Bad Link Research Articles

Interbank systemic risk network in an emerging economy

PurposeInterconnections among banks are an essential feature of the banking system as it helps in an effective payment system and liquidity management. However, it can be a nightmare during a crisis when these interconnections can act as contagion channels. Therefore, it becomes essentially important to identify good links (non-contagious channels) and bad links (contagious channels).Design/methodology/approachThe article estimated systemic risk using quantile regression through the ΔCoVaR approach. The interconnected phenomenon among banks has been analyzed through Granger causality, and the systemic network properties are evaluated. The authors have developed a fixed effect panel regression model to predict interconnectedness. Profitability-adjusted systemic index is framed to identify good (non-contagious) or bad (contagious) channels. The authors further developed a logit model to find the probability of a link being non-contagious. The study sample includes 36 listed Indian banks for the period 2012 to 2018.FindingsThe study indicated interconnections increased drastically during the Indian non-performing asset crisis. The study highlighted that contagion channels are higher than non-contagious channels for the studied periods. Interbank bad distance dominates good distance, highlighting the systemic importance of banking network. It is also found that network characteristics can act as an indicator of a crisis.Originality/valueThe study is the first to differentiate the systemic contagious and non-contagious channels in the interbank network. The uniqueness also lies in developing the normalized systemic index, where systemic risk is adjusted to profitability.

The problem of false positives in automated census linking: Nineteenth-century New York’s Irish immigrants as a case study

Automated census linkage algorithms have become popular for generating longitudinal data on social mobility, especially for immigrants and their children. But what if these algorithms are particularly bad at tracking immigrants? This study utilizes a database on nineteenth-century Irish immigrants, generated from the most widely used algorithms, created by Abramitzky, Boustan, and Eriksson (ABE). Our objective is to assess the extent to which different individuals are erroneously linked together across census years and the consequences of these “false positives” for calculating social mobility. Our findings raise serious questions about the quality of the matches generated by the “first generation” of automated census linkage algorithms. False positives range from about one-third to one-half of all links. These bad links lead to sizeable estimation errors when measuring Irish immigrant social and geographic mobility.

Spam Detection in Connected Networks Using Particle Swarm and Genetic Algorithm Optimization: Youtube as a Case study

Although there are many networks security tools, both wire and wireless connected networks are still suffering from many types of attacks. YouTube's meteoric rise to prominence as a social platform speaks for itself. The sheer volume of comments on YouTube has made it an ideal medium for spammers to spread their malicious software. Phishing attacks, in which anyone who clicks on a bad link might be a victim, have contributed to this problem. Classification systems may be used to examine spam for its unique characteristics and identify it. This is why it is suggested that YouTube already has built-in mechanisms for identifying spam. A YouTube Spam detection framework was designed with the five stages of data collection, pre-processing, features extraction, classification, and detection, allowing for the execution of the tests. To analyze and validate each stage of the YouTube detection methodology presented in this study, two metaheuristic optimization methods are employed to optimize the parameters of a new voting ensemble classifier. These methods are the particle swarm optimization (PSO) and the Genetic Algorithm (GA). The ensemble model is based on three classifiers: neural. Results indicate that the proposed approach is accurate. In addition, statistical analysis is performed to emphasize the superiority and effectiveness of the proposed methodology.

A New WoT Cryptography Algorithm Based on GOST and Novel 5d Chaotic System

The concept Web of Things (WoT) goes well beyond the emphasis on the Internet as a means of sharing data, instead of introducing all resources and connections involving computers, data, and people to the Web. It, therefore, focuses on a range of problems and opportunities, thus paving the way for several exciting industries applications. In cryptography a range of main characteristics of chaotic systems such as non-linearity, initial condition sensitivity, and mixing properties are available. These characteristics provide an essential connection between cryptography and chaos. GOST block cipher is based on secret key secrecy. However, when the encryption process with the same key is used for plaintext, the same cipher text is created. Message replication can be easily detected by an adversary who is a bad link in every communication. In this paper, propose to use a 5d chaotic system combined with GOST block cipher to create a new secure Web of Things (WoT) cryptography system. The 5D chaotic system was used to generate chaotic random keys used in GOST algorithm to provide proper security with as high hardness randomly enhances the NIST fifteen statistical tests and modifies key schedule as security operations.

Design and Optimization for Energy-Efficient Full-Duplex Transmission With Direct Links

Full-duplex (FD) technique has been extensively studied recently, due to its effective improvement in spectral efficiency (SE) and significant advance on self-interference cancellation (SIC). Relay technique can expand network coverage, reduce power consumption and improve energy efficiency (EE) under bad direct links situation. Combining the FD technique with the relay technique can further improve the system’s SE and EE. In this paper, both bidirectional direct and relay FD transmission strategies for transmitting the signal as much as possible with fewer antennas and less self-interference are designed first. At the same time, the SE analysis of the designed transmission strategies under the existence of residual self-interference (RSI) is given. In addition, minimum total energy consumption (TEC) problems and their solutions of the designed transmission strategies with joint optimization of transmit power (TP) and transmit time (TT) are given. The minimum TEC problems consider non-ideal power amplifiers (PAs) efficiency and non-negligible circuit powers (CPs) consumption. Furthermore, a simple EE analysis of the designed transmission strategies with symmetric and asymmetric transmission tasks in two directions is given. Simulations reveal that when RSI coefficients are below 0.2, our two-way FD relay transmission (TWFDT) strategy can improve the system’s SE and EE.

Lightweight, Fluctuation Insensitive Multi-Parameter Fusion Link Quality Estimation for Wireless Sensor Networks

Accurate and agile link quality estimation is essential for wireless sensor networks. Using the mapping models between physical layer parameters and packet reception ratio, link quality can be estimated with advantages of high agility and low overhead. However, existing estimators based on physical layer parameters fail to utilize link quality information carried by different physical layer parameters efficiently and effectively and fail to effectively solve the problem that physical layer parameters fluctuate greatly, which makes them difficult to describe link conditions really. In this study, a lightweight, fluctuation insensitive multi-parameter fusion link quality estimator is proposed. Two physical layer parameters, Signal-to-Noise Ratio and Link Quality Indicator are preprocessed by exponential weighted Kalman filtering to get more stable estimation values. Then, these two parameters are fused using lightweight weighted Euclidean distance to fully utilize link quality information carried by them. On this basis, link quality is estimated quantitatively with the mapping model of the fused parameter and packet reception ratio, which is constructed by logistic regression. Experimental results show that the proposed estimator could reflect link quality more realistically. Compared with similar estimators, estimate error of the proposed one is reduced by 18.32% to 60.11% under moderate and bad links with large fluctuations, by 1.42% to 83.43% under sudden changed links, and by 16.64% to 65.61% under a long-time link. More importantly, computation overhead of the proposed estimator is equivalent to that of single-parameter estimators, but much less than other multi-parameter fusion estimators. Compared with the later, computation overhead is reduced by 72.36% to 95.61%.

Characterizing Urban Vehicle-to-Vehicle Communications for Reliable Safety Applications

The IEEE 802.11p-based dedicated short range communication (DSRC) is essential to enhance driving safety and improve road efficiency by enabling rapid cooperative message exchanging. However, there is a lack of good understanding on the DSRC performance in urban environments for vehicle-to-vehicle (V2V) communications, which impedes its reliable and efficient application. In this paper, we first conduct intensive data analytics on V2V performance, based on a large amount of real-world DSRC communications trace collected in Shanghai city, and obtain several key insights as follows. First, among many context factors, the non-line-of-sight (NLoS) link condition is the major factor degrading V2V performance. Second, the durations of line-of-sight (LoS) and NLoS transmission conditions follow power law distributions, which indicate that the probability of experiencing long LoS/NLoS conditions both could be high. Third, the packet inter-reception (PIR) time distribution follows an exponential distribution in the LoS conditions but a power law in the NLoS conditions, which means that the consecutive packet reception failures rarely appear in the LoS conditions but can constantly appear in the NLoS conditions. Based on these findings, we propose a context-aware reliable beaconing scheme, called CoBe , to enhance the broadcast reliability for safety applications. The CoBe is a fully distributed scheme, in which a vehicle first detects the link condition with each of its neighbors by machine learning algorithms, then exchanges such link condition information with its neighbors, and finally selects the minimal number of helper vehicles to rebroadcast its beacons to those neighbors in bad link condition. To analyze and evaluate the CoBe performance, a two-state Markov chain is devised to model beaconing behaviors. The extensive trace-driven simulations are conducted to demonstrate the efficacy of CoBe .

Collaborative Search Engine for Enhancing Personalized User Search Based on Domain Knowledge.

In the fast moving world, users cross over large amount of data for their daily life. Due to the misinterpretation of the context, user cannot retrieve the proper context or failure to retrieve the information. The main aim of this paper is to design and implement a personalized search engine which works based on the domain of the user with the specific constraints suggested by the user. In this paper, the proposed system, build a search engine with web content which get information from the document corpus for the domain through the cloud databases. Web search engine re-ranks the generic results based on a ranking of a context linked with the domain. In this system, collaborative search service helps to improve the relevancy of the search results and to reduce the overtime on bad links and hence caters to customized needs with collaborative feedback using fuzzy decision tree based on fuzzy rules.

Adaptive Fuzzy-Based Energy and Delay-Aware Routing Protocol for a Heterogeneous Sensor Network

In a heterogeneous sensor actor network, packet loss may occur due to bad link quality, overflow of buffer, and low energy levels. Retransmission of the lost packets leads to more energy consumption and delay. Ensuring data reliability and minimum delay requirement while improving energy efficiency are challenging issues in a resource-constrained heterogeneous sensor actor network. In this paper, a fuzzy-based delay and energy-aware intelligent routing mechanism has been proposed to select efficient routes. In the proposed mechanism, routing decisions are taken using a fuzzy logic system by considering network resources, such as residual energy, quality of link, available buffer size, and distance (proximity). In a network, a node with higher residual energy, higher free available buffer, good link quality, and close distance (proximity) gets opportunity to become a next hop node in a routing path. Furthermore, network performance has been analyzed with various network states. Simulation has been carried out using Network Simulator 3 by considering performance metrics, such as delay, number of retransmissions, energy consumption, lifetime, and network stability of the network.

Design-Based Estimation with Record-Linked Administrative Files and a Clerical Review Sample

Abstract This article looks at the estimation of an association parameter between two variables in a finite population, when the variables are separately recorded in two population registers that are also imperfectly linked. The main problem is the occurrence of linkage errors that include bad links and missing links. A methodology is proposed when clerical-reviews may reliably determine the match status of a record-pair, for example using names, demographic and address information. It features clerical-reviews on a probability sample of pairs and regression estimators that are assisted by a statistical model of comparison outcomes in a pair. Like other regression estimators, this estimator is design-consistent regardless of the model validity. It is also more efficient when the model holds.

A web page distillation strategy for efficient focused crawling based on optimized Naïve bayes (ONB) classifier

The target of a focused crawler (FC) is to retrieve pages related to a specific domain of interest (DOI). However, FCs may be hasted if bad links were injected into their crawling queue. Hence, they will be gradually skewed away from their DOI. This paper introduces an effective modification on the behavior of FCs by adding a domain distiller. Hence, before passing the retrieved page to the indexer or embedding its links into the crawling queue, the page must pass through a domain distiller. The proposed domain distiller relies on an Optimized Naïve Bayes (ONB) classifier, which combines naïve Bayes (NB) and Support Vector Machines (SVM). Initially, genetic algorithm (GA) is used to optimize the soft margins of SVM. Then the optimized SVM is employed to eliminate the outliers from the available training examples. Next, the pruned examples are used to train the traditional NB classifier. Moreover, ONB employs word sense disambiguation (WSD) to identify the accurate sense of each domain keyword extracted from the input page. This is accomplished by using a proposed domain ontology, which is called Disambiguation Domain Ontology (D2O). ONB has been tested against recent classification techniques. Experimental results have proven the effectiveness of ONB as it introduces the maximum classification accuracy. Also, results indicate that the proposed distiller improves the performance of focused crawling in terms of crawling harvest rate.

Intelligent Management of Multiple Access Schemes in Wireless Body Area Network

Wireless Body Area Network is a novel technology to provide efficient, convenient and safe health, medical and personal entertainment services but it still faces longstanding challenges in the application. A smart communication standard is essential to solve some problems in wireless data transmission and optimize system performance. This paper proposes an intelligent management of multiple access schemes for contention access and contention free access with game theory. The strategies are determined by requirements of applications and channel status. Nodes in a network choose various strategies for best payoff according to different conditions including normal status, packets-oriented services, emergent situation and bad link states with specific utility functions. The novel management model supports flexible resource allocation and enhances the system performance, which are evaluated by simulations of Castalia under various conditions.

Usibility Evaluation of some Selected Nigerian Universities' Websites

This study carried out a usability evaluation of some selected Nigerian universities websites. A total number of ten randomly selected universities though; mostly first and second generations universities were taken into account. This was done by making use of automated tools such as web page analyzer and HTML toolbox for data collection. The internal attributes that were taken into consideration embodied Total number of html files, Total html page size, Total size of images, Total number of images, Total number of external files, Total size of external files, as well as Load time, HTML check and repair, Browsers compatibility, Pages with bad links respectively and the various values were collected and analysed and presented in the graphical form using bar charts. The results showed that some of universities' websites adhered to the laid down threshold values of these attributes while some are still very much lacking. These include University of Calabar, Nnmadi Azikiwe University and University of Ibadan. Generally there it was also observed that no single university adhered to the threshold values as stipulated by the two automated tools used. A conclusion was made and some necessary suggestions were also proffered so as to enhance the usability of the stated universities' websites.

Collaborative search using an implicitly formed academic network

Purpose – The purpose of this paper is to propose the Collaborative Search System that attempts to achieve collaboration by implicitly identifying and reflecting search behaviour of collaborators in an academic network that is automatically and dynamically formed. By using the constructed Collaborative Hit Matrix (CHM), results are obtained that are based on the search behaviour and earned preferences of specialist communities of researchers, which are relevant to the user's need and reduce the time spent on bad links. Design/methodology/approach – By using the Digital Bibliography Library Project (DBLP), the research communities are formed implicitly and dynamically based on the users’ research presence in the search environment and in the publication scenario, which is also used to assign users’ roles and establish links between the users. The CHM, to store the hit count and hit list of page results for queries, is also constructed and updated after every search session to enhance the collaborative search among the researchers. Findings – The implicit researchers community formation, the assignment and dynamic updating of roles of the researchers based on research, search presence and search behaviour on the web as well as the usage of these roles during Collaborative Web Search have highly improved the relevancy of results. The CHM that holds the collaborative responses provided by the researchers on the search query results to support searching distinguishes this system from others. Thus the proposed system considerably improves the relevancy and reduces the time spent on bad links, thus improving recall and precision. Originality/value – The research findings illustrate the better performance of the system, by connecting researchers working in the same field and allowing them to help each other in a web search environment.

Spectral-efficiency and Demand-based Joint Relay and Bandwidth Assignment for Cooperative Relay Network

Cooperative communication system by exploiting multiple relay nodes (RN) offers significant performance improvement in terms of coverage and capacity. However, using all available RNs in the network is not optimal. Some RNs are located far from user equipment (UE), or having bad link quality due to fading and shadowing. Therefore, only several RNs with good link quality to the UE need to be chosen. Furthermore, in a high user density network, bandwidth is limited which requires proper resource allocation. In addition, each UE has different traffic demand to be satisfied. There are scenarios where eNodeB (eNB) and RN are wasting their resources to UE with low demand, whereas the resources can be used for different UE to compensate for its high demand. In this project, joint problem of relay and bandwidth assignment in a network with heterogeneous user traffic are studied. Accordingly, a Spectral-efficiency and Demand-based Joint Relay and Bandwidth Assignment (SE-D-JRBA) scheme is proposed which is flexible for network with diverse user traffic demands. Numerical evaluation is analyzed for SE-D-JRBA with full-duplex (FDX) and half-duplex (HDX) RN and decode-and-forward (DCF) operation, hence compared to system without relay cooperation. The results demonstrated that the proposed method obtained good system efficiency and fairness.

To connect the nature of what we do with how we feel is a mistake

Your editorial (June 5) links nurses who are ‘worn down and worn out’ with patients who ‘rarely get better’. It is a bad link.

Bank performance evaluation using dynamic DEA A slacks-based measure approach

Data envelopment analysis (DEA) has been applied in many studies in the banking industry but deficiency of empirical studies in Iranian banking sector that incorporate time factor into the efficiency, have still remained. Previous studies measured the efficiency of bank branches in a single period within cross-sectional data. They did not considered effect of interconnecting activities (links) between two consecutive terms. The main contribution of this paper is to evaluate the efficiency of an Iranian bank using dynamic SBM model in DEA during three consecutive terms considering net profit as a good link and loan losses as a bad link. In order to realize most important variables (inputs-outputs), relative to our case, we made a checklist and distributed them among headmen of branches and arranged an interview with the CEO of bank. Dynamic SBM efficiency is compared with its static efficiency to check the validity of described model. In addition, input-bad link excesses and output-good link shortfalls (slacks) are analyzed and further suggestions to the management are provided.

스마트그리드를 위한 지그비 기반의 라우팅 알고리즘에 관한 연구

본 논문에서는 스마트그리드 환경에서 적용되고 있는 ZigBee 무선 통신 환경의 주소 지정 방식과 라우팅 알고리즘의 성능을 향상시키기 위한 새로운 위치 기반 좌표 라우팅 알고리즘을 제안하였다. 기존 kip 알고리즘을 이용한 분산 주소 할당 기법의 낭비되는 주소공간의 문제를 해결하기 위해 (x,y,z) 3개의 좌표 축을 제안하여 16bit 주소공간을 분할하여 사용한다. 그러나 좌표 라우팅은 채널 상태를 고려하지 않는다. 채널 상태를 고려하지 않는다면, 라우팅 테이블이 업데이트 될 때 채널 상태가 좋지 않은 노드가 테이블에 업데이트 되어 릴레이 노드로 선택 되어질 수 있다. 따라서, 본 논문에서는 위치 기반 라우팅에서 채널 상태를 고려함으로 신뢰성 있는 데이터 전송을 보장하고 소비되는 에너지를 최소화 할 수 있는 위치 기반 좌표 라우팅 알고리즘 라우팅 방법을 제시하였다. 그리고 제안한 알고리즘의 평균멀티홉수, 부하에 대한 패킷전달률, 지연시간, 에너지 소비를 ZigBee 위치 기반 라우팅의 안전 영역과 전이 영역에 대해 비교하였다. 성능 평가 결과 각 항목에 대해 각각 성능 향상을 보였다. In this paper, we proposed the location-aware coordinate routing algorithm for improving the performance of routing algorithm by using ZigBee in Smart Grid environment. A distributed address allocation scheme used an existing algorithm that has wasted in address space. The x, y and z coordinate axes from divided address space of 16 bit to solve this problems. However, coordinate routing does not take account of wireless link condition. If wiress link condition is not considered, when the routing table is updated, the nodes with bad link conditions are updated in the routing table and can be chosen as the next hop. This brings out the retransmissions because of received packet's errors. Also, because of these retransmissions, additional power is consumed. In this paper, we propose the location-aware coordinate routing algorithm considering wiress link condition, where reliable data transmission is made and the consumed enegy is minimize. and we compared and connected region and transition region of ZigBee location based routing in the aspect of average number of multi hops, subordinate packet delivery ratio, delay time, and energy consumption of proposed algorithm. It turned out that there were improvements in performances of each items.

Max–min relay selection in bidirectional cooperative networks with imperfect channel estimation

The authors study the performance of wireless bidirectional relay-assisted networks in the presence of imperfect channel state information, where two end-source terminals S1 and S2 communicate with the assistance of M relay terminals Rj's. The max - min relay selection criterion is used to select the best relay that maximises the minimum signal-to-noise ratio of the links S1 �R jS 2 and S2 �R jS 1 over all relay terminals. The authors investigate the impact of imperfect channel estimation on the outage probability Pout of the system by means of the correlation coefficient rSi of the estimated channel gains and their actual values. Furthermore, the authors show that in a bidirectional relay-assisted network neither of the links S1 �R jS 2 and S2 �R jS 1 dominates the performance of the system. Instead, the performance is determined by the average performance of the two links, based on that the authors then discuss the power allocation in such networks. The authors demonstrate that in order to minimise Pout of the entire system, increasing the transmission power of the link with better estimation cannot compensate for the effect of the worse link and therefore the optimum power allocation with the least complexity is to transmit at each source terminals S1 and S2 with equal powers. Numerical results are also presented to corroborate the analytical expressions.

How Well Do Ontario Library Web Sites Meet New Accessibility Requirements?

New changes to Ontario law will require library web sites to comply with the Web Content Accessibility Guidelines, version 2.0 (WCAG 2.0). This study evaluates 64 Ontario university, college, and public library web sites to see how well they comply with WCAG 2.0 guidelines at present. An average of 14.75 accessibility problems were found per web page. The most common problems included invalid html, poor color contrast, incorrect form controls and labels, missing alt text, bad link text, improper use of headings, using html to format pages, using absolute units of measure, and issues with tables and embedded objects.