Space Savings Research Articles

Efficient lossless compression for depth information in traffic scenarios

Modern day automotive features (e.g., in-vehicle augmented reality) require a depth of the environment as the input source. It is important that depth data can be transferred from one processing unit to another in a car. About 10 years ago, Stixel has been introduced as a mid-level representation of depth maps (disparities) which reduces the data volume thereof significantly. Since then, Stixel has been extensively researched and is nowadays a seriously considered solution for series production cars. Nevertheless, even after using a Stixel representation, the depth data can hardly fit into a low- or medium-bandwidth in-vehicle communication system, e.g., via a CAN bus. Hence, the cost-sensitive automotive industry is still seeking new solutions for the transmission of depth information using in-vehicle communication buses. In this paper, we present an efficient lossless compression scheme for Stixels as a potential solution to this problem. Our proposed algorithm removes both spatial and temporal redundancies in Stixels through a combination of predictive modeling and entropy coding. Evaluation shows that it outperforms general purpose compression schemes, e.g., zlib, by more than $$60\%$$ in space savings. More importantly, we prove that using the proposed Stixel compression, depth information could be transmitted through a less expensive CAN bus, whereas a much more expensive FlexRay bus is needed otherwise. We believe that this finding has great relevance for the automotive industry.

Adaptive deduplication of virtual machine images using AKKA stream to accelerate live migration process in cloud environment

Cloud Computing is a paradigm which provides resources to users from its pool based on demand to satisfy their requirements. During this process, many servers are overloaded and underloaded in the cloud environment. Thus, power consumption and load balancing are the major problems and are resolved by live virtual machine (VM) migration. Load balancing is addressed by moving virtual machines from overloaded host to under loaded host and from under loaded host to any other host which is not overloaded called VM migration. If this process is done without power off (Live) the virtual machines then it is called live VM migration. By this process, the issue of power consumption by physical hosts is also resolved. Migrating virtual machines involves virtualized components like storage disks, memory, CPU and networking, the entire state of VM is captured as a collection of data files. These data files are virtual disk files, configuration files, and log files. The virtual disk files take larger memory and take more migration time and hence the downtime. These disk files include many zero pages, similar and redundant pages. Many techniques such as compression, deduplication is used reduce the size of VM disk image file. Compression techniques are not widely used, due to the disadvantage of compression ratio and decompression time. Many researchers hence used deduplication techniques for reducing the VM disk image file in the live migration process. The significance of the research work is to design an adaptive deduplication mechanism for reducing VM disk image file size by performing fixed length and variable length block-level deduplication processes. The Rabin-Karp rolling hash algorithm is used in variable length block-level deduplication. Akka stream is used for streaming the VM disk image files as it is the bulk volume of live data transfer. To reduce the time of the deduplication process, many researchers used multithreading and multi-core technologies. We use multithreading in Akka framework to run the deduplication process concurrently without OutofMemory errors. The experiment results show that we achieved a maximum of 83% overall reduction in image storage space and 89.76% reduction in total migration time are achieved by adaptive deduplication method. 3% improvement in deduplication rate when compared with the existing image management system. The results are significant because when we apply this in the storage of data centres, there are much space savings. The reduction in size is dependent on the dataset was taken and the applications running on the VM.

Modelling of CO2 absorption in a rotating packed bed using an Eulerian porous media approach

The rotating packed bed (RPB) is a promising reactor for CO2 capture with liquid amine because of its high mass transfer rate and energy and space savings. The CFD simulations of RPBs generally use the volume of fluid (VOF) method, but this method is prohibitively expensive for 3D simulations, in particular for large-scale reactors. The Eulerian method is a promising and effective method; however, there are still several difficulties, such as the settings for the porous media models in the gas-liquid counter-current flow and the interfacial area between the gas and liquid. To overcome these difficulties in the Eulerian method, this paper uses a new porous media model, a novel liquid generation-elimination model for numerically investigating the gas-liquid counter-current flow in RPBs and a new interfacial area model derived from the VOF simulation. These new models, incorporating the two-film reaction-enhancement mass transfer model, have successfully simulated the CO2 capture process with monoethanolamine (MEA) solutions in a RPB under both low (30 wt%) and high (90 wt%) concentration conditions. The results show that the overall gas phase mass transfer coefficient (KGa) increases with increasing the rotation speeds and the liquid to gas mass flow rate (L/G ratio). The simulations were validated by the experimental data and the results were analysed and discussed.

Text representation and classification based on bi-gram alphabet

In text classification, texts have to be transformed into numeric representations suitable for the learning algorithms. A main problem with the commonly used bag of words method is the high dimensions of vector space, as well as the need for language-dependent tools. In the present study, text classification is performed based on a novel bi-gram alphabet approach to construct feature terms. The proposed approach has two main contributions to text classification area. First, we have demonstrated the possibility of using constant feature terms that are based on the standard alphabet without the need for the documents vocabularies; this definitely helps in reducing the dimensions of the vector space for large corpus. Second, it does not require natural language processing tools. The current work has proved the ability to classify collections of Arabic or English text documents successfully. It showed approximately 80% savings in vector space and 2% performance improvement compared to the best recorded results on Arabic dataset Aljazeera News.

Optimal Choice of When to Garbage Collect

We consider the ultimate limits of program-specific garbage collector (GC) performance for real programs. We first characterize the GC schedule optimization problem. Based on this characterization, we develop a linear-time dynamic programming solution that, given a program run and heap size, computes an optimal schedule of collections for a non-generational collector. Using an analysis of a heap object graph of the program, we compute a property of heap objects that we call their pre-birth time. This information enables us to extend the non-generational GC schedule problem to the generational GC case in a way that also admits a dynamic programming solution with cost quadratic in the length of the trace (number of objects allocated). This improves our previously reported approximately optimal result. We further extend the two-generation dynamic program to any number of generations, allowing other generalizations as well. Our experimental results for two generations on traces from Java programs of the DaCapo benchmark suite show that there is considerable promise to reduce garbage collection costs for some programs by developing program-specific collection policies. For a given space budget, optimal schedules often obtain modest but useful time savings, and for a given time budget, optimal schedules can obtain considerable space savings.

Improving Soft Decoding by Spectral Leakage Reduction in Presence of Narrow Band Interference in PLC

Communications over power lines (PLC) is a promising technology for a variety of applications. The use of a single network for power and data transmission with PLC provides weight, space, and cost savings for vehicular communications. Current work focuses on broadband PLC (BPL) systems compliant with the IEEE 1901 standard. Given that transmissions occur on a physical medium not designed for data communication, the channel and noise characteristics are mostly unfavorable. To deal with these conditions, turbo codes have been widely employed due to their high performance. However, their performance strongly depends on the accuracy of the noise estimation. This work addresses the estimation of the noise power spectral density (PSD) to perform soft-decoding. A general background noise (GBN) model and a narrowband interference (NBI) model is considered. To the best of our knowledge, this is the first work that analyzes the effects of the NBI leakage on noise estimation when it is performed during the reception of the data frame. We propose the use of the frame control (FC) symbol to reduce interference leakage on noise estimation. In addition, we investigate the use of payload symbols to further reduce spectral leakage. Finally, we show that system performance considerably improves by using the FC-based estimation in soft-decoding procedures.

Write Deduplication and Hash Mode Encryption for Secure Nonvolatile Main Memory

For nonvolatile main memory (NVMM), both security and endurance are important. However, the diffusion property of memory encryption renders existing bit-level write reduction techniques ineffective. This paper proposes DeWrite, a line-level write reduction technique to enhance the endurance and performance of secure NVMM. Moreover, DeWrite leverages a new encryption technique, i.e., hash mode encryption, and exploits opportunistic parallelism between encryption and deduplication operations to efficiently synergize deduplication and encryption for space and time savings.

How to determine slot sizes in a unit-load warehouse

Storage racks in a unit-load warehouse typically have slots of equal height, whereas the unit-loads themselves have heights that vary significantly. The result of this mismatch is unused vertical space and storage areas larger than they otherwise could be. We propose the use of storage racks with multiple slot heights to better match the distribution of pallet heights. The slot profile design problem seeks the best set of slot heights and their corresponding quantities such that a desired service level is met, where service level is the probability that all pallets present in a period can be stored. Using data from several companies, we found that the potential space savings of using multiple slot heights are between 29% and 45%.

Heating, Ventilation, and Air Conditioning (HVAC) Noise Detection in Open-Plan Offices Using Recursive Partitioning

Open-plan offices have lower construction costs, allowing for significant savings in space and, according to designers, facilitate communication between workers, thus, improving collaboration, as well as the exchange of ideas. For these reasons, this type of office has become widespread, while highlighting numerous limitations and various problems. These include the control of anthropic and electromechanical noise. In this study, measurements of the noise emitted by a heating, ventilation, and air conditioning (HVAC) system were carried out in an open-plan office. The average spectral levels in a 1/3 octave band were compared through correlation analysis, to identify any redundant data. A model was then adapted to evaluate the importance of the variables, in order to classify the characteristics, by importance. To reduce the number of predictor variables, a selection analysis of the characteristics was carried out. A subset of predictors was extracted to be used to produce an accurate prediction model. Finally, a model based on recursive partitioning, to detect the operating conditions of an HVAC system, was developed and applied, so as to provide insights into the development and application of this technique, in these contexts. The high accuracy of the model (Accuracy = 0.9981) suggests the adoption of this tool for several applications.

Experimentally Study the Effects of Fins Height and Space Ratio (H\\S) to the Fin thermal performance by Natural Convections

Heat transfer enhancement devices are widely used in various industrial, transportation, or domestic applications such as thermal power plants, means of transport, heating and air conditioning systems, electronic equipments and space vehicles. In all these applications, improvements in the efficiency of heat exchangers can lead to substantial cost, space and materials savings. The research work summarized in this articles presents an experimental investigation on the effect of fin space (S) on the fin performance using rectangular plate type fins. The steady-state natural convection heat transfer from vertical rectangular fins extending perpendicularly from horizontal square base was investigated experimentally at high range of temperatures from 50 to 150 C°. The effects of fin space parameter, fin height-space (H\\S) ratio and base-to-ambient temperature difference on the heat transfer performance of fin arrays were observed and the environmental condition were determined.. Five fin height-space ratios settings 1.31,1.43,1.67,1.85 and 2.27 with constant fin surface area were employed under free convection heat transfer conditions. The heat transfer area was kept the same. The performance of the fin expressed in terms of fin efficiency, effectiveness and thermal resistance as a function of the ambient temperature and fin space parameters has been study in this work. The dimensionless parameter Biot no. on the locally variable environmental condition is examined for different fin spaces and fin height-space (H\\S) ratio to the fin heat transfer rate. Also, the effect of environmental condition is study at the same (H\\S) ratio. Experimental results show that the effect of Height-Space ratio (H\\S) on fin performance is more significant.. The maximum increase in convection heat transfer coefficient value obtained is about 19 percent. The increase in heat transfer coefficient value is also manifested by a corresponding decrease in the fin base temperature. Also, it is concluded from the experimental results that the performance of heat transfer rate increase with increasing the height- space ratio (H\\S) and decreasing the fin space in respect of heat transfer coefficient, thermal resistance, overall efficiency and effectiveness.

A Simple Harmonic Reduction Method in 20-Pulse AC–DC Converter

This paper proposes a simple and passive harmonic reduction method at dc link of 20-pulse rectifier. The 20-pulse topology is obtained via two paralleled 10-pulse ac–dc converters, each of them consisting of a five-phase (five-leg) diode bridge rectifier. For independent operation of the paralleled diode-bridge rectifiers, a zero sequence blocking transformer (ZSBT) is designed and implemented. Connection of a tapped inter-phase transformer (IPT) at the output of the ZSBT results in doubling the number of the output voltage pulses. The application of the pulse doubling technique with a low power rating (2% of the load power rating) results in a simpler and more economical configuration of the whole system and increased number of pulses. The design is suitable for retrofit applications where a six-pulse diode bridge rectifier is being utilized. The proposed structure is simulated using Matlab/Simulink software under different loading conditions. The simulation results confirm the significant improvement of the power quality indices (IEEE-519 standard requirements) at the point of common coupling (PCC). Experimental results are obtained using the designed and constructed laboratory prototype of the proposed converter to validate the design procedure and the simulation results. The VA rating of the magnetic circuit is calculated to confirm the savings in space, volume, weight and cost of the proposed configuration.

An experimentally investigate the fin thermal performance to the different fin spaces by natural convections

In oil and gas industries there are a lot off heat transfer devices used for different purposes. These devices are widely used in various industrial, transportation, or domestic applications such as heat exchangers thermal power plants, means of transport, heating and air conditioning systems, electronic equipments and space vehicles. In all these applications, improvements in the efficiency of heat exchangers can lead to substantial cost, space and materials savings. The research work summarized in this articles presents an experimental investigation on the effect of fin space (s) and aluminum materials on the fin performance using rectangular fins. The steady-state natural convection heat transfer from vertical rectangular fins extending perpendicularly from horizontal square base was investigated experimentally at new range not found in the previous works, this range of temperatures from 50 to 150 Co . The effects of fin space parameter and base-to-ambient temperature difference on the heat transfer performance of fin arrays were observed and the environmental condition were determined. Five fin space settings,( 22, 27, 30, 35 and 38 mm) with a constant fin height is 50mm for all types of configuration are presented in this work were employed under free convection heat transfer conditions. This range of fin space not found on previous study or research. The heat transfer area was kept the same. The performance of the fin expressed in terms of fin efficiency, effectiveness and thermal resistance as a function of the ambient temperature and fin space parameters has been study in this work. The dimensionless parameter Biot no. on the locally variable environmental condition is examined for different fin spaces to the fin heat transfer rate. Also, the effect of environmental condition is study. Experimental results show that the effect fin space on fin performance is more significant.. The maximum increase in convection heat transfer coefficient value obtained is about 22 percent. The increase in heat transfer coefficient value is also manifested by a corresponding decrease in the fin base temperature. Also, it is concluded from the experimental results that the performance of heat transfer rate increase with decreasing the fin space in respect of heat transfer coefficient, thermal resistance ,overall efficiency and effectiveness.

A method to choose between carton from rack picking or carton from pallet picking

Abstract In a manual picker-to-parts picking warehouse, a usual approach is to divide the whole stocking area in two different zones, the reserve and the forward areas. The dimensioning of the forward area, which is dedicated to picking activities, has an important impact on the overall performance of the picking system. Indeed, its size as well as the item allocation deeply influence the travel time of the operators on one side and the frequency of the refilling activities on the other. The present paper aims to provide a new method that can be easily used to assess the most suitable way of storing a product in the forward area, considering the possibility of keeping a product directly in a pallet or storing it in racks. Starting from simple data, such as the picking orders of the items to pick and their physical dimensions, as well as the characteristics of the warehouse, the method focuses on the comparison of the total times to define the Carton Pick from rack Convenience Condition (CPCC). The CPCC formulation and its application methodology allow to quickly establish which items should be stored on pallets and which on racks, with interesting impacts on space and time savings. This is shown also in the reported case study, the results of which prove the effectiveness as well as the easy and full applicability of the methodology, also in different warehouse contexts.

A Device-Independent Efficient Actigraphy Signal-Encoding System for Applications in Monitoring Daily Human Activities and Health.

Actigraphs for personalized health and fitness monitoring is a trending niche market and fit aptly in the Internet of Medical Things (IoMT) paradigm. Conventionally, actigraphy is acquired and digitized using standard low pass filtering and quantization techniques. High sampling frequencies and quantization resolution of various actigraphs can lead to memory leakage and unwanted battery usage. Our systematic investigation on different types of actigraphy signals yields that lower levels of quantization are sufficient for acquiring and storing vital movement information while ensuring an increase in SNR, higher space savings, and in faster time. The objective of this study is to propose a low-level signal encoding method which could improve data acquisition and storage in actigraphs, as well as enhance signal clarity for pattern classification. To further verify this study, we have used a machine learning approach which suggests that signal encoding also improves pattern recognition accuracy. Our experiments indicate that signal encoding at the source results in an increase in SNR (signal-to-noise ratio) by at least 50–90%, coupled with a bit rate reduction by 50–80%, and an overall space savings in the range of 68–92%, depending on the type of actigraph and application used in our study. Consistent improvements by lowering the quantization factor also indicates that a 3-bit encoding of actigraphy data retains most prominent movement information, and also results in an increase of the pattern recognition accuracy by at least 10%.

Fabrication and Performance of Supercapacitor Devices Using Binder-Free CNT Electrodes

Electric double layer capacitors (EDLCs) are a category of supercapacitors that generally compliment the performance of batteries through delivery of high power with significantly longer cycle life. The conventional active electrode material utilized in these EDLCs is activated carbon (AC) possessing high surface area through templated porosity. However, one of the primary limitations with AC-based supercapacitors using organic electrolytes is the operational voltage maximum around 2.75 V. Operation at higher voltages that push the 2.75 V barrier is the next essential developmental breakthrough to enable significant boosts to both energy and power densities of supercapacitors. Research into alternative active electrode materials is equally critical to enable and support high voltage operation of supercapacitors. This work demonstrates the fabrication of carbon nanotube (CNT) electrodes from organic-based dispersions without the inclusion of surfactant or binder, and subsequent assembly into supercapacitor devices. The performance of pouch cells assembled from the CNT electrodes and using conventional organic electrolytes at operating voltages ≥ 2.7 V is discussed. A significant and linear voltage dependence of capacitance (~ 3 times higher than AC) was observed for cells with CNT electrodes up to operational voltages ~ 3.5 V, which are currently not achievable using AC-based cells. Repeatable charge-discharge operation of the CNT-based EDLCs was demonstrated at 3.5 V and 70°C, with consequential increase to capacitance by ~ 25 - 30 % compared to 2.7 V operation. Power and energy densities were increased by 1.5 and 2 times respectively at 3.5 V compared to operation at 2.7 V. The performance characteristics from such CNT-based pouch cells were benchmarked against commercial-grade AC supercapacitor devices using organic electrolytes and rated at 2.75 V (single cell). Long-term performance advantages were observed for the CNT-based monocells at 3.5 V and 70°C, which passed 100k cycling tests at full discharge. Under the same test conditions, commercial AC-based cells failed early during the 100k cycling. Response times approaching 2 ms (at -45° phase angle) were also demonstrated with EDLC devices using thin CNT electrodes with 1 mF capacitance. Such EDLC devices may potentially rival aluminum electrolytic capacitors (AECs) for alternating current line-filtering applications, offering significant space savings compared to the bulky AEC components. Finally, the scalable fabrication of binder-free CNT electrodes from surfactant-free dispersion of the material was demonstrated by roll-to-roll, slot-die coating onto an Al foil current collector. The processing of these conformal CNT coatings, assembly into 18650 cylindrical cells, and the resulting EDLC performance characteristics are discussed. The CNT-based 18650 cells had an average capacitance of 7 F at 2.7 V, with low average ESR of 7 mΩ at 1 kHz, and average response time of 120 ms at -45° phase angle. Figure 1

Deepening subwavelength acoustic resonance via metamaterials with universal broadband elliptical microstructure

Slow sound is a frequently exploited phenomenon that metamaterials can induce in order to permit wave energy compression, redirection, imaging, sound absorption, and other special functionalities. Generally, however, such slow sound structures have a poor impedance match to air, particularly at low frequencies and consequently exhibit strong transmission only in narrow frequency ranges. This therefore strongly restricts their application in wave manipulation devices. In this work, we design a slow sound medium that halves the effective speed of sound in air over a wide range of low frequencies (hence our referral to the microstructure as “broadband”), whilst simultaneously maintaining a near impedance match to air. This is achieved with a rectangular array of acoustically rigid cylinders of elliptical cross section, a microstructure that is motivated by combining transformation acoustics with homogenization. Microstructural parameters are optimized in order to provide the required anisotropic material properties as well as near impedance matching. We then employ this microstructure in order to halve the size of a quarter-wavelength resonator (QWR) or equivalently to halve the resonant frequency of a QWR of a given size. This provides significant space savings in the context of low-frequency tonal noise attenuation in confined environments where the absorbing material is adjacent to the region in which sound propagates, such as in a duct. We employ the term “universal” since we envisage that this microstructure may be employed in a number of diverse applications involving sound manipulation.

Morton filters

Approximate set membership data structures (ASMDSs) are ubiquitous in computing. They trade a tunable, often small, error rate ( ϵ ) for large space savings. The canonical ASMDS is the Bloom filter, which supports lookups and insertions but not deletions in its simplest form. Cuckoo filters (CFs), a recently proposed class of ASMDSs, add deletion support and often use fewer bits per item for equal ϵ . This work introduces the Morton filter (MF), a novel AS-MDS that introduces several key improvements to CFs. Like CFs, MFs support lookups, insertions, and deletions, but improve their respective throughputs by 1.3x to 2.5x, 0.9x to 15.5x, and 1.3x to 1.6x. MFs achieve these improvements by (1) introducing a compressed format that permits a logically sparse filter to be stored compactly in memory, (2) leveraging succinct embedded metadata to prune unnecessary memory accesses, and (3) heavily biasing insertions to use a single hash function. With these optimizations, lookups, insertions, and deletions often only require accessing a single hardware cache line from the filter. These improvements are not at a loss in space efficiency, as MFs typically use comparable to slightly less space than CFs for the same epsis; .

CFRP retrofit of concrete circular columns: Evaluation of design guidelines

Carbon fiber reinforced polymer (CFRP) composite external wrapping has become an increasing popular strengthening and confining method for deteriorated or damaged concrete structures. The benefits are high strength-to-weight ratio, corrosion resistance, economy of labor and space savings. This study involved a non-linear theoretical modeling of axially loaded concrete columns with external CFRP laminate application. One-layer and two-layer application, and hoop versus inclined application, were considered. The theoretical of representative confined columns were contrasted against corresponding values from design guidelines. It was found that the guidelines significantly under-predict the strength, maximum stress and strain in CFRP confined columns. The extra CFRP layer was helpful in enhancing the column performance. The numerical model axial capacities were in line with published literature. The failure tensile strain in CFRP was quite a bit larger than the manufacturer suggested value. Inclined CFRP application was not as effective as the hoop application. An optimum value of the CFRP confining strength can be recommended to increase the accuracy of the design guidelines. The strain efficiency factor from ACI, which accounts for premature failure of the CFRP jacket, does not take into account the FRP contributions.

ENTICE VM Image Analysis and Optimised Fragmentation

Virtual machine (VM) images (VMIs) often share common parts of significant size as they are stored individually. Using existing de-duplication techniques for such images are non-trivial, impose serious technical challenges, and requires direct access to clouds' proprietary image storages, which is not always feasible. We propose an alternative approach to split images into shared parts, called fragments, which are stored only once. Our solution requires a reasonably small set of base images available in the cloud, and additionally only the increments will be stored without the contents of base images, providing significant storage space savings. Composite images consisting of a base image and one or more fragments are assembled on-demand at VM deployment. Our technique can be used in conjunction with practically any popular cloud solution, and the storage of fragments is independent of the proprietary image storage of the cloud provider.

String constraints with concatenation and transducers solved efficiently

String analysis is the problem of reasoning about how strings are manipulated by a program. It has numerous applications including automatic detection of cross-site scripting, and automatic test-case generation. A popular string analysis technique includes symbolic executions, which at their core use constraint solvers over the string domain, a.k.a. string solvers. Such solvers typically reason about constraints expressed in theories over strings with the concatenation operator as an atomic constraint. In recent years, researchers started to recognise the importance of incorporating the replace-all operator (i.e. replace all occurrences of a string by another string) and, more generally, finite-state transductions in the theories of strings with concatenation. Such string operations are typically crucial for reasoning about XSS vulnerabilities in web applications, especially for modelling sanitisation functions and implicit browser transductions (e.g. innerHTML). Although this results in an undecidable theory in general, it was recently shown that the straight-line fragment of the theory is decidable, and is sufficiently expressive in practice. In this paper, we provide the first string solver that can reason about constraints involving both concatenation and finite-state transductions. Moreover, it has a completeness and termination guarantee for several important fragments (e.g. straight-line fragment). The main challenge addressed in the paper is the prohibitive worst-case complexity of the theory (double-exponential time), which is exponentially harder than the case without finite-state transductions. To this end, we propose a method that exploits succinct alternating finite-state automata as concise symbolic representations of string constraints. In contrast to previous approaches using nondeterministic automata, alternation offers not only exponential savings in space when representing Boolean combinations of transducers, but also a possibility of succinct representation of otherwise costly combinations of transducers and concatenation. Reasoning about the emptiness of the AFA language requires a state-space exploration in an exponential-sized graph, for which we use model checking algorithms (e.g. IC3). We have implemented our algorithm and demonstrated its efficacy on benchmarks that are derived from cross-site scripting analysis and other examples in the literature.