Miracle-dz/UniFAR-FTUs huggingface dataset:
Secure Abstractions for Trusted Cloud Computation

Cloud computing is adopted by most organizations due to its characteristics, namely offering on-demand resources and services that can quickly be provisioned with minimal management effort and maintenance expenses for its users. However it still suffers from security incidents which have lead to many data security concerns and reluctance in further adherence. With the advent of these incidents, cryptographic technologies such as homomorphic and searchable encryption schemes were leveraged to provide solutions that mitigated data security concerns. The goal of this thesis is to provide a set of secure abstractions to serve as a tool for programmers to develop their own distributed applications. Furthermore, these abstractions can also be used to support trusted cloud computations in the context of NoSQL data stores. For this purpose we leveraged conflict-free replicated data types (CRDTs) as they provide a mechanism to ensure data consistency when replicated that has no need for synchronization, which aligns well with the distributed and replicated nature of the cloud, and the aforementioned cryptographic technologies to comply with the security requirements. The main challenge of this thesis consisted in combining the cryptographic technologies with the CRDTs in such way that it was possible to support all of the data structures functionalities over ciphertext while striving to attain the best security and performance possible. To evaluate our abstractions we conducted an experiment to compare each secure abstraction with their non secure counterpart performance wise. Additionally, we also analysed the security level provided by each of the structures in light of the cryptographic scheme used to support it. The results of our experiment shows that our abstractions provide the intended data security with an acceptable performance overhead, showing that it has potential to be used to build solutions for trusted cloud computation.
Analysis and Design of Various Key Pre- Distribution Schemes

The real emerging challenge in the field of Wireless Sensor Networks is to prevent sensor nodes by providing security and conserving scarce resources. Sensors are inexpensive, very low power devices which have limited resources and works on battery power. To provide security secret key plays a vital role, which is generated through some key pre-distribution schemes for providing a secure channels among sensor nodes in Wireless Sensor Networks. In this paper, we compare the proposed new key pre-distribution scheme called SHI-KPD Scheme with the existing key pre-distribution schemes based on some evaluation metrics such as resilience.
Assessing the organizational readiness for implementing BI systems in ERP environment

BI (Business Intelligence) is considered as a top priority of enterprises in investment decisions on information systems. Deploying a BI system is very complex, not just installing software and hardware, its success depends on assessing the current situation, planning, analyzing and improving business processes. This study was conducted to identify the factors influence the readiness of deploying BI in enterprises using ERP systems. Base on that, we suggest some solutions to increase the readiness and availability to better support enterprises in preparing for BI system deployment in the future. We surveyed participants in the process of deploying and using ERP system in theirs companies at Ho Chi Minh City. The research uses a combination of qualitative and quantitative methods to propose a research model, test model, discuss results and propose solutions. The experimental research results show that the readiness factors that enterprises need to pay attention to when deploying BI systems, in the order: Organization, Technology, Process and People.
Improved dynamic load balancing algorithm based on feed_back

Load balance is an important problem ofcluster.Thecore oftask distribution is the loadbalance algorithm.LVS load balance technology is introduced briefly,the known load balancing,algorithms and their merits and demerits are discussed;And then,according to these defects,a improved load-balancing algorithm is presented based on feed_back. A remained_capacity is brought in to describe the load state of cluster node more accurately to balance the load more optimization considering the real load and capability of server.Test results proved that this improved dynamic load balancing algorithm is more effective than static algorithm.
Low-PAPR Preamble Design for FBMC Systems

This paper presents a family of training preambles for offset quadratic-amplitude modulation based filter-bank multi-carrier (FBMC) modulations with low peak-to-average power ratio (PAPR) property. We propose to use binary Golay sequences as FBMC preambles and analyze the maximum PAPR for different numbers of zero guard symbols. For both the PHYDYAS and Hermite prototype filters with overlapping factor of 4, as an illustration of the proposed preambles, we show that a preamble PAPR less than 3 dB can be achieved with probability of one, when three or more zero guard symbols are inserted in the vicinity of each preamble.
From machine learning to deep learning: Advances in scoring functions for protein–ligand docking

Molecule docking has been regarded as a routine tool for drug discovery, but its accuracy highly depends on the reliability of scoring functions (SFs). With the rapid development of machine learning (ML) techniques, ML‐based SFs have gradually emerged as a promising alternative for protein–ligand binding affinity prediction and virtual screening, and most of them have shown significantly better performance than a wide range of classical SFs. Emergence of more data‐hungry deep learning (DL) approaches in recent years further fascinates the exploitation of more accurate SFs. Here, we summarize the progress of traditional ML‐based SFs in the last few years and provide insights into recently developed DL‐based SFs. We believe that the continuous improvement in ML‐based SFs can surely guide the early‐stage drug design and accelerate the discovery of new drugs.
Comperatively Investigation Pretreatments of H2SO4 and Ultrasound Effect for Corncob to Increase Available Bioenergy Potential by Response Surface Methodology

Bioenergy is a sort of renewable energy source, such as bioenergy, bioethanol, biogas or bioethanol, and it has widespread application in the world. The main purpose of this work is to optimize the physicochemical processes of sulfuric acid and ultrasound + sulfuric acid pretreatment application to get more energy per unit mass from the corncob. In order to optimize the best reaction conditions, a statistical experimental design method which is Box Behnken was used. The parameters such as acid concentration, temperature, reaction time, ultrasound power were selected as the factors to be optimized. The solid concentration was fixed at 1% and the particle mesh size was fixed at 0.2. In acid pretreatment, the highest total sugar concentration according to the statistical software model is 5.05 g/L in 4.74% acid concentration, 100 °C temperature and 117 min reaction time. If the concentration of reducing sugar is desired to be maximum in the acid pretreatment, a concentration of 5% acid, 80°C temperature and a reaction time of 180 minutes can be obtained. In ultrasound supported acid pretreatment application, while total sugar concentration rise up to 22%, reduced sugar concentration increased up to 70%. Finally it could be said that ultrasound assisted acid pretreatment has much more effective than the solely acid pretreatment.
Assessing the Impact of Internet Testing: Lower Perceived Performance

This chapter provides the results of a comparison between two sections of a graduate programming class, where one was an on-campus class and the other, a distance class. The course content, instructor, syllabus, lecture materials, notes, assessments and semester (time of year) were the same. Both groups were surveyed to test their satisfaction with the testing procedure and with their perception of certain aspects of the social environment. The results showed differences in perceived test performance. Two conjectures about possible causes underlying the difference and suggestions for possible future research end the discussion. 701 E. Chocolate Avenue, Suite 200, Hershey PA 17033, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.idea-group.com INFORMATION SCIENCE PUBLISHING This chapter appears in the book, Distance Learning and University Effectiveness: Changing Educational Paradigms for Online Learning, edited by Caroline Howard, Karen Schenk, and Richard Discenza. Copyright © 2004, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Copyright © 2004, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. 178 Martz and Shepherd
Towards Energy Efficiency for Cloud Computing Services

Over the past decade, the increasing complexity of data-intensive cloud computing services along with the exponential growth of their demands in terms of computational resources and communication bandwidth, posed significant challenges to be addressed by the scientific research community. Relevant concerns have been specifically arisen for the massive amount of energy necessary for operating, connecting and maintaining the thousands of data centres supporting cloud computing services, as well as for their drastic impact on the environment in terms of increased carbon footprint. This chapter provides a survey of the most popular energy‐conservation and “green” technologies that can be applied at data centre and network level in order to overcome these issues. After introducing the reader to the general problem of energy consumption in cloud computing services, we illustrate the state‐of‐the‐art strategies for the development of energy‐efficient data centres; specifically we will discuss principles and best practices for energy-efficient data centre design focusing on hardware, power supply specifications and cooling infrastructure. We further consider the problem from the perspective of the network energy consumption, analysing several approaches achieving power efficiency for access and core networks. Additionally, we provide an insight to recent development in energy-efficient virtual machine placement and dynamic load balancing. Finally, we conclude the chapter providing the reader a novel research work for the establishment of energy-efficient lightpaths in computational grids.
Wormhole Attack Detection in Zigbee Wireless Sensor Networks using Intrusion Detection System

Objective: Wormhole attack is a serious threat to Wireless Sensor Networks (WSN) due to its wireless broadcast nature of communication, multi hop nature and resource constraints. Hence, to enhance the security and energy efficiency of a WSN, energy efficient Intrusion Detection System (IDS) is needed to detect and mitigate the attacks. In this paper, an Energy Efficient Intrusion Detection System (EE-IDS) has been proposed for IEEE 802.15. 4 based WSN to detect and mitigate the effect of wormhole attacks. Methods/Statistical Analysis: The wormhole attack is detected by using the optimized watchdog system. The optimized watchdog mechanism is a trust based method which is used to evaluate the validity of all the nodes of the network. In proposed approach, the optimization has been done in the selection of watchdog nodes, in order to consume less energy compared to that of the existing approaches. The detection of wormhole attack is also completely relies on the three main factors like trustworthiness, packet delivery ratio and end-to-end delay. Findings: The proposed EE-IDS is examined through extensive simulations by considering static and mobility model, and then it is compared with the existing IDS for detecting wormhole attacks. The performance of zigbee WSN is analyzed in terms of metrics such as packet delivery ratio, average end-to-end delay and energy consumption for static model. In mobility model, the Proposed EE-IDS is evaluated in terms of detection rate, false positive rate and detection time. Application/ Improvements: The proposed EE-IDS is used to detect the wormhole attack and improve the energy efficiency in zigbee based wireless sensor networks, which can be used for military, environmental, health and commercial applications.
Multi Objective Modulated Model Predictive Control of Stand-Alone Voltage Source Converters

This paper introduces a novel model predictive control (MPC) strategy for stand-alone voltage source converters (VSCs) with constant switching frequency. Multiple control targets are incorporated in a single cost function. This allows fulfilling all the requirements for an uninterruptible power supply (UPS) inverter in terms of fast dynamic response, elimination of steady-state error, and harmonic compensation capability. The control output vector is determined as an analytical solution that corresponds to the minimum value of the cost function. The space vector modulation (SVM) is then used to synthesize the corresponding switching sequence. Therefore, this control strategy is equivalent to the linear state feedback control, which allows the usage of linear theory for tuning the parameters. The superior characteristics of this control strategy compared to cascaded linear control and finite control set MPC are, finally, demonstrated experimentally.
Optimal estimation of internal rate of return in engineering project

The internal rate of return method is currently an important analysis tool for economic feasibility evaluation of engineering project. The estimation valve of internal rate of return is materially relative to sign change of cash f low in engineering project, which is frequently neglected in both theory and pra ctice of engineering economics at present. Therefor in this paper, two practical formulas are induced to compute internal rate of return. An accelerating geneti c algorithm (AGA) developed by the authors is suggested to optimize internal rat e of return. The example results show that AGA method is simple, effective and high computation precision.
Value Iteration for Perishable Inventory Control

This thesis focuses on finding optimal order policies for perishable inventory in supermarkets. By means of value iteration (VI) and simulation, several inventory dynamics are compared. First, several cases were designed: three cases without taking perishability into account, and one case based on perishability. Case 1-3 have the following characteristics, respectively: 1) backlogging is possible, and costs should be minimized; 2) backlogging is not permitted, and profit should be maximized; 3) the customer service level (CSL) should be met, and costs should be minimized. The fourth case, 4) contains products which perish after one day, and the profit should be maximized. The calculation of an optimal order policy is performed by implementing a VI method. The optimal order quantity per inventory level calculated in VI, is used in the simulation. The four cases gave different optimal order-policies. The first three cases showed a lot of similarities, and had the characteristics of an (s, S)-policy. Case 4, containing perishable products, was highly influenced by the fixed order cost k. If the fixed order costs were low, an optimal order policy could be determined. This was not possible for high fixed order costs, the order moments and order quantities turned out to be periodic. For fixed costs which were too high, no orders were placed. The order policy for the low fixed costs did not match the policies in the inventory control chapter. In case 4, we had to deal with the curse of dimensionality. The limited shelf-life causes an increase in state space. To deal with this problem, we had to keep the elements per set of states low.
Screening and Optimization of Thermo-Tolerant Bacillus Sp. For Amylase Production and Antifungal Activity

Amylases are starch degrading enzymes which are produced by plants, animals and microorganisms. Amylases produced by microorganisms have a wide range of industrial applications such as in pharmaceutical, food, textile and paper industries. However, there are still limitations in the isolation of amylase producing microorganisms. The objective of this study was to isolate the potent amylase producing Bacillus sp. from soil samples and evaluate their abilities for inhibiting the aflatoxin producing Aspergillus flavus. In this study, 30 soil samples were used. For the screening and identification of Bacillus strain, morphological and biochemical tests were performed. Iodine assay was done to screen the potent amylase producers. Two parameters (pH and temperature) were used to optimize the cultural conditions for the production of amylase. To determine the total reducing sugar, dinitrosalicylic acid (DNS) assay was used. Altogether 29 colonies were selected and identified as Bacillus spp out of which 16 were selected to determine enzyme activity by cup plate method. Four isolates (DK9, DK10, IM4 and KD7) showing highest amylolytic activities (16 mm, 12 mm, 14 mm and 14 mm zone of hydrolysis) were subjected for further study. Isolate KD7 showed the highest amylolytic activity (0.19 U/mL) compared to other isolates. Maximum amylase production was found at pH 6 and temperature 50° C (0.19 U/mL). Among these 4 isolates, DK9 and KD9 showed strong antagonistic activity against Aspergillus flavus while DK10 and IM4 showed moderate antifungal activities. Thus, the bacterial isolate KD7 was identified as the most potent strain for maximum amylase production.
Preparation of a novel magnetic geopolymer/zero–valent iron composite with remarkable adsorption performance towards aqueous Acid Red 97

Abstract A magnetic geopolymer was prepared from the silica and metakaolin under presence of zero–valent iron (ZVI). The magnetic geopolymer was characterized by Fourier–Transform Infrared spectroscopy, X-ray diffraction, N2 adsorption/desorption isotherms, scanning electron microscopy, and vibrating sample magnetometer. The geopolymer was employed as adsorbent of Acid Red 97 dye. The results showed that the magnetic geopolymer have mesoporous structure and sufficient magnetization to be removed by a magnetic field from aqueous solution. Both the pseudo–first and pseudo–second order models satisfactorily described the adsorption kinetics, and the isotherms were properly adjusted by the Henry’s model. High adsorptive capacity of dye (1814 mg g−1) was obtained, and the geopolymer can be used for five times with the same initial adsorption capacity. An efficient adsorbent was developed from low cost materials. This adsorbent presented extremely high adsorption capacity and can be easily separated from the treated liquid effluent.
Framework for cloud‐based software test data generation service

This paper presents the framework of cloud‐based software test data generation service (CSTS) that caters to cost‐effective test data generation service in a cloud environment. In contrast to existing conventional or cloud‐based testing frameworks, CSTS has a number of unique benefits. First, CSTS is designed to facilitate test data generation in minimum time and cost. Second, unlike existing frameworks which mandates clients to opt for resources to test their jobs, CSTS guides customer for selecting best cluster configuration in order to minimize the cost. While the existing models do not provide any solution for trust establishment in cloud computing services, CSTS delivers it by implementing security mechanism with the provision of role based access control. The security mechanism proposed in this paper ensures the protection of data and code of different users. Third, CSTS provides a mathematical pricing model to fulfill the expectations of customers and also to maximize the net profit of service providers. Cloud service request model has also been designed that postulates service level agreements between customers and service providers. We have evaluated, compared, and analyzed our framework and have found that it outperforms other existing cloud‐based frameworks.
Fluorescence Microscopy Assay to Measure HIV-1 Capsid Uncoating Kinetics in vitro

The stability of the HIV-1 capsid and the spatiotemporal control of its disassembly, a process called uncoating, need to be finely tuned for infection to proceed. Biochemical methods for measuring capsid lattice disassembly in bulk are unable to resolve intermediates in the uncoating reaction. We have developed a single-particle fluorescence microscopy method to follow the real-time uncoating kinetics of authentic HIV capsids in vitro. The assay utilizes immobilized viral particles that are permeabilized with the a pore-former protein, and is designed to (1) detect the first defect of the capsid by the release of a solution phase marker (GFP) and (2) visualize the disassembly of the capsid over time by “painting” the capsid lattice with labeled cyclophilin A (CypA), a protein that binds weakly to the outside of the capsid. This novel assay allows the study of dynamic interactions of molecules with hundreds of individual capsids as well as to determine their effect on viral capsid stability, which provides a powerful tool for dissecting uncoating mechanisms and for the development of capsid-binding drugs.
Chitosan biopolymer improves the fruit quality of litchi (Litchi chinensis Sonn.)

Chitosan (CHT) is a natural compound that has been used to control postharvest pathogenic diseases due to its capability of eliciting natural defense responses in plants. The aim of this study was to investigate the effect of foliar CHT application on yield and quality of the litchi fruit. Chitosan was applied by spraying on to fruit and foliage just after fruit set four times at 7-day intervals with four varying doses viz. 100, 250, 500, and 1,000 µg L−1 and a control (0 µg L−1). Although the application of CHT had no significant effect on the size of the fruits (length and width), the total contents of phenolics, flavonoids, and ascorbic acid and the antioxidant activity of litchi fruit arils were significantly increased in CHT-treated fruit compared with the untreated control. The highest phenolic, flavonoid, and ascorbic acid contents were 334 µg gallic acid g−1, 881 μg quercetin g−1, and 178 µg g−1, respectively, in fruits treated with 500 µg L−1 CHT. However, the highest antioxidant activity (622 μg butylated hydroxytoluene g−1) was recorded in 250 µg L−1 CHT-treated fruits. Our findings revealed that the application of low doses of CHT in a litchi orchard might improve fruit quality by increasing the content of antioxidants and antioxidant activities.
Online data‐driven approach of yaw error estimation and correction of horizontal axis wind turbine

Active yaw system is a very important component of modern horizontal axis wind turbines to keep the nacelle aligning with the stochastic wind direction. However, in practice, it is hard to keep the rotor facing into the wind precisely, which will lead to not only the loss in power production but the increment in aerodynamic loads. This study presents a data-driven approach to estimate yaw error for remote terminal unit.