scholarly journals A Survey of Outlier Detection Techniques in IoT: Review and Classification

2022 ◽  
Vol 11 (1) ◽  
pp. 4
Author(s):  
Mustafa Al Samara ◽  
Ismail Bennis ◽  
Abdelhafid Abouaissa ◽  
Pascal Lorenz
Keyword(s):  
Outlier Detection ◽  
Large Scale ◽  
Base Station ◽  
Home Networks ◽  
Detection Techniques ◽  
Advantages And Disadvantages ◽  
Large Scale Networks ◽  
Data Efficiency ◽  
Different Sources

The Internet of Things (IoT) is a fact today where a high number of nodes are used for various applications. From small home networks to large-scale networks, the aim is the same: transmitting data from the sensors to the base station. However, these data are susceptible to different factors that may affect the collected data efficiency or the network functioning, and therefore the desired quality of service (QoS). In this context, one of the main issues requiring more research and adapted solutions is the outlier detection problem. The challenge is to detect outliers and classify them as either errors to be ignored, or important events requiring actions to prevent further service degradation. In this paper, we propose a comprehensive literature review of recent outlier detection techniques used in the IoTs context. First, we provide the fundamentals of outlier detection while discussing the different sources of an outlier, the existing approaches, how we can evaluate an outlier detection technique, and the challenges facing designing such techniques. Second, comparison and discussion of the most recent outlier detection techniques are presented and classified into seven main categories, which are: statistical-based, clustering-based, nearest neighbour-based, classification-based, artificial intelligent-based, spectral decomposition-based, and hybrid-based. For each category, available techniques are discussed, while highlighting the advantages and disadvantages of each of them. The related works for each of them are presented. Finally, a comparative study for these techniques is provided.

scholarly journals A Survey of Methods for Gas-Lift Optimization

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Kashif Rashid ◽  
William Bailey ◽  
Benoît Couët
Keyword(s):  
Large Scale ◽  
Optimization Problem ◽  
Multivariate Optimization ◽  
Flow Lines ◽  
Single Well ◽  
Large Scale Networks ◽  
Optimization Schemes ◽  
Gas Lift ◽  
Insight Into

This paper presents a survey of methods and techniques developed for the solution of the continuous gas-lift optimization problem over the last two decades. These range from isolated single-well analysis all the way to real-time multivariate optimization schemes encompassing all wells in a field. While some methods are clearly limited due to their neglect of treating the effects of inter-dependent wells with common flow lines, other methods are limited due to the efficacy and quality of the solution obtained when dealing with large-scale networks comprising hundreds of difficult to produce wells. The aim of this paper is to provide an insight into the approaches developed and to highlight the challenges that remain.

GROUP COGNITIVE THERAPY: TREATMENT OF CHOICE OR SUB-OPTIMAL OPTION?

2001 ◽  
Vol 29 (3) ◽  
pp. 311-332 ◽  
Author(s):  
Norma Morrison
Keyword(s):  
Group Therapy ◽  
Cognitive Therapy ◽  
Large Scale ◽  
Cost Effective ◽  
Advantages And Disadvantages ◽  
Quality Of Therapy ◽  
Group Format ◽  
Cognitive Behavioural ◽  
Therapy Treatment

In the present climate of limited resources and long waiting lists, it is not surprising that there is more emphasis on making sure that psychological treatments are not only clinically sound but also cost-effective. One solution to this is to provide time-limited, focused interventions such as cognitive therapy. Another obvious solution is to deliver treatment in groups rather than individually. However, what evidence is there that therapy can be delivered as effectively in groups as individually? This review will look at which different formats have been tried, what the advantages and disadvantages of those formats might be, which client groups have been targeted for cognitive- behavioural group therapy (CBGT), and whether a group format in general offers any advantages over individual CBT. Outcome studies and their implications for the use of CBGT are considered. Results suggest that, in most client groups, there is little difference in efficacy between group and individual CBT, although there is some evidence that results for some types of patient can be disappointing in CBGT. It may be that the best compromise in terms of cost- effectiveness between quality of therapy and quantity of patients treated is offered by large-scale psychoeducational didactic group therapy.

scholarly journals Analisis Perbandingan Quality Of Service (Qos) Pada Performa Bandwidth Jaringan Dengan Metode Hierarchical Token Bucket (Htb) Dan Per Connection Queque (Pcq).

Respati ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. 24
Author(s):  
Adytia A. Tambunan ◽  
Lukman Lukman
Keyword(s):  
Quality Of Service ◽  
Large Scale ◽  
Improve Quality ◽  
Bandwidth Management ◽  
Available Bandwidth ◽  
Service Parameter ◽  
Token Bucket ◽  
Large Scale Networks ◽  
Network Administrators

INTISARIQuality of Service (QoS) adalah cara cerdas untuk mengalokasikan bandwidth yang tersedia. Penggunaan manajemen bandwidth sebagai parameter Quality of Service tidak hanya membatasi tetapi menjaga kualitas bandwidth, sehingga semua pengguna yang terhubung dalam satu jaringan mendapatkan kualitas internet yang merata dan stabil. Ada beberapa cara untuk mengaplikasikan bandwidth managemen untuk meningkatkan Quality of Service, salah satunya yakni menggunakan mikrotik.Ada banyak metode manajemen   bandwidth yang dapat digunakan atau diterapkan pada jaringan yang menggunakan router mikrotik. Adapun yang paling sering digunakan dalam jaringan berskala menengah atau pun besar seperti metode Hierarchical Token Bucket (HTB) dan Per Connection Queue (PCQ).Penelitian ini akan melakukan analisis variabel Quality of Service (QoS) terhadap performa bandwidth dengan membandingkan dua metode antrian yaitu metode Hierarchical Token Bucket (HTB) dan metode Per Connection Queue (PCQ).  Penelitian dilakukan untuk mengetahui metode manakah lebih baik untuk di implementasikan oleh administrator jaringan agar efesien dan tepat untuk digunakan.Kata kunci: Manajemen Bandwidth, QOS, PCQ, HTB, Mikrotik. ABSTRACTQuality of Service (QoS) is a smart way to allocate available bandwidth. The use of bandwidth management as a Quality of Service parameter not only limits but maintains bandwidth quality, so that all users connected in one network get an even and stable internet quality. There are several ways to apply bandwidth management to improve Quality of Service, one of which is using a proxy.There are many bandwidth management methods that can be used or applied to networks that use a proxy router. As for what is most often used in medium or large scale networks such as the Hierarchical Token Bucket (HTB) and Per Connection Queue (PCQ) methods.This study will analyze the Quality of Service (QoS) variable on bandwidth performance by comparing two queuing methods, namely the Hierarchical Token Bucket (HTB) method and the Per Connection Queue (PCQ) method. The study was conducted to determine which method is better for network administrators to implement in order to be efficient and appropriate to use.Keywords: Bandwidth Management, QOS, PCQ, HTB, Mikrotik.

scholarly journals MOBILE NETWORKING FOR “SMART DUST” WITH RFID SENSOR NETWORKS

2013 ◽  
pp. 272-276
Author(s):  
SHYAM D. BAWANKAR ◽  
SONAL B. BHOPLE ◽  
VISHAL D. JAISWAL
Keyword(s):  
Sensor Networks ◽  
Large Scale ◽  
Mobile Network ◽  
Base Station ◽  
Sensor Nodes ◽  
Node Localization ◽  
Fine Grained ◽  
Mobile Networking ◽  
Smart Dust ◽  
Large Scale Networks

Large-scale networks of wireless sensors are becoming an active topic of research.. We review the key elements of the emergent technology of “Smart Dust” and outline the research challenges they present to the mobile networking and systems community, which must provide coherent connectivity to large numbers of mobile network nodes co-located within a small volume. Smart Dust sensor networks – consisting of cubic millimeter scale sensor nodes capable of limited computation, sensing, and passive optical communication with a base station – are envisioned to fulfil complex large scale monitoring tasks in a wide variety of application areas. RFID technology can realize “smart-dust” applications for the sensor network community. RFID sensor networks (RSNs), which consist of RFID readers and RFID sensor nodes (WISPs), extend RFID to include sensing and bring the advantages of small, inexpensive and long-lived RFID tags to wireless sensor networks. In many potential Smart Dust applications such as object detection and tracking, fine-grained node localization plays a key role.

scholarly journals Large Scale MIMO Analysis Using Enhanced LAMA

2021 ◽  
Author(s):  
Hanumantharao Bitra ◽  
Palanisamy Ponnusamy
Keyword(s):  
Message Passing ◽  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Research Work ◽  
Base Station ◽  
Superior Performance ◽  
Gram Matrix ◽  
Data Detection ◽  
Detection Techniques

Abstract In this research work, a novel enhanced large scale multi-input multi-output (MIMO) approximate message passing (LAMA) based optimal data detection is proposed for large scale MIMO systems. Existing LAMA and sub-optimal detection techniques suffer from iteration complexity and performance loss in finite dimensional systems due to large scale user fading. To over come these, Gram matrix and message damping techniques are incorporated in the traditional LAMA. The effectiveness of the proposed enhanced LAMA and existing techniques are analyzed with 64, 32 and 16 user antennas, 256, 128, 64 and 16 base station elements with 64QAM, 16QAM, QPSK and BPSK. The simulation results show that the proposed enhanced LAMA gives superior performance when compared to existing matrix inversion methods such as Gauss sidle and Neumann, box techniques such as optimal co-ordinate descent and alternating direction method of multipliers based on the infinity norm, minimum mean square error and LAMA.

PageRank Algorithm-Based Recommender System Using Uniformly Average Rating Matrix

2019 ◽  
pp. 99-112
Author(s):  
Bathrinath S. ◽  
Saranyadevi S. ◽  
Thirumalai Kumaran S. ◽  
Saravanasankar S.
Keyword(s):  
Recommender Systems ◽  
Large Scale ◽  
User Behavior ◽  
Personalized Recommendation ◽  
Pagerank Algorithm ◽  
Large Scale Networks ◽  
Matrix Construction ◽  
Item Item ◽  
New Item

Applications of web data mining is the prediction of user behavior with respect to items. Recommender systems are being applied in knowledge discovery techniques to the problem of making decisions on personalized recommendation of information. Traditional CF approaches involve the amount of effort increases with number of users. Hence, new recommender systems need to be developed to process high quality recommendations for large-scale networks. In this chapter, a model for UAR matrix construction method for item rank calculations, a Page Rank-based item ranking approach are proposed. The analysis of various techniques for computing item-item similarities to identify relationship between the selected items and to produce a qualified recommendation for users to acquire the items as their wish. As a result, the new item rank-based approaches improve the quality of recommendation outcome. Results show that the proposed UAR method outperforms than the existing method. The same method is applied for the large real-time rating dataset like Movie Lens.

scholarly journals Adaptive solar shading of buildings

2018 ◽  
Vol 9 (2) ◽  
pp. 107-113
Author(s):  
J. Hraska
Keyword(s):  
Large Scale ◽  
Energy Performance ◽  
Climate Conditions ◽  
Climatic Regions ◽  
Advantages And Disadvantages ◽  
European Climate ◽  
Solar Shading ◽  
The Individual

Adaptive solar shading systems have in comparison with the traditional systems of shading increased potential ability to improve the quality of the indoor environment and to increase the energy performance of buildings. Their extension allows all-around technological progress, but also the extensive application of large-scale glazing in building envelopes almost in all climatic regions. The literature review shows that the characteristics of the individual adaptive shading systems differ. Some have better performance in the sun protection or in improving the building's energy balance; others for example are better in glare elimination or in redistribution of daylight. The main purpose of this contribution is to provide a classification of the adaptive solar shading systems. In the article are compared merits and shortcomings of adaptive shading systems and are shortly analyzed assumptions of their wider application in central European climate conditions. Attention is also given to advantages and disadvantages, which brings the application of some kinds of adaptive solar shading systems. Several examples of adaptive shading systems are shown and briefly characterized.

scholarly journals METHODS FOR SENTINEL LYMPH NODE DETECTION IN PATIENTS WITH BREAST CANCER

2020 ◽  
Vol 19 (5) ◽  
pp. 88-96
Author(s):  
A. D. Zikiryakhodzhaev ◽  
T. I. Grushina ◽  
M. V. Starkova ◽  
L. P. Kazaryan ◽  
Yu. I. Volkova ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Sentinel Lymph Node ◽  
Lymph Node Biopsy ◽  
Detection Methods ◽  
Sentinel Lymph Node Detection ◽  
Detection Techniques ◽  
Advantages And Disadvantages ◽  
Node Biopsy

Objective: to provide various methods for sentinel lymph node detection considering their advantages and disadvantages.Material and Methods. The search of the relevant articles published in Pubmed, MedLine, RINTs, etc. database was conducted. 49 publications from 1970 to 2018 were analyzed.Results. Currently, sentinel lymph node biopsy (SLN biopsy) has become a worthy alternative to traditional lymphatic surgery for early breast cancer. SLN biopsy significantly decreases the number of postoperative complications caused by lymphadenectomy and improves the quality of life of cancer patients. So far, a large number of SLN detection techniques have accumulated. Each of these techniques has its own advantages and disadvantages.Conclusion. Despite a large number of SLN detection methods, the question of the optimal technique is currently debatable. 

scholarly journals Charge critical sensors first: Minimize data loss in wireless rechargeable sensor networks

2018 ◽  
Vol 14 (7) ◽  
pp. 155014771878447
Author(s):  
Tong Li ◽  
Tang Liu ◽  
Jian Peng ◽  
Feng Lin ◽  
Wenzheng Xu
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Large Scale ◽  
Base Station ◽  
The Novel ◽  
Monitoring Task ◽  
Wireless Rechargeable Sensor Networks ◽  
Alternative Routing ◽  
The Impact

In this article, we study the scheduling of a charging vehicle to replenish sensor energy in a large-scale wireless sensor network, by utilizing the novel wireless energy transfer technology. We note that existing studies do not treat different sensors in the network discriminatively and consider only how to charge as many sensors as possible before their energy expirations. However, there are some critical sensors in the network, so that many other sensors have no alternative routing paths to upload their sensing data to the base station if the critical sensors die. Therefore, the energy expiration of a critical sensor will result in that not only the sensor itself cannot continue its monitoring task, but also many other sensors cannot send their data during the dead period of the critical sensor. Then, the monitoring quality of the sensor network will significantly deteriorate due to the energy expirations of the critical sensor. Unlike existing studies, we take into account the impact of energy depletions of critical sensors and investigate a charging scheduling problem for sensor networks, which is to schedule a charging vehicle to replenish a set of to-be-charged sensors, such that not only the amount of lost data by dead sensors is minimized, but also the traveling cost of the vehicle for charging sensors is minimized, too. We then propose a novel algorithm for the problem. We finally compare the proposed algorithm with existing studies and simulation results show that the amount of lost data by the proposed algorithm is only about 50% of those by the existing studies, and the weighted sum of the amount of lost data and the vehicle travel distance is about 70% of those by the existing ones.

Sign in / Sign up

Export Citation Format

Share Document