Miracle-dz/UniFAR-FTUs huggingface dataset:
Issues & Solution of SAAS Model in Cloud Computing

Cloud computing of is an Internet-based computing, where shared resources, software and information, are provided to computers and devices on-demand. It provides people the way to share distributed resources and services that belong to different organization. Cloud computing is a set of IT services that are provided to a customer over a network on a leased basis and with the ability to scale up or down their service requirements. Usually cloud computing services are delivered by a third party provider who owns the infrastructure. Security is one of the major issues which hamper the growth of cloud. in This paper we introduce what is cloud computing in saas model. And also provide the security issues & solution of cloud computing. And detail description of what are the security issues & Solution in SAAS model. And also define the Solution on that issue.
An Approach for Benin Automatic Licence Plate Recognition

In this work, we read licence plates using Optical Character Recognition. Our algorithm relies on the detection of plates on the basis of contours and text that they contain. Thank to the combinaison of these two detection mode, our algorithm remains effective even when the plate is slightly obstructed. For the separation of false positive from real images of license plates, we use filters based on text and registration plates general characteristics. This gives our algorithm a great ability to adapt to different contexts. Following our experimental test on license plates in Benin, we obtained a recall rate of 86% and an accuracy rate of 60%.
Betting exclusively by private labels: could it have negative consequences for retailers?

PurposeThe authors analyze the relationship between different consumer attitudinal variables and a number of variables related to consumer perception of the store and purchasing behavior, in assortments composed exclusively of private labels (PLs). Design/methodology/approachThe authors developed an experiment based on an online survey to test the hypotheses formulated. The model’s causal relationships are established using structural equations.FindingsThe image of stores that only offer their own brand is mainly configured by price consciousness and the attitude toward the private label. The private label purchase intention is strongly influenced by the store image and a favorable attitude toward the brand, and loyalty strategies should be aimed at securing a clear perception of providing real value.Practical implicationsFor retailers who only offer their own brands, an assortment with price-competitive PLs is key to the strategy of differentiating them from other retailers. It is reasonable to assume that, if retailers have a favorable image, customers transfer this brand value to their PLs and trust them. Customer loyalty strategies of these retailers should be aimed at ensuring that consumers clearly perceive that their assortment provides real value and that, although it is limited in terms of number of brands, it can meet all their needs.Originality/valueThis research represents a significant contribution to brand management literature because, includes, together with loyalty to the store, its image and the PL purchase intention as consumer response variables. Another differentiating feature is the methodology used. Estimation of the structural equation model permits the simultaneous estimation of the relationships between the variables.
ASSESSMENT OF 2 LEVEL INTERCONNECT QUALITY IN FLIP CHIP BALL GRID ARRAY (FCBGA) PACKAGE USING LASER ULTRASONIC INSPECTION TECHNIQUE

Flip chip packaging has a higher performance, and I/O density when compared with wire bonded packaging. However, wire bonding is extensively used in the electronic packaging industry. One of the difficulties with flip chip technology is testing its reliability. Advancements in Scanning Acoustic Microscopy (SAM) can provide insight into 1st level joint interconnects. However, these traditional solder joint inspection methods have been very unsatisfactory in assessing 2 level interconnects because of the location and physical configuration of these solder joints. Non-destructive methods like SAM and X-Ray have their own limitations in assessment of 2 level interconnects. The Laser Ultrasonic Inspection Technique uses laser pulses to generate bulk ultrasonic waves in the package, and the reflected waves from the 2 level interconnect can give us information about the quality of the joint. A fiber-coupled laser interferometer is used to measure the transient out of plane displacements on the surface of the package. This is a direct measure of the reflected ultrasonic wave strength. Laser power can be adjusted depending on the size of the package to generate bulk waves of sufficient strength to reach the interconnections. In this project, Flip Chip Ball Grid Array (FCBGA) packages (foot print size 52.5mm x 52.5mm) from Cisco Systems were subjected to mechanical shock tests and analyzed using a Laser Ultrasonic Inspection (LUI) system. The results are validated using cross sectioning method. The samples are also tested using X-Ray and CSAM, and the results are compared with those of the LUI system. The LUI system test results have demonstrated that the LUI method holds a great promise for assessing the presence of defects in 2nd level interconnects.
Rural Realities 1-2.indd

http://www.ruralsociology. org Hurricane Katrina will forever be one of the most devastating natural disasters in American history. In addition to the extremely high death toll (it was the third deadliest storm since 1900), Katrina displaced hundreds of thousands of individuals. Current estimates suggest that total damage will exceed $75 billion, making it the costliest hurricane, indeed disaster, in U.S. history.1
ON THE CONSTRUCTION AND PROPERTIES OF BOOTSTRAP- t PREDICTION INTERVALS FOR STATIONARY TIME SERIES

We consider the construction of unconditional bootstrap-t prediction intervals for stationary time series. Our approach relies on t he sieve bootstrap resampling scheme introduced by Bühlmann [8]. Basic theoretical properties concerned with consistency o f the bootstrap approximation as well as consistency of constructed intervals are p roved. We generalize results obtained earlier by Stine [26], Masar otto [21] and Grigoletto [16] for autoregressive time series of finite order to the ric h class of linear and invertible stationary models. Finite sample accuracy of proposed bootstrap-t prediction intervals is verified by computer simulations. Empirical results of a comparative s tudy show that our method is a superior alternative to both traditional Box-Jenkins a pproach and hybrid sievebootstrap prediction intervals proposed recently by Róż ański and Zagdański [24]. 2000 AMS Mathematics Subject Classification:62G09, 62G15, 62M20.
ACMUS-MIR: A new annotated data set of Andean Colombian music

The music from the Andean region of Colombia has many particularities in terms of tempo, meter complexity and sesquialteras, tuning systems, scales, timbre, and texture. These particularities make its analysis with state-of-the-art music information retrieval (MIR) methods both interesting and challenging. To support future research efforts in the context of Andean Colombian music, a new public data set was compiled and annotated by expert musicologists in Colombia. Our collection comprises three subsets: (1) The rhythm set with tempo and meter annotations, (2) the instrumental format set including number and types of instruments for each recording, and (3) the scale set reporting the musical scale of each audio segment. The data set was conceived with the goal of supporting the development of MIR techniques better suited for extraction of semantic information in Andean Colombian music. We hope that our data set will also encourage a wide range of studies in the fields of musicology, ethnomusicology, and music information retrieval.
Assessing the Citation Impact of Book-Based Disciplines: The Role of Google Books, Google Scholar and Scopus

Although peer review is likely to dominate quality assessment of research in the future UK Research Excellence Framework (REF), citation indictors will also be used in some subject areas to support the peer-review process. However, traditional journal-based citation indexes may be inadequate for the citation impact assessment of book-based disciplines. This article examines whether online citations from Google Books and Google Scholar can provide an alternative. We compared the citation counts to books submitted to 2008 Research Assessment Exercise (RAE – the forerunner of the REF) from Google Books and Google Scholar with Scopus citations across seven book-based disciplines (archaeology, law, politics and international studies, philosophy, sociology, history, and communication, cultural and media studies) based upon a sample of 1,000 authored books. Google books and Google Scholar citations to authored books were 1.4 and 3.2 times bigger than Scopus citations and their medians were also more than twice and three times as high as Scopus citations respectively. This large number of citations is evidence that in book-oriented disciplines in the social sciences, arts and humanities, online book citations are needed to support the peer-review process in the UK REF.
Extension Strategies for Poverty Alleviation : Lessons from China , India and Egypt

This paper highlights the transition from a national extension system focus on production-oriented agriculture and food security during the last half of the 20 century toward an emerging focus on supplying urban consumers with higher-value products within an increasingly integrated global economy. Although most developing countries now have food surpluses, many nations have not solved the problem of rural poverty and hunger. It is now being recognized that “hunger is not a food problem, but a money problem. ” Therefore, if national research and extension systems are to address rural poverty, then they must reallocate some programmatic resources from “increasing food production” to “increasing rural incomes and employment. ” This paper draws lessons from China, India and Egypt as these national extension systems have directly or indirectly addressed the problem of improving farm incomes and rural livelihoods. The lessons learned from these experiences suggest that three major institutional and/or programmatic changes are needed to enable extension to effectively alleviate rural poverty. First, both research and extension will need to refocus some of their program resources toward higher-value, labor-intensive crops/products that are specifically designed to increase farm income and rural employment among the rural poor. Second, for small-scale producers to effectively serve urban and/or foreign markets, they must get organized into groups (social capital) to achieve economies of scale and become linked with “supply chains” that serve these markets. Third, to enable extension programs to become more farmer-centered and market-driven, extension planning and management must become more decentralized.
Research Regarding the Colour Naming

The paper presents some of the findings revealed after performing an experiment aimed to verify some aspects regarding colour naming. The experiment was designed to test the idea that focal colours are named better and, also, to test their features: their name consists of a single word and they can be used easily in constructing the name of a shade. The experiment confirmed that the concept of focal colour is true. The extended set of focal colours is composed of yellow, black, red, white, blue, green, azure, orange, violet, brown, pink and grey. The colours green, red, pink, yellow and blue were used rather well in the construction of shade names.
Assessing the Vegetation Condition of Herat Province, Afghanistan Using GIS

Drought is a severe problem in Herat Province, Afghanistan where more than 80% of population relies directly or indirectly on agriculture and livestock sector. Severe drought, exacerbated by climate change, both results to the degradation of vegetation cover in rangelands and the reduction of soil fertility in agricultural lands. Rangelands and rainfed agricultural lands are most susceptible to drought due to limitation of irrigation facilities. The main objective of this study was to assess the vegetation condition of Herat Province in scale of time and space. MODIS-Aqua Normalized Difference Vegetation Index (NDVI) products (MYD13A1) of 2003-2014 were used to analyze spatial and temporal variation of Vegetation Condition Index (VCI) in a GIS domain. The results shown that 2008 was the driest year of the period 2003-2014 followed by 2006 and 2004; But 2009 proceeds to 2005 and 2003 were the greenest years of the period with limited drought conditions. Based on VCI index, 87%, 85%, 82%, 75%, 70% and 47% of rangelands in Herat Province experienced extreme and severe drought in June, July, August, May, April and March of 2008, respectively. Extension of this study in various regions of Afghanistan is recommended for sustainable management of communities’ livelihoods as well as reduction of loss and damages associated with food insecurity and immigration.
MR Image Segmentation of Patients’ Brain Using Disease Specific a Priori Knowledge

Segmentation of high quality brain MR images using a priori knowledge about brain structures enables a more accurate and comprehensive interpretation. Benefits of applying a priori knowledge about the brain structures may also be employed for image segmentation of specific brain and neural patients. Such procedure may be performed to determine the disease stage or monitor its gradual progression over time. However segmenting brain images of patients using general a priori knowledge which corresponds to healthy subjects would result in inaccurate and unreliable interpretation in the regions which are affected by the disease. In this paper, a technique is proposed for extracting a priori knowledge about structural distribution of different brain tissues affected by a specific disease to be applied for accurate segmentation of the patients’ brain images. For this purpose, extracted a priori knowledge is gradually represented as disease specific probability maps throughout an iterative process, and then is utilized in a statistical approach for segmentation of new patients’ images. Experiments conducted on a large set of images acquired from patients with a similar neurodegenerative disease implied success of the proposed technique for representing meaningful a priori knowledge as disease specific probability maps. Promising results obtained also indicated an accurate segmentation of brain MR images of the new patients using the represented a priori knowledge, into three tissue classes of gray matter, white matter, and cerebrospinal fluid. This enables an accurate estimation of tissues’ thickness and volumes and can be counted as a substantial forward step for more reliable monitoring and interpretation of progression in specific brain and neural diseases.
Evaluarea utilizabilităţii şi eficacităţii pedagogice a unui

REZUMAT Deşi există numeroase metode de evaluare a sistemelor interactive de e-learning, puţine dintre acestea au fost adaptate pentru evaluarea eficacităţii pedagogice şi a utilizabilităţii sistemelor de realitate îmbogăţită – AR (Augmented Reality). In cadrul acestei lucrări se prezintă şi se analizează rezultatele obţinute în evaluarea unui scenariu de învăţare pentru Biologie, dezvoltat în cadrul proiectului european ARiSE (Augmented Reality for School Environments) şi testat cu utilizatori în cadrul şcolii de vară ARiSE care a avut loc la Bucureşti, în 2007.
GLUE-CLEAVE: KERFLESS WAFERING FOR SILICON WAFERS WITH METAL ON GLUEING AND REMOVABLE INTERFACE

In literature different methods can be found to cleave silicon wafers or chips from the silicon block. These techniques are interesting for cost effective PV production, since they are kerf-less and material consumption for one wafer is at a minimum. In this paper a new method is proposed, which is based on mechanical loads in a layer system of silicon, glueing material, and a re-usable metal stripe. In its final stage, this method does not need to heat up and cool down the whole silicon crystal for each spalling cycle and thus may be considerably more time and energy efficient than previous thermal spalling methods. First experiments were successfully performed to thermally cleave (10x10) mm2 silicon chips. By using analytical and numerical models, more insight in the fracture mechanical process was given and important material and geometry parameters were identified in order to optimize the process.
Using iRODS to Preserve and Publish a Dataverse Archive

We developed a method for transferring the contents of an archive running Dataverse, a publishing program for scientific data, into iRODS [5]. This method respects the encapsulation of the Dataverse archive by exporting its contents through documented methods using the OAI-PMH and HTTP protocols. Since the metadata exported from Dataverse conforms to documented standards (including the OAI-PMH and at least one other metadata specification), we were able to use an XSL transformation to reformat it into a document whose contents can be deserialized into the iRODS metadata catalog. As a result, iRODS users can use iRODS metadata to do keyword searches on the serialized copy of the Dataverse archive. Furthermore, this method lets administrators use iRODS to apply data preservation policies, including storage resource redundancy, to the contents of a Dataverse archive. Index Keyword Terms—OAI-PMH, DDI, data archive, digital library, descriptive metadata, preservation, web publishing, migration, interoperability, XML, XSL transformation, serializa– tion, HTTP, search.
IntML: Natural Compression for Distributed Deep Learning

Distributed machine learning has become common practice, given the increasing model complexity and the sheer size of real-world datasets. While GPUs have massively increased compute power, networks have not improved at the same pace. As a result, in large deployments with several parallel workers, distributed ML training is increasingly network bounded [9]. Parallelization techniques like mini-batch Stochastic Gradient Descent (SGD) alternate computation phases with model update exchanges among workers. In the widely-used synchronous setting, at the end of every SGD iteration, every node communicates hundreds of MBs of gradient values. This means that network performance often has a substantial impact on overall training time. To prevent the network from becoming a bottleneck, several prior works [10, 1, 13, 12, 6, 3] have proposed lossy compression methods that reduce the communication data volume. These methods include sparsification methods that communicate only a fraction of the original gradients, and quantization methods that use fewer bits to represent the gradients. The main challenge underlying the design of compression methods is that the more compression is applied, the more information is lost, and the more will the compressed gradients differ from the original gradients, increasing its statistical variance. Higher variance implies slower convergence [1, 8], i.e., more communication rounds. So, compression offers a trade-off between the communication cost per iteration and the number of communication rounds. In this work, we introduce a new, remarkably simple yet theoretically and practically effective compression technique, which we call natural compression (Cnat). Our technique is applied individually to all gradient values and works by randomized rounding to the nearest (negative or positive) power of two. Cnat is “natural” since the nearest power of two of a real value expressed as a float is computationally inexpensive and can be obtained by ignoring the mantissa. Thus, our scheme communicates just the exponents and signs of the original floats. Importantly, natural compression enjoys a provably small variance. The interested reader can find a complete theoretical analysis in our technical report [5]. 1 2 2.5 4 3 4 1 4
Return and Volatility in Tehran Stock Exchange

The aim of this paper is considering the relationship between return and volatility in Tehran Stock Exchange. We have used the daily data of price index of TSE during 2009-2010. The data are available on website of TSE. We have estimated ARMA (1, 1)-GARCH (1, 1) model for estimation volatility of Tehran stock exchange. Results indicate that there is a negative relationship between volatility and rate of return in TSE. The correlation coefficient between volatility and return is -0.00182. The hypothesis of “return does not Granger Cause volatility” has rejected. Also, the hypothesis of volatility does not Granger because return has not rejected. [Seyed Hossein Miri. Return and Volatility in Tehran Stock Exchange. Life Sci J 2013;10(1):1255-1259] (ISSN:1097-8135). http://www.lifesciencesite. com. 191
Impact of Banking Sector Reforms On Stock Market Performance in Nigeria (2004-2018)

Central Bank of Nigeria (CBN) has over time structured out different kinds of banking sector reforms to boost commercial banks and its allies in the sector to adequately perform essentially their intermediation function. Therefore, this study critically examined banking sector reforms impact on stock market performance in Nigeria considered from 2004-2018; with particular interest to proxy banking sector reforms: as broad money supply, domestic credit to the private sector and interest rate spread. The variables employed in the study where tested using an ADF, Johansen co-integration and model stability test, while the error correction mechanism (ECM) was used to estimate the individual parameters and to validate the hypothesis outlined in the study. The empirical results of the study found a collective insignificant impact of banking sector reforms on stock market performance for the period under study. The study further reveals that, broad money supply as a reform proxy has a linear relationship with stock market performance. The study strongly recommends the need for Central Bank of Nigeria (CBN) and other monetary authorities to periodically review and sustain existing banking sector reforms in consonance with current challenges in the banking sector so as to boost performance in the Nigerian stock market.
Differential diagnosis, three-dimensional imaging aspects and interceptive orthodontic management of molar–incisor malformation

Introduction: Molar–incisor malformation is a condition described in 2014, with few reports in the literature and characterized by atypical root formation in incisors and first permanent molars. Case Report: We report a case of an 8-year-old patient with central incisors and upper and lower first permanent molars with short roots and open apexes, situation not compatible with the chronological age. The patient was evaluated clinically, radiographically, and by blood tests. Anatomopathological analyses of a primary tooth were performed. Computed tomography (CT) was used to evaluate root development of first permanent molars and incisors and compare, by superimposition, the radicular aspect of affected with unaffected teeth of a control patient of the same sex and age. Clinically, the patient presented tongue-thrust habit, central incisors with premature contact and abnormal mobility, and enamel hypoplasia at teeth #8 and #24. Imaging exams showed teeth #3, #8, #9, #14, #19, #24, #25, and #30 with short roots and open apexes. One year follow-up CT images evidenced absence of root development of these teeth and thin roots walls, especially at the incisors. Interceptive orthodontic treatment with fixed palatal crib was performed. Conclusion: This report showed the importance of early diagnosis and treatment of molar–incisor malformation patients.