Nonlinear convective flow with variable thermal conductivity and Cattaneo-Christov heat flux

An analysis is introduced to investigate the salient features of nonlinear convective flow of thixotropic fluid in the version of Cattaneo-Christov heat flux theory. The stagnation point flow is present. The flow phenomenon is by an impermeable stretching sheet. The energy expression is modeled through the theory of Cattaneo-Christov heat flux. Characteristics of heat transfer phenomenon are described within the frame of variable thermal conductivity. Suitable variables reduced to the nonlinear partial differential expressions to the ordinary differential expressions. Series solutions of resulting systems are acquired within the frame of homotopy theory. Convergence analysis is achieved and suitable values are determined by capturing the so-called ℏ−curves. Graphical results for velocity and temperature are displayed and argued for sundry physical variables. Expression of skin friction coefficient is calculated through numerical values. Higher values of mixed convection parameter, Prandtl number, and thermal relaxation time lead to decay the temperature and layer thickness.

     

A new algorithm of modified binary particle swarm optimization based on the Gustafson-Kessel for credit risk assessment

Neural Computing and Applications - To increase the quality of loans provision and reduce the risk involved in this process, several credit scoring models have been developed and utilized to...     

SCM: Secure and accountable TLS certificate management

In classical public‐key infrastructure (PKI), the certificate authorities (CAs) are fully trusted, and the security of the PKI relies on the trustworthiness of the CAs. However, recent failures and compromises of CAs showed that if a CA is corrupted, fake certificates may be issued, and the security of clients will be at risk. As emerging solutions, blockchain‐ and log‐based PKI proposals potentially solved the shortcomings of the PKI, in particular, eliminating the weakest link security and providing a rapid remedy to CAs' problems. Nevertheless, log‐based PKIs are still exposed to split‐world attacks if the attacker is capable of presenting two distinct signed versions of the log to the targeted victim(s), while the blockchain‐based PKIs have scaling and high‐cost issues to be overcome. To address these problems, this paper presents a secure and accountable transport layer security (TLS) certificate management (SCM), which is a next‐generation PKI framework. It combines the two emerging architectures, introducing novel mechanisms, and makes CAs and log servers accountable to domain owners. In SCM, CA‐signed domain certificates are stored in log servers, while the management of CAs and log servers is handed over to a group of domain owners, which is conducted on the blockchain platform. Different from existing blockchain‐based PKI proposals, SCM decreases the storage cost of blockchain from several hundreds of GB to only hundreds of megabytes. Finally, we analyze the security and performance of SCM and compare SCM with previous blockchain‐ and log‐based PKI schemes.     

Queue length‐based load balancing in data center networks

Traffic load balancing in data centers is an important requirement. Traffic dynamics and possibilities of changes in the topology (e.g., failures and asymmetries) make load balancing a challenging task. Existing end‐host–based schemes either employ the predominantly used ECN or combine it with RTT to get congestion information of paths. Both congestion signals, ECN and RTT, have limitations; ECN only tells whether the queue length is above or below a threshold value but does not inform about the extent of congestion; similarly, RTT in data center networks is on the scale of up to few hundreds of microseconds, and current data center operating systems lack fine‐grained microsecond‐level timers. Therefore, there is a need of a new congestion signal which should give accurate information of congestion along the path. Furthermore, in end‐host–based schemes, detecting asymmetries in the topology is challenging due to the inability to accurately measure RTT on the scale of microseconds. This paper presents QLLB, an end‐host–based, queue length–based load balancing scheme. QLLB employs a new queue length–based congestion signal that gives an exact measure of congestion along the paths. Furthermore, QLLB uses relative‐RTT to detect asymmetries in the topology. QLLB is implemented in ns‐3 and compared with ECMP, CONGA, and Hermes. The results show that QLLB significantly improves performance of short flows over the other schemes and performs within acceptable level, of CONGA and Hermes, for long flows. In addition, QLLB effectively detects asymmetric paths and performs better than Hermes under high loads.     

Optical GFDM: an improved alternative candidate for indoor visible light communication

Photonic Network Communications - This paper proposes generalized frequency division multiplexing (GFDM) for indoor visible light communication (VLC). GFDM is a flexible multi-carrier scheme that...     

Fast and Ultraclean Approach for Measuring the Transport Properties of Carbon Nanotubes

In this work, a fast approach for the fabrication of hundreds of ultraclean field‐effect transistors (FETs) is introduced, using single‐walled carbon nanotubes (SWCNTs). The synthesis of the nanomaterial is performed by floating‐catalyst chemical vapor deposition, which is employed to fabricate high‐performance thin‐film transistors. Combined with palladium metal bottom contacts, the transport properties of individual SWCNTs are directly unveiled. The resulting SWCNT‐based FETs exhibit a mean field‐effect mobility, which is 3.3 times higher than that of high‐quality solution‐processed CNTs. This demonstrates that the hereby used SWCNTs are superior to comparable materials in terms of their transport properties. In particular, the on–off current ratios reach over 30 million. Thus, this method enables a fast, detailed, and reliable characterization of intrinsic properties of nanomaterials. The obtained ultraclean SWCNT‐based FETs shed light on further study of contamination‐free SWCNTs on various metal contacts and substrates.     

The Growing Impact of Micro/Nanomaterial‐Based Systems in Precision Oncology: Translating “Multiomics” Technologies

The field of precision oncology is rapidly progressing toward integrated “multiomics” analysis of multiple molecular species (such as DNA, RNA, or proteins) to provide a more complete profile of tumor heterogeneity. Micro/nanomaterial‐based systems, which leverage the unique properties of miniature materials, are currently well positioned to expand beyond rudimentary biomarker detection toward multiomics signature analysis. To enable clinical translation, the rational design and implementation of miniaturized systems should be driven by the unique clinical challenges present at various crucial cancer stages. This review features micro/nanomaterial‐based systems that are robustly tested on real patient samples for molecular biomarker detection at i) initial cancer screening and/or diagnosis, ii) cancer prognosis and risk stratification, and iii) longitudinal treatment/recurrence monitoring. Furthermore, this review discusses the use of micro/nanomaterials to facilitate sample preparation for different molecular biomarker species. Finally, this review deliberates on the recent paradigm shift of micro/nanomaterial‐based system innovation toward integrated multiomics cancer signature analysis and puts forth insights and perspectives on existing challenges. It is anticipated that this review could stimulate the propagation of new concepts and approaches to kick‐start a new generation of clinically translational technologies that capitalize on multiomics cancer signatures.     

An anti‐collision algorithm based on balanced incomplete block design in RFID systems

An important challenge in radio frequency identification (RFID) systems is the collision concern. When an interrogator send a request, it has several tags to answer to in its transmission range, and a tag collision has occurred. The interrogator must be able to recognize tags as rapidly as possible. A collision problem is a power‐consuming occurrence that diminishes the operation of RFID structure. This article proposes a tag anti‐collision power‐clustering RFID algorithm for all tag identification. The tags are boundaries into the several power level clusters based on distances of the reader. Specifically, in the proposed algorithm, tags and readers use of balanced incomplete blocks design (BIBD) to reach a fast identification. In a BIBD matrix, any two columns intersect exactly in one component that makes it possible for easy transmission of any two tags via the tag's identification in their read cycles. The aim of this article is to propose a joint organization that while decreases power consumption increases the working lifetime of RFID structure. The reader can get each tag ID by distinguishing each unit of BIBD symbols, one by one. The use of proposed algorithm brings about a great improvement in the power consumption and identification time.     

Multi-Objective Surface Water Resource Management Considering Conflict Resolution and Utility Function Optimization

In the present research, a multi-objective model is developed for surface water resource management in the river basin area which is connected to the lake. This model considers different components of sustainable water resource management including economic, social and environmental aspects, and simultaneously tries to resolve conflicts between different stakeholders by means of non-symmetric Nash bargaining, which is linked to the multi-objective optimization method. This study proposes a new methodology to improve Nash Conflict Resolution through finding the optimum degree of the utility function. The proposed model is examined in the Zarrineh River basin in Iran. The results show that the amount of available resources or volume of reservoirs play a significant role in determining the optimal degree of the utility function and efficiency of the proposed method in such a way that the higher amount of resources or the larger reservoirs will result in the higher optimal degree of the utility function. In the proposed multi-objective model, two different amounts of surface water inflow are considered. The first assumed amount is the long-term average flow rate and the second one is equal to 80% of the first mode, which is reduced based on the estimated impacts of climate changes. This multi-objective allocation model could supply 100 and 97.5% of the environmental demand of Lake Urmia in the first and second situations, respectively.     

Numerical solutions of systems of first-order,two-point BVPs based on the reproducing kernel algorithm

The aim of the present analysis is to implement a relatively recent computational algorithm, reproducing kernel Hilbert space, for obtaining the solutions of systems of first-order, two-point boundary value problems for ordinary differential equations. The reproducing kernel Hilbert space is constructed in which the initial–final conditions of the systems are satisfied. Whilst, three smooth kernel functions are used throughout the evolution of the algorithm in order to obtain the required grid points. An efficient construction is given to obtain the numerical solutions for the systems together with an existence proof of the exact solutions based upon the reproducing kernel theory. In this approach, computational results of some numerical examples are presented to illustrate the viability, simplicity, and applicability of the algorithm developed. Finally, the utilized results show that the present algorithm and simulated annealing provide a good scheduling methodology to such systems compared with other numerical methods.