Traditional Setup Research Articles

A Conceptual Framework of Information Security Database Audit and Assessment

Today, databases are on of the most important things in the IT world and it is also becoming more and more popular and organizations globally are gradually moving their traditional IT setup to database model to gain the benefits of securing the data and in terms of providing easy access to, and elasticity of IT services. With database security, the IT service roles within an organization become integrated hence giving the overall IT operating model a more structured layout. Such objectivity however can only be materialized when proper planning and execution are put in place. As such, a proper execution and implementation of database system would include a stringent set of checks and audit processes. The goal of database auditing is central towards determining if the services engaged and its―maintainers are meeting certain legal requirements in terms of protecting customers data and organization standards to achieve secure data assets success against various security threats. Therefore, this project explores the factors influencing security audit quality by collecting data using structured group discussion.

Active Management of Heat Customers Towards Lower District Heating Return Water Temperature

The traditional way of managing the supply and return water temperatures in a district heating system (DHS) is by controlling the supply water temperature. The return water temperature then becomes a passive result that reflects the overall energy efficiency of the DHS. A DHS with many poorly functioning district heating centrals will create a high return water temperature, and the energy efficiency of the DHS will be affected negatively in several ways (e.g., lower efficiency of the flue gas condenser, higher heat losses in pipes, and lower electricity production for a DHS with combined heat and power (CHP)). With a strategic introduction of low-grade heat customers, the return water temperature can be lowered and, to some extent, controlled. With the heat customers connected in parallel, which is the traditional setup, return water temperatures can only be lowered at the same rate as the heat customers are improved. The active management of some customers can lower the return water temperatures faster and, in the long run, lead to better controlled return water temperatures. Active management is defined here as an adjustment of a domestic heating system in order to improve DHS efficiency without affecting the heating service for the individual building. The opposite can be described as passive management, where heat customers are connected to the DHS in a standardized manner, without taking the overall DHS efficiency into consideration. The case study in this article shows possible efficiency gains for the examined DHS at around 7%. Looking at fuel use, there is a large reduction for oil, with 10–30% reduction depending on the case in question, while the reduction is shown to be largest for the case with the lowest return water temperature. The results also show that efficiency gains will increase electricity production by about 1–3%, and that greenhouse gas (GHG) emissions are reduced by 4–20%.

Distributed training of deep neural networks with spark: The MareNostrum experience

Deployment of a distributed deep learning technology stack on a large parallel system is a very complex process, involving the integration and configuration of several layers of both, general-purpose and custom software. The details of such kind of deployments are rarely described in the literature. This paper presents the experiences observed during the deployment of a technology stack to enable deep learning workloads on MareNostrum, a petascale supercomputer. The components of a layered architecture, based on the usage of Apache Spark, are described and the performance and scalability of the resulting system is evaluated. This is followed by a discussion about the impact of different configurations including parallelism, storage and networking alternatives, and other aspects related to the execution of deep learning workloads on a traditional HPC setup. The derived conclusions should be useful to guide similarly complex deployments in the future.

Bistatic RCS Measurements of Large Targets in a Compact Range

This communication illustrates the ability to perform bistatic radar cross-section (RCS) measurements at a fixed bistatic angle in a compact range. Literature regarding bistatic RCS measurements in compact ranges is limited. The traditional setup of a compact range was adapted to perform bistatic RCS measurements. These bistatic measurements were conducted on canonical and complex realistic scale airframe models. The targets were illuminated with a plane wave created by an offset parabolic dish reflector. The bistatic scattering of the targets was measured by placing a receive antenna at a fixed bistatic angle and finite distance in the compact range. This communication also investigates the effect of the finite separation between the targets and the receiver on the bistatic scattering measurements of large complex targets. The accuracy of the bistatic RCS measurements is compared to full-wave simulations conducted with FEKO using the multilevel fast multipole method solver. Quantitative comparisons are drawn between the simulations and measurements using the feature selective validation method.

A novel testing setup for determining the flexural properties of tunnel segmental joints: Development and application

A novel testing setup is developed for structural tests on segmental joints of shield tunnels. It lies on the ground and is a self-balanced system. The applied axial force and bending moment are coupled, and the combination of target axial force and bending moment at the joint can be achieved by adjusting the horizontally-applied forces. It is more economic and flexible than the traditional two-point bending testing setups. The effectiveness of internal force/moment transmission of the testing setup was verified by comparing the experimental data with theoretically-determined values and numerical simulation results. It was then applied to investigate the flexural behaviour of longitudinal joint of a deeply-buried tunnel subjected to both sagging and hogging moments. The rotational stiffnesses of the testing joint were determined. The influences of bending moment and axial force on joint deformation were unified through eccentricity. In both the sagging moment and hogging moment cases, the joint deformation varied with eccentricity following a bilinear trend composed of an axial-force-dominant stage and a bending-moment-dominant stage. The slopes of the relationships between eccentricity and joint rotation angle are steeper in the hogging moment case than in the sagging moment case due to the absence of bolts at the extrados.

OTree Manager: Multi-user oTree installations made easy

oTree Manager is a software package designed to support the setup and management of multiple, production-ready oTree installations on the same server. Running in Docker containers, the individual instances run completely independent of each other while being less resource-intensive than traditional virtual machine setups. A convenient web interface provides both experimenters and laboratory managers with easy access to the most common actions and eliminates the need for command line interaction. Finally, oTree Manager comes with a novel Lobby feature which makes laboratory experiments that use oTree’s rooms feature more convenient to run.

Compact integrated magnetometer based on nitrogen-vacancy centres in diamond

We demonstrate an integrated and miniaturised magnetic field sensor based on the negatively charged nitrogen-vacancy centres (NV−) in diamond. The compact device includes all optical components, both for the optical excitation path and for the detection of the emitted fluorescence signal. We experimentally verify that it enables optically detected magnetic resonance (ODMR) measurements and we specify noise and sensitivity of the magnetometer. The minimal detectable magnetic field of the device is ≈ 1 μT for a given integration time of 1 ms, which is approximately one order of magnitude larger than its photon shot-noise limit. It has the significant advantage over traditional setups using NV− centres (including a laser and a complex optical system) that the specific construction volume is about 2.9 cm3 with a total power consumption of ≈ 1.5 W, which enables the device for a wide range of industrial sensing applications.

Lipolysis-Permeation Setup for Simultaneous Study of Digestion and Absorption in Vitro.

Lipid-based formulations (LBFs) are a delivery strategy to enhance intestinal absorption of poorly water-soluble drugs. LBF performance is typically evaluated by in vitro lipolysis studies, but these do not accurately predict the in vivo performance. One possible reason is the absence of an absorptive membrane driving sink conditions in the serosal compartment. To explore the impact of absorption under sink conditions on the performance evaluation, we developed a lipolysis-permeation setup that allows simultaneous investigation of intestinal digestion of an LBF and drug absorption. The setup consists of two chambers, an upper one for digestion (luminal), and a lower, receiving one (serosal), separated by a Caco-2 monolayer. Digestions were performed with immobilized lipase, instead of the pancreatic extract typically used during lipolysis, since the latter has proven incompatible with Caco-2 cells. Danazol-loaded LBFs were used to develop the setup, and fenofibrate-loaded LBFs were used to establish an in vitro in vivo correlation. As in regular lipolysis studies, our setup allows for the evaluation of (i) the extent of digestion and (ii) drug distribution in different phases present during lipolysis of drug-loaded LBFs (i.e., oil, aqueous, and solid phase). In addition, our setup can determine drug permeation across Caco-2 monolayers and hence, the absorptive flux of the compound. The presence of the absorptive monolayer and sink conditions tended to reduce aqueous drug concentrations and supersaturation in the digestion chamber. The drug transfer across the Caco-2 membrane accurately reflected in vivo drug exposure upon administration of three different LBFs loaded with fenofibrate, where the traditional lipolysis setup failed to predict in vivo performance. As the new setup reflects the dynamic processes occurring in the gastrointestinal tract, it is a valuable tool that can be used in the development of LBFs prior to in vivo studies.

Ear field adaptive noise control for snoring: an real-time experimental approach

In this paper, an active noise control &#x0028 ANC &#x0029 system is developed to provide an effective and non-intrusive solution for reducing loud snoring to provide a quiet environment for a snorer &#x02BC s bed partner. An adaptive least mean square &#x0028 LMS &#x0029 algorithm optimized for different kinds of snore signals is introduced and theoretically analyzed. Also, a residual noise masking approach is proposed to further reduce the effect of the snore noise without interfering with the LMS algorithm. Computer simulations followed by real-time experiments are conducted to demonstrate the feasibility of the snore ANC systems based on a pillow setup. For the optimum effect based on the characteristics of human hearing, the performance of the proposed approach is evaluated by using the multi-channel feedforward ANC systems based on the filtered-X least mean square &#x0028 FXLMS &#x0029 algorithm. Compared with a traditional headboard setup for snoring noise control, the proposed snore ANC systems optimized for ear field operation yield much higher noise reduction around the ears of the snorer&#x02BC s bed partner.

Feedback Stackelberg-Nash Equilibria in Mixed Leadership Games with an Application to Cooperative Advertising

In this paper we characterize the feedback equilibrium of a general infinite-horizon Stackelberg-Nash differential game where the roles of the players are mixed. By mixed we mean that one player is a leader on some decisions and a follower on other decisions. We prove a verification theorem that reduces the task of finding equilibrium strategies in functional spaces to two simple steps: First solving two static Nash games at the Hamiltonian level in a nested version and then solving the associated system of Hamilton-Jacobi-Bellman equations. As an application, we study a novel manufacturer-retailer cooperative advertising game where, in addition to the traditional setup into which the manufacturer subsidizes the retailer’s advertising effort, we also allow the reverse support from the retailer to the manufacturer. In this representative case, we find an equilibrium that can be expressed by a solution of a set of algebraic equations. We then conduct an extensive numerical study to assess the impact of model parameters on the equilibrium.

DeepFog: Fog Computing-Based Deep Neural Architecture for Prediction of Stress Types, Diabetes and Hypertension Attacks

The use of wearable and Internet-of-Things (IoT) for smart and affordable healthcare is trending. In traditional setups, the cloud backend receives the healthcare data and performs monitoring and prediction for diseases, diagnosis, and wellness prediction. Fog computing (FC) is a distributed computing paradigm that leverages low-power embedded processors in an intermediary node between the client layer and cloud layer. The diagnosis for wellness and fitness monitoring could be transferred to the fog layer from the cloud layer. Such a paradigm leads to a reduction in latency at an increased throughput. This paper processes a fog-based deep learning model, DeepFog that collects the data from individuals and predicts the wellness stats using a deep neural network model that can handle heterogeneous and multidimensional data. The three important abnormalities in wellness namely, (i) diabetes; (ii) hypertension attacks and (iii) stress type classification were chosen for experimental studies. We performed a detailed analysis of proposed models’ accuracy on standard datasets. The results validated the efficacy of the proposed system and architecture for accurate monitoring of these critical wellness and fitness criteria. We used standard datasets and open source software tools for our experiments.

Fast-bunching design of compact heavy ion RFQ linac

We propose the construction of a compact linac as the injector of a cancer therapy facility at the Institute of Modern Physics (IMP) of the Chinese Academy of Sciences (CAS). Based on a traditional setup, a new compact fast-bunching design is first introduced to optimize the 600 keV/u RFQ with a 0.05 pmA $$^{12}\hbox {C}^{4+}$$ beam. This shortens the RFQ structure length from the standard design value of 272–230 cm while effectively regulating the particle loss and emittance growth. In addition, a detailed error analysis was performed after the optimization process. The error sources cover input beam parameters errors, machining errors and alignment errors. The simulation results show that the beam loss and emittance growth of the RFQ are acceptable and within typical ranges of error.

Alternative edge illumination set-up for single-shot X-ray phase contrast imaging

Edge illumination (EI) is a promising X-ray phase contrast imaging (XPCI) technique and is expected to translate XPCI into practical applications with laboratory X-ray sources. However, traditional double-mask EI setup requires two acquisitions for extracting phase and absorption information. Although the latest single-mask EI setup allows phase retrieval with single-shot, it requires a nearly ideal detector point spread function (PSF). In this paper, an alternative EI setup is proposed, which remains double-mask but requires only a single-shot. It can implement single-shot XPCI and relax the detector requirements. Numerical calculations are carried out to compare the characteristics of the double- and single-mask EI setup and the proposed setup. The performance of this setup with different illumination conditions is evaluated theoretically. The results suggest that the proposed setup is less affected by the detector PSF compared to the single-mask EI setup and therefore has higher contrast and contrast-to-noise ratio. Phase retrieval can be implemented by this setup with a single-shot, which helps to simplify the operations and eliminate the potential errors in the double-mask EI setup. A narrow illumination width contributes to the contrast but adversely affects the radiation utilization efficiency, and some appropriate trade-offs should be selected according to the practical applications and experimental conditions. On the basis of this setup, the extraction of the quantitative phase and absorption information was also conducted by numerical calculation.

Surface Guided Radiation Therapy as a Replacement for Patient Marks in Treatment of Breast Cancer

To determine potential improvement of patient setup accuracy and efficiency using Surface Guided Radiation Therapy (SGRT) instead of traditional three-point markers for breast irradiation. The current standard for patient positioning at isocenter uses at least three markers, placed directly on the skin (e.g., tattoos or other semi-permanent methods). Multiple sets of marks are often required as significant shifts are determined during the treatment planning process and/or throughout treatment to match image guidance. Anecdotally, patients often complain about the inconvenience and cosmetic disadvantages of maintaining skin marks. Contrastingly, SGRT uses visual (non-ionizing), real-time monitoring of the patient’s external surface contour and quantitatively compares to a calculated or acquired reference image. If proven at least as accurate and efficient as the traditional setup technique, SGRT potentially allows for the abandonment of physical marking systems. Data was collected for over 250 breast treatments involving 17 patients over a 90 day period. For each patient, half the total fractions were setup using the SGRT method, while the remaining fractions were setup using the three-point marker method. Total setup time was also tracked during each verification procedure, which is typically much longer in duration than a normal treatment fraction. For each patient, the same therapist(s) performed all setups to reduce variability. Data recorded for each fraction included total time in treatment room, source-to-surface distance (SSD; as compared to the expected value from the treatment planning system), and the magnitude of couch shifts based on weekly image guidance (as determined by a physician). The average magnitude of time spent setting up and treating breast patients via the three-point marker technique was 5.48 ± 1.52 minutes. Contrastingly, using SGRT, the respective times were consistently lower, at an average of 4.72 ± 0.87 minutes. The average shift magnitudes subsequent to setup and based on image guidance was 0.71 ± 0.29 cm for the marker setups, but reduced to 0.47 ± 0.31 cm for SGRT setups. The average difference in SSD (treatment plan vs. final treatment position) was 0.30 ± 0.14 cm using the three-point setup, and 0.27 ± 0.12 cm for SGRT setup. Statistically significant differences in efficiency and accuracy were similarly recorded during initial setup (i.e., verification) appointments. SGRT setup for breast patients was observed to be more accurate and efficient than the marker-based technique. Fully utilizing SGRT allows for the implementation of a completely markless system of simulation and treatment, thereby simultaneously improving patient satisfaction, throughput, and setup accuracy. This study demonstrates potential similar improvements if SGRT is applied to the entire spectrum of treatment sites.

A Compendium of Performance Metrics, Pricing Schemes, Optimization Objectives, and Solution Methodologies of Demand Side Management for the Smart Grid

The curtailing of consumers’ peak hours demands and filling the gap caused by the mismatch between generation and utilization in power systems is a challenging task and also a very hot topic in the current research era. Researchers of the conventional power grid in the traditional power setup are confronting difficulties to figure out the above problem. Smart grid technology can handle these issues efficiently. In the smart grid, consumer demand can be efficiently managed and handled by employing demand-side management (DSM) algorithms. In general, DSM is an important element of smart grid technology. It can shape the consumers’ electricity demand curve according to the given load curve provided by the utilities/supplier. In this survey, we focused on DSM and potential applications of DSM in the smart grid. The review in this paper focuses on the research done over the last decade, to discuss the key concepts of DSM schemes employed for consumers’ demand management. We review DSM schemes under various categories, i.e., direct load reduction, load scheduling, DSM based on various pricing schemes, DSM based on optimization types, DSM based on various solution approaches, and home energy management based DSM. A comprehensive review of DSM performance metrics, optimization objectives, and solution methodologies is’ also provided in this survey. The role of distributed renewable energy resources (DERs) in achieving the optimization objectives and performance metrics is also revealed. The unpredictable nature of DERs and their impact on DSM are also exposed. The motivation of this paper is to contribute by providing a better understanding of DSM and the usage of DERs that can satisfy consumers’ electricity demand with efficient scheduling to achieve the performance metrics and optimization objectives.

High-yield production of high-quality graphene by novel electrochemical exfoliation at air-electrolyte interface

An end-face electrochemical exfoliation (EFEE) strategy for scalable graphene preparation is established, which has the confined area and thus guarantees uniform current density at the air-electrolyte interface, different from the traditional electrode set-up. The production of graphene is presented that has excellent yield (∼100%) and outstanding conductivity (3.8 × 104 S m−1 with a graphene loading of 0.7 mg cm−2). The exfoliation mechanism is also discussed.

Development of Information Evaluation System for Smart City Planning Using Geoinformatics Techniques

Urbanization is a continuous process, which transforms the traditional setup into the modern era. Uneven population growth over the next 3 decades is expected in cities. In this context, the new technology-based solutions are desirable, which can provide more efficient and robust approaches for urban infrastructure planning. Keeping these visions, the smart city concept is evolving in the developing countries like India, which appears a new paradigm of systematic intelligent urban infrastructure planning in the city. This research work comprises of grids-based, eight different land use and infrastructure-related information evaluation systems namely urban settlements information evaluation system, water resource information evaluation system, urban green space information evaluation system, intelligent transportation information evaluation system, basic infrastructure information evaluation system, power distribution information evaluation system, telecommunication mast information evaluation system and city surveillance information evaluation system for the development of smart city priority zones in the Bhopal city, capital of Madhya Pradesh, India. The LISS IV and Cartosat 1 sensor digital Image data along with ancillary data were used. The GPS survey was carried out to confirm ground realities, and digital intelligent map was prepared for various utilities after integration of thematic layers. The geostatistical analysis and weights-based methods were used for the creation of information evaluation system for city planning. The investigation of results have shown that various parameters related to smart city planning can be analyzed in a more efficient manner by dividing the area into an appropriate size grid. The spatial integration of information evaluation systems were carried out and areas were divided into low-, medium- and high-priority zones. These prominent categories such as high-priority zones covered the 14% of the study area, similarly medium-priority zones covered the 34% of the study area and low-priority zones covered the 52% of the study area. This research work investigations are very useful for the formulation of new strategic plans, in order to achieve better land use and infrastructure features utilization for the smart city planning.

Intelligent use of fog devices in edge‐cloud paradigm to assist in E‐polling

SummaryInternet is playing a vital role in providing information to billions of people around the world. It is the fastest way to communicate information worldwide. Over the years, information technology has provided solutions to many problems in different domains of life. With the advent of cloud computing and the internet of things (IOT), most of these domains are now employing cloud networks to save resources and money. Cloud provides a platform to store and process information with minimal resources and investment. Due to the vast geographical distribution and large distances between the cloud networks and the end user nodes, transmission of data over cloud networks provides problems of latency and delay that can cause major hazards in applications that require real‐time processing. In order to analyze the issues related to slow/no response from Clouds, a case study based on a mock E‐poll held under the Election commission of Pakistan is analyzed, and a remedy to the latency experienced during the polling process has been suggested. It involves the use of the newly proposed Fog Computing Paradigm to allow fast processing of real‐time data. This paper provides a solution to latency issues in cloud networks by proposing an intelligent way of identifying which data can be processed on close‐proximity Fog networks and which can be sent to the cloud for bulk processing. The aim is to reduce the time consumed for real‐time processing over the traditional cloud setup.

Two-factor authentication for trusted third party free dispersed storage

We propose a trusted third party free protocol for secure (in terms of content access, manipulation, and confidentiality) data storage and multi-user collaboration over an infrastructure of untrusted storage servers. It is achieved by the application of data dispersal, encryption as well as two-factor (knowledge and possession) based authentication and access control techniques so that unauthorized parties (attackers) or a small set of colluding servers cannot gain access to the stored data. The protocol design takes into account usability issues as opposed to the closest prior work Esiner and Datta (2016). We explore the security implications of the proposed model with event tree analysis and report on experiment results to demonstrate the practicality of the approach concerning computational overheads. Given that the protocol does not rely on any trusted third party, and most operations including actual collaboration do not require users to be online simultaneously, it is suitable not only for traditional multi-cloud setups but also for edge/fog computing environments.

High-throughput transient thermal interface testing method using time-domain thermal response

In the field of thermal interface testing, the one-dimensional (1D) reference bar method has been the most popular and trusted among many available techniques. However, this steady-state method has several drawbacks, including low test speed and inability to capture dynamic response. In this paper, we report a high-throughput transient method that can be used in concert with the traditional 1D reference bar setup without hardware modifications. Instead of waiting for steady-state conditions, the method requires only an arbitrary segment of the transient thermal response in the time domain. The transient thermal model and data fitting algorithm are presented. Radiation heat loss and temperature-dependent thermophysical properties are incorporated in the model to improve high-temperature accuracy. The measurement uncertainty is quantified numerically, and the criteria for choosing the input segment are discussed. The effects of the TIM (thermal interface material) heat capacity are also investigated, and reveal that in most practical cases, the measurement result is not sensitive to the heat capacity of the TIM. In the end, we demonstrate this method on a commercial TIM sample over a wide temperature range (room temperature to 400 °C) and show that the results are comparable to those obtained from a steady-state method but with drastically reduced testing time.