Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Common Encryption Algorithm and Scope of Advanced Algorithm for Simulated Wireless Network

- Encryption algorithms play a vital role in information security systems. The study discovers the progress of Encryption algorithms in terms of their diversity of applications. Some of the Encryption algorithms have been developed to make transmission and storage of data more secured and confidential. Different levels of securities are offered by different algorithms depending on how difficult is to break them. If it is difficult to recover the plain text in spite of having substantial amount of cipher text then an algorithm is unconditionally secured. This study provides evaluation of eight of the most common encryption algorithms namely: DES, 3DES, AES (Rijndael), Blowfish, RSA, RC2, RC4, and RC6. From our analysis we came to conclusion that the best algorithm is the one which fulfills our need of security and speed. We come with new design of encryption algorithm based on AES or RSA or RC4, various scripts on NS2 or MATLAB or SCILAB, simulation environment of encrypted wireless network based on NS2 or MATLAB or SCILAB. We will implement newly proposed encryption algorithm on simulated environment and also test performance of proposed algorithm on wireless simulated network. We come with design and implement technique to store encrypted data on secondary storage device.
Accurate and efficient scene recognition with compact BoW and ensemble ELM

Scene recognition applications on mobile devices receive increasing attentions in recent years. Due to mobile users' real-time requirement, an accurate and efficient scene recognition system is urgent for mobile applications. In this paper, we propose a novel discriminative codeword selection method by using the ensemble extreme learning machine (ELM) algorithm for fast and accurate scene recognition. First, the hierarchical k-means clustering algorithm is applied to generate a set of preliminary codewords for scene images. An information entropy based codebook learning algorithm is then proposed to select those discriminative codewords to create a compact codebook, which is used to quantize a scene image into a compact Bag-of-Words (BoW) histogram. Finally, the ensemble ELM algorithm is developed for scene recognition, which contains fast ELM algorithm and the ensemble approach using the ELM classifier. Experiments on the Nanyang Technological University campus's scene database show the effectiveness and efficiency of the proposed approach.
NETp1-07: A Novel Approach for Real Time Flows Scheduling

A plethora of packet-scheduling algorithms have been proposed in the literature in order to meet the stringent time constraints of real time flows at an IP router level. In this regard, the so-called EDF algorithm attracted special attention since it is prominent for optimally managing flows with strict time constraints. However, EDF is complex and expensive as far as implementation is concerned, especially when compared with the standard FIFO algorithm. As a main contribution in this paper, we therefore propose a novel hybrid scheduling approach, which combines the optimality of EDF and the simplicity of FIFO. This approach allows reducing EDF's implementation complexity while making efficient use of its optimal flow management. Our simulation results underline the benefits behind such a proposal.
Reliability Design for Large Scale Data Warehouses

Data reliability has been drawn much concern in large-scale data warehouses with 1PB or more data. It highly depends on many inter-dependent system parameters, such as the replica placement policies, number of nodes and so on. Previous work has roughly and separately discussed the individual impacts of these parameters, and seldom provided their optimal values, nor mentioned their optimal combination. In this paper, we present a new object-based-repairing Markov model. Based on analyzing this model in three popular replica placement policies, we figure out the individual optimal values of these parameters at first, and then work out their optimal combination by GA. Compared with the existing models, our model is easier to solve while reaching more integrative and practical conclusions. These conclusions can effectively instruct the designers to build more reliable large-scale data warehouses.
Computational challenges in the analysis of large, sparse, spatiotemporal data

The pervasive sources of data in today's networked computing environment provide many innovative opportunities, from mining patterns of individual behavior, to enabling data-intensive approaches for scientific discovery, to supporting new kinds of personal interactions and experiences. Passively collected metadata can also be mined for a variety of social analysis. However, due to the vast size and diversity of these data resources, they can pose serious computational challenges to researchers and analysts. This paper highlights several of the key challenges involved in efficiently collecting, storing, and analyzing datasets consisting of millions of sparse files with spatial, temporal, and network features. We focus on the computational issues faced in analyzing Call Detail Records (CDRs), the metadata (i.e., log files) passively collected by mobile phone operators about transactions on their telecommunications networks. CDRs and related data provide a rich foundation for research in fields ranging from anthropology and sociology to electrical engineering and urban planning. After describing the data and its challenges, we present our current framework for computational analysis, and discuss opportunities for future work.
Price as a Signal of Product Quality: Some Experimental Evidence*

Abstract We use experimental data to disentangle the signaling and budgetary effects of price on wine demand. The experimental design allows us to isolate the two effects in a simple and intuitive way. The signaling effect is present and nonlinear: it is strongly positive between 3 euros and 5 euros and undetectable between 5 euros and 8 euros. We find a similar nonlinear price–quality relationship in a large sample of wine ratings from the same price segment, supporting the hypothesis that taster behavior in the experiment is consistent with rationally using prices as signals of quality. Price signals also have greater importance for inexperienced (young) consumers. (JEL Classification: D11, D12, D82)
Learning Efficient Parsing

A corpus-based technique is described to improve the efficiency of wide-coverage high-accuracy parsers. By keeping track of the derivation steps which lead to the best parse for a very large collection of sentences, the parser learns which parse steps can be filtered without significant loss in parsing accuracy, but with an important increase in parsing efficiency. An interesting characteristic of our approach is that it is self-learning, in the sense that it uses unannotated corpora.
Identification of blood meal sources of Lutzomyia longipalpis using polymerase chain reaction-restriction fragment length polymorphism analysis of the cytochrome B gene

An analysis of the dietary content of haematophagous insects can provide important information about the transmission networks of certain zoonoses. The present study evaluated the potential of polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis of the mitochondrial cytochrome B (cytb) gene to differentiate between vertebrate species that were identified as possible sources of sandfly meals. The complete cytb gene sequences of 11 vertebrate species available in the National Center for Biotechnology Information database were digested with Aci I, Alu I, Hae III and Rsa I restriction enzymes in silico using Restriction Mapper software. The cytb gene fragment (358 bp) was amplified from tissue samples of vertebrate species and the dietary contents of sandflies and digested with restriction enzymes. Vertebrate species presented a restriction fragment profile that differed from that of other species, with the exception of Canis familiaris and Cerdocyon thous. The 358 bp fragment was identified in 76 sandflies. Of these, 10 were evaluated using the restriction enzymes and the food sources were predicted for four: Homo sapiens (1), Bos taurus (1) and Equus caballus (2). Thus, the PCR-RFLP technique could be a potential method for identifying the food sources of arthropods. However, some points must be clarified regarding the applicability of the method, such as the extent of DNA degradation through intestinal digestion, the potential for multiple sources of blood meals and the need for greater knowledge regarding intraspecific variations in mtDNA.
Virtual simulation study of shipborne manipulator based on CMAC control

The shipborne manipulator studied in this paper is a new foldaway crane system with retractable arms working on ships and controlled by the drive of its hydraulic system. A visual simulation system for this shipborne manipulator with virtual reality (VR) completed by OpenGL is studied and put up with based on the synthetical research of the characteristics and work condition for this kind of shipborne manipulator. The main characteristics of structure and functions of the simulation system are also presented. The intelligent controller based on CMAC (Cerebellar Model Articulation Controller) is described. It is a useful simulation model and system for the further study on the kinematics and dynamics control theory of this kind of system similar as robot. The results of simulation show that controller has good stability and accuracy and the virtual simulation system is workable and effective. This system is not only an important virtual environment for the crane's work on the sea but also the necessary reference of training for the operator and control.
Increasing loyalty using predictive modeling in Business-to-Business Telecommunication

Customer Relationship Management (CRM) is a key element of modern marketing strategies. One of the most practical way to build useful knowledge on customers in a CRM system to produce scores to forecast churn behavior, propensity to subscribe to a new service. In AMEA zone (Asia, Middle East and Africa zone), the context of fierce competition may represent a higher percentage, and particularly in B2B market. But by contrast, to our knowledge, no scientific papers were dedicated and published to detail the way to improve loyalty in B2B Telco market. If we can assume at low segments similarities between B2B and B2C, some research is required in order to model B2B user behavior versus B2C behavior. This problematic stands actual as "Bring Your own Device" (BYOD) becomes more and more trendy. Answering business requirements, our team applied some B2C predictive tools with adapting them to B2B in an AMEA country Orange affiliate.
An extremely wideband printed antenna with WLAN stop band using SRR

Deign and performance of an extremely wideband printed antenna with wireless local area network (WLAN) stop band are analyzed and presented in this paper. In the proposed antenna, an extremely wideband is achieved by modifying ground plane structure and stop band is achieved by inserting split ring resonator (SRR) in the radiating patch. Predicted impedance bandwidth of an antenna is 2.77-21.84 GHz, for VSWR <; 2. The stop band 5.20-6.04 GHz, for VSWR > 2 is achieved for rejecting WLAN (5.15-5.825 GHz) band signal. Significant gain reduction over the stop band is also observed. The antenna shows average omnidirectional radiation patterns in the passband with a compact size of 38 × 34 mm2.
Hypervolume-based Multi-objective Bayesian Optimization with Student-t Processes

Student-$t$ processes have recently been proposed as an appealing alternative non-parameteric function prior. They feature enhanced flexibility and predictive variance. In this work the use of Student-$t$ processes are explored for multi-objective Bayesian optimization. In particular, an analytical expression for the hypervolume-based probability of improvement is developed for independent Student-$t$ process priors of the objectives. Its effectiveness is shown on a multi-objective optimization problem which is known to be difficult with traditional Gaussian processes.
Use of conventional PCR and smear microscopy to diagnose pulmonary tuberculosis in the Amazonian rainforest area

The diagnostic usefulness of Ziehl-Neelsen (ZN)-stained sputum smears combined with conventional polymerase chain reaction (ZN/PCR) to amplify IS6110 region DNA extracted from ZN slides was evaluated. The objective was to verify if this association could improve tuberculosis (TB) diagnosis in patients at remote sites. The study was carried out in 89 patients with culture-confirmed pulmonary TB as defined by the Brazilian Manual for TB Treatment. The participants were recruited in a reference unit for TB treatment in Rondônia, a state in the Amazonian area in northern Brazil. ZN, PCR, and culture performed in the sputum samples from these patients were analyzed in different combinations (i.e., ZN plus PCR and ZN plus culture). The prevalence rates of pulmonary TB in these patients were 32.6 and 28.1% considering culture and ZN/PCR, respectively. The sensitivity and specificity of ZN/PCR were 86 and 93%, respectively. ZN/PCR was able to detect more TB cases than ZN alone. This method could offer a new approach for accurate tuberculosis diagnosis, especially in remote regions of the world where culture is not available.
Research on computer-aided diagnosis of lung nodule

With the development of Computer in recent years, computer-Aided Diagnosis becomes a new technology applied in image processing techniques. For analyzing lung CT image as the research object, pulmonary nodules of computer automatic detection as the goal, the main region are in the segmentation of lung parenchyma, perceptual ROI extraction, feature extraction. The article presents two ways of image-preprocessing and adaptive threshold binarization, after getting the preliminary pulmonary parenchyma, taking the method of removal of trachea and bronchia in region-growing and edge patch with rolling ball, resulting the final segmentation of pulmonary areas.
Problematic alcohol use and problem gambling: Associations to structural and functional aspects of social ties in a Finnish population sample

Aims This study aims to explore associations between structural and functional aspects of social networks and relationships (here labelled social ties) among individuals exhibiting problematic alcohol use and problem gambling, respectively. Material & Methods Data was collected in the 2011 Western Finland Mental Health Survey, a postal questionnaire survey applying a stratified random sampling approach. The survey response rate was 46.2% (n = 4624, age range 15–80 years). Problem behaviours were assessed using the CAGE and Lie/Bet tools. Logistic regression analyses were performed, with problematic alcohol use and problem gambling as dependent variables. Demographic variables, structural social tie factors (marital status, frequency of social contacts, engagement in association activities) and functional social tie factors (experienced loneliness, social support, neighbourhood trust, general trust) constituted explanatory variables. Results In this representative population sample, only one structural social tie variable, marital status, proved to be significantly associated with one of the outcomes (problematic alcohol use). Identical functional social tie variables were associated with both problematic alcohol use and problem gambling: individuals exhibiting the problem behaviours experienced higher levels of experienced loneliness and low levels of neighbourhood trust. Identified interaction effects with demographic factors highlight the complexity of links. Conclusions Functional aspects of individual-level social ties appear to be more relevant when studying problematic alcohol use or problem gambling, similarly to other forms of mental health problems. The role of social ties as preventive or risk factors for problem behaviour development, as a part of problem behaviour maintenance or as a cessation and a recovery resource should be further explored, considering also interactions with demographic variables.
Multiplexed temporal coding of electric communication signals in mormyrid fishes

Summary The coding of stimulus information into patterns of spike times occurs widely in sensory systems. Determining how temporally coded information is decoded by central neurons is essential to understanding how brains process sensory stimuli. Mormyrid weakly electric fishes are experts at time coding, making them an exemplary organism for addressing this question. Mormyrids generate brief, stereotyped electric pulses. Pulse waveform carries information about sender identity, and it is encoded into submillisecond-to-millisecond differences in spike timing between receptors. Mormyrids vary the time between pulses to communicate behavioral state, and these intervals are encoded into the sequence of interspike intervals within receptors. Thus, the responses of peripheral electroreceptors establish a temporally multiplexed code for communication signals, one consisting of spike timing differences between receptors and a second consisting of interspike intervals within receptors. These signals are processed in a dedicated sensory pathway, and recent studies have shed light on the mechanisms by which central circuits can extract behaviorally relevant information from multiplexed temporal codes. Evolutionary change in the anatomy of this pathway is related to differences in electrosensory perception, which appears to have influenced the diversification of electric signals and species. However, it remains unknown how this evolutionary change relates to differences in sensory coding schemes, neuronal circuitry and central sensory processing. The mormyrid electric communication pathway is a powerful model for integrating mechanistic studies of temporal coding with evolutionary studies of correlated differences in brain and behavior to investigate neural mechanisms for processing temporal codes.
Sentiment Analysis of Hindi Reviews based on Negation and Discourse Relation

With recent developments in web technologies, percentage of web content in Hindi language is growing up at a lightning speed. Opinion classification research has gained tremendous momentum in recent times mostly for English language. However, there has been little work in this area for Indian languages. There is a need to analyse the Hindi language content and get insight of opinions expressed by people and various communities. In this paper, a method is proposed to increase the coverage of the Hindi SentiWordNet for better classification results. In addition to this, impact of the negation and discourse rules are investigated for Hindi sentiment analysis. Proposed algorithm produces 82.89% for positive reviews and 76.59 % for negative reviews, and an overall accuracy of 80.21%.
Adaptive mesh refinement for micromagnetics simulations

We present a methodology for efficient micromagnetics simulation. The method combines an unconditionally stable, finite differences scheme with an adaptive mesh refinement technique. It enhances accuracy by covering locally special regions of the domain with a sequence of nested, progressively finer rectangular grid patches that dynamically follow sharp transitions of the magnetization field (e.g., walls and vortices). To illustrate our approach, we consider a rectangular sample of infinite thickness with strong anisotropy in the out-of-plane direction
A Deep Detection Scheme against Pollution Attacks in Wireless Inter-flow Network Coding

Wireless inter-flow network coding can improve the performance of multi-source unicast communication in multihop wireless networks. However, it encounters with serious security threat of pollution attack. In this paper, by combining signature and arbitration in wireless inter-flow network coding, we propose a deep detection scheme to locate malicious nodes after detecting pollution attacks. Firstly, we design a digital signature scheme which is uncorrelated with field size to detect pollution attacks and locate malicious nodes within one hop. Secondly, we design an arbitration scheme based on trusted node to solve the hard problem of locating malicious nodes beyond one hop, which results from the coding operation of inter-flow network coding. Analysis results indicate that the detection scheme is able to defend against all four types of pollution attacks thoroughly with better performance.
Struggles for recognition: a content analysis of messages posted on the Internet

Background The Internet has enlarged the possibilities of human communication and opened new ways of exploring perceptions of mental health. This study is part of a research project aiming to explore, describe, and analyze different discourses of mental health in Norway and Sweden, using material from Internet-based services. Aim To examine messages posed by users of publicly available question-and-answer services and to describe their content. Methods A Web search was used to identify Norwegian and Swedish Websites offering mental health services by email or posted messages. A total of 601 messages from 20 services, 10 Norwegian and 10 Swedish, were analyzed by means of qualitative content analysis and further interpreted in light of the social theory of recognition by Honneth. Results Eight categories emerged from the analysis: family life, couples, others, violence, the ungovernable, self-image, negotiating normality, and life struggles. These categories were then grouped into three themes: (1) relationship to significant others, (2) relationship to self, and (3) relationship to the social community. The themes promoted an understanding of mental health as closely connected to political and social factors. Conclusions The results showed a variety of concerns from various parts of life and empowered the view that mental health should be understood broadly, at a conceptual level. Mental health emerged as a deeply relational concept that emphasized the equal distribution of chances in life. It strengthened the moral grammar of social inclusion and the acceptance of plurality in social life.