Search Results - (( data distribution sensor algorithm ) OR ( data distribution detection algorithm ))

Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
Get full text
Get full text

A systematic literature review on outlier detection in wireless sensor networks by Safaei, Mahmood, Asadi, Shahla, Driss, Maha, Boulila, Wadii, Alsaeedi, Abdullah, Chizari, Hassan, Abdullah, Rusli, Safaei, Mitra

“…Therefore, an efficient local/distributed data processing algorithm is needed to ensure: (1) the extraction of precise and reliable values from noisy readings; (2) the detection of anomalies from data reported by sensors; and (3) the identification of outlier sensors in a WSN. …”
Get full text
Get full text
Get full text

A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
Get full text

An Efficient Distributed Slotted Multi-Hop Wireless Mac Protocol For Internet Of Things by Sarvghadi, Mohammad Ali

Get full text
Get full text

Energy-Aware Routing Hole Detection Algorithm in the Hierarchical Wireless Sensor Network by Najm Us, Sama, Kartinah, Zen, Atiq Ur, Rahman, Aziz Ud, Din

“…In this paper a novel energy efficient routing hole detection (EEHD) algorithm is presented, on the detection of routing hole, the periodic re-clustering is performed to avoid the long detour path. …”
Get full text
Get full text
Get full text

Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

“…Current FDD technologies mostly rely on data-driven solutions by making full use of abundant process data collected by the state-of-the-art distributed process instruments and sensors. …”
Get full text
Get full text
Get full text

Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network by Sama, Najm Us

“…A Wireless Sensor Network (WSN) consists of spatially distributed autonomous sensors which produces a measurable response to a change in a physical or chemical condition, e.g. temperature and ground composition. …”
Get full text
Get full text

Improving Prediction Accuracy and Extraction Precision of Frequency Shift from Low-SNR Brillouin Gain Spectra in Distributed Structural Health Monitoring by Nordin N.D., Abdullah F., Zan M.S.D., Bakar A.A.A., Krivosheev A.I., Barkov F.L., Konstantinov Y.A.

“…Brillouin scattering; Concretes; Curve fitting; Data handling; Extraction; Fiber optic sensors; Fiber optics; Learning algorithms; Machine learning; Structural health monitoring; BOTDA; Brillouin frequency shift extraction; Brillouin frequency shifts; Brillouin gain spectrum; Correlation techniques; Distributed fiber-optic sensors; Frequency shift; Generalized linear model; Low signal-to-noise ratio; Prediction accuracy; Signal to noise ratio; algorithm; fiber optics; noise; signal noise ratio; Algorithms; Fiber Optic Technology; Noise; Signal-To-Noise Ratio…”

ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs by Khan, T., Singh, K., Hasan, M.H., Ahmad, K., Reddy, G.T., Mohan, S., Ahmadian, A.

“…However, a trust-based attack detection algorithm (TADA) assesses the reliability of SNs to detect internal attacks. …”
Get full text
Get full text

Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

“…Therefore, a new reference-free damage detection algorithm is proposed. The RWPE measurements of different sensor-to-sensor pairs are applied for defining the reference-free damage index (RDI) of each sensor location. …”
Get full text
Get full text
Get full text

Analysis on the Effect of Sensor Views in Image Reconstruction Produced by Optical Tomography System Using Charge-Coupled Device by Jamaludin J., Rahim R.A., Fazul Rahiman M.H., Mohd Rohani J.

Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model by Jasim, Ahmed Abdulhadi, Idris, Mohd Yamani Idna, Azzuhri, Saaidal Razalli, Issa, Noor Riyadh, Noor, Noorzaily Mohamed, Kakarla, Jagadeesh, Amiri, Iraj Sadegh

“…Furthermore, the attacks are detected and prevented by utilizing secure node authentication, data fragmentation algorithms, fully homomorphic encryption, and access control model. …”
Get full text
Get full text

Analysis on the Effect of Sensor Views in Image Reconstruction Produced by Optical Tomography System Using Charge-Coupled Device by Jamaludin J., Rahim, RA, Rahiman, MHF, Rohani, JM

Internet of Things-based Home Automation with Network Mapper and MQTT Protocol by Alam T., Rokonuzzaman M., Sarker S., Abadin A.F.M.Z., Debnath T., Hossain M.I.

Water quality monitoring using machine learning and IoT: a review by Hasan, Tahsin Fuad, Kabbashi, Nassereldeen Ahmed, Saleh, Tanveer, Alam, Md. Zahangir, Abd Wahab, Mohd Firdaus, Nour, Abdurahman Hamid

“…Long-term cost savings can be seen in different ways as reduced labor costs, lower operational costs, early detection and intervention prevent costly repairs and emergencies, minimized infrastructure costs, distributed IoT sensors reduce the need for extensive physical infrastructure, optimized resource allocation and efficiency improvements with IoT and Machine Learning in water quality monitoring can be highlighted in the following points, real-time monitoring: immediate data analysis allows for prompt adjustments and decision-making, enhanced accuracy, advanced sensors and algorithms improve data precision and reliability, scalability, systems can be easily expanded or adapted to meet evolving needs, predictive maintenance, automated systems proactively address issues before they escalate, reducing manual oversight. …”
Get full text
Get full text
Get full text
Get full text

Fault detection and diagnosis using correlation coefficients by Mak, Weng Yee

“…A fractionation column from a palm oil fractionation plant is chosen as the case study and the model of the case study is simulated in Matlab. Data collected with a process sampling time, TMSPC, of 4.6 hours and following the normal distribution are used as Nominal Operation Condition (NOC) data. …”
Get full text
Get full text

Charge-coupled device based on optical tomography system in detecting solid and transparent objects in non-flowing crystal clear water by Juliza Jamaludin, Rahim, RA, Rahim, HBA, Rahiman, MHF, Rohani, JM, Muji, SZBM

“…Tomography is a method to capture a cross-sectional image based on the data obtained by sensors, distributed around the periphery of the analyzed system. …”

Totally opportunistic routing algorithm for underwater wireless sensor network by Rahman, Ziaur

“…Whereas in NA-TORA, Expected Transmission Count (ETX) and residual energy of a node are considered for data transmission to ensure packet delivery. The suggested data forwarding algorithms are designed to abstain horizontal transmission, to lower end to end delay and improve throughput and energy efficiency. …”
Get full text
Get full text

Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Saleh Ahmed,, Ali Mohammed, Ali Majeed Alhammadi, Nafea, Ahmad Khalaf, Bashar, A. Mostafa, Salama

“…Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. …”
Get full text
Get full text
Get full text

Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Ahmed, Ali Mohammed Saleh, Majeed Alhammadi, Nafea Ali, Ahmad Khalaf, Bashar, A. Mostafa, Salama

“…Subsequently, this study proposes combining three deep learning algorithms, namely recurrent neural network (RNN), long short-term memory (LSTM)-RNN, and convolutional neural network (CNN), to build a bidirectional CNN-BiLSTM DDoS detection model. …”
Get full text
Get full text
Get full text