The stream data acquired by heterogeneous Internet of Things (IoT) sensors are seldom perfect. Most the collected streams include either missing or abnormal values caused various factors such as failure, malfunction, integrity attacks. Such unreliable affect real-time monitoring and compromise quality analysis. By simply analyzing sensor via anomaly detection, applications may still be over incomplete streams. Therefore, a reliable method for recovering detecting ones is indispensable in IoT...

Machine-based generation of clinical pathways that utilizes sequential pattern mining to extract the from historical electronic medical record (EMR) systems has gained much attention. We previously proposed a method generate including time intervals provides rich information workers. However, this is difficult use in real applications because slow pathway as large number duplicate patterns are included. In paper, speed up generation, we deploy an occurrence check adds only closed results...

Electronic medical record systems have been adopted by many large hospitals worldwide, enabling the recorded data to be analyzed various computer-based techniques gain a better understanding of hospital-based disease treatments. Among such techniques, sequential pattern mining, already widely used for mining and knowledge discovery in other application domains, has shown great potential discovering frequent patterns sequences However, studies yet evaluate use medical-order sequence variants...

Many heterogeneous sensors exhibit a strong correlation in both space and time that can be used to enhance the abnormal node detection problem wireless sensor network (WSN). Corruption these correlations has been shown effective detecting false data injection attacks. However, extracting such is considered challenging task WSNs. In this paper, we adopt new cross-correlation-based method extract relationships. It utilizes observed spatiotemporal (ST) multivariate-attribute (MVA) decide...

Power-saving storage in data centers is now gaining much interest because of the increase power requirements. In particular, with expansion services requiring distributed-processing frameworks, proportionality power-aware file systems attracting great attention from academia and industry. The concept that a system should perform work proportion to energy it consumes. To provide this important characteristic, placement methods enable operate multiple gears, each containing different number...

The Internet of things (IoT) is a distributed, networked system composed many embedded sensor devices. Unfortunately, these devices are resource constrained and susceptible to malicious data-integrity attacks failures, leading unreliability sometimes major failure parts the entire system. Intrusion detection handling essential requirements for IoT security. Nevertheless, as far we know, area has yet receive much attention. Most previous intrusion-detection methods proposed IoT, particularly...

In wireless sensor networks (WSNs), data can be subject to malicious attacks and failures, leading unreliability. This vulnerability poses a challenge environmental monitoring applications by creating false alarms. To guarantee trustworthy system, we therefore need detect abnormal nodes. this paper, propose new framework for detecting nodes in clustered heterogeneous WSNs. It makes use of observed spatiotemporal (ST) multivariate-attribute (MVA) correlations, while considering the background...

Electronic medical record (EMR) systems have now been widely adopted to support workers. There also has much interest in the machine-based generation of clinical pathways that can utilize sequential pattern mining (SPM) extract them from historical EMR systems. However, existing methods do not protect individual privacy, even though they involve sensitive data. To ensure privacy data, this paper describes two algorithms deploy differential by adding noise during calculations SPM considering...

Power-aware distributed file systems for efficient Big Data processing are increasingly moving towards power-proportional designs. However, current data placement methods such have not given careful consideration to the effect of gear-shifting during operations. If system wants shift a higher gear, it must reallocate updated datasets that were modified in lower gear when subset nodes was inactive, but without disrupting servicing requests from clients. Inefficient requires large amount...

Recently, combining a video recording of presentation along with the digital slides used in it has become popular e-learning and archives. For users archives, is useful to preview digest such content grasp atmosphere and/or an outline presentation. This paper proposes method automatic generation by extracting important scenes from content. The extracted are chosen based on several factors as frequency specificity words, scene duration order. Finally, effectiveness proposed methods evaluated...

Energy-aware commodity-based distributed file systems for efficient Big Data processing are increasingly moving towards power-proportional designs. However, current data placement methods such have not given careful consideration to the effect of gear-shifting during operations. If system wants shift a higher gear, it must reallocate updated datasets that were modified in lower gear when subset nodes was powered off, but without disrupting servicing requests from clients. Inefficient...

Energy-aware distributed file systems are increasingly moving toward power-proportional designs. However, current works have not considered the cost of updating data sets that were modified in a low-power mode, where subset nodes powered off. In detail, when system moves to high-power it must internally replicate updated reactivated nodes. Effectively reflecting is vital making system, such as Hadoop Distributed File System (HDFS), power proportional. HDFS design, changes block replication...

Entity-relation extraction aims to jointly solve named entity recognition (NER) and relation (RE). Recent approaches use either one-way sequential information propagation in a pipeline manner or two-way implicit interaction with shared encoder. However, they still suffer from poor due the gap between different task forms of NER RE, raising controversial question whether RE is really beneficial NER. Motivated by this, we propose novel unified cascade framework that combines advantages both...

Diffusion models excel at high-quality image and video generation. However, a major drawback is their high latency. A simple yet powerful way to speed them up by merging similar tokens for faster computation, though this can result in some quality loss. In paper, we demonstrate that preserving important during significantly improves sample quality. Notably, the importance of each token be reliably determined using classifier-free guidance magnitude, as measure strongly correlated with...

The recent performance improvements in commodity hardware have made server-based storage a practical alternative to dedicated-storage appliances. Because of the low reliability servers, data redundancy across multiple servers is required for high availability system. However, extra capacity enable this increases system cost significantly. Although erasure coding (EC) promising approach reducing amount redundant data, it only available systems using distributed storage. There remains need...

With the increasing use of electronic medical records, support from analysis accumulated information is expected. Currently, new treatment methods and drugs are being developed for diseases, but transition history orders has yet to be visualized diseases such as COVID-19. In this paper, we sequential pattern mining extract frequent then apply longest common subsequence variant (LCSV) merged sequence (MSV) analyze differences in patterns at different times. We also propose three types sliding...

Next-item recommendation solutions based on sequential pattern mining have been widely used in empirical studies. However, current do not consider recommendations involving large combinations of items with varied values. For example, inspecting many specimens is key to understanding a patient's health status and checking medical prescription's effectiveness. Typically, specimen inspection may involve dozens selected from more than thousand possible items, each item being associated measured...

Sequential pattern mining (SPM) is widely used for data and knowledge discovery in various application domains. Recently, we have proposed an analyzing method to evaluate the sequence variant (SPV) that original containing frequent patterns including variants. Such a study meaningful medical tasks such as improving quality of disease's treatment method. This paper aims effectiveness more detail when it was applied Electronic Medical Record Systems. Using real dataset, observed successful...