a data structure representing the classification problem to discover rules. As more ants take the same path, the path is reinforced through pheromone updating, eventually leading to the discovery of classification rules. The authors apply Ant-Miner to a standard intrusion detection dataset and find it outperforms other classification methods in terms of accuracy and classification rate.
This document presents a proposed hybrid intrusion detection system that combines k-means clustering, k-nearest neighbor classification, and decision table majority rule-based approaches. The system is evaluated on the KDD-99 dataset to detect intrusions and classify them into four categories: R2L, DoS, Probe, and U2R. The goal is to decrease the false alarm rate and increase accuracy and detection rate compared to existing intrusion detection systems. The proposed system applies k-means clustering first, then k-nearest neighbor classification, and finally decision table majority rules. Results show the proposed hybrid approach improves performance metrics compared to existing techniques.
This paper presents a brief study of recent advances in wireless network security issues. The paper makes a number of contributions to the wireless networking field. First, it studies the 4G mail threats and risk and their design decisions. Second, the security of 4G architecture with next generation network security and 8-security dimensions of 4G network. Third, security issues and possible threats on 4G are discussed. Finally, we proposed four layer security model which manages to ensure more secure packets transmission by taking all the necessary security measures.
Integrated Framework for Secure and Energy Efficient Communication System in ...IJECEIAES
Irrespective of different forms and strategies implementing for securing Wireless Sensor Network (WSN), there are very less strategies that offers cost effective security over heterogeneous network. Therefore, this paper presents an integrated set of different processes that emphasize over secure routing, intellectual and delay-compensated routing, and optimization principle with a sole intention of securing the communication to and from the sensor nodes during data aggregation. The processed system advocates the non-usage of complex cryptography and encourages the usage of probability their and analytical modelling in order to render more practical implementation. The simulated outcome of study shows that proposed system offers reduced delay, more throughputs, and reduced energy consumption in contrast to existing system.
Secure masid secure multi agent system for intrusion detection-2IAEME Publication
This document discusses securing a multi-agent system for intrusion detection (MASID) by encrypting communications between agents. It first reviews existing intrusion detection systems including standalone, distributed, hierarchical, and agent-based approaches. It then proposes applying the AES encryption algorithm to the collaboration agent in MASID, which exchanges messages between detection and response agents. This would secure the detection-related information transferred between agents against attacks on the collaboration agent. The implementation and potential benefits of this "secure MASID" approach are discussed.
An intrusion detection system for packet and flow based networks using deep n...IJECEIAES
Study on deep neural networks and big data is merging now by several aspects to enhance the capabilities of intrusion detection system (IDS). Many IDS models has been introduced to provide security over big data. This study focuses on the intrusion detection in computer networks using big datasets. The advent of big data has agitated the comprehensive assistance in cyber security by forwarding a brunch of affluent algorithms to classify and analysis patterns and making a better prediction more efficiently. In this study, to detect intrusion a detection model has been propounded applying deep neural networks. We applied the suggested model on the latest dataset available at online, formatted with packet based, flow based data and some additional metadata. The dataset is labeled and imbalanced with 79 attributes and some classes having much less training samples compared to other classes. The proposed model is build using Keras and Google Tensorflow deep learning environment. Experimental result shows that intrusions are detected with the accuracy over 99% for both binary and multiclass classification with selected best features. Receiver operating characteristics (ROC) and precision-recall curve average score is also 1. The outcome implies that Deep Neural Networks offers a novel research model with great accuracy for intrusion detection model, better than some models presented in the literature.
Finding Critical Link and Critical Node Vulnerability for Networkijircee
The document discusses network vulnerability assessment and finding critical links and nodes. It proposes using a belief propagation algorithm to calculate the vulnerability of each node and the overall network vulnerability over time. It provides an example network and shows the results of analyzing it to find the critical nodes and links using the proposed algorithm. The algorithm works by having each node calculate the vulnerability of its neighbors and share this information over time to determine the overall network vulnerability.
IRJET- Securing on Demand Source Routing Protocol in Mobile Ad-Hoc Networks b...IRJET Journal
This document discusses securing the Ad-Hoc On-Demand Distance Vector (AODV) routing protocol from wormhole attacks in mobile ad-hoc networks. It proposes using clustering to mitigate the effects of wormhole attacks. Wormhole attacks are powerful attacks in ad-hoc networks that involve tunneling network traffic between two colluding attackers. The document reviews related work on clustering algorithms, TCP and SYN cookies, security-enhanced RFID systems, wormhole detection algorithms, analyzing the impact of wormhole attacks, and new clustering protocols for mobile ad-hoc networks. It aims to simulate the effect of wormhole attacks on AODV and analyze network performance with and without such attacks using the NS2 network simulator.
This document summarizes a research paper that proposes a rule-based technique using fuzzy logic to detect security attacks in wireless sensor networks. The paper identifies 10 common security attacks in wireless sensor networks including denial of service, eavesdropping, traffic analysis, etc. A fuzzy rule-based system is developed to calculate the impact of these security attacks. The system uses MATLAB tools and mouse dataset to test performance. Case studies are presented to demonstrate how the system can predict the likelihood and impact of security attacks on a wireless sensor network.
Secure data dissemination protocol in wireless sensor networks using xor netw...eSAT Publishing House
1. The document discusses a secure data dissemination protocol for wireless sensor networks using XOR network coding. It aims to achieve fast, secure, reliable and energy efficient data dissemination.
2. Wireless sensor networks require regular software updates through the wireless medium, which is known as data dissemination or network reprogramming. Existing dissemination protocols have security issues when combined with network coding techniques.
3. The proposed protocol uses simple cryptographic techniques with network coding to prevent pollution and denial of service attacks, while still achieving fast dissemination. It focuses on disseminating small data values securely and efficiently in wireless sensor networks.
IRJET- Security in Ad-Hoc Network using Encrypted Data Transmission and S...IRJET Journal
This document discusses security techniques for data transmission in ad-hoc networks, specifically encrypted data transmission and steganography. It proposes a system that enables encrypted data transmission between nodes and uses steganography to hide encrypted data in cover files like images, audio, and video during transmission for additional security. The system architecture includes modules for user interface, embedding secret data in cover files, extracting secret data, sending files between nodes, and receiving files. It aims to securely transmit data in ad-hoc networks using both encryption and steganography to protect confidentiality and integrity of transmitted data.
Efficient Data Aggregation in Wireless Sensor NetworksIJAEMSJORNAL
Sensor network is a term used to refer to a heterogeneous system combining tiny sensors and actuators with general/special-purpose processors. Sensor networks are assumed to grow in size to include hundreds or thousands of low-power, low-cost, static or mobile nodes. This system is created by observing that for any densely deployed sensor network, high redundancy exists in the gathered information from the sensor nodes that are close to each other we have exploited the redundancy and designed schemes to secure different kinds of aggregation processing against both inside and outside attacks.
Application of neural network and PSO-SVM in intrusion detection of networkIRJET Journal
This document proposes a new approach for network intrusion detection that uses machine learning and deep learning techniques. Specifically, it uses a 1D convolutional neural network (CNN) for feature extraction from network traffic data, and a support vector machine (SVM) classifier optimized with particle swarm optimization (PSO) for attack classification. The proposed approach is evaluated on the widely-used NSL-KDD network traffic dataset, which contains labeled examples of normal traffic and different types of network attacks. The CNN is used to extract features from the dataset, which are then classified with the PSO-optimized SVM to detect intrusions and different attack types. The approach aims to better identify stealthy attacks that may blend in with normal traffic.
IRJET- Survey on SDN based Network Intrusion Detection System using Machi...IRJET Journal
This document summarizes a survey on using machine learning techniques in an SDN-based network intrusion detection system. It discusses how SDN allows centralized control and monitoring of network traffic. Machine learning and deep learning can be applied to the monitored traffic to detect anomalies and threats. Specifically, the document examines using long short-term memory neural networks and artificial neural networks to classify traffic and improve detection accuracy in the SDN environment. The goal is to increase the effectiveness of the network intrusion detection system at identifying security issues.
IRJET- Machine Learning Processing for Intrusion DetectionIRJET Journal
This document evaluates different machine learning algorithms for network intrusion detection using the KDD dataset. It analyzes the accuracy of logistic regression, naive bayes, support vector machine, K-nearest neighbor, and decision tree classifiers based on their confusion matrices and receiver operating characteristic curves. The results show that the decision tree algorithm achieved the highest accuracy rate of 99.83% on the KDD dataset for intrusion detection.
An Enhanced Technique for Network Traffic Classification with unknown Flow De...IRJET Journal
This document presents a technique for classifying network traffic and detecting unknown flows in wireless sensor networks. The technique aims to improve on previous work by using fewer labeled training samples and investigating flow correlation in real-world network environments. It proposes a method that selects a sender and receiver node, establishes a path between them by avoiding faulty nodes, and evaluates the system based on propagation rate, training purity, and accuracy. The results show the proposed method achieves higher propagation rate, training purity, and overall accuracy compared to an existing semi-supervised technique.
A Comparative Study of Deep Learning Approaches for Network Intrusion Detecti...IRJET Journal
This document presents a comparative study of deep learning approaches for network intrusion detection. It employs deep neural networks to predict attacks on network intrusion detection systems using the KDD Cup-99 dataset. A DNN with 3 layers demonstrated superior performance compared to other machine learning algorithms and DNNs with varying layers. The study finds that deep learning techniques can function at a superhuman level when combined with intrusion detection systems due to their ability to adapt to new data and detect novel attacks.
IRJET- Confidential Data Access through Deep Learning Iris BiometricsIRJET Journal
This document describes a study that explores using iris recognition and deep learning as a biometric authentication method for sensitive mobile transactions. The proposed system uses a deep neural network classifier and edge detection with adaptive contour segmentation to identify individuals from iris images. It authenticates website access through MATLAB. The system is said to enhance security compared to existing methods by fusing information from iris and surrounding eye region features. Evaluation shows it reduces computation time and improves specificity, sensitivity and accuracy compared to region-based segmentation alone.
Energy Efficinet Intrusion Detection System in mobile ad-hoc networksIJARIIE JOURNAL
This document summarizes a proposed energy efficient intrusion detection system for mobile ad-hoc networks. It begins with an introduction to intrusion detection systems and mobile ad-hoc networks. It then discusses related work on intrusion detection in mobile ad-hoc networks. The proposed system uses an "impact factor" calculation to select cluster heads in an energy-efficient manner while preventing selfish behavior. Cluster heads run the intrusion detection system using a watchdog method to detect misbehaving nodes. Simulation results show that forming clusters reduces energy consumption compared to all nodes running intrusion detection independently.
Intrusion Detection for HealthCare Network using Machine LearningIRJET Journal
1) The document discusses using machine learning techniques for intrusion detection in healthcare networks. It aims to build an effective intrusion detection system that can efficiently detect intrusions and provide safety for sensitive patient health information and medical data.
2) The methodology involves pre-processing the NSL-KDD dataset, training a decision tree classifier model, and using the trained model to predict intrusions. Accuracy of 90.3% was achieved using cross-validation.
3) Future work could include using all dataset features, immediately alerting administrators of attacks, and making the system multi-lingual. The system aims to provide secure access of healthcare data for authorized users and detect unauthorized access attempts.
IRJET- Design and Implementation 4G Scenario on Qualnet 5.0.2IRJET Journal
This document discusses the design and implementation of a 4G network scenario using the QualNet network simulator. The authors created a virtual 4G network model in QualNet comprising of nodes such as routers, access points, and mobile phones connected by links like LAN segments and LTE connections. They simulated the behavior of the network under different operating scenarios and traffic patterns. The results of simulating Constant Bit Rate traffic showed a total of 12.5 MB of data sent, 24 packets transmitted, and a throughput of 4.4 Mbps. The authors concluded that QualNet is useful for network design, protocol research, and analysis of wireless applications but has some disadvantages like difficulty of installation on Linux. They proposed future work involving designing new protocol
IRJET- Machine Learning based Network SecurityIRJET Journal
The document discusses using machine learning algorithms to classify network traffic as malicious or non-malicious. It describes capturing packets from a dummy website under distributed denial of service (DDoS) attack to create a dataset. Two machine learning algorithms, naive Bayes and support vector machines (SVM), are used to classify the network traffic. Both algorithms achieved over 98% accuracy in detecting spam traffic. The paper proposes creating a real-time network traffic classification system using machine learning algorithms to improve network security.
Literature Review on DDOS Attacks Detection Using SVM algorithm.IRJET Journal
This document provides a literature review on detecting DDoS attacks using machine learning algorithms like SVM in SDN environments. It summarizes 10 research papers on this topic, identifying gaps such as specifying the number of clusters in advance for detection and dealing with non-linearly separable training data for SVM. The document also describes using SVM and advanced SVM techniques on the KDD99 and CIC-IDS 2018 datasets to classify network traffic as normal or malicious in an SDN environment, finding SVM provides better accuracy than other algorithms. It concludes SVM works well in their simulated environment and plan to implement advanced SVM to gain higher accuracy in detecting DDoS attacks.
To Design a Hybrid Algorithm to Detect and Eliminate Wormhole Attack in Wirel...IRJET Journal
This document proposes a hybrid algorithm to detect and eliminate wormhole attacks in wireless mesh networks. It describes how wormhole attacks work by establishing a tunnel between two malicious nodes. Most existing defenses are not secure against different types of wormhole attacks. The proposed algorithm aims to detect wormholes by calculating the neighbor list and directional neighbor list of the source node to approximate node locations and identify the effects of wormhole attacks. The performance is evaluated by varying the number of wormholes. The results show the algorithm is effective at detecting wormholes and its impact on the network.
Proactive Population-Risk Based Defense Against Denial of Cyber-Physical Serv...IRJET Journal
This document discusses proactive population-risk based defense against denial of cyber-physical service attacks. It proposes using test packets to test network state and rules across switches to detect faults. The goals are to augment human debugging, reduce downtime, and save money. Related work discussed network tomography using end-to-end measurements to identify lossy links. Striped unicast probes were also explored to infer link-level loss rates. The algorithm aims to generate test packets that exercise every rule on each switch to detect faults with a minimum number of packets.
Efficient Secure Multi-Neuron Attack Defensive and Routing Security Technique...IRJET Journal
This document proposes a new secure routing technique for wireless mesh networks using unmanned aerial vehicles. The technique uses encryption algorithms like Data Encryption Standard and neural networks to establish a secure routing algorithm. It generates unique IDs for nodes, uses a key distribution center for authentication, and implements encryption to prevent attacks. Simulation results show the proposed approach reduces delay and improves packet delivery rate compared to existing routing protocols like PASER when there is frame error.
4.report (cryptography & computer network)JIEMS Akkalkuwa
This document discusses network security and cryptography. It begins by defining network security and explaining the key areas of secrecy, authentication, non-repudiation, and integrity control. It then discusses what cryptography is, explaining that it uses mathematics to encrypt and decrypt data to provide security. The document provides an overview of symmetric and asymmetric key encryption techniques as well as hash functions. It also discusses some existing network security systems and their use of symmetric encryption with periodic key distribution and refresh.
IRJET- Software Defined Network: DDOS Attack DetectionIRJET Journal
This document discusses software defined networks (SDNs) and detecting distributed denial-of-service (DDoS) attacks in SDNs. It provides background on SDN architecture and how DDoS attacks work. The paper aims to address risks of DDoS attacks in SDNs and focuses on detection. It describes existing DDoS attack techniques and solutions. The document proposes using algorithms like TCM-KNN and DPTCM-KNN for detection of attacks in network traffic flows, and compares the two algorithms using parameters like packet length and response time.
IRJET- Improving Cyber Security using Artificial IntelligenceIRJET Journal
This document discusses using artificial intelligence techniques like machine learning algorithms to improve cyber security. It proposes a methodology that uses Splunk to extract relevant fields from cybersecurity data, feeds that into a K-means clustering algorithm to form attack clusters, then sends those clusters to individual artificial neural networks (ANNs). The aggregated ANN results are then fed into a support vector machine (SVM) which classifies attacks as malicious, non-malicious, or benign. Testing this approach on a dataset achieved a classification accuracy of over 92% when using Splunk, K-means, ANNs, and SVM together.
IRJET- A Secured Method of Data Aggregation for Wireless Sensor Networks in t...IRJET Journal
This document summarizes a research paper that proposes using iterative filtering (IF) algorithms to securely aggregate sensor data in wireless sensor networks in the presence of collusion attacks. Collusion attacks occur when nodes secretly or illegally agree to corrupt transmitted data, causing a mismatch in data aggregation. The paper aims to implement IF algorithms to avoid collusion attacks. IF algorithms work by repeatedly applying a function, using the output of one iteration as the input for the next. This helps maximize the likelihood of inferring accurate data from partially observed systems. The document outlines the methodology, benefits of IF algorithms, and basic steps of how they are implemented.
Simulations on Computer Network An Improved Study in the Simulator Methodolog...YogeshIJTSRD
This document discusses and compares various network simulation tools. It begins by explaining that network simulators are used to analyze network performance and behavior without real-world implementation. It then categorizes and describes several popular simulators: NS2, NS3, OPNET, OMNeT++, NetSim, QualNet, and J-Sim. For each simulator, it provides details on features, advantages, disadvantages and basic architecture. It concludes by recommending choosing a simulator based on requirements and focusing on analyzing statistical results to validate performance.
IRJET- Revisiting Security Aspects of Internet of Things for Self-Managed...IRJET Journal
This document discusses security aspects of internet of things (IoT) devices and proposes solutions. It summarizes 3 existing approaches:
1) An IoT reference model that includes authorization, encryption, and authentication mechanisms at each layer independently.
2) A protocol for IoT security using elliptic curve cryptography to allow encryption and decryption of messages between devices and gateways.
3) A mechanism using elliptic curve cryptography to provide security for communication between IPv4 and IPv6 networks, translating addresses and incorporating encryption.
The document also motivates the need for lightweight cryptographic algorithms for resource-constrained IoT devices and surveys existing schemes to provide confidentiality, integrity, and availability while addressing vulnerabilities.
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React based fullstack edtech web applicationIRJET Journal
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This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
20CDE09- INFORMATION DESIGN
UNIT I INCEPTION OF INFORMATION DESIGN
Introduction and Definition
History of Information Design
Need of Information Design
Types of Information Design
Identifying audience
Defining the audience and their needs
Inclusivity and Visual impairment
Case study.
OCS Training Institute is pleased to co-operate with
a Global provider of Rig Inspection/Audits,
Commission-ing, Compliance & Acceptance as well as
& Engineering for Offshore Drilling Rigs, to deliver
Drilling Rig Inspec-tion Workshops (RIW) which
teaches the inspection & maintenance procedures
required to ensure equipment integrity. Candidates
learn to implement the relevant standards &
understand industry requirements so that they can
verify the condition of a rig’s equipment & improve
safety, thus reducing the number of accidents and
protecting the asset.
In May 2024, globally renowned natural diamond crafting company Shree Ramkrishna Exports Pvt. Ltd. (SRK) became the first company in the world to achieve GNFZ’s final net zero certification for existing buildings, for its two two flagship crafting facilities SRK House and SRK Empire. Initially targeting 2030 to reach net zero, SRK joined forces with the Global Network for Zero (GNFZ) to accelerate its target to 2024 — a trailblazing achievement toward emissions elimination.
Conservation of Taksar through Economic RegenerationPriyankaKarn3
This was our 9th Sem Design Studio Project, introduced as Conservation of Taksar Bazar, Bhojpur, an ancient city famous for Taksar- Making Coins. Taksar Bazaar has a civilization of Newars shifted from Patan, with huge socio-economic and cultural significance having a settlement of about 300 years. But in the present scenario, Taksar Bazar has lost its charm and importance, due to various reasons like, migration, unemployment, shift of economic activities to Bhojpur and many more. The scenario was so pityful that when we went to make inventories, take survey and study the site, the people and the context, we barely found any youth of our age! Many houses were vacant, the earthquake devasted and ruined heritages.
Conservation of those heritages, ancient marvels,a nd history was in dire need, so we proposed the Conservation of Taksar through economic regeneration because the lack of economy was the main reason for the people to leave the settlement and the reason for the overall declination.
An Internet Protocol address (IP address) is a logical numeric address that is assigned to every single computer, printer, switch, router, tablets, smartphones or any other device that is part of a TCP/IP-based network.
Types of IP address-
Dynamic means "constantly changing “ .dynamic IP addresses aren't more powerful, but they can change.
Static means staying the same. Static. Stand. Stable. Yes, static IP addresses don't change.
Most IP addresses assigned today by Internet Service Providers are dynamic IP addresses. It's more cost effective for the ISP and you.
Encontro anual da comunidade Splunk, onde discutimos todas as novidades apresentadas na conferência anual da Spunk, a .conf24 realizada em junho deste ano em Las Vegas.
Neste vídeo, trago os pontos chave do encontro, como:
- AI Assistant para uso junto com a SPL
- SPL2 para uso em Data Pipelines
- Ingest Processor
- Enterprise Security 8.0 (Maior atualização deste seu release)
- Federated Analytics
- Integração com Cisco XDR e Cisto Talos
- E muito mais.
Deixo ainda, alguns links com relatórios e conteúdo interessantes que podem ajudar no esclarecimento dos produtos e funções.
https://www.splunk.com/en_us/campaigns/the-hidden-costs-of-downtime.html
https://www.splunk.com/en_us/pdfs/gated/ebooks/building-a-leading-observability-practice.pdf
https://www.splunk.com/en_us/pdfs/gated/ebooks/building-a-modern-security-program.pdf
Nosso grupo oficial da Splunk:
https://usergroups.splunk.com/sao-paulo-splunk-user-group/
Natural Is The Best: Model-Agnostic Code Simplification for Pre-trained Large...YanKing2
Pre-trained Large Language Models (LLM) have achieved remarkable successes in several domains. However, code-oriented LLMs are often heavy in computational complexity, and quadratically with the length of the input code sequence. Toward simplifying the input program of an LLM, the state-of-the-art approach has the strategies to filter the input code tokens based on the attention scores given by the LLM. The decision to simplify the input program should not rely on the attention patterns of an LLM, as these patterns are influenced by both the model architecture and the pre-training dataset. Since the model and dataset are part of the solution domain, not the problem domain where the input program belongs, the outcome may differ when the model is trained on a different dataset. We propose SlimCode, a model-agnostic code simplification solution for LLMs that depends on the nature of input code tokens. As an empirical study on the LLMs including CodeBERT, CodeT5, and GPT-4 for two main tasks: code search and summarization. We reported that 1) the reduction ratio of code has a linear-like relation with the saving ratio on training time, 2) the impact of categorized tokens on code simplification can vary significantly, 3) the impact of categorized tokens on code simplification is task-specific but model-agnostic, and 4) the above findings hold for the paradigm–prompt engineering and interactive in-context learning and this study can save reduce the cost of invoking GPT-4 by 24%per API query. Importantly, SlimCode simplifies the input code with its greedy strategy and can obtain at most 133 times faster than the state-of-the-art technique with a significant improvement. This paper calls for a new direction on code-based, model-agnostic code simplification solutions to further empower LLMs.
Online music portal management system project report.pdfKamal Acharya
The iMMS is a unique application that is synchronizing both user
experience and copyrights while providing services like online music
management, legal downloads, artists’ management. There are several
other applications available in the market that either provides some
specific services or large scale integrated solutions. Our product differs
from the rest in a way that we give more power to the users remaining
within the copyrights circle.
Development of Chatbot Using AI/ML Technologiesmaisnampibarel
The rapid advancements in artificial intelligence and natural language processing have significantly transformed human-computer interactions. This thesis presents the design, development, and evaluation of an intelligent chatbot capable of engaging in natural and meaningful conversations with users. The chatbot leverages state-of-the-art deep learning techniques, including transformer-based architectures, to understand and generate human-like responses.
Key contributions of this research include the implementation of a context- aware conversational model that can maintain coherent dialogue over extended interactions. The chatbot's performance is evaluated through both automated metrics and user studies, demonstrating its effectiveness in various applications such as customer service, mental health support, and educational assistance. Additionally, ethical considerations and potential biases in chatbot responses are examined to ensure the responsible deployment of this technology.
The findings of this thesis highlight the potential of intelligent chatbots to enhance user experience and provide valuable insights for future developments in conversational AI.