nils-herrmann/clean_scirepeval huggingface dataset:
Analysis of Electronic Banking Services Its Issues in Pakistan

Technology is making a tremendous impact upon financial services sector is no exception. Today, banks take special attention to customers' perspective by providing quality of services. Loyalty is a very important issue for customers and for the sake of organizational benefits, the banks need to obtain customer satisfaction due to competitive market. In the areas of services the concept of service quality plays a central role in understanding customer satisfaction and retention. To improve the efficiency and enhance pace of working information technology is playing a fundamental role in any business. This becoming a critical success factor to gain competitive edge than competitors. Electronic banking includes phone or mobile banking, Internet or online banking and email banking and ATM. banking Sector or industry, bringing up new product called online banking or e banking. Customer needs and requirements are changing day by day. Customer wants instant response, access, convenience and security. There are several issues in electronic banking which customer face; including Non availability of sufficient cash in ATM in particular occasion and time, Link down, customer account debited but receiver's account is not debited, pin generation process and card blocking process and any cash transaction related problems. The Banks now use different mobile applications app, MAC ID system and code generation to double verify the PIN and customer verification tactics in online banking to secure the customers transactions. The technology brings easiness, reliability and competence. The rate of success of these new products will depend on the suitability of the technology selected for the customers in banks. A well defined security system and audit plan will ensure the long term success of IT plans of banks. Security is the most critical factor for banks now a days.  Customer perspective, Service quality, Electronic banking, ATM, MAC ID, Information technology.
Social engineering attack examples, templates and scenarios
Venue: Comput. Secur.

The field of information security is a fast growing discipline. Even though the effectiveness of security measures to protect sensitive information is increasing, people remain susceptible to manipulation and thus the human element remains a weak link. A social engineering attack targets this weakness by using various manipulation techniques to elicit sensitive information. The field of social engineering is still in its early stages with regard to formal definitions, attack frameworks and templates of attacks. This paper proposes detailed social engineering attack templates that are derived from real world social engineering examples. Current documented examples of social engineering attacks do not include all the attack steps and phases. The proposed social engineering attack templates attempt to alleviate the problem of limited documented literature on social engineering attacks by mapping the real world examples to the social engineering attack framework. Mapping several similar real world examples to the social engineering attack framework allows one to establish a detailed flow of the attack whilst abstracting subjects and objects. This mapping is then utilised to propose the generalised social engineering attack templates that are representative of real world examples, whilst still being general enough to encompass several different real world examples. The proposed social engineering attack templates cover all three types of communication, namely bidirectional communication, unidirectional communication and indirect communication. In order to perform comparative studies of different social engineering models, processes and frameworks, it is necessary to have a formalised set of social engineering attack scenarios that are fully detailed in every phase and step of the process. The social engineering attack templates are converted to social engineering attack scenarios by populating the template with both subjects and objects from real world examples whilst still maintaining the detailed flow of the attack as provided in the template. Furthermore, this paper illustrates how the social engineering attack scenarios are applied to verify a social engineering attack detection model. These templates and scenarios can be used by other researchers to either expand on, use for comparative measures, create additional examples or evaluate models for completeness. Additionally, the proposed social engineering attack templates can also be used to develop social engineering awareness material.
Exploring Boosted Neural Nets for Rubik s Cube Solving

We explore whether neural nets can learn good actions in the Rubik's Cube setting when given minimal domain knowledge. In doing so, we experiment with integrating neural nets with AdaBoost to dynamically weight important instances from the data set at training time. Inspired by FilterBoost, we develop a variant of AdaBoost that is better suited to problem settings with a sampling oracle, while making fewer calls to that oracle. We then test that variant using neural nets as a weak learner. Experiments demonstrate that neural nets can acheive some success at Rubik's Cube solving with minimal domain knowledge, but our variant of AdaBoost does not work well with the current trend towards larger, deeper neural nets.
Chemical, morphological, and thermogravimetric of Terminalia catappa Linn

The objective of this study is to evaluate the chemical composition, morphology, and the thermogravimetric behavior of the pulp of Terminalia catappa, also known as tropical almond. The analytical results show, based mainly on its lipid content, that this fruit has a considerable energy value. Its fiber content contributes to enhance the functional properties of the fruit. Morphological characteristics show a spongy like structure with dispersion of starch granules and high concentration of fiber bundles, confirming the results of the chemical composition analysis. The thermogravimetric behavior exhibited by this fruit pulp when submitted to progressive temperature increase under dynamic air atmosphere shows that this raw material has great potential for industrial use due to its high absorption rate of water soluble and/or lipid based compounds, allowing its use as a dietary complement or supplement ingredient in food products.
Examining Productive Failure, Productive Success, Unproductive Failure, and Unproductive Success in Learning

Learning and performance are not always commensurable. Conditions that maximize performance in the initial learning may not maximize learning in the longer term. I exploit this incommensurability to theoretically and empirically interrogate four possibilities for design: productive success, productive failure, unproductive success, and unproductive failure. Instead of only looking at extreme comparisons between discovery learning and direct instruction, an analysis of the four design possibilities suggests a vast design space in between the two extremes that may be more productive for learning than the extremes. I show that even though direct instruction can be conceived as a productive success compared to discovery learning, theoretical and empirical analyses suggests that it may well be an unproductive success compared with examples of productive failure and productive success. Implications for theory and the design of instruction are discussed.
Persistent and transient productive inefficiency: a maximum simulated likelihood approach

The productive efficiency of a firm can be seen as composed of two parts, one persistent and one transient. The received empirical literature on the measurement of productive efficiency has paid relatively little attention to the difference between these two components. Ahn and Sickles (Econ Rev 19(4):461 492, 2000) suggested some approaches that pointed in this direction. The possibility was also raised in Greene (Health Econ 13(10):959 980, 2004. doi:10.1002/hec.938) who expressed some pessimism over the possibility of distinguishing the two empirically. Recently, Colombi (A skew normal stochastic frontier model for panel data, 2010) and Kumbhakar and Tsionas ( 2012) in a milestone extension of the stochastic frontier methodology have proposed a tractable model based on panel data that promises to provide separate estimates of the two components of efficiency. The approach developed in the original presentation proved very cumbersome actually to implement in practice. A stochastic frontier model with short run and long run inefficiency random effects, 2011,  2014) Kumbhakar et al. ( 2012) and Kumbhakar and Tsionas (2012) have suggested other strategies, including a four step least squares method. The main point of this paper is that full maximum likelihood estimation of the model is neither complex nor time consuming. The extreme complexity of the log likelihood noted in Colombi (2010) Colombi et al. (2011, 2014) is reduced by using simulation and exploiting the Butler and Moffitt (Econometrica 50:761 764, 1982) formulation. In this paper, we develop a practical full information maximum simulated likelihood estimator for the model. The approach is very effective and strikingly simple to apply, and uses all of the sample distributional information to obtain the estimates. We also implement the panel data counterpart of the Jondrow et al. ( 1982) estimator for technical or cost inefficiency. The technique is applied in a study of the cost efficiency of Swiss railways.
The investigation of environmental Kuznets curve hypothesis in the advanced economies: The role of energy prices

The aim of this research is to examine the effect of energy prices on pollution and investigate the existence of environmental Kuznets curve (EKC) hypothesis in 27 advanced economies. The panel non stationary techniques were used to examine the selected economies taking the period of 1990 2012. The panel Kao and Fisher cointegration results showed that CO2 emission (CO2) gross domestic product (GDP) renewable energy consumption (RE) non renewable energy consumption (NR) trade openness (TD) urbanization (UR) and energy prices (PC) are cointegrated. Moreover, the panel fully modified ordinary least square and the vector error correction Granger causality results revealed that GDP, NR, and UR increase CO2 emission while RE, TD, and PC reduce it. Furthermore, the inverted U shaped relationship between GDP and CO2 emission was confirmed which signifies the presence of the EKC hypothesis. From the obtained results, multiple policy implications were provided for the investigated countries to help them control and reduce air pollution without harming their economic growth and development.
Pollutant Emissions from Starting a Common Rail Diesel Engine Fueled with Different Biodiesel Fuels

AbstractEngine start is a critical process of diesel engine operation with respect to the stability of the combustion process, specific fuel consumption, and pollutant emissions among others. Additionally, the starting is a transient process included into the New European Driving Cycle (NEDC) established for the certification of light duty vehicles. In this work, a turbocharged, direct injection (DI) diesel engine equipped with a common rail injection system and an exhaust gas recirculation (EGR) strategy has been tested during the starting. The engine was tested at two different starting modes: NEDC cold start mode (temperature of cooling water and lube oil were approximately ambient temperature ~20degC) and warm start (the engine was previously warmed up) Regulated pollutant emissions and operating parameters such as engine speed, air and fuel mass flow rates, EGR valve position, etc. were registered during the tests. The engine was fueled with a low sulfur fossil diesel fuel and with three different bi.
The impact of depreciation savings on investment: Evidence from the corporate Alternative Minimum Tax

Over the past decade, the United States has offered investment incentives in the form of larger depreciation savings, namely, bonus depreciation. The neoclassical investment model implies that investment responds to changes in depreciation savings, but there have been few direct attempts to investigate this implication. This paper examines investment patterns surrounding the 1999 shortening of the Alternative Minimum Tax (AMT) depreciation recovery periods, finding strong evidence that firms subject to the AMT increase investment in response to the AMT reform. The empirical results show that firms subject to the AMT increase their investment, measured as the ratio of capital expenditures to capital stock, by around 0.0418 to 0.0622, compared to firms subject to the regular tax. Given their average annual investment rate of approximately 0.27 during this period, the results imply a relative increase in investment of 15% 23% By contrast, I find that the 2002 introduction of bonus depreciation, available both for firms subject to the regular tax and for firms subject to the AMT, affects both groups of firms similarly. The estimation uses an empirical specification developed from the Summers (1981) tax adjusted q model, and the results imply that the responsiveness of investment to the tax term is somewhat larger than previously estimated.
Partial preference models using translated cones in discrete multi objective optimization
Venue: 2016 IEEE Symposium Series on Computational Intelligence (SSCI)

Decision makers tend to define their optimization problems as multi objective optimization problems. Generating the whole nondominated set is often unrealistic due to its size but also because most of these points are irrelevant to the decision maker. Another approach consists in obtaining preference information and integrating it a priori, in order to reduce the size of the nondominated set and have a gain in computation time. In this work we focus on a partial preference relation based on requirement and tolerance thresholds that translate the Pareto dominance cone. After introducing this preference relation, we present adaptations to use it in existing discrete multi objective optimization algorithms. Numerical experiments on multi objective combinatorial optimization problems show the applicabiliy of our approach.
Factor Analysis and Methods of Supplier Selection

We discuss in this paper the decision making in choosing the best alternative from some available options based on possibly a large number of selection criteria. This multi criteria decision problem typically arises in supplier selection in supply chain management. Recently, there has been an increasing interest in the applications of dimensional reduction methods such as factor analysis to such decision processes. They have been widely applied in conjunction with some classical methods such as AHP to create a hierarchical structure and identify the underlying factors or constructs. There are, however, a number of inherent issues and difficulties which have not been adequately addressed in the literature. For instance, there may be some criteria which load significantly on more than one factor, creating considerable difficulties in categorizing the criteria into mutually exclusive groups. More importantly, it is seen in this paper that it is not always sensible to determine the importance of an identified factor according to its amount of shared common variance or explained variation. Similarly, attempts to routinely determine the local relative weight (within a factor) of importance of a criterion based on its factor loading or correlation with the factor may also lead to results markedly different from those based on the views or judgement of the practitioner or expert. To circumvent these difficulties, a simple, practical and easily implemented procedure is proposed. Although factor analysis is employed, it merely serves as a means of facilitating the direct rating of importance of each criterion, alleviating many of the difficulties of the classical factor analysis approach. Two examples are given to illustrate the proposed method and illustrate some potential problems of current approaches in the literature.
Workloads in the clouds

Despite the fast evolution of cloud computing, up to now the characterization of cloud workloads has received little attention. Nevertheless, a deep understanding of their properties and behavior is essential for an effective deployment of cloud technologies and for achieving the desired service levels. While the general principles applied to parallel and distributed systems are still valid, several peculiarities require the attention of both researchers and practitioners. The aim of this chapter is to highlight the most relevant characteristics of cloud workloads as well as identify and discuss the main issues related to their deployment and the gaps that need to be filled.
Enabling Enterprise Class Workloads in the Cloud
Venue: 2016 IEEE International Conference on Cloud Engineering (IC2E)

Enterprise level workloads such as SAP and Oracle workloads require infrastructure with high availability, clustering, or physical server appliances, features which are often not a part of a cloud offering. As a result, businesses are forced to run enterprise workloads in their legacy environments, and cannot take advantage of the cloud's flexibility, elasticity, and low cost. IBM Cloud Managed Services (CMS) cloud implements shared storage, clustering support, and private networks. These features effectively enable a large number of SAP and Oracle workloads to run in both virtualized and non virtualized cloud environments. In this paper, we discuss a diverse set of enterprise applications implemented in the IBM CMS cloud.
An Innovative Approach to Investigate Various Software Testing Techniques and Strategies

Software testing is a way of finding errors from the system. It helps us to identify and debug mistakes, errors, faults and failures of a system. There are many techniques and strategies emerged since the concept of software development emerged. The aim of testing is to make the quality of software as efficient as possible.in this paper we discuss most widely used techniques and strategies. Where they can be used and how they can be used. How they work and how they differ (from each other).They are the following.  Unit Testing, System Testing, And Acceptance Testing.
A Probabilistic Analysis of the Efficiency of Automated Software Testing
Venue: IEEE Transactions on Software Engineering

We study the relative efficiencies of the random and systematic approaches to automated software testing. Using a simple but realistic set of assumptions, we propose a general model for software testing and define sampling strategies for random (R) and systematic (S0) testing, where each sampling is associated with a sampling cost: 1 and c units of time, respectively. The two most important goals of software testing are: (i) achieving in minimal time a given degree of confidence x in a program's correctness and (ii) discovering a maximal number of errors within a given time bound n. For both (i) and (ii) we show that there exists a bound on c beyond which R performs better than S0 on the average. Moreover for (i) this bound depends asymptotically only on x. We also show that the efficiency of R can be fitted to the exponential curve. Using these results we design a hybrid strategy H that starts with R and switches to S0 when S0 is expected to discover more errors per unit time. In our experiments we find that H performs similarly or better than the most efficient of both and that S0 may need to be significantly faster than our bounds suggest to retain efficiency over R.
Tartaric acid induced conversion of protopanaxadiol to ginsenosides Rg3 and Rg5 and their in situ recoveries by integrated expanded bed adsorption chromatography.
Venue: Journal of separation science

Panax ginseng has been applied in traditional Chinese medicine for over 2000 years. It is still one of the most popular herbs in recent decades. The prescribed ginseng containing medicines consist of protopanaxadiol and protopanaxatriol ginsenosides, which are the major constituents of the herb. Minor ginsenosides at low levels in the herb, such as Rg3 and Rg5 have attracted more rising attention than the major ones. The existing approaches to prepare Rg3 and Rg5 usually rely on either steamed red ginseng as the source or chemical/enzymatic conversion of protopanaxadiol to the targets. It is still highly desirable to effectively achieve such minor components. In this paper, a method integrated extraction of protopanaxadiol and conversion of it to Rg3 and Rg5 has been proposed. Protopanaxadiol was extracted and simultaneously converted to Rg3 and Rg5 by d,l tartaric acid. The targets were absorbed by resins on expanded bed adsorption chromatography and were then separated from other ginsenosides in different stages. Compared with conventional methods, the developed process has advantages in shortening time consumption and improving the conversion ratio of protopanaxadiol, which is promising in directly achieving Rg3 and Rg5 from P. ginseng.
Critical conditions of polymer adsorption and chromatography on non porous substrates.
Venue: Journal of colloid and interface science

We present a novel thermodynamic theory and Monte Carlo simulation model for adsorption of macromolecules to solid surfaces that is applied for calculating the chain partition during separation on chromatographic columns packed with non porous particles. We show that similarly to polymer separation on porous substrates, it is possible to attain three chromatographic modes: size exclusion chromatography at very weak or no adsorption, liquid adsorption chromatography when adsorption effects prevail, and liquid chromatography at critical conditions that occurs at the critical point of adsorption. The main attention is paid to the analysis of the critical conditions, at which the retention is chain length independent. The theoretical results are verified with specially designed experiments on isocratic separation of linear polystyrenes on a column packed with non porous particles at various solvent compositions. Without invoking any adjustable parameters related to the column and particle geometry, we describe quantitatively the observed transition between the size exclusion and adsorption separation regimes upon the variation of solvent composition, with the intermediate mode occurring at a well defined critical point of adsorption. A relationship is established between the experimental solvent composition and the effective adsorption potential used in model simulations.