Multi-Keyword search over encrypted data with scoring and search pattern obfuscation

Search over encrypted data recently became a critical operation that raised a considerable amount of interest in both academia and industry. Especially, as outsourcing, sensitive data to cloud prove to be a strong trend to benefit from the unmatched storage and computing capacities thereof. Indeed, privacy-preserving search over encrypted data, an apt term to address privacy-related issues concomitant in outsourcing sensitive data, have been widely investigated in the literature under different models and assumptions. In this work, we propose an efficient scheme that allows privacy-preserving search over encrypted data using queries with multiple keywords. Most important contributions of this work are as follows. Firstly, using a property referred as \(\delta \)-mean query obfuscation, the proposed scheme hides the search patterns, which are allowed to leak in many works in the literature including our preliminary work on the subject Orencik et al. (2013) [1]. Secondly, a two-server setting is employed to eliminate the correlation between the queries and matching documents sent to the user under the assumption that the two servers are not colluding. Thirdly, we propose a novel compression scheme that reduces both the communication cost between the two servers and the computation cost of the search operation more than 55 times compared to the standard approach. And finally, the proposed scheme also provides an effective scoring and ranking capability that is based on term frequency–inverse document frequency (tf-idf) weights of keyword–document pairs. Our analyses demonstrate that the proposed scheme is privacy-preserving, efficient and effective.     

An expert system based on S-transform and neural network for automatic classification of power quality disturbances

In this paper, an S-transform-based neural network structure is presented for automatic classification of power quality disturbances. The S-transform (ST) technique is integrated with neural network (NN) model with multi-layer perceptron to construct the classifier. Firstly, the performance of ST is shown for detecting and localizing the disturbances by visual inspection. Then, ST technique is used to extract the significant features of distorted signal. In addition, an optimum combination of the most useful features is identified for increasing the accuracy of classification. Features extracted by using the S-transform are applied as input to NN for automatic classification of the power quality (PQ) disturbances that solves a relatively complex problem. Six single disturbances and two complex disturbances as well pure sine (normal) selected as reference are considered for the classification. Sensitivity of proposed expert system under different noise conditions is investigated. The analysis and results show that the classifier can effectively classify different PQ disturbances.     

Fuzzy axiomatic design-based performance evaluation model for docking facilities in shipbuilding industry: The case of Turkish shipyards

The closest relationships between ship management companies and shipyards begin with the initial design process of new ships and they continue during the life cycle of operating ships. Periodic docking facilities which can be recognized as the biggest logistical issue in the content of ship maintenance program are the critical processes from the viewpoint of ship owners. Hence, this process should be well-planned and organized to satisfy the various expectations such as quality of service, capacity limitations, and geographical advantages, by taking cost and time constraints into account. Hence, the selection problem with respect to several criteria to find the most suitable shipyards is getting more important for ship management companies. This paper investigates a systematic evaluation model on docking facilities of shipyards to provide a decision aid for technical ship managers and to perform this responsibility in an efficient manner. Multiple criteria fuzzy axiomatic design (FAD) approach is used for selection among shipyards since FAD lets us define the design interval of each criterion. The original contributions of the paper are seemed in both enhancing the theoretical frame of FAD in terms of managing group consensus and performing an application to a real case in maritime industry.     

Classification of design parameters for E-commerce websites: A novel fuzzy Kano approach

Websites have gained vital importance for organizations along with the growing competition in the world market. It is known that usability requirements heavily depend on the type, audience and purpose of websites. For the e-commerce environment, usability assessment of a website is required to figure out the impact of website design on customer purchases. Thus, usability assessment and design of online pages have become the subject of many scientific studies. However, in any of these studies, design parameters were not identified in such a detailed way, and they were not classified in line with customer expectations to assess the overall usability of an e-commerce website. This study therefore aims to analyze and classify design parameters according to customer expectations in order to evaluate the usability of e-commerce websites in a more comprehensive manner. Four websites are assessed using the proposed novel approach with respect to the identified design parameters and the usability scores of the websites are examined. It is revealed that the websites with high usability score are more preferred by customers. Therefore, it is indicated that usability of e-commerce websites affects customer purchases.     

Optimization of reagent dosages with the use of response surface methodology and evaluation of test results with upgrading curves in graphite flotation

The aim of this study is to reduce reagent consumptions in graphite flotation with the addition of Aero 3477 promoter to the flotation stage. A three-level Box–Behnken design is used for optimization and modeling of flotation stages. For this purpose, the flotation experiments are performed in two steps. The maximum weight recovery and the minimum ash content values of the rougher concentrate are calculated as 21.41 and 32.49% using diesel oil dosage (714.24?g/t), methyl isobutyl carbinol (MIBC) dosage (212.81?g/t), and sodium silicate (Na₂SiO₃) dosage (1451.189?g/t), respectively, in the preliminary experiment tests. Subsequently, keeping the Na₂SiO₃ dosage constant, Aero 3477 promoter is added to the flotation stage to provide reduction at reagent consumptions. As a result, the reagent consumptions of diesel oil dosage (162.10?g/t), MIBC dosage (129.58?g/t), and Aero 3477 promoter dosage (168.96?g/t) are supplied to reach the approximate weight recovery and the ash content as in primary experimental results. Considerable dosage decreases in both diesel oil and MIBC are achieved using promoter. Moreover, experimental studies are also evaluated using upgrading curves.     

Energy Drink Induced Lipid Peroxidation and Oxidative Damage in Rat Liver and Brain When Used Alone or Combined with Alcohol

Energy drinks (ED) are containing large doses of metabolic stimulants and its use with ethanol has increased dramatically among young adults. In this study, we examined the effects of ED exposure either alone or in combination with ethanol on oxidative stress parameters including superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH‐Px), and lipid peroxidation parameter malondialdehyde (MDA) in rat. Some histopathological findings were also evaluated. ED exposure led to a dose‐dependent increase in liver MDA compared to the control indicating oxidative damage. Histopathological findings also revealed that ED alone may generate liver damage. Ethanol exposure increased MDA level and SOD, CAT, and GSH‐Px activity in both the brain and the liver. The combination of ethanol and ED produced greater damage which is considered by further increases in SOD and GSH‐Px activity in the brain. Similar results for MDA were observed in both the liver and brain as well. Our findings suggest that ED consumption alone or combination with ethanol may represent a significant public health concern.     

Exergetic sustainability indicators for a high pressure hydrogen production and storage system

This study examines the exergetic sustainability effect of PEM electrolyzer (PEME) integrated high pressure hydrogen gas storage system whose capacity is 3 kg/h. For this purpose, the indicators, previously used in the literature, are taken into account and their variations are parametrically studied as a function of the PEME operating pressure and storage pressure by considering i) PEME operating temperature at 70 °C, ii) PEME operating pressures at 10, 30, 50 and 100 bar, iii) hydrogen gas flow rate at 3 kg/h and iv) storage pressure between 200 and 900 bar. Consequently, the results from the parametric investigation indicate that, with the ascent of storage pressure from 200 to 900 bar at a constant PEME operating pressure (=50 bar), exergetic efficiency changes decreasingly between 0.612 and 0.607 while exergetic sustainability between 1.575 and 1.545. However, it is estimated that waste exergy ratio changes increasingly between 0.388 and 0.393 while environmental effect factor between 0.635 and 0.647. Additionally, it is said that the higher PEME outlet pressure causes the higher exergetic sustainability index, the lower environmental effect factor, the lower waste exergy output, the higher exergetic efficiency. However, the higher storage pressure causes the lower exergetic efficiency, the higher waste exergy output, the higher environmental effect factor and the lower exergetic sustainability index. Thus, it is recommended that this type of the system should be operated at higher PEME outlet pressure, and at an optimum hydrogen storage pressure.     

Analytical HFACS for investigating human errors in shipping accidents

Despite the innovative trends in marine technology and the implementation of safety-related regulations, shipping accidents are still a leading concern for global maritime interests. Ensuring the consistency of shipping accident investigation reports is recognized as a significant goal in order to clearly identify the root causes of these accidents. Hence, the goal of this paper is to generate an analytical Human Factors Analysis and Classification System (HFACS), based on a Fuzzy Analytical Hierarchy Process (FAHP), in order to identify the role of human errors in shipping accidents. Integration of FAHP improves the HFACS framework by providing an analytical foundation and group decision-making ability in order to ensure quantitative assessment of shipping accidents.     

Optical element for generation of accelerating Airy beams

We demonstrate an optical element for generation of accelerating Airy beams. The element is conveniently constructed by combination of positive and negative cylindrical lenses of matching radii of curvature. With proper choice of lens curvatures, the resulting surface profile closely follows a cubic polynomial. Passing a gaussian beam through this element and performing optical Fourier transform yields beam profiles close to the Airy function. Our experiments demonstrate parabolic propagation, or acceleration, of the resulting focal spots.