Miracle-dz/UniFAR-FTUs huggingface dataset:
Safety Defending Delegated Admittance Mechanism in Public Clouds

Cloud computing, as a rising registering standard. Cloud computing empowers clients to remotely store their information in a cloud furthermore profit by administrations on-interest. With fast improvement of cloud computing, more endeavors will outsource their delicate information for partaking in a cloud. To keep up the mutual information secret against untrusted cloud administration suppliers (CSPs), a characteristic route is to store just the encoded information in a cloud. The real issues of this methodology incorporate building up Decomposing Access Control Polices, designated access control for the encoded information, verification of proprietorship permit stockpiling server to check a client information possession in view of hash worth and the entrance rights from clients when they are no more approved to get to the scrambled information. In the proposed approach the security of clients is ensured while authorizing property based ACPs and using the two layer of encryption lessen the overhead at Owner, restricted to unapproved access to information and to any information break amid sharing procedure, giving levels of access control confirmation. The inspiration of this paper is to propose a protected Access control plan, for open mists. We proposed a Privacy Preserving Two layer Encryption Access control out in the open mists, which gives more protection and security contrasted with the conventional methodologies. Current ways to deal with authorize ACPs on outsourced information utilizing specific encryption oblige associations to deal with all keys and encryptions and transfer the encoded information to the remote stockpiling. Such methodologies cause high correspondence and calculation expense to oversee keys and encryptions at whatever point client accreditations change. In this paper, we proposed a two layer encryption based way to deal with take care of this issue by assigning however much of the entrance control implementation obligations as could be expected to the Cloud while minimizing the data presentation dangers because of conspiring Users and Cloud.
CONSTRUCTION OF OBSTACLE ELEMENT MAP BASED ON INDOOR SCENE RECOGNITION

Abstract. Route planning and navigation in indoor space have become a hot topic recently. To accomplish this task, a map and a real-time detection system are needed. Due to Lidar systems’ high efficiency in data acquisition, Lidar sensors have become an indispensable part of an object detection system. In this paper, we use Lidar points to generate obstacle maps. The obstacle maps can be used as a reference for route planning and navigation. To identify single objects more precisely, a deep network combined PointNet with Markov Random Field (MRF) is designed in our work to classify Lidar points. Then, single objects are segmented by using the Euclidean clustering method. After that, the prior rules and derived criteria we summarized from large amount images are used to determine objects’ kind between Influence Movement Obstacles (IMO) and Non-Influence Movement Obstacles (N-IMO). Finally, objects are projected into a 2D plane to generate obstacle maps. To evaluate the performance of our method, experiments were performed on the S3DIS dataset of Stanford University. The results show that our method greatly improves the overall accuracy compared to the original PointNet model, and can generate high-quality obstacle maps.
The Economic Consequences of Loan Maturity Mismatching in the Unhampered Economy

Some economists of the Austrian School contend that business cycles are created when banks use the proceeds of short-term time deposits to create longer-term loans. These authors claim that while loan maturity mismatching of this kind does not create fiduciary media, it nevertheless artificially lowers the market rate of interest and causes forced saving and malinvestment. According to this view, Austrian business cycle theory, which hitherto has assumed forced saving occurs only in the quantity dimension as a result of fractional reserve banking, must also consider forced saving in the time dimension engendered by loan maturity mismatching. The present paper disputes this and argues that while loan maturity mismatching does affect the rate of interest and alters the production structure, it cannot independently cause forced saving or any systemic discoordination. Hence in the unhampered economy, it is not responsible for causing business cycles.
Application of a differential reflectivity technique to the EDOP radar in ground-based operation

This paper discusses the modification of a single-frequency Doppler radar (9.6 GHz) to accommodate dual-frequency operation for the study of the microphysical character of precipitation. The modification involves the ER-2 Doppler radar (EDOP), an airborne, meteorological research radar of the NASA/Goddard Space Flight Center. Radar operation is modified to provide reflectivity signals at two distinct frequencies at 9% separation. Differential reflectivity results are shown from ground-based measurement. Future work will derive drop size distribution estimates from these measurements.
A Discussion on Risk Factors, Therapeutic Approach of Endometritis and Metritis in Cattle

After parturition, uterine involution, regeneration of the endometrium, return of ovarian cyclic activity and the control of pathogenic bacteria in the uterus is required before cows are likely to conceive again (Gautam et al., 2009). Uterine infections during the postpartum period such as metritis and endometritis affect a large population of cattle and are associated with economical as well as production losses in dairy animals (Fourichon et al., 1999, 2000).
GIStorage: um serviço de informação para grades com suporte a algoritmos de predição de desempenho

In order to allocate resources and submit jobs to a grid, resource discovery and scheduling services need to know in advance the performance of the candidate resources. Since jobs will be executed in a future time, these services may use prediction algorithms to forecast resources performance, improving the quality of their decisions. Additionally, prediction algorithms that use time series analysis demand historical performance information to predict future behavior. To support prediction algorithms and services we propose GIStorage, a grid information service designed for storing historical performance information about resources. GIStorage is GMA compliant and is structured as a tree in order both to achieve good response times and to store large amount of information.
Instruction scheduling optimizations for energy efficient VLIW processors

Very Long Instruction Word (VLIW) processors are wide-issue statically scheduled processors. Instruction scheduling for these processors is performed by the compiler and is therefore a critical factor for its operation. Some VLIWs are clustered, a design that improves scalability to higher issue widths while improving energy efficiency and frequency. Their design is based on physically partitioning the shared hardware resources (e.g., register file). Such designs further increase the challenges of instruction scheduling since the compiler has the additional tasks of deciding on the placement of the instructions to the corresponding clusters and orchestrating the data movements across clusters. In this thesis we propose instruction scheduling optimizations for energy-efficient VLIW processors. Some of the techniques aim at improving the existing state-of-theart scheduling techniques, while others aim at using compiler techniques for closing the gap between lightweight hardware designs and more complex ones. Each of the proposed techniques target individual features of energy efficient VLIW architectures. Our first technique, called Aligned Scheduling, makes use of a novel scheduling heuristic for hiding memory latencies in lightweight VLIW processors without hardware load-use interlocks (Stall-On-Miss). With Aligned Scheduling, a software-only technique, a SOM processor coupled with non-blocking caches can better cope with the cache latencies and it can perform closer to the heavyweight designs. Performance is improved by up to 20% across a range of benchmarks from the Mediabench II and SPEC CINT2000 benchmark suites. The rest of the techniques target a class of VLIW processors known as clustered VLIWs, that are more scalable and more energy efficient and operate at higher frequencies than their monolithic counterparts. The second scheme (LUCAS) is an improved scheduler for clustered VLIW processors that solves the problem of the existing state-of-the-art schedulers being very susceptible to the inter-cluster communication latency. The proposed unified clustering and scheduling technique is a hybrid scheme that performs instruction by instruction switching between the two state-of-the-art clustering heuristics, leading to better scheduling than either of them. It generates better performing code compared to the state-of-the-art for a wide range of inter-cluster latency values on the Mediabench II benchmarks. The third technique (called CAeSaR) is a scheduler for clustered VLIW architectures that minimizes inter-cluster communication by local caching and reuse of already
QoE driven adaptive video with Overlapping Network Coding for Best Effort Erasure Satellite Links

The demand for multimedia services has been boosted by broadband networks penetration. In particular, video services in the ubiquitous satellite networks are suitable for a diverse range of application, from recreational to ehealth, or situational awareness in disaster scenarios. Nevertheless, at the expense of ubiquity or portability, the offered Quality of Service (QoS) in satellite communications can be limited, affecting the end user Quality of Experience. In this work our aim is to offer a solution that is driven by the user’s QoE and copes with limitations of the satellite links, focused on point-to-point video applications. This solution will benefit the user experience and further enhance video’s feasibility in satellite networks, to be used in applications on e.g. the recently launched Alphasat satellite with extended coverage in the L band spectrum. We consider a best effort QoS, which entails shared resources with no guarantee on available bandwidth and expected time-variations of the network, e.g. congestion events. Furthermore, shadowing effects blocking the Line of Sight in the satellite link [1] during transmission may results in bursty erasures at packet level. In order to tackle the above network dynamics, in our QoE driven approach our proposal is two-fold. Firstly, we investigate forward erasure correction through content-aware Overlapping Network Coding (ONC). In [2], authors investigate rateless ONC for content aware protection. The objective of ONC is to have a better protection of the intra-coded frames of the source message and increase their recovery probability. In this work, we focus on the fixed rate ONC. It has been shown in [3] that for the fixed rate cases, Random Network Coding (RNC) has erasure correction performance very similar to the MDS codes. In this work, we show that ONC for content-aware protection which also uses RNC to generate coded packets, provides better performance than MDS codes in terms of erasure recovery for the intra-coded frames. Secondly, we propose a QoE cross-layer adaptive video solution that is optimized online according to the changing network dynamics in the best effort scenarios. In terms of QoS this solution is driven by delay, which is a major factor in satellite communications QoS, and is able to overcome variations of available bandwidth maintaining a high QoE. We take upon previous work where we validated the solution at emulation stage [4], and show in this paper experimental results in a real point-to-point video streaming setup. Moreover, we study the feasibility of joining the two proposals and show how QoE is improved by considering content-ware ONC in a scenario where available network rate is known through the QoE adaptive video solution.
Diversity management and gender equality outcomes in research, development and innovation organisations: Lessons for practitioners

Understanding the impact of various diversity management (DM) practices in terms of their effectiveness in achieving desired outcomes within the organisation is a prevalent research gap in the general DM literature and the new stream of literature on DM in the research, development, and innovation (RDI) sector. Therefore, this article reviews the literature on gender diversity practices in RDI workplaces and how DM contributes to gender equality outcomes. For this purpose, we introduced a conceptual framework to demonstrate the interrelatedness of the forms and reasons for gender inequality, and the choice of DM practices and their outcomes. Moreover, we compiled an extensive list of DM practices for practitioners related to how to address the different forms and underlying reasons for gender inequality. Finally, by comparing the literature on DM outcomes in the business and the RDI sector, we concluded that research on measuring the outcomes of DM practices was less developed for RDI organisations, but gaps of knowledge on the outcomes of DM practices prevailed in both sectors. Organisational contexts in which specific diversity practices were implemented had a significant role in determining their effectiveness,highlighting the relevance of the institutionalist theory.
Design of Reference Model for Complex Embedded Software Testing

As information telecommunication industry develops and systems get integrated gradually, the importance of complex embedded software testing is growing significantly. On the contrary, the reliability of complex embedded software testing has worsened. Accordingly, testing of software is an essential part in designing and building up embedded system and the volume of testing required is immense. This paper elaborates on design and testing reference model for complex embedded software testing, providing guidelines to collect requirements for complex embedded software testing.
A COMPARATIVE ANALYSIS OF DIFFERENT FEATURE SET ON THE PERFORMANCE OF DIFFERENT ALGORITHMS IN PHISHING WEBSITE DETECTION

Reducing the risk pose by phishers and other cybercriminals in the cyber space requires a robust and automatic means of detecting phishing websites, since the culprits are constantly coming up with new techniques of achieving their goals almost on daily basis. Phishers are constantly evolving the methods they used for luring user to revealing their sensitive information. Many methods have been proposed in past for phishing detection. But the quest for better solution is still on. This research covers the development of phishing website model based on different algorithms with different set of features in order to investigate the most significant features in the dataset.
Electromagnetic‐based maximum output power control in new two‐layer BLDC generator using optimal control of turn‐on and turn‐off angles in variable speed applications

In this study, by using the electromagnetic field analysis, the design of brushless DC generator with a novel construction and controller, appropriate for variable speed applications, is proposed. In the proposed machine, unlike the conventional structure, an assisted DC field coil is employed instead of permanent magnet excitation to provide a regulated voltage. Results of the electromagnetic field analysis show that including the DC field coil increases the controllability of the flux in different machine parts which provide a regulated terminal voltage in a wide speed range appropriate for variable speed applications. Moreover, the maximum power point tracking is achieved by controlling the DC field current along with producing optimal turn-on and turn-off angles for stator winding using the electromagnetic analysis based on optimal finite element analysis. Also, an appropriate controller is designed to control the DC field coil current. To verify the actual performance of the proposed configuration, a 1.5 Kw machine is manufactured and tested followed by the discussion on results. The obtained experimental results are in good agreement with the results of the electromagnetic analysis which confirm the maximum power trackability and robust output voltage regulation of the proposed conversion system under different shaft speeds and load conditions.
A low-complexity frame memory compression algorithm and its implementation for MPEG-2 video decoder

An algorithm and its implementation to compress video frame data to be stored in external memory are proposed, thereby enabling a reduction of memory requirements and bandwidth. To support random access capability, frames are organized as 1/spl times/8 fixed-length segments, which are used as compression units. For both compression efficiency and low complexity, modified Hadamard transform (MHT) and Golomb-Rice (GR) coding are utilized. The compression ratio is fixed at 50% and objective and subjective video quality assessments are performed. Efficient ASIC implementation including Golomb-Rice encoding/decoding is also proposed to reduce the total compression/decompression latency time.
Comparison Of SAR Polarimetric Calibration Techniques Using Clutter

Polarimetric calibration presents unique challenges and can require several reference targets to calibrate. As an aid in calibration, the polarimetric scattering prop­ erties of clutter can be exploited in calibration. Because of the cost of reference targets and the effort required to deploy them, using clutter data is desirable for some aspects of calibration if it can be reliably used. In this paper, polarimetric, L-band SAR imagery collected by the NADC/ERIM P-3/SAR system over a forested re­ gion will be examined. Reference reflectors deployed for calibration included trihedrals, dihedrals at a Variety of orientations, and Active Radar Calibrators (ARCs). The imaged areas consisted of forest and grassy fields, as well as some crop land. Phase calibration methods using these clutter regions can be verified by compari­ son to methods using reference targets. Once verified, the clutter statistics will be used to extend calibration spatially over the image. After the image is calibrated the signatures of various targets will be compared to expected signatures.
An Adaptive Hand-free Design Technique for Mobile Communication in Vehicle

— Nowadays Using mobile phone has increased worldw ide at the same ti me w e have to consider the risk associated w ith it . Using a mobile phone while driving can affect the cognitive functions of persons, distract his or her visual concentration and also the speed of processing information. The theme of the project is to make the driver to attend only the emergency calls. Initially when a call is made to driver then he will receive a message intimating that he is in driving. If once again the person makes a calls to the driver then the driver will understood that it is emergency. So the driver will get an intimation regarding the emergency call in voice and automatically the car speed need to be reduced using PWM inorder to prevent accidents due to mobile phone
Buffer architectures for predictable quality of service at the ATM layer

Providing guaranteed quality of service (QoS) in cell and packet based networks places additional demands upon the design of switch fabrics. This paper considers the application of various fundamental buffering approaches in ATM, for support of predictable QoS. The paper identifies the functional requirements of the switch fabric at the ATM layer, and make recommendations for an improved architecture that considers QoS at the switch fabric level. The relative merits of each buffering scheme has been determined by applying realistic broadband traffic loads involving CBR, VBR and UBR traffic to simulated models of the buffer strategies. Simulation results are presented, along with a performance analysis for each scheme. The resultant architecture allows switches to be realised which have reliable and predictable parameters in the ATM layer and which guarantee QoS as well as reducing connection admission control complexity.
Wait, There’s Torture in Zootopia? Examining the Prevalence of Torture in Popular Movies

Roughly half of the U.S. public thinks that torture can be acceptable in counterterrorism. According to recent research, dramatic depictions of torture increase public support for the practice. Yet we do not know how frequently—and in what context—torture is depicted across popular media. What messages about the acceptability and effectiveness of torture do Americans receive when they watch popular films? To address this question, we coded each incident of torture in the twenty top-grossing films each year from 2008 to 2017 to analyze how torture is portrayed in terms of its frequency, efficacy, and social acceptability. Results show that the majority of popular films—including films aimed toward children—have at least one torture scene. Across films, the messages sent about torture are fairly consistent. As expected, movies tend to depict torture as effective. Further, how movies portray torture is also a function of who is perpetrating it. Specifically, protagonists are more likely to torture for instrumental reasons or in response to threats and are more likely to do so effectively. In contrast, antagonists are more likely to use torture as punishment and to torture women. The frequency and nature of torture’s depiction in popular films may help explain why many in the public support torture in counterterrorism.
A Learning Algorithm for Behavior-based PortScan Automatic Detection and Its Evaluation

In recent years, behavior-based methods have attracted many researchers in the field of cyberattack detection. As such methods exploit the normal behavior modes extracted from learning data to detect anomalies, it is no longer necessary to set thresholds in advance that are used to distinguish normal and abnormal traffic. For extracting the normal behavior modes, a learning algorithm is often used after the frequency diagrams have been built. However, even the frequency diagrams have been drawn, there are still some parameters need to be determined in advance in the existing learning algorithms for extracting normal modes from the frequency diagrams and such parameters are often not easy to decide in advance. To solve this problem, we propose a novel learning algorithm, in which no parameters need to be tuned. According to our discussion and experimental results, our proposed learning algorithm is efficient for detecting cyber-attacks.
Study on Shunt Active Power Filter with Improved Control Method

Keywords—SAPF, improved control method, Ip-Iq current detection method , repetitive control, PI control, harmonic compensation Abstract.In order to improve power quality and ensure stable operation of power system, shunt active power filter (SAPF) is widely used o filter out harmonics. This paper proposed an improved control method for SAPF. The whole improved control strategy could be divided into two parts: IpIq current detection method to obtain compensation current reference value, and repetitive control combined with PI control to generate PWM pulse to control SAPF to deliver compensation current. The MATLAB simulation results show that SAPF with the proposed control method has good harmonic compensation performance.