Search results for: violation data discovery

Authors: Christine S. Veviani

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By observing the Brazilian labor reality, considered as degrading and oppressive, as well as responsible for creating obstacles to rights, this paper is aimed at demonstrating the obligatoriness of complying with the Constitution, as an effective instrument of the Democratic and Social State of Law established in the country since 1988, which identifies and determines the recognition of a single type of citizenship, as representation of equality, social inclusion and human dignity. To achieve this purpose, that is, to awake to a new culture focused on human respect / fundamental rights engraved in the Brazilian Constitution, doctrinal works, case law and labor courts (how they work) will be used as methodology. Thus, by concluding that there is a need for a change in behavior, by employers, intended to respect the Constitution, especially with regard to the concept and citizenship content if an attempt is made to achieve as a result few steps effectiveness of fundamental social rights protective of the Brazilian working class. Thus, by analyzing the Brazilian labor reality, the result is the employers' denial of full and single citizenship of workers, whose effects are directly related to the violation of rights, which leads to the conclusion that there is a need for a change in the behavior regarding the respect for the Constitution, especially concerning the effectiveness of fundamental social rights, which protect the working class in Brazil.

Keywords: employment relationships, opposing citizenships, constitutionalism, capitalism

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Authors: Francisco José Plácido da Cunha, Tassio Ferenzini Martins Sirqueira, Marx Leles Viana, Carlos José Pereira de Lucena

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Open Multiagent Systems (MASs) are societies in which heterogeneous and independently designed entities (agents) work towards similar, or different ends. Software agents are autonomous and the diversity of interests among different members living in the same society is a fact. In order to deal with this autonomy, these open systems use mechanisms of social control (norms) to ensure a desirable social order. This paper considers the following types of norms: (i) obligation — agents must accomplish a specific outcome; (ii) permission — agents may act in a particular way, and (iii) prohibition — agents must not act in a specific way. All of these characteristics mean to encourage the fulfillment of norms through rewards and to discourage norm violation by pointing out the punishments. Once the software agent decides that its priority is the satisfaction of its own desires and goals, each agent must evaluate the effects associated to the fulfillment of one or more norms before choosing which one should be fulfilled. The same applies when agents decide to violate a norm. This paper also introduces a framework for the development of MASs that provide support mechanisms to the agent’s decision-making, using norm-based reasoning. The applicability and validation of this approach is demonstrated applying a traffic intersection scenario.

Keywords: BDI agent, BDI4JADE framework, multiagent systems, normative agents

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Authors: Rimmy Yadav, Anmol Preet Kaur

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Big Data has demonstrated the vast potential in streamlining, deciding, spotting business drifts in different fields, for example, producing, fund, Information Technology. This paper gives a multi-disciplinary diagram of the research issues in enormous information and its procedures, instruments, and system identified with the privacy, data storage management, network and energy utilization, adaptation to non-critical failure and information representations. Other than this, result difficulties and openings accessible in this Big Data platform have made.

Keywords: big data, privacy, data management, network and energy consumption

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Authors: Panda Krouse

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This work is a marriage of the science of Applied Behavioral Analysis and an educator’s look at Neuroscience. The focus is integrating what we know about the anatomy of the brain in autism and evidence-based practices in education. It is a bold attempt to present links between neurological research and the application of evidence-based practices in education. In researching for this work, no discovery of articles making these connections was made. Consideration of the areas of structural differences in the brain are aligned with evidence-based strategies. A brief literary review identifies how identified areas affect overt behavior, which is what, as educators, is what we can see and measure. Giving further justification and validation of our practices in education from a second scientific field is significant for continued improvement in intervention for students on the autism spectrum.

Keywords: autism, evidence based practices, neurological differences, education intervention

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Authors: Nizar Ahmad

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Peace without community participation will remain a vision, so, this study presents the contribution and efforts made by community base organization in views of local conflict affect population in Pakhtun society. A four conflict affected villages of Malakad Division were selected and a sample size of 278 household respondents were determined through online survey system software out of total 982 households. A Chi-square test was applied to ascertain association between various communication base organizations factors with state of peace in the area. It was found that provision of humanitarian aid, rehabilitation of displaced population, rebuilding of trust in government and peace festivals by communication organization had significant association with state of peace in the area. In contrast provision of training, peace education monitoring and reporting of human rights violation in war zone by local organization was non-significantly related to the state of peace in the area. Community base organization play an active role in building peace in the area but lack capacity, linkages with external actors and outside support. National and international organization actors working in the area of peace and conflict resolution need to focus on the capacity, networking and peace initiatives of local organizations working in fragile context.

Keywords: community base peacebuilding, conflict resolution, terrorism, violence

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: Aishwarya Shekhar, Himanshu Sharma

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Data deduplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. In this process, duplicate data is expunged, leaving only one copy means single instance of the data to be accumulated. Though, indexing of each and every data is still maintained. Data deduplication is an approach for minimizing the part of storage space an organization required to retain its data. In most of the company, the storage systems carry identical copies of numerous pieces of data. Deduplication terminates these additional copies by saving just one copy of the data and exchanging the other copies with pointers that assist back to the primary copy. To ignore this duplication of the data and to preserve the confidentiality in the cloud here we are applying the concept of hybrid nature of cloud. A hybrid cloud is a fusion of minimally one public and private cloud. As a proof of concept, we implement a java code which provides security as well as removes all types of duplicated data from the cloud.

Keywords: confidentiality, deduplication, data compression, hybridity of cloud

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Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

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Authors: Tomy Prihananto, Damar Apri Sudarmadi

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Indonesia recognizes the right to privacy as a human right. Indonesia provides legal protection against data management activities because the protection of personal data is a part of human rights. This paper aims to describe the arrangement of data management and data management in Indonesia. This paper is a descriptive research with qualitative approach and collecting data from literature study. Results of this paper are comprehensive arrangement of data that have been set up as a technical requirement of data protection by encryption methods. Arrangements on encryption and protection of personal data are mutually reinforcing arrangements in the protection of personal data. Indonesia has two important and immediately enacted laws that provide protection for the privacy of information that is part of human rights.

Keywords: Indonesia, protection, personal data, privacy, human rights, encryption

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Authors: Munira Al-Azraqi

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Modern South Arabian Languages (MSAL) belong to the Semitic language family and are believed to be either a southern member of the west Semitic branch (Rubin 2010; Moscati et al 1969) or an eastern member of the south Semitic branch (Faber 1997), (Watson 2012). They are six languages which are still spoken in southern Arabia. They are used in Oman, Yemen, Saudi Arabia and in some of the Gulf states. Mehri is one of them however it has the highest number of speakers comparing to the other members of MSAL. It is used in Yemen, Oman, in parts of southern and eastern Saudi Arabia and in some of the Gulf states. The number of Mehri speakers is estimated at between 100,000 and 180,000. The problem that this language might face is that its speakers live in different places which are belonging to different countries. This might cause the language to change rapidly due to education and communication. There are some studies on Omani and Yemeni Mehri but not in Saudi Mehri. In the nineteenth century, travelers, western scholars and explorers played their parts in the discovery of these peoples and their languages. The historical turning point for the knowledge of the MSAL is 1898, when the Südarabische Expedition of the Imperial Academy of Vienna started. The three scholars, Müller, Jahn and Hein began their systematic collection of texts, which were later studied grammatically and lexically by Bittner (1908-1917), Jahn (1915), Leslau (1938) and Wagner (1953). Saudi Mehri has not been studied. This might be caused by the lack of information or the difficulty in collecting the data which this paper aims to shed light on.

Keywords: Modern South Arabian, Mehri, Saudi Arabia, endangered languages

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Authors: Moustafa Gabr

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Galectin-3 has been identified as a critical player in driving the neuroinflammatory responses in Alzheimer's disease (AD). A key feature of this function of galectin-3 is associated with its interaction with the triggering receptor expressed on myeloid cells-2 (TREM2). Herein, we report a high-throughput screening (HTS) platform that can be used for the identification of inhibitors of TREM2 and galectin-3 interaction. We have utilized this HTS assay to screen a focused library of compounds optimized for central nervous system (CNS)-related diseases. MG-257 was identified from this screen as the first example of a small molecule that can attenuate TREM2 signaling based on its high affinity to galectin-3 (endogenous ligand of TREM2). Remarkably, MG-257 reduced the levels of proinflammatory cytokines in activated microglial cells, which highlights its ability to inhibit the neuroinflammatory response associated with AD.

Keywords: medicinal chemistry, Alzheimer's disease, drug discovery, therapeutics

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Authors: Bounoua Nadia, Rebizi Mohamed Nadjib

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Chiral molecules in relation to particular biological roles are stereoselective. Enantiomers differ significantly in their biochemical responses in a biological environment. Despite the current advancement in drug discovery and pharmaceutical biotechnology, the chiral separation of some racemic mixtures continues to be one of the greatest challenges because the available techniques are too costly and time-consuming for the assessment of therapeutic drugs in the early stages of development worldwide. Various nanoparticles became one of the most investigated and explored nanotechnology-derived nanostructures, especially in chirality, where several studies are reported to improve the enantiomeric separation of different racemic mixtures. The production of surface-modified nanoparticles has contributed to these limitations in terms of sensitivity, accuracy, and enantioselectivity that can be optimized and therefore makes these surface-modified nanoparticles convenient for enantiomeric identification and separation.

Keywords: chirality, enantiomeric recognition, selectors, analysis, surface-modified nanoparticles

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Authors: Amy Gooden

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When human genomic data is considered, this is often done through only one dimension of the law, or the interplay between the various dimensions is not considered, thus providing an incomplete picture of the legal framework. This research considers and analyzes the various dimensions in South African law applicable to genomic sequence data – including property rights, personality rights, and intellectual property rights. The effective use of personal genomic sequence data requires the acknowledgement and harmonization of the rights applicable to such data.

Keywords: artificial intelligence, data, law, genomics, rights

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Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

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Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: data integration, data warehousing, federated architecture, Online Analytical Processing (OLAP)

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Authors: Rameez Ahmad, Aqib Mehmood, Imran Khan

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Self-directed car (SDC) that can drive itself from one fact to another without support from a driver. Certain trust that self-directed car obligate the probable to transform the transportation manufacturing while essentially removing coincidences, and cleaning up the environment. This study realizes the effects that SDC (also called a self-driving, driver or robotic) vehicle travel demands and ride scheme is likely to have. Without the typical obstacles that allows detection of a audio vision based hardware and software construction (It (SDC) and cost benefits, the vehicle technologies, Gold (Generic Obstacle and Lane Detection) to a knowledge-based system to predict their potential and consider the shape, color, or balance) and an organized environment with colored lane patterns, lane position ban. Discovery the problematic consequence of (SDC) on GT (grand trunk road) road and brand the car further effectual.

Keywords: SDC, gold, GT, knowledge-based system

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Authors: Zhiwei Yan, Jong-Hyouk Lee, Yong-Jin Park, Xiaodong Lee

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In this paper, we analyze NEtwork MObility (NEMO) supporting problems in Content-Centric Networking (CCN), and propose the CCN-NEMO which can well support the deployment of the content-centric paradigm in large-scale mobile Internet. The CCN-NEMO extends the signaling message of the basic CCN protocol, to support the mobility discovery and fast trigger of Interest re-issuing during the network mobility. Besides, the Mobile Router (MR) is extended to optimize the content searching and relaying in the local subnet. These features can be employed by the nested NEMO to maximize the advantages of content retrieving with CCN. Based on the analysis, we compare the performance on handover latency between the basic CCN and our proposed CCN-NEMO. The results show that our scheme can facilitate the content-retrieving in the NEMO scenario with improved performance.

Keywords: NEMO, CCN, mobility, handover latency

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Authors: Yingxu Wang

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This work presents basic research on the recursive structures and dual sequential patterns of primes for the formal proof of the Twin-Prime Conjecture (TPC). A rigorous methodology of Twin-Prime Decomposition (TPD) is developed in MATLAB to inductively verify potential twins in the dual sequences of primes. The key finding of this basic study confirms that the dual sequences of twin primes are not only symmetric but also infinitive in the unique base 6 cycle, except a limited subset of potential pairs is eliminated by the lack of dual primality. Both theory and experiments have formally proven that the infinity of twin primes stated in TPC holds in the P x P space.

Keywords: number theory, primes, twin-prime conjecture, dual primes (P x P), twin prime decomposition, formal proof, algorithm

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Authors: Sikander Singh Cheema, Jasmeen Kaur

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In this paper, the concept of data mining is summarized and its one of the important process i.e KDD is summarized. The data mining based on Genetic Algorithm is researched in and ways to achieve the data mining Genetic Algorithm are surveyed. This paper also conducts a formal review on the area of data mining tasks and genetic algorithm in various fields.

Keywords: data mining, KDD, genetic algorithm, descriptive mining, predictive mining

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Authors: Seung-Lock Seo

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This work presents a data-mining empirical monitoring scheme for industrial processes with partially unbalanced data. Measurement data of good operations are relatively easy to gather, but in unusual special events or faults it is generally difficult to collect process information or almost impossible to analyze some noisy data of industrial processes. At this time some noise filtering techniques can be used to enhance process monitoring performance in a real-time basis. In addition, pre-processing of raw process data is helpful to eliminate unwanted variation of industrial process data. In this work, the performance of various monitoring schemes was tested and demonstrated for discrete batch process data. It showed that the monitoring performance was improved significantly in terms of monitoring success rate of given process faults.

Keywords: data mining, process data, monitoring, safety, industrial processes

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Authors: Islam Tarek, Moataz Soliman

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With the amazing development of nanoscience’s and the discovery of the unique properties of nanometric materials, the ideas of scientists and researchers headed to take advantage of this progress in various fields, and one of the most important of these areas is the field of heat transfer and benefit from it in saving energy used for heat transfer, so nanometric materials were used to improve the properties of heat transfer fluids and increase the efficiency of the liquid. In this paper, we will compare two types of heat transfer fluid, one industrial type (the base fluid is a mix of ethylene glycol and deionized water ) and another natural oils(the base fluid is a mix of jatropha oil and expired olive oil), explaining the method of preparing each of them, starting from the method of preparing CNT, collecting and sorting jatropha seeds, and the most appropriate method for extracting oil from them, and characterization the both of two fluids and when to use both.

Keywords: nanoscience, heat transfer, thermal conductivity, jatropha oil

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Authors: Yingxu Wang

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The base 6 structure and properties of mirror primes are discovered in this work towards the proof of Goldbach Conjecture. This paper reveals a fundamental pattern on pairs of mirror primes adjacent to any even number nₑ > 2 with symmetrical distances on both sides determined by a methodology of Mirror Prime Decomposition (MPD). MPD leads to a formal proof of the Goldbach conjecture, which states that the conjecture holds because any pivot even number, nₑ > 2, is a sum of at least an adjacent pair of primes divided by 2. This work has not only revealed the analytic pattern of base 6 primes but also proven the infinitive validation of the Goldbach conjecture.

Keywords: number theory, primes, mirror primes, double recursive patterns, Goldbach conjecture, formal proof, mirror-prime decomposition, applications

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Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

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Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: biological ontology, linked data, semantic data integration, semantic web

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Authors: Thrivikraman Aswathi, S. Advaith

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As there can be cases where the use of real data is somehow limited, such as when it is hard to get access to a large volume of real data, we need to go for synthetic data generation. This produces high-quality synthetic data while maintaining the statistical properties of a specific dataset. In the present work, a generative adversarial network (GAN) is trained to produce multivariate time series (MTS) data since the MTS is now being gathered more often in various real-world systems. Furthermore, the GAN-generated MTS data is fed into a transformer-based deep learning architecture that carries out the data categorization into predefined classes. Further, the model is evaluated across various distinct domains by generating corresponding MTS data.

Keywords: GAN, transformer, classification, multivariate time series

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Authors: Ahmad Mansoor Stanikzai, Yoshitaka Kajita

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This research is a very essential towards transportation planning of Kabul New City. In this research, the travel demand of Kabul metropolitan area (Existing and Kabul New City) are evaluated for three different target years (2015, current, 2025, mid-term, 2040, long-term). The outcome of this study indicates that, though currently the vehicle volume is less the capacity of existing road networks, Kabul city is suffering from daily traffic congestions. This is mainly due to lack of transportation management, the absence of proper policies, improper public transportation system and violation of traffic rules and regulations by inhabitants. On the other hand, the observed result indicates that the current vehicle to capacity ratio (VCR) which is the most used index to judge traffic status in the city is around 0.79. This indicates the inappropriate traffic condition of the city. Moreover, by the growth of population in mid-term (2025) and long-term (2040) and in the case of no development in the road network and transportation system, the VCR value will dramatically increase to 1.40 (2025) and 2.5 (2040). This can be a critical situation for an urban area from an urban transportation perspective. Thus, by introducing high-capacity public transportation system and the development of road network in Kabul New City and integrating these links with the existing city road network, significant improvements were observed in the value of VCR.

Keywords: Afghanistan, Kabul new city, planning, policy, urban transportation

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Authors: Lakshmi Prayaga, Chandra Prayaga. Aaron Wade, Gopi Shankar Mallu, Harsha Satya Pola

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Synthetic data generated by Generative Adversarial Networks and Autoencoders is becoming more common to combat the problem of insufficient data for research purposes. However, generating synthetic data is a tedious task requiring extensive mathematical and programming background. Open-source platforms such as the Synthetic Data Vault (SDV) and Mostly AI have offered a platform that is user-friendly and accessible to non-technical professionals to generate synthetic data to augment existing data for further analysis. The SDV also provides for additions to the generic GAN, such as the Gaussian copula. We present the results from two synthetic data sets (CTGAN data and CTGAN with Gaussian Copula) generated by the SDV and report the findings. The results indicate that the ROC and AUC curves for the data generated by adding the layer of Gaussian copula are much higher than the data generated by the CTGAN.

Keywords: synthetic data generation, generative adversarial networks, conditional tabular GAN, Gaussian copula

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Authors: H. Gholami, M. Jalali Azizpour

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Stress Corrosion Crack (SCC) in pipeline is a type of environmentally assisted cracking (EAC), since its discovery in 1965 as a possible cause of failure in pipeline, SCC has caused, on average, one of two failures per year in the U.S, According to the NACE SCC DA a pipe line segment is considered susceptible to SCC if all of the following factors are met: The operating stress exceeds 60% of specified minimum yield strength (SMYS), the operating temperature exceeds 38°C, the segment is less than 32 km downstream from a compressor station, the age of the pipeline is greater than 10 years and the coating type is other than Fusion Bonded Epoxy(FBE). In this paper as a practical experience in NISOC, Direct Assessment (DA) Method is used for identification SCC defect in unpiggable pipeline located downstream of compressor station.

Keywords: stress corrosion crack, direct assessment, disbondment, transgranular SCC, compressor station

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Authors: Feng Tao, Ma Jing, Guo Xian, Wang Jing

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Named Data Networking (NDN) replaces IP address of traditional network with data name, and adopts dynamic cache mechanism. In the existing mechanism, however, only one-to-one search can be achieved because every data has a unique name corresponding to it. There is a certain mapping relationship between data content and data name, so if the data name is intercepted by an adversary, the privacy of the data content and user’s interest can hardly be guaranteed. In order to solve this problem, this paper proposes a one-to-many fuzzy search scheme based on order-preserving encryption to reduce the query overhead by optimizing the caching strategy. In this scheme, we use hash value to ensure the user’s query safe from each node in the process of search, so does the privacy of the requiring data content.

Keywords: NDN, order-preserving encryption, fuzzy search, privacy

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Authors: Isaiah Chacha, Samuel Arimi, Andrew Thaiya

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Background: This study was conducted to assess knowledge, attitudes and practices regarding anthrax in Maragua, Kenya to provide baseline information to design interventions. Methods: A cross sectional survey was conducted among head of households, health and veterinary workers in Maragua Sub-county in August and September 2014. Administered questionnaires were used to collect data from household members and a key informant interview held with health and veterinary workers. Multi stage sampling was used to obtain participants’ knowledge, attitudes and practices. Questions were scored and descriptively analyzed using Excel spreadsheet then exported to GenStat Discovery Edition 4. Results: A total of 293 community members were recruited in this study. The overall level of knowledge was 77.9% of all community members regarding cause, transmission, symptoms and prevention of the disease in both humans and animals. Majority of the participants (96.3%) had heard about anthrax. A total of 99 (33.8%) correspondents had seen a person with anthrax and 75.1% think that anthrax is a very serious disease in the area. Of the interviewed correspondents, 14.3% of them have had their animals (mostly cattle) suffer from anthrax while 15.7% had either suffered from anthrax or have had their family member who suffered from anthrax. Conclusion: The study findings indicate above average knowledge on cause, symptoms, transmission and prevention of anthrax among community members in humans and animals. Practices in this study were still risk among community members. Veterinary and Medical health planners should design anthrax awareness interventions as a team targeting to reach these communities and the public through barazas, radio, CHW and other communication channel on a regular basis.

Keywords: anthrax, attitudes, Kenya, knowledge, Maragua, practices

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Authors: Moon-Tak Oh, Kyung-Min Park, Tae-Eun Yoon, Hoon Choi, Chil-Woo Lee

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This paper is about middle-ware which enables group-user applications on mobile devices in physical proximity to interact with other devices without intervention of a central server. Requirements of the middle-ware are identified from service usage scenarios, and the functional architecture of the middle-ware is specified. These requirements include group management, synchronization, and resource management. Group Management needs to provide various capabilities to such applications with respect to managing multiple users (e.g., creation of groups, discovery of group or individual users, member join/leave, election of a group manager and service-group association) using D2D communication technology. We designed the middle-ware for the above requirements on the Android platform.

Keywords: group user, middleware, mobile service, physical proximity

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Authors: Nihar Ranjan, Derrick Watkins, Dev P. Arya

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Current methods in the study of antibiotic activity of ribosome targeted antibiotics are dependent on cell based bacterial inhibition assays or various forms of ribosomal binding assays. These assays are typically independent of each other and little direct correlation between the ribosomal binding and bacterial inhibition is established with the complementary assay. We have developed novel high-throughput capable assays for ribosome targeted drug discovery. One such assay examines the compounds ability to bind to a model ribosomal RNA A-site. We have also coupled this assay to other functional orthogonal assays. Such analysis can provide valuable understanding of the relationships between two complementary drug screening methods and could be used as standard analysis to correlate the affinity of a compound for its target and the effect the compound has on a cell.

Keywords: bacterial resistance, aminoglycosides, screening, drugs

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