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The purpose of this paper is to explore the challenges posed by Big Data to current trends in computation, networking and storage technology at various stages of Big Data analysis. The work aims to bridge the gap between theory and practice, and highlight the areas of potential research.

The study employs a systematic and critical review of the relevant literature to explore the challenges posed by Big Data to hardware technology, and assess the worthiness of hardware technology at various stages of Big Data analysis. Online computer-databases were searched to identify the literature relevant to: Big Data requirements and challenges; and evolution and current trends of hardware technology.

The findings reveal that even though current hardware technology has not evolved with the motivation to support Big Data analysis, it significantly supports Big Data analysis at all stages. However, they also point toward some important shortcomings and challenges of current technology trends. These include: lack of intelligent Big Data sources; need for scalable real-time analysis capability; lack of support (in networks) for latency-bound applications; need for necessary augmentation (in network support) for peer-to-peer networks; and rethinking on cost-effective high-performance storage subsystem.

The study suggests that a lot of research is yet to be done in hardware technology, if full potential of Big Data is to be unlocked.

The study suggests that practitioners need to meticulously choose the hardware infrastructure for Big Data considering the limitations of technology.

This research arms industry, enterprises and organizations with the concise and comprehensive technical-knowledge about the capability of current hardware technology trends in solving Big Data problems. It also highlights the areas of potential research and immediate attention which researchers can exploit to explore new ideas and existing practices.

The purpose of this paper is to investigate the structure and electrical properties of eutectic Sb_7.4Te_92.6 as made thin films to evaluate their potentiality for application to non-volatile phase-change memories.

The films were prepared by the pulsed laser deposition technique. The films were characterized by using X-ray diffraction in grazing-incident geometry, differential scanning calorimetry, Raman spectroscopy and transversal current–voltage curves.

The memory effect state, characteristic of a typical phase-change memory material, was observed. The temperature of crystallization was about 100ºC.

Further studies on endurance, scaling and SET/RESET operations are needed.

One of the main characteristic values, the hold voltage and the threshold voltage values, were about 0.85 and 1.2 V, respectively, in a line with those of Ge₂Sb₂Te₅, GeTe and Sb₂Te being considered to date as the main compounds for phase-change memory devices.

The conduction mechanism in the amorphous regime is highly agreed with the Poole–Frenkel effect in deep traps.

The purpose of this paper is to investigate electrical properties of eutectic In8Sb8Te84 and In10Sb51Te39 as made thin films to evaluate their potential for non-volatile phase-change memories, once the thermal measurements are very optimistic.

The films were deposited by pulse laser deposition technique. By using a very simple home-made cell, transversal current-voltage curves films were measured involving both voltage controlled-pulses generator and current controlled-pulses generator, employing different pulse shapes: triangular and sine shaped.

The memory effect, characteristic of a typical phase-change memory material, was observed in both materials under research. For higher tellurium content in the film, lower is the value of threshold voltage.

Further studies on endurance, scaling and SET/RESET operations are needed.

The values of the key parameters, threshold voltage and hold voltage are comparable with those of Ge2Sb2Te5, GeTe and Sb2Te being considered to date as the main compounds for PCM devices.

The conduction mechanism in the amorphous regime is agreed with Poole–Frenkel effect in deep traps.

The purpose of this paper is to investigate the prospects of current storage technologies for long-term preservation of big data in digital libraries.

The study employs a systematic and critical review of the relevant literature to explore the prospects of current storage technologies for long-term preservation of big data in digital libraries. Online computer databases were searched to identify the relevant literature published between 2000 and 2016. A specific inclusion and exclusion criterion was formulated and applied in two distinct rounds to determine the most relevant papers.

The study concludes that the current storage technologies are not viable for long-term preservation of big data in digital libraries. They can neither fulfil all the storage demands nor alleviate the financial expenditures of digital libraries. The study also points out that migrating to emerging storage technologies in digital libraries is a long-term viable solution.

The study suggests that continuous innovation and research efforts in current storage technologies are required to lessen the impact of storage shortage on digital libraries, and to allow emerging storage technologies to advance further and take over. At the same time, more aggressive research and development efforts are required by academics and industry to further advance the emerging storage technologies for their timely and swift adoption by digital libraries.

The study reveals that digital libraries, besides incurring significant financial expenditures, will suffer from potential loss of information due to storage shortage for long-term preservation of big data, if current storage technologies are employed by them. Therefore, policy makers and practitioners should meticulously choose storage technologies for long-term preservation of big data in digital libraries.

This type of holistic study that investigates the prospects of magnetic drive technology, solid-state drive technology, and data-reduction techniques for long-term preservation of big data in digital libraries has not been conducted in the field previously, and so provides a novel contribution. The study arms academics, practitioners, policy makers, and industry with the deep understanding of the problem, technical details to choose storage technologies meticulously, greater insight to frame sustainable policies, and opportunities to address various research problems.

This paper aims to forecast the future of data storage technologies, using the case of two major technologies driving the data storage world; hard disk drive (HDD) or conventional longitudinal recording and flash memory.

Four principal tools of forecasting technology are applied to present the coming future of data storage technologies. These tools consist of bibliometric trend analysis, patent trend analysis, technology cycle time (TCT), and growth curve. Numbers of publications each year and cumulative patents are used to analyze the future of these competitive technologies. The median age of the patents is applied to find the technology lifecycle of both technologies. Finally, areal density of HDD is plotted on the growth curve to forecast the saturation point of researching on conventional longitudinal recording.

The results produced from utilizing these tools indicate that these two technologies are continuously under development. It is found that the growth of improving areal density of conventional recording will be nearing zero by year 2013 and the maximum growth rate of development was in year 2006.

The forecasting is based on principal technologies of conventional longitudinal recording of HDD. Also, NOR and NAND are considered as two main technologies dominating flash memory. Other emerging data storage technologies such as holographic data storage, phase‐change memory (PCM) are not included in this paper. Likewise, the growth curve of flash memory is not analyzed as part of this paper.

This paper forecasts the future of data storage technologies. Integration of scientific indicators and growth curves is demonstrating a powerful tool for forecasting technology futures.

The paper aims to provide an overview of the area of smart textiles.

The paper describes and discusses new and developing materials and technologies used in the textile industries.

Significant progress has been achieved in the area of technical textiles. Fibres, yarns, fabrics and other structures with added‐value functionality have been successfully developed for technical and/or high performance end‐uses. The basic building blocks are already in place in the field of smart textiles and clothing.

As progress in science and engineering research advances, and as the gap between designers and scientists narrows, the area of smart clothing is likely to keep on expanding for the foreseeable future. Growth is predicted to occur in two distinct directions: performance‐driven smart clothing and fashion‐driven smart clothing. There are challenges that have to be addressed.

The paper provides information of value to those interested in the future directions of the textile industry.

This paper outlines the innovations in high functional and high performance fibres for applications in protective clothing, including fibres for flame and heat protection. It also describes some typical woven and non‐woven constructions for such applications. And presents the trends in producing smart textile materials, capable of interacting with human/environmental conditions.

This study aims to present an architectural application of 4D-printed climate-adaptive kinetic architecture and parametric façade design.

This work investigates experimental prototyping of a reversibly self-shaping façade, by integrating the parametric design approach, smart material and 4D-printing techniques. Thermo-responsive building skin modules of two-way shape memory composite (TWSMC) was designed and fabricated, combining the shape memory alloy fibers (SMFs) and 3D-printed shape memory polymer matrices (SMPMs). For geometry design, deformation of the TWSMC was simulated with a dimension-reduced mathematical model, and an optimal arrangement of three different types of TWSMC modules were designed and fabricated into a physical scale model.

Model-based experiments show robust workability and formal reversibility of the developed façade. Potential utility of this module for adaptive building design and construction is discussed based on the results. Findings help better understand the shape memory phenomena and presented design-inclusive technology will benefit architectural communities of smart climate-adaptive building.

Two-way reversibility of 4D-printed composites is a topic of active research in material science but has not been clearly addressed in the practical context of architectural design, due to technical barriers. This research is the first architectural presentation of the whole design procedure, simulation and fabrication of the 4D-printed and parametrically movable façade.

The purpose of this paper is to analyze and compare the characteristics of hybrid conventional complementary metal oxide semiconductor/magnetic tunnel junction (CMOS/MTJ) logic gates based on spin transfer torque (STT) and differential spin Hall effect (DSHE) magnetic random access memory (MRAM).

Spintronics technology can be used as an alternative to CMOS technology as it is having comparatively low power dissipation, non-volatility, high density and high endurance. MTJ is the basic spin based device that stores data in form of electron spin instead of charge. Two mechanisms, namely, STT and SHE, are used to switch the magnetization of MTJ.

It is observed that the power consumption in DSHE based logic gates is 95.6% less than the STT based gates. DSHE-based write circuit consumes only 5.28 fJ energy per bit.

This paper describes how the DSHE-MRAM is more effective for implementing logic circuits in comparison to STT-MRAM.