Miracle-dz/UniFAR-FTUs huggingface dataset:
Database Performance Comparisons: An Inspection of Fairness

Special benchmarks and performance comparisons have been published to analyze and stress the outstanding performance of new database technologies. Quite often, the comparisons show that newly upcoming database technologies provide higher performance than traditional relational ones. In this paper, we show that these performance comparisons are not always meaningful and should not encourage one to jump to fast conclusions. We revisit certain statements about comparisons between the Neo4j graph database and relational systems and indicate a couple of possible reasons for coming up with bad performance such as inappropriate or default configurations, and too straightforward implementations. Moreover, we refute some stated issues about the bad performance of relational systems by using a PostgreSQL database for commonly used test scenarios. We conclude with some considerations of fairness.
The effect of modification of autonomic activity on cardiac acetylcholine, tissue glycogen and blood sugar in albino rats and frogs

The effects of a number of autonomic agents and procedures which modify cholinergic and/or adrenergic activity were studied on cardiac acetylcholine, cardiac, skeletal muscle and hepatic glyeogen and blood sugar contents in albino rats and frogs. Tissue glycogen content was found to be higher, blood sugar much lower and cardiac acetylcholine slightly lower in frogs than in rats. Physostigmine treatment increased cardiac acetylcholine content in rats as well as in frogs. Atropine reduced cardiac acetylcholine contents in rats as well as in frogs. Vagotomy and pentolinium reduced cardiac acetylcholine content in rats and frogs, respectively. Modification of adrenergic activity did not affect cardiac acetylcholine content. Physostigmine in higher doses slightly increased ventricular glycogen in rats. Vagotomy reduced ventricular es well as hepatic glycogen in rats. Propranolol produced an increase in ventricular as well as muscle glycogen and decrease in blood sugar in rats but not in frogs. Adrenalectomy and 6-hydroxydopamine produced tissue glycogenolysis in rats. Pentolinium had variable effects in rats and frogs. The results indicate that cardiac acetylcholine content can be modified by altering parasympathetic activity and that adrenergic as well as cholinergic systems both effect tissue glycogen level.
Comprehension, Use Cases and Requirements

Within requirements engineering it is generally accepted that in writing specifications (or indeed any requirements phase document), one attempts to produce an artefact which will be simple to comprehend for the user. That is, whether the document is intended for customers to validate requirements, or engineers to understand what the design must deliver, comprehension is an important goal for the author. Indeed, advice on producing ‘readable’ or ‘understandable’ documents is often included in courses on requirements engineering. However, few researchers, particularly within the software engineering domain, have attempted either to define or to understand the nature of comprehension and it’s implications for guidance on the production of quality requirements. In contrast, this paper examines thoroughly the nature of textual comprehension, drawing heavily from research in discourse process, and suggests some implications for requirements (and other) software documentation. In essence, we find that the guidance on writing requirements, often prevalent within software engineering, may be based upon assumptions which are an oversimplification of the nature of comprehension. Furthermore, that these assumptions may lead to rules which detract from the quality of the requirements document and, thus, the understanding gained by the reader. Finally the paper suggests lessons learned which may be useful in formulating future guidance for the production of requirements documentation.
Profiling lexical bundles in an EAP pre-sessional course: A corpus-based study on textbooks and instructors' materials

i Dedication . ii Acknowledgments . iii Table of contents . v List of figures . ix List of tables . xi Definition of terms . xiii Chapter One: Introduction . 1 Chapter Two: Review of literature . 8 2.1 The scope of formulaic sequences . 8 2.1. 1 Formulaic sequences and generative language . 10 2.1. 2 Formulaic sequences: storage and retrieval . 11 2.2 Lexical bundles . 14 2.2.1 Idiomaticity and fixedness . 15 2.2.2 Identification of bundles . 16 2.2.2.1 Frequency of bundles . 16 2.2.2.2 Distribution of bundles . 17 2.2.2.3 Length of bundles . 18 2.2.2.4 An additional method of bundle identification . 18 2.2.3 Structural and functional classifications of bundles . 20 2.2.3.1 Structure of bundles . 20 2.2.3.2 Functions of bundles . 21 2.3 Lexical bundles and metadiscourse . 26 2.3.1 The issue of definition . 27 2.3.2 The issue of function . 31 2.4 The role of corpora in analysing sequences and bundles . 35 2.4. 1 A brief overview of corpus linguistics . 35 2.4. 2 The issue of the size and representativeness of corpora . 36 2.4. 3 Influence of corpus studies on the intersection between lexis and grammar . 39 2.4. 4 Contributions of corpus studies to the analysis of sequences and bundles . 41 2.4. 5 Methodological approaches to investigating sequences and bundles . 42 2.4. 6 Corpus-based research studying sequences and bundles . 44 2.4. 6.1 Sequences and bundles in academic discourse . 44 2.4. 6.2 Sequences and bundles in EAP . 49 2.4. 6.3 Treatment of sequences and bundles in EAP textbooks . 53
Xqx Based Modeling For General Integer Programming Problems

We present a new way to model general integer programming (IP) problems with inequality and equality constraints using XQX. We begin with the definition of IP problems followed by their practical applications, and then present the existing XQX based models to handle such problems. We then present our XQX model for general IP problems (including binary IP) with equality and inequality constraints, and also show how this model can be applied to problems with just inequality constraints. We then present the local optima based solution procedure for our XQX model. We also present new theorems and their proofs for our XQX model. Next, we present a detailed literature survey on the 0-1 multidimensional knapsack problem (MDKP) and apply our XQX model using our simple heuristic procedure to solve benchmark problems. The 0-1 MDKP is a binary IP problem with inequality constraints and variables with binary values. We apply our XQX model using a heuristics we developed on 0-1 MDKP problems of various sizes and found that our model can handle any problem sizes and can provide reasonable quality results in reasonable time. Finally, we apply our XQX model developed for general integer programming problems on the general multi-dimensional knapsack problems. The general MDKP is a general IP problem with inequality constraints where the variables are positive integers. We apply our XQX model on GMDKP problems of various sizes and find that it can provide reasonable quality results in reasonable time. We also find that it can handle problems of any size and provide feasible and good quality solutions irrespective of the starting solutions. We conclude with a discussion of some issues related with our XQX model.
Linking Algorithm between IoT devices for smart factory environment of SMEs

SMEs and small enterprises are making various attempts to manage SMEs in terms of equipment, safety and energy management as well as production management. However, SMEs do not have the investment capacity and it is not easy to build a smart factory to improve management and productivity of SMEs. In this paper, we propose a smart factory construction algorithm that partially integrates the factory equipment currently operated by SMEs. The proposed algorithm supports collection, storage, management and processing of product information and release information through IoT device during the whole manufacturing process so that SMEs' smart factory environment can be constructed and operated in stages. In addition, the proposed algorithm is characterized in that central server manages authentication information between devices to automate the linkage between IoT devices regardless of the number of IoT devices. As a result of the performance evaluation, the proposed algorithm obtained 13.7% improvement in the factory process and efficiency before building the Smart Factory environment, and 19.8% improvement in the processing time in the factory. Also, the cost of input of manpower into process process was reduced by 37.1%.
Quality Assessment of Surface and Drinking Water of Nakla Paurosova, Sherpur, Bangladesh

Water is one of the most vital elements of ecosystem and human being, but unfortunately nowadays, the pollution of surface and drinking water is an alarming problem. The present work deals with the assessment of physicochemical and bacteriological profile of several pond, jar and tube-well water samples to ensure its suitability for using and drinking. Total 30 samples were randomly selected and collected from Nakla Paurosova of Sherpur district by following the standard procedure. Bacteriological analysis was carried out by following the standard bacteriological methods. Most of the surface water sampling points were polluted by dumping of waste, cattle wash and were not suitable for drinking or other domestic purposes. Among three heavy metals, only Iron was detected in six tube-well water samples, one was also positive to arsenic, rest of the water bodies were negative to all of these metals. In case of most of the water bodies, different physicochemical properties were below standard limit. In pond water, the Total Viable Count (TVC) ranged from 2.7 × 107 cfu/100ml to 4.4 × 1015 cfu/100ml and Total Coliform Count (TCC) were 3.4 × 105 cfu/100ml to 4.8 × 1013 cfu/100ml, where the mean concentration of Heterotrophic Plate Count (HPC) was 2.4 × 105 cfu/100ml and 1.8 × 105 cfu/100ml in jar and tube-well water respectively. On the other hand, the Total Coliform Count of supply water was 33 cfu/100ml and tube-well water was 14 cfu/100ml. Fecal coliform was detected in all of the pond water samples, four jar and three tube-well water too. E. coli was present in all pond water samples, and also detected in 80% supply and 50% tube-well water also. Shigella spp. was found in two pond water and in one supply water, where tube-well water was free from it. Salmonella spp. was also detected in 30% of pond and 20% of supply water, whereas absent in tube-well water. 50% of pond, 40% of supply and 30% of tube-well water were contaminated with Vibrio spp. The total counts of these pathogenic bacteria exceeded the acceptable limit both surface and drinking water and also showed resistance against a broad range of commercially available antibiotics. Survey-based result revealed that, peoples of the study area who were using or drinking these water, were suffering from various water borne diseases. These kinds of water sources pose a major threat to public health. So, public awareness, proper treatment and precise management are needed prior to use and drink of these water.
Wasserstein Generative Adversarial Privacy Networks

A method to filter private data from public data using generative adversarial networks has been introduced in an article "Generative Adversarial Privacy" by Chong Huang et al. in 2018. We attempt to reproduce their results, and build further upon their work by introducing a new variant based on Wasserstein generative adversarial networks. For certain classes of probability distributions, we prove theorems relating the 1-Wasserstein distance to the amount of private data leaked, and provide counterexamples showing that this relation is not trivial.
WPTherml: A Python Package for the Design of Materials for Harnessing Heat

WPTherml is a Python package for the design of materials with tailored optical and thermal properties for the vast number of energy applications where control of absorption and emission of radiation, or conversion of heat to radiation or vice versa, is paramount. The optical properties are treated within classical electrodynamics via the Transfer Matrix Method which rigorously solve Maxwell's equations for layered isotropic media. A flexible multilayer class connects rigorous electrodynamics properties to figures of merit for a variety of thermal applications, and facilitates extensions to other applications for greater reuse potential. WPTherml can be accessed at https://github.com/FoleyLab/wptherml.
A Survey on Controller Placement in SDN

In recent years, Software Defined Networking (SDN) has emerged as a pivotal element not only in data-centers and wide-area networks, but also in next generation networking architectures such as Vehicular ad hoc network and 5G. SDN is characterized by decoupled data and control planes, and logically centralized control plane. The centralized control plane in SDN offers several opportunities as well as challenges. A key design choice of the SDN control plane is placement of the controller(s), which impacts a wide range of network issues ranging from latency to resiliency, from energy efficiency to load balancing, and so on. In this paper, we present a comprehensive survey on the controller placement problem (CPP) in SDN. We introduce the CPP in SDN and highlight its significance. We present the classical CPP formulation along with its supporting system model. We also discuss a wide range of the CPP modeling choices and associated metrics. We classify the CPP literature based on the objectives and methodologies. Apart from the primary use-cases of the CPP in data-center networks and wide area networks, we also examine the recent application of the CPP in several new domains such as mobile/cellular networks, 5G, named data networks, wireless mesh networks and VANETs. We conclude our survey with discussion on open issues and future scope of this topic.
Impact of Hedonic Motivation on Consumer Satisfaction Towards Online Shopping: Evidence from Malaysia

ABSTRACT:This study examines the antecedents that influence consumer satisfaction towards online shopping in Malaysia. We developed a theoretical framework that is informed by the theory of planned behaviour (TPB) and the technology acceptance model (TAM) where customer satisfaction is primarily driven by their attitude and perception, which in turn are driven by risk, utilitarian motivation, as well as hedonic motivation. A survey analysis from 150 respondents in Malaysia revealed that hedonic motivation is the key attribute that drives consumer satisfaction directly as well as through the mediating role of attitude and perception. This implies that online shopping is viewed as an entertaining and fun activity by Malaysian shoppers. This tendency must be fully exploited by online marketers to not only improve the overall online shopping experience but also to employ user-friendly technology. Implications of the study extend to government policies and economic transformation strategies of the country, while from a theoretical perspective, it contributes towards the better understanding of TPB and TAM. Although the research is ideal for developing countries that are exploring technological benefits, it is equally important for developed countries for a wider customer reach.
Risk Assessment: Intercepting VoIP Calls

This paper addresses the problem of intercepting a phone call based on the voice-over-IP (VoIP) protocols. The importance of this problem arises both from the interest that the VoIP service is gaining in the Internet, and from the peculiarities of the VoIP communication systems. In this respect, we show how to adapt a general methodology for risk assessment towards the specific aspects of the VoIP service by means of a concrete case study: protecting the VoIP phone calls from being intercepted.
Interlacing mathematics and art: hands-on non-Euclidean geometry

Elliot Eisner (1933-2014), a pioneer in arts education, suggested that an artistic approach to education could improve its quality and lead to a new vision for teaching and learning. This is true for any subject, including mathematics. Geometry related topics make a perfect setting for a deeper contribution of art to education. One such topic is the study of non-Euclidean geometry. In this paper, we present some results of a professional development course for mathematics teachers where the participants studied non-Euclidean geometry concepts. The participants created ceramic pieces using the Poincaré disk and styrofoam balls covered with fabrics using spherical geometry.
A process partitioning technique for constructing decentralized web service compositions

Web service compositions have been widely applied in different applications. A service composition is usually implemented in either a centralized or decentralized manner. Compared with the centralized service composition, the decentralized composition has no central control component, and components interact with each other directly, thereby achieving better performance. Process partitioning is a technique to divide a process into multiple parts and has been shown that it can be successfully applied to decentralizing process‐driven service compositions. This paper proposes a new process partitioning technique for constructing decentralized service compositions. The proposed technique, which is based on typed digraphs and a graph transformation technique, is used for exploring available process partitioning solutions. For applications, this paper discusses the topology and interaction features about the partitioning solutions and summarizes a ranking method for them. Three experiments are conducted to evaluate the proposed methods in this paper. Experimental results show that the proposed methods can be applied in constructing decentralized service compositions effectively. In addition, the results also show that the decentralized compositions can have lower average response times and higher throughputs than the corresponding centralized compositions in the experiments.
Selection of a location for the development of multimodal logistics center: Application of single-valued neutrosophic MABAC model

A logistics center (LC) is unique technological, spatial, organizational and economic unity that brings together different providers and users of logistics services. By selecting the optimal LC location, transport costs are reduced and business performance, competitiveness and profitability are improved. In order to achieve the overall optimum, it is necessary to perform adequate evaluation and selection of the optimal location for the construction of a LC. In this paper is performed the evaluation of potential locations based on new approach in the field of logistics. Weight coefficients of criteria are determined using objective model integrated in Single-Valued Neutrosophic (SVNN) Multi-Attributive Border Approximation Area Comparison (MABAC) model. In order to determine the stability of the model, the SVNN MABAC model is compared with other representative multi-criteria models. In the final part of the model validation, statistical correlation between the SVNN MABAC model and other proposed approaches (SVNN WASPAS, SVNN VIKOR, SVNN TOPSIS and SVNN CODAS) is performed.
Detecting Anomalies From Big Data System Logs

Nowadays, big data systems (e.g., Hadoop and Spark) are being widely adopted by many domains for offering effective data solutions, such as manufacturing, healthcare, education, and media. A common problem about big data systems is called anomaly, e.g., a status deviated from normal execution, which decreases the performance of computation or kills running programs. It is becoming a necessity to detect anomalies and analyze their causes. An effective and economical approach is to analyze system logs. Big data systems produce numerous unstructured logs that contain buried valuable information. However manually detecting anomalies from system logs is a tedious and daunting task. This dissertation proposes four approaches that can accurately and automatically analyze anomalies from big data system logs without extra monitoring overhead. Moreover, to detect abnormal tasks in Spark logs and analyze root causes, we design a utility to conduct fault injection and collect logs from multiple compute nodes. (1) Our first method is a statistical-based approach that can locate those abnormal tasks and calculate the weights of factors for analyzing the root causes. In the experiment, four potential root causes are considered, i.e., CPU, memory, network, and disk I/O. The experimental results show that the proposed approach is accurate in detecting abnormal tasks as well as finding the root causes. (2) To give a more reasonable probability result and avoid ad-hoc factor weights calculating, we propose a neural network approach to analyze root causes of abnormal tasks. We leverage General Regression Neural Network (GRNN) to identify root causes for abnormal tasks. The likelihood of reported root causes is presented to users according to the weighted factors by GRNN. (3) To further improve anomaly detection by avoiding feature extraction, we propose a novel approach by leveraging Convolutional Neural Networks (CNN). Our proposed model can automatically learn event relationships in system logs and detect anomaly with high accuracy. Our deep neural network consists of logkey2vec embeddings, iii three 1D convolutional layers, a dropout layer, and max pooling. According to our experiment, our CNN-based approach has better accuracy compared to other approaches using Long Short-Term Memory (LSTM) and Multilayer Perceptron (MLP) on detecting anomaly in Hadoop Distributed File System (HDFS) logs. (4) To analyze system logs more accurately, we extend our CNN-based approach with two attention schemes to detect anomalies in system logs. The proposed two attention schemes focus on different features from CNN’s output. We evaluate our approaches with several benchmarks, and the attention-based CNN model shows the best performance among all state-of-the-art methods.
Evaluating Software Metrics for Sorting Software Modules in Order of Defect Count

Sorting software modules in order of defect count can help testers to focus on software modules with more defects. Many approaches have been proposed to accomplish this. In order to compare approaches more fairly, researchers have provided publicly available data sets. In this paper, we provide a new metric selection approach and evaluate the usefulness of software metrics of eleven publicly available data sets, in order to investigate the quality of these data sets and find out the software metrics that are most efficient for sorting modules in order of defect count. Unexpectedly, experimental results show that only one metric can work well over most of these data sets, which implies that more effective metrics should be introduced. We also obtain other findings from these data sets, which can help to introduce new metrics for sorting software modules in order of defect count to some extent.