An Approximate Model of Multistage Automatic Transfer Lines with Possible Scrapping Of Workpieces

We consider multistage automatic transfer lines with unreliable stages, finite interstage buffer storages, and possible scrapping of workpieces. It is assumed that the first stage never idles and the last stage never becomes blocked. Assuming that uptimes and downtimes of a stage are geometrically distributed, an approximate model is developed to compute different performance measures of the transfer line. The results obtained through the approximate model are compared to the exact results for three-stage transfer lines and to simulation results for longer transfer lines. It is observed that the approximate results are good in almost all cases considered.     

Anthocyanins characterization of 15 Iranian pomegranate (Punica granatum L.) varieties and their variation after cold storage and pasteurization

Anthocyanins (ACs) are phenolic compounds that are distributed widely in fruits and vegetables. Apart from imparting color to plants, ACs also have an array of health-promoting benefits. In this research, the amounts of major ACs of 15 pomegranate (Punica granatum L.) varieties obtained from Yazd province were determined. The major ACs detected in the studied varieties were as follows: delphinidin 3-glucoside (2.19–16.29 mg/L), delphinidin 3,5-diglucoside (2.36–63.07 mg/L), pelargonidin 3-glucoside (0.26–1.36 mg/L), pelargonidin 3,5-diglucoside (0.01–8.11 mg/L), cyanidin 3-glucoside (5.78–30.38 mg/L), and cyanidin 3,5-diglucoside (4.39–166.32 mg/L). The effect of storage time of unprocessed and pasteurized juices on ACs content of four selected varieties was also studied. Average degradation percentage of each AC was between 23.0 and 83.0% during 10 days at 4 °C. Moreover, in pasteurized juices average degradation of ACs was 42.8 ± 0.5% after 10 weeks storage at 4 °C.     

Query processing optimization in broadcasting XML data in mobile communications

Todays, XML as a de facto standard is used to broadcast data over mobile wireless networks. In these networks, mobile clients send their XML queries over a wireless broadcast channel and recieve their desired XML data from the channel. However, downloading the whole XML data by a mobile device is a challenge since the mobile devices used by clients are small battery powered devices with limited resources. To meet this challenge, the XML data should be indexed in such a way that the desired XML data can be found easily and only such data can be downloaded instead of the whole XML data by the mobile clients. Several indexing methods are proposed to selectively access the XML data over an XML stream. However, the existing indexing methods cause an increase in the size of XML stream by including some extra information over the XML stream. In this paper, a new XML stream structure is proposed to disseminate the XML data over a broadcast channel by grouping and summarizing the structural information of XML nodes. By summarizing such information, the size of XML stream can be reduced and therefore, the latency of retrieving the desired XML data over a wirless broadcast channel can be reduced. The proposed XML stream structure also contains indexes in order to skip from the irrelevant parts over the XML stream. It therefore can reduce the energy consumption of mobile devices in downloading the results of XML queries. In addition, our proposed XML stream structure can process different types of XML queries and experimental results showed that it improves the performace of XML query processing over the XML data stream compared to the existing research works in terms of access and tuning times.

     

A study on the mechanical strength of Fe2O3/Cr2O3/CuO catalyst for high temperature water gas shift reaction

Journal of Porous Materials - The present study aims to investigate the effects of iron (hydr)oxide phases formed during precipitation and the addition of different binders on the mechanical and...     

Multicast routing protocols in wireless mesh networks: a survey

Wireless mesh networks (WMNs) introduce a new type of network that has been applied over the last few years. One of the most important developing issues in WMNs is multicast routing, which is a key technology that provides dissemination of data to a group of members in an efficient way. In this article, after an introduction about the structure of a WMN, multicast routing algorithms and protocols in WMNs are surveyed in a detailed and efficient manner. Moreover, effort is made to scale the study into one of the important potential capabilities of multicast routing mechanisms in WMNs, which is taking advantage of using different channels and radios association. While nodes in a single-radio mesh network operating on single-channel have restrictions for capacity, equipping mesh routers with multiple radios using multiple channels can decrease the intention of capacity problem as well as increase the aggregate bandwidth available to the network and improving the throughput. Hence, the purpose of channel assignment is to decrease the interferences while increasing the network capacity and keeping the connectivity of the network. Therefore, this article investigates the multicast protocols considering a definition of three types of WMNs, based on channel-radio association including SRSC, SRMC and MRMC. In its follow, a classification for multicast routing algorithms regarding the achieved optimal solutions will be presented. Finally, a study of MRMC and its relevant problems will be offered, considering the joint channel assignment and the multicast tree construction problem.     

Effect of stabilizer type on the physicochemical properties of rigid PVC. III

The crystallinity of rigid PVC specimens, stabilized by a tin mercaptide or a lead stabilizer, has been studied. It is found that the crystallinity of rigid PVC is greatly influenced by the type of stabilizer added, and that the response of the PVC toward subsequent UV exposure was also different. The effects of unstable structures and crystallinity, after UV irradiation, on the mechanical properties of rigid PVC have been investigated.     

Reserve estimation of an open pit mine under price uncertainty by real option approach

Reserve estimation is a key to find the correct NPV in a mining project. The most important factor in reserve estimation is the metal price. Metal price fluctuations in recent years were exaggerated, and imposed a high degree of uncertainty to the re-serve estimation, and in consequence to the whole mine planning procedure. Real option approach is an efficient method of deci-sion making in the uncertain conditions. This approach has been used for evaluation of defined natural resources projects until now. This study considering the metal price uncertainty used real option approach to prepare a methodology for reserve estimation in open pit mines. This study was done on a copper cylindrical deposit, but the achieved methodology can be adjusted for all kinds of deposits. This methodology was comprehensively described through the examples in such a manner that can be used by the mine planners.     

A GMM/HMM model for reconstruction of missing speech spectral components for continuous speech recognition

This paper presents a method for reconstructing unreliable spectral components of speech signals using the statistical distributions of the clean components. Our goal is to model the temporal patterns in speech signal and take advantage of correlations between speech features in both time and frequency domain simultaneously. In this approach, a hidden Markov model (HMM) is first trained on clean speech data to model the temporal patterns which appear in the sequences of the spectral components. Using this model and according to the probabilities of occurring noisy spectral component at each states, a probability distributions for noisy components are estimated. Then, by applying maximum a posteriori (MAP) estimation on the mentioned distributions, the final estimations of the unreliable spectral components are obtained. The proposed method is compared to a common missing feature method which is based on the probabilistic clustering of the feature vectors and also to a state of the art method based on sparse reconstruction. The experimental results exhibits significant improvement in recognition accuracy over a noise polluted Persian corpus.     

Optimal Deep Learning Based Intruder Identification in Industrial Internet of Things Environment

With the increased advancements of smart industries, cybersecurity has become a vital growth factor in the success of industrial transformation. The Industrial Internet of Things (IIoT) or Industry 4.0 has revolutionized the concepts of manufacturing and production altogether. In industry 4.0, powerful Intrusion Detection Systems (IDS) play a significant role in ensuring network security. Though various intrusion detection techniques have been developed so far, it is challenging to protect the intricate data of networks. This is because conventional Machine Learning (ML) approaches are inadequate and insufficient to address the demands of dynamic IIoT networks. Further, the existing Deep Learning (DL) can be employed to identify anonymous intrusions. Therefore, the current study proposes a Hunger Games Search Optimization with Deep Learning-Driven Intrusion Detection (HGSODL-ID) model for the IIoT environment. The presented HGSODL-ID model exploits the linear normalization approach to transform the input data into a useful format. The HGSO algorithm is employed for Feature Selection (HGSO-FS) to reduce the curse of dimensionality. Moreover, Sparrow Search Optimization (SSO) is utilized with a Graph Convolutional Network (GCN) to classify and identify intrusions in the network. Finally, the SSO technique is exploited to fine-tune the hyper-parameters involved in the GCN model. The proposed HGSODL-ID model was experimentally validated using a benchmark dataset, and the results confirmed the superiority of the proposed HGSODL-ID method over recent approaches.     

F-LEACH: a fuzzy-based data aggregation scheme for healthcare IoT systems

The Journal of Supercomputing - Internet of Things (IoT) is an emerging paradigm that consists of numerous connected and interrelated devices with embedded sensors, exchanging data with each other...