A proposed cloud-based billers hub using secured e-payments system

Automation of several payment processes from start to end is a challenging task, particularly when multiple payments from online and offline billers are involved. In this paper, we introduced a new aggregator system to combine all billing system types, in which it is possible to pay invoices electronically. The proposed aggregator system was designed to be employed in a cloud-based Billers Hub (CBBH) developed by the central banks. Furthermore, many applications can be realized such as; deposit e-money, withdrawal e-money, and other applications. A Gateway translator is used to apply authentication rules, security, and privacy. The proposed system was employed in the Jordanian payment gateway and successfully fulfills its purpose

SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis

Data annotation is an important but time-consuming and costly procedure. To sort a text into two classes, the very first thing we need is a good annotation guideline, establishing what is required to qualify for each class. In the literature, the difficulties associated with an appropriate data annotation has been underestimated. In this paper, we present a novel approach to automatically construct an annotated sentiment corpus for Algerian dialect (a Maghrebi Arabic dialect). The construction of this corpus is based on an Algerian sentiment lexicon that is also constructed automatically. The presented work deals with the two widely used scripts on Arabic social media: Arabic and Arabizi. The proposed approach automatically constructs a sentiment corpus containing 8000 messages (where 4000 are dedicated to Arabic and 4000 to Arabizi). The achieved F1-score is up to 72% and 78% for an Arabic and Arabizi test sets, respectively. Ongoing work is aimed at integrating transliteration process for Arabizi messages to further improve the obtained results.Comment: To appear in the 9th International Conference on Brain Inspired Cognitive Systems (BICS 2018

An optimized energy saving mechanism in IEEE 802.16e mobile WiMAX systems

The IEEE 802.16e standard defines a sleep mode operation for conserving power to support the battery life of mobile broadband wireless access (BWA) devices. The system saves energy when it goes through a sleep period with some delay in packet arrival response time. The relationship between energy consumption and the delay is studied to ensure best performance for mobile devices. This relationship has been analyzed by using a mathematical model. A new scheduling method is proposed to adjust the sleep cycle periods by adding a small increase to the next sleep cycle compared with the previous cycle instead of just simply doubling the previous cycle. The simulated results were obtained after adjusting the length of the first sleep cycle period (Tmin). Adjusting Tmin  provides a result of 54% reduction in the time needed for every frame to get a response especially in a lower traffic region. In a high traffic region, a reduction of 21.5% has been obtained in energy consumption for each sleep mode operation. Therefore, the proposed idea confirms a faster frame response time at lower energy consumption

Analyzing D-wave quantum macro assembler security

As we enter the quantum computing era, security becomes of at most importance. With the release of D-Wave One in 2011 and most recently the 2000Q, with 2,000 qubits, and with NASA and Google using D-wave Systems quantum computers, a thorough examination of quantum computer security is needed. Quantum computers underlying hardware is not compatible with classical boolean and binary-based computer systems and software. Assemblers and compliers translate modern programming languages and problems into quantum-annealing methods compatible with quantum computers. This paper presents a vulnerability assessment utilizing static source code analysis on Qmasm Python tool. More specifically, we use flow-sensitive, inter-procedural and context-sensitive data flow analysis to uncover vulnerable points in the program. We demonstrate the Qmasm security flaws that can leave D-Wave 2X system vulnerable to severe threats

Analyzing D-wave quantum macro assembler security

As we enter the quantum computing era, security becomes of at most importance. With the release of D-Wave One in 2011 and most recently the 2000Q, with 2,000 qubits, and with NASA and Google using D-wave Systems quantum computers, a thorough examination of quantum computer security is needed. Quantum computers underlying hardware is not compatible with classical boolean and binary-based computer systems and software. Assemblers and compliers translate modern programming languages and problems into quantum-annealing methods compatible with quantum computers. This paper presents a vulnerability assessment utilizing static source code analysis on Qmasm Python tool. More specifically, we use flow-sensitive, inter-procedural and context-sensitive data flow analysis to uncover vulnerable points in the program. We demonstrate the Qmasm security flaws that can leave D-Wave 2X system vulnerable to severe threats

Feature extraction and selection for Arabic tweets authorship authentication

© 2017, Springer-Verlag Berlin Heidelberg. In tweet authentication, we are concerned with correctly attributing a tweet to its true author based on its textual content. The more general problem of authenticating long documents has been studied before and the most common approach relies on the intuitive idea that each author has a unique style that can be captured using stylometric features (SF). Inspired by the success of modern automatic document classification problem, some researchers followed the Bag-Of-Words (BOW) approach for authenticating long documents. In this work, we consider both approaches and their application on authenticating tweets, which represent additional challenges due to the limitation in their sizes. We focus on the Arabic language due to its importance and the scarcity of works related on it. We create different sets of features from both approaches and compare the performance of different classifiers using them. We experiment with various feature selection techniques in order to extract the most discriminating features. To the best of our knowledge, this is the first study of its kind to combine these different sets of features for authorship analysis of Arabic tweets. The results show that combining all the feature sets we compute yields the best results

Immune Response to Bifidobacterium bifidum Strains Support Treg/Th17 Plasticity

In this work we analyzed the immune activation properties of different Bifidobacterium strains in order to establish their ability as inductors of specific effector (Th) or regulatory (Treg) responses. First, we determined the cytokine pattern induced by 21 Bifidobacterium strains in peripheral blood mononuclear cells (PBMCs). Results showed that four Bifidobacterium bifidum strains showed the highest production of IL-17 as well as a poor secretion of IFNγ and TNFα, suggesting a Th17 profile whereas other Bifidobacterium strains exhibited a Th1-suggestive profile. Given the key role of Th17 subsets in mucosal defence, strains suggestive of Th17 responses and the putative Th1 Bifidobacterium breve BM12/11 were selected to stimulate dendritic cells (DC) to further determine their capability to induce the differentiation of naïve CD4+ lymphocytes toward different Th or Treg cells. All selected strains were able to induce phenotypic DC maturation, but showed differences in cytokine stimulation, DC treated with the putative Th17 strains displaying high IL-1β/IL-12 and low IL-12/IL-10 index, whereas BM12/11-DC exhibited the highest IL-12/IL-10 ratio. Differentiation of naïve lymphocytes confirmed Th1 polarization by BM12/11. Unexpectedly, any B. bifidum strain showed significant capability for Th17 generation, and they were able to generate functional Treg, thus suggesting differences between in vivo and vitro responses. In fact, activation of memory lymphocytes present in PBMCS with these bacteria, point out the presence in vivo of specific Th17 cells, supporting the plasticity of Treg/Th17 populations and the key role of commensal bacteria in mucosal tolerance and T cell reprogramming when needed

Phenotypic characterisation of regulatory T cells in dogs reveals signature transcripts conserved in humans and mice

Regulatory T cells (Tregs) are a double-edged regulator of the immune system. Aberrations of Tregs correlate with pathogenesis of inflammatory, autoimmune and neoplastic disorders. Phenotypically and functionally distinct subsets of Tregs have been identified in humans and mice on the basis of their extensive portfolios of monoclonal antibodies (mAb) against Treg surface antigens. As an important veterinary species, dogs are increasingly recognised as an excellent model for many human diseases. However, insightful study of canine Tregs has been restrained by the limited availability of mAb. We therefore set out to characterise CD4+CD25high T cells isolated ex vivo from healthy dogs and showed that they possess a regulatory phenotype, function, and transcriptomic signature that resembles those of human and murine Tregs. By launching a cross-species comparison, we unveiled a conserved transcriptomic signature of Tregs and identified that transcript hip1 may have implications in Treg function