Abstract: This paper presents an integrated model, which hybridized data envelopment analysis (DEA) and support vector machine (SVM) together, to class countries according to their efficiency and performance. This model takes into account aspects of multi-dimensional indicators, decision-making hierarchy and relativity of measurement. Starting from a set of indicators of performance as exhaustive as possible, a process of successive aggregations has been developed to attain an overall evaluation of a country’s competitiveness.
Abstract: The main objective of the current work is to introduce sustainability factors in optimizing the supply chain model for process industries. The supply chain models are normally based on purely economic considerations related to costs and profits. To account for sustainability, two additional factors have been introduced; environment and risk. A supply chain for an entire petroleum organization has been considered for implementing and testing the proposed optimization models. The environmental and risk factors were introduced as indicators reflecting the anticipated impact of the optimal production scenarios on sustainability. The aggregation method used in extending the single objective function to multi-objective function is proven to be quite effective in balancing the contribution of each objective term. The results indicate that introducing sustainability factor would slightly reduce the economic benefit while improving the environmental and risk reduction performances of the process industries.
Abstract: Wireless Sensor Networks (WSNs) are suitable for many scenarios in the real world. The retrieval of data is made efficient by the data aggregation techniques. Many techniques for the data aggregation are offered and most of the existing schemes are not energy efficient and secure. However, the existing techniques use the traditional clustering approach where there is a delay during the packet transmission since there is no proper scheduling. The presented system uses the Velocity Energy-efficient and Link-aware Cluster-Tree (VELCT) scheme in which there is a Data Collection Tree (DCT) which improves the lifetime of the network. The VELCT scheme and the construction of DCT reduce the delay and traffic. The network lifetime can be increased by avoiding the frequent change in cluster topology. Secure and Efficient Transmission of Aggregated data (SETA) improves the security of the data transmission via the trust value of the nodes prior the aggregation of data. Since SETA considers the data only from the trustworthy nodes for aggregation, it is more secure in transmitting the data thereby improving the accuracy of aggregated data.
Abstract: In the last decades, concerns about the environmental issues lead to professional and academic efforts on green supplier selection problems. In this sake, one of the main issues in evaluating the green supplier selection problems, which could increase the uncertainty, is the preferences of the experts' judgments about the candidate green suppliers. Therefore, preparing an expert system to evaluate the problem based on the historical data and the experts' knowledge can be sensible. This study provides an expert evaluation system to assess the candidate green suppliers under selected criteria in a multi-period approach. In addition, a ranking approach under interval-valued hesitant fuzzy set (IVHFS) environment is proposed to select the most appropriate green supplier in planning horizon. In the proposed ranking approach, the IVHFS and the last aggregation approach are considered to margin the errors and to prevent data loss, respectively. Hence, a comparative analysis is provided based on an illustrative example to show the feasibility of the proposed approach.
Abstract: This paper explores efficient ways to implement various
media-updating features like news aggregation, video conversion,
and bulk email handling. All of these jobs share the property
that they are periodic in nature, and they all benefit from being
handled in a distributed fashion. The data for these jobs also often
comes from a social or collaborative source. We isolate the class of
periodic, one round map reduce jobs as a useful setting to describe
and handle media updating tasks. As such tasks are simpler than
general map reduce jobs, programming them in a general map
reduce platform could easily become tedious. This paper presents
a MediaUpdater module of the Yioop Open Source Search Engine
Web Portal designed to handle such jobs via an extension of a
PHP class. We describe how to implement various media-updating
tasks in our system as well as experiments carried out using these
implementations on an Amazon Web Services cluster.
Abstract: Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.
Abstract: Connected vehicles are equipped with wireless sensors
that aid in Vehicle to Vehicle (V2V) and Vehicle to Infrastructure
(V2I) communication. These vehicles will in the near future
provide road safety, improve transport efficiency, and reduce traffic
congestion. One of the challenges for connected vehicles is how
to ensure that information sent across the network is secure. If
security of the network is not guaranteed, several attacks can occur,
thereby compromising the robustness, reliability, and efficiency of
the network. This paper discusses existing security mechanisms and
unique properties of connected vehicles. The methodology employed
in this work is exploratory. The paper reviews existing security
solutions for connected vehicles. More concretely, it discusses
various cryptographic mechanisms available, and suggests areas
of improvement. The study proposes a combination of symmetric
key encryption and public key cryptography to improve security.
The study further proposes message aggregation as a technique to
overcome message redundancy. This paper offers a comprehensive
overview of connected vehicles technology, its applications, its
security mechanisms, open challenges, and potential areas of future
research.
Abstract: Wireless Sensor Network (WSN) clustering architecture enables features like network scalability, communication overhead reduction, and fault tolerance. After clustering, aggregated data is transferred to data sink and reducing unnecessary, redundant data transfer. It reduces nodes transmitting, and so saves energy consumption. Also, it allows scalability for many nodes, reduces communication overhead, and allows efficient use of WSN resources. Clustering based routing methods manage network energy consumption efficiently. Building spanning trees for data collection rooted at a sink node is a fundamental data aggregation method in sensor networks. The problem of determining Cluster Head (CH) optimal number is an NP-Hard problem. In this paper, we combine cluster based routing features for cluster formation and CH selection and use Minimum Spanning Tree (MST) for intra-cluster communication. The proposed method is based on optimizing MST using Simulated Annealing (SA). In this work, normalized values of mobility, delay, and remaining energy are considered for finding optimal MST. Simulation results demonstrate the effectiveness of the proposed method in improving the packet delivery ratio and reducing the end to end delay.
Abstract: Wireless Sensor Networks (WSNs) have many advantages. Their deployment is easier and faster than wired sensor networks or other wireless networks, as they do not need fixed infrastructure. Nodes are partitioned into many small groups named clusters to aggregate data through network organization. WSN clustering guarantees performance achievement of sensor nodes. Sensor nodes energy consumption is reduced by eliminating redundant energy use and balancing energy sensor nodes use over a network. The aim of such clustering protocols is to prolong network life. Low Energy Adaptive Clustering Hierarchy (LEACH) is a popular protocol in WSN. LEACH is a clustering protocol in which the random rotations of local cluster heads are utilized in order to distribute energy load among all sensor nodes in the network. This paper proposes Connected Dominant Set (CDS) based cluster formation. CDS aggregates data in a promising approach for reducing routing overhead since messages are transmitted only within virtual backbone by means of CDS and also data aggregating lowers the ratio of responding hosts to the hosts existing in virtual backbones. CDS tries to increase networks lifetime considering such parameters as sensors lifetime, remaining and consumption energies in order to have an almost optimal data aggregation within networks. Experimental results proved CDS outperformed LEACH regarding number of cluster formations, average packet loss rate, average end to end delay, life computation, and remaining energy computation.
Abstract: The advanced information technology is becoming an important factor in the development of financial services industry, especially the banking industry. It has introduced new ways of delivering banking to the customer, such as Internet Banking. Banks began to look at electronic banking (e-banking) as a means to replace some of their traditional branch functions using the Internet as a new distribution channel. Some consumers have at least more than one account, and across banks, and access these accounts using e-banking services. To look at the current net worth position, customers have to login to each of their accounts and get the details and work on consolidation. This not only takes ample time but it is a repetitive activity at a specified frequency. To address this point, an account aggregation concept is added as a solution. E-banking account aggregation, as one of the e-banking types, appeared to build a stronger relationship with customers. Account Aggregation Service generally refers to a service that allows customers to manage their bank accounts maintained in different institutions through a common Internet banking operating a platform, with a high concern to security and privacy. This paper presents an overview of an e-banking account aggregation approach as a new service in the e-banking field.
Abstract: The main cause of several neurodegenerative diseases such as Alzhemier, Parkinson and spongiform encephalopathies is formation of amyloid fibrils and plaques in proteins. We have analyzed different sets of proteins and peptides to understand the influence of sequence based features on protein aggregation process. The comparison of 373 pairs of homologous mesophilic and thermophilic proteins showed that aggregation prone regions (APRs) are present in both. But, the thermophilic protein monomers show greater ability to ‘stow away’ the APRs in their hydrophobic cores and protect them from solvent exposure. The comparison of amyloid forming and amorphous b-aggregating hexapeptides suggested distinct preferences for specific residues at the six positions as well as all possible combinations of nine residue pairs. The compositions of residues at different positions and residue pairs have been converted into energy potentials and utilized for distinguishing between amyloid forming and amorphous b-aggregating peptides. Our method could correctly identify the amyloid forming peptides at an accuracy of 95-100% in different datasets of peptides.
Abstract: Environmental security clearly articulates the perfections and developments of various communities around the world irrespective of the region, culture, religion or social inclination. Although, the present state of insecurity has become serious issue devastating the peace, unity, stability and progress of man and his physical environment particularly in developing countries. Recently, measure of security and it management in Nigeria has been a bottle-neck to the effectiveness and advancement of various sectors that include; business, education, social relations, politics and above all an economy. Several measures have been considered on mitigating environment insecurity such as surveillance, demarcation, security personnel empowerment and the likes, but still the issue remains disturbing. In this paper, we present the application of new technology that contributes to the improvement of security surveillance known as “Wireless Sensor Network (WSN)”. The system is new, smart and emerging technology that provides monitoring, detection and aggregation of information using sensor nodes and wireless network. WSN detects, monitors and stores information or activities in the deployed area such as schools, environment, business centers, public squares, industries, and outskirts and transmit to end users. This will reduce the cost of security funding and eases security surveillance depending on the nature and the requirement of the deployment.
Abstract: In wireless sensor network, sensor node transmits the
sensed data to the sink node in multi-hop communication
periodically. This high traffic induces congestion at the node which is
present one-hop distance to the sink node. The packet transmission
and reception rate of these nodes should be very high, when
compared to other sensor nodes in the network. Therefore, the energy
consumption of that node is very high and this effect is known as the
“funneling effect”. The tree based-data aggregation technique
(TBDA) is used to reduce the energy consumption of the node. The
throughput of the overall performance shows a considerable decrease
in the number of packet transmissions to the sink node. The proposed
scheme, TBDA, avoids the funneling effect and extends the lifetime
of the wireless sensor network. The average case time complexity for
inserting the node in the tree is O(n log n) and for the worst case time
complexity is O(n2).
Abstract: The main cause of Alzheimer disease (AD) was
believed to be mainly due to the accumulation of free radicals owing
to oxidative stress (OS) in brain tissue. The mechanism of the
neurotoxicity of Aluminum chloride (AlCl3) induced AD in
hippocampus Albino wister rat brain tissue, the curative & the
protective effects of Lipidium sativum group (LS) water extract were
assessed after 8 weeks by attenuated total reflection spectroscopy
ATR-IR and histologically by light microscope. ATR-IR results
revealed that the membrane phospholipid undergo free radical
attacks, mediated by AlCl3, primary affects the polyunsaturated fatty
acids indicated by the increased of the olefinic -C=CH sub-band area
around 3012 cm-1 from the curve fitting analysis. The narrowing in
the half band width (HBW) of the sνCH2 sub-band around 2852 cm-1
due to Al intoxication indicates the presence of trans form fatty acids
rather than gauch rotomer. The degradation of hydrocarbon chain to
shorter chain length, increasing in membrane fluidity, disorder, and
decreasing in lipid polarity in AlCl3 group indicated by the detected
changes in certain calculated area ratios compared to the control.
Administration of LS was greatly improved these parameters
compared to the AlCl3 group. Al influences the Aβ aggregation and
plaque formation, which in turn interferes to and disrupts the
membrane structure. The results also showed a marked increase in
the β-parallel and antiparallel structure, that characterize the Aβ
formation in Al-induced AD hippocampal brain tissue, indicated by
the detected increase in both amide I sub-bands around 1674, 1692
cm-1. This drastic increase in Aβ formation was greatly reduced in the
curative and protective groups compared to the AlCl3 group and
approached nearly the control values. These results supported too by
the light microscope. AlCl3 group showed significant marked
degenerative changes in hippocampal neurons. Most cells appeared
small, shrieked and deformed. Interestingly, the administration of LS
in curative and protective groups markedly decreases the amount of
degenerated cells compared to the non-treated group. In addition, the
intensity of congo red stained cells was decreased. Hippocampal
neurons looked more/or less similar to those of control. This study showed a promising therapeutic effect of Lipidium
sativum group (LS) on AD rat model that seriously overcome the
signs of oxidative stress on membrane lipid and restore the protein
misfolding.
Abstract: Wireless Sensor Network (WSN) routing is complex
due to its dynamic nature, computational overhead, limited battery
life, non-conventional addressing scheme, self-organization, and
sensor nodes limited transmission range. An energy efficient routing
protocol is a major concern in WSN. LEACH is a hierarchical WSN
routing protocol to increase network life. It performs self-organizing
and re-clustering functions for each round. This study proposes a
better sensor networks cluster head selection for efficient data
aggregation. The algorithm is based on Tabu search.
Abstract: Wireless Sensor Networks (WSNs) enable new
applications and need non-conventional paradigms for the protocol
because of energy and bandwidth constraints, In WSN, sensor node’s
life is a critical parameter. Research on life extension is based on
Low-Energy Adaptive Clustering Hierarchy (LEACH) scheme,
which rotates Cluster Head (CH) among sensor nodes to distribute
energy consumption over all network nodes. CH selection in WSN
affects network energy efficiency greatly. This study proposes an
improved CH selection for efficient data aggregation in sensor
networks. This new algorithm is based on Bacterial Foraging
Optimization (BFO) incorporated in LEACH.
Abstract: We present a gas-liquid microfluidic system as a
reactor to obtain magnetite nanoparticles with an excellent degree of
control regarding their crystalline phase, shape and size. Several
types of microflow approaches were selected to prevent nanomaterial
aggregation and to promote homogenous size distribution. The
selected reactor consists of a mixer stage aided by ultrasound waves
and a reaction stage using a N2-liquid segmented flow to prevent
magnetite oxidation to non-magnetic phases. A milli-fluidic reactor
was developed to increase the production rate where a magnetite
throughput close to 450 mg/h in a continuous fashion was obtained.
Abstract: Complexation of anthocyanins to mimic natural
copigmentation process was investigated. Cyanidin-rich extracts from
Zea mays L. ceritina Kulesh. and delphinidin-rich extracts from
Clitoria ternatea L. were used to form 4 anthocyanin complexes,
AC1, AC2, AC3 and AC4, in the presence of several polyphenols and
a trace metal. Characterizations of the ACs were conducted by UV,
FTIR, DSC/TGA and morphological observations. Bathochromic
shifts of the UV spectra of 4 formulas of ACs were observed at peak
wavelengths of about 510-620 nm by 10 nm suggesting complex
formation. FTIR spectra of the ACs indicate shifts of peaks from
1,733 cm-1 to 1,696 cm-1 indicating interactions and a decrease in the
peak areas within the wavenumber of 3,400-3,500 cm-1 indicating
changes in hydrogen bonding. Thermal analysis of all of the ACs
suggests increases in melting temperature after complexation. AC
with the highest melting temperature was morphologically observed
by SEM and TEM to be crystal-like particles within a range of 50 to
200 nm. Particle size analysis of the AC by laser diffraction gave a
range of 50-600 nm, indicating aggregation. This AC was shown to
have no cytotoxic effect on cultured HGEPp0.5 and HGF (all p>
0.05) by MTT. Therefore, complexation of anthocyanins was simple
and self-assembly process, potentially resulting in nanosized particles
of anthocyanin complex.
Abstract: The aim of present study was to monitor the presence
of Trichodina sp. in Rainbow trout, Oncorhynchus mykiss collected
from various fish farms in the western provinces of Iran during
January, 2013- January, 2014. Out of 675 sampled fish 335, (49.16%)
were infested with Trichodina. The highest prevalence was observed
in the spring and winter followed by autumn and summer. In general,
the intensity of infection was low except in cases where outbreaks of
Trichodiniasis endangered the survival of fish in some ponds. In light
infestation Trichodina is usually present on gills, fins and skin of
apparently healthy fish. Clinical signs of Trichodiniasis only appear
on fish with heavy infections and cases of moderate ones that are
usually exposed to one or more stress factors including, rough
handling during transportation from ponds, overcrowdness,
malnutrition, high of free ammonia and low of oxygen concentration.
Clinical signs of Trichodiniasis in sampled fish were sluggish
movement, loss of appetite, black coloration, necrosis and ulcer on
different parts of the body, detached scales and excessive
accumulation of mucous in gill pouches. The most obvious
histopathological changes in diseased fish were sloughing of the
epidermal layer, aggregation of leucocytes and melanine-carrying
cells (between the dermis and hypodermis) and proliferative changes
including hyperplasia and hypertrophy of the epithelial lining cells of
gill filaments which resulted in fusion of secondary lamellae. Control
of Trichodiniasis, has been achieved by formalin bath treatment at a
concentration of 250 ppm for one hour.
Abstract: In this study, a comparative analysis of the approaches
associated with the use of neural network algorithms for effective
solution of a complex inverse problem – the problem of identifying
and determining the individual concentrations of inorganic salts in
multicomponent aqueous solutions by the spectra of Raman
scattering of light – is performed. It is shown that application of
artificial neural networks provides the average accuracy of
determination of concentration of each salt no worse than 0.025 M.
The results of comparative analysis of input data compression
methods are presented. It is demonstrated that use of uniform
aggregation of input features allows decreasing the error of
determination of individual concentrations of components by 16-18%
on the average.