Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors affecting e-commerce adoption among SMEs in Ghana

Electronic commerce (e-commerce) is widening the concept of business from a simple transactional approach to a broader and more complex concept of inter-firm co-operation. Amidst market globalization, growing interpenetration of national economies and the increased interdependence of national economies, e-commerce adoption remains a vital yet complex and elusive phenomenon, with very little known about its determinants. This study identifies the major determining factors in Ghanaian small and medium sized enterprises’ (SMEs) e-commerce adoption, offers practical implications, and indicates the actions required. This research integrates technological, organizational, and environmental determinisms with social constructivism to build a practical framework for understanding e-commerce adoption among SMEs in Ghana. Structural equation modeling was employed for data analysis. The results indicate that government support has the greatest direct impact on intentions to use e-commerce. Managerial support and the influence of enabling and regulatory conditions also play a vital role in stimulating SME e-commerce adoption in Ghana. The results also show that Ghanaian SMEs tend to imitate successful first-movers to avoid the risks that attend e-commerce technology.
Comparing Chemical Composition and Digestibility of Pedicels and Palm Leaves as a Source for Livestock Feeding by in vitro and in situ Techniques

The aim of this study was to determine the chemical composition and in vitro digestibility, and to estimate the in vitro fermentation parameters of palm leaves and pedicels from Ghars palm variety. A rumen in situ technique was also used to examine In vitro Digestible Dry Matter (IDDM), In vitro Digestible Crude Protein (IDCP), and In vitro Digestible Neutral Fiber (IDNF), and rate and extent of gas production. Vetch-oat hay was taken as a reference feed material. The samples were collected in Tolga district (southeast Algeria). The Crude Protein (CP) content of the plant species was low for pedicels and palm leaves (33 and 60 g kg−1 DM, respectively). The highest content of total extractable phenols, tannins and condensed tannins was observed in palm leaves whereas pedicels showed lower concentrations. In vitro digestibility and in situ DM disappearance were slightly different for the examined forages. Analogue trends were observed for the in vitro fermentation kinetics estimated from the gas production curves. Pedicels showed the highest DM effective degradability (ED; assuming a passage rate of 0.03 h-1) whereas palm leaves seemed to be a poorly degradable material with an ED coefficient of 0.39 and 0.14 g g-1DM, respectively. Despite the moderate CP and high fiber content along with in vitro digestibility and in situ DM disappearance found in pedicels, in comparison with vetch oat hay degradation, it indicated that this plant could have a greater nutritional value. Dry matter disappearance after 144 h of incubation was negatively correlated with phenolic compounds and total extractable tannins, suggesting that the in vitro techniques can be appropriate for detecting the presence of anti-nutritional substances in shrubs.
Novel Approaches to Optimise Early Growth in Willow Crops

Willow is a fast growing, high yielding biomass crop that can help reduce reliance on fossil fuels. However, long establishment times to get to profitability and sustainable yield may deter interest in planting the crop. A number of different approaches were investigated to optimise and accelerate early growth. These approaches were water immersion, plastic application, altering stem orientation at planting, altering coppicing timings and applying growth hormone. Glasshouse and field trials were used to test the different approaches. In this work, planting material was soaked for a varying number of days and plastic was applied or not applied in field trials. In the planting orientation approach, stems were planted diagonally or vertically with half of the planting material above the ground level or horizontally below ground level. Additionally, willow crops were coppiced at different times throughout their first growing season and a growth hormone trial was also incorporated in this work. Water soaking, plastic application, coppicing during the growing season or hormone application did not improve early growth or yield. However, early growth and yield were increased by manipulating the planting orientation of willow stems. Planting orientation treatments in which part of the stem was left above the ground increased early growth and yield significantly compared to the control without requiring extra inputs at planting. The beneficial effects of coppicing can be achieved by manipulating the planting procedure so that the first year’s growth is not disregarded.
Validation of real-time systems using a virtual reality simulation tool

Simulation tools have being innovated through the use of virtual reality technology. Virtual reality involves an advanced style of human-computer interfaces which enables the user to enter, be present, interact, and explore the real world. This presence is achieved by three-dimensional graphical representation and control, and non-conventional devices, such as gloves and head-mounted displays. The main objective of this paper is to present the VR-SIM, a virtual reality simulation tool, which is intended to support software engineers in the validation of RTS. The following topics are covered: characteristics and overview of the tool; detailing of the virtual reality component; and examples of use.
Parallel neural network-fuzzy expert system strategy for short-term load forecasting: system implementation and performance evaluation

The online implementation and results from a hybrid short-term electrical load forecaster that is being evaluated by a power utility are documented in this paper. This forecaster employs a new approach involving a parallel neural-fuzzy expert system, whereby Kohonen's self-organizing feature map with unsupervised learning, is used to classify daily load patterns. Post-processing of the neural network outputs is performed with a fuzzy expert system which successfully corrects the load deviations caused by the effects of weather and holiday activity. Being highly automated, little human interference is required during the process of load forecasting. A comparison made between this model and a regression-based model currently being used in the control centre has shown a marked improvement in load forecasting results.
How middle managers integrate knowledge within projects

This qualitative study explores the interwoven strategic and tactical processes that middle management uses to integrate knowledge in multidivisional organizations. I add to the management literature by not only examining the new roles of middle managers but also by explaining the dynamics of these middle managers' roles when pursuing projects. In summary, my research contributes to the process literature by focusing on middle management. These findings indicate that middle managers used three processes (analytic, intuitive and pragmatic) to create and integrate dispersed knowledge into organizational knowledge delivered to their clients. Copyright © 2004 John Wiley & Sons, Ltd.
Large magnetic molecules and what we learn from them

ABSTRACT Magnetic molecules are zero-dimensional quantum spin objects. This article is devoted to the general scientific knowledge we obtained through their study. In particular the following concepts will be touched: anisotropy and bistability, translational invariance and sign rules, frustration, localised magnons and flat bands, quantum phase transitions as well as isentrope design.
An analysis on dynamics of pulse propagation networks

We study pulse propagation networks (PPN), in which every action potential is important, rather than average firing rates as in conventional neural networks. As we use pulses of action potential as the information signals propagating in this networks, the PPN are essentially a continuous time model. However, the internal variable of each neuron changes if and only if the neuron has received a pulse. Therefore, the PPN have event discrete dynamics. We adopt a kind of an excitable neuron model called "Z-model" as the fundamental element in the PPN and numerically analyze dynamics of some simple PPN.
802.11 wireless network policy recommendation for usage within unclassified government networks

In September 2002, the Secretary of Defense issued a memorandum prohibiting most uses of wireless technology in government facilities because of the exploitation vulnerabilities. This paper will examine the current risks of allowing wireless 802.11 networks within government space for unclassified usage and will compare those risks to other existing remote access risks such as dial-up and through internet firewalls. The paper will explore risk mitigation techniques to enforce an acceptable level of security, and it will discuss the impacts on the unclassified networks if the risk mitigation techniques fail. The paper will also recommend a wireless security model to deploy 802.11 wireless networks for unclassified government use. Various implementations (including encrypted virtual private network (VPN) tunnels, Wi-Fi protected access (WPA), and next generation 802.11i wireless solutions) will be compared to the proposed security model resulting in a recommended wireless security policy for government (or commercial) use. The paper will conclude that mutually authenticated encrypted VPN tunnels are acceptably secure and recommend networks migrate to next generation 802.11i solutions when available.
Muliilingual corpora for cooperation

MLCC was a corpus, acquisition project funded by the EC Telematics program.The aim was to collect a set of texts representing a substantial improvement in range, quantity and quality of corpus material available. Two sub-corpora have been defined to help meet the needs for multilingual data consisting of a comparable set of texts in six languages and a parallel set of data in 9 languages. The comparable text collection includes financial newspaper articles from the early '90s. The parallel data is taken from the Official Journal of the European Commission, sub-series Written Questions to Parliament and from the Proceedings of the European Parliament. The data has been converted to an SGML, TEI-conformant mark-up and is distributed by ELRA.
POSITION LEVERAGE SMOOTH HANDOVER ALGORITHM

Mobile IP is designed to support uninterrupted connectivity of mobile computers as they roam from place to place. We propose a fast intra-domain and inter-domain handoff scheme using the location of routers to meet the delay and packet loss requirements of real-time services. The scheme achieves an intelligent and dynamic neighborhood discovery and avoids the use of multicast addresses in intra-domain handoff. In addition, it decreases the registration time and distributes home agent data base dynamically in inter-domain handoff depending on howfar from the home agent mobile host is. Simulation and implementation results for an interactive voice communication are presented.
Documentation for the machine-readable version of the Cordoba Durchmusterung (CD)

The machine-readable version of the catalog, as it is currently being distributed from the Astronomical Data Center, is presented. The complete catalog is contained in the magnetic tape file, and corrections published in all corrigenda were made to the data. The machine version contains 613959 records, but only 613953 stars (six stars were later deleted, but their logical records are retained in the file so that the zone counts are not different from the published catalog).
A combination of genetic algorithm‐based fuzzy C‐means with a convex hull‐based regression for real‐time fuzzy switching regression analysis: application to industrial intelligent data analysis

Processing an increasing volume of data, especially in industrial and manufacturing domains, calls for advanced tools of data analysis. Knowledge discovery is a process of analyzing data from different perspectives and summarizing the results into some useful and transparent findings. To address such challenges, a thorough extension and generalization of well‐known techniques such as regression analysis becomes essential and highly advantageous. In this paper, we extend the concept of regression models so that they can handle hybrid data coming from various sources which quite often exhibit diverse levels of data quality. The major objective of this study is to develop a sound vehicle of a hybrid data analysis, which helps in reducing the computing time, especially in cases of real‐time data processing. We propose an efficient real‐time fuzzy switching regression analysis based on a genetic algorithm‐based fuzzy C‐means associated with a convex hull‐based fuzzy regression approach. The method enables us to deal with situations when one has to deal with heterogeneous data which were derived from various database sources (distributed databases). In the proposed design, we emphasize a pivotal role of the convex hull approach, which is essential to alleviate the limitations of linear programming when being used in modeling of real‐time systems. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Verification of Computer Simulation Models

The problem of validating computer simulation models of industrial systems has received only limited attention in the management science literature. The purpose of this paper is to consider the problem of validating computer models in the light of contemporary thought in the fields of philosophy of science, economic theory, and statistics. In order to achieve this goal we have attempted to gather together and present some of the ideas of scientific philosophers, economists, statisticians, and practitioners in the field of simulation which are relevant to the problem of verifying simulation models. We have paid particular attention to the writings of economists who have been concerned with testing the validity of economic models. Among the questions which we shall consider are included: What does it mean to verify a computer model of an industrial system? Are there any differences between the verification of computer models and the verification of other types of models? If so, what are some of these differences? Also considered are a number of measures and techniques for testing the "goodness of fit" of time series generated by computer models to observed historical series.
Detecting activity from deep brain areas with magnetoencephalographic arrays

Magnetoencephalographic (MEG) sensors detect with millisecond resolution current flow in the brain which is generated by tens of thousands of simultaneously active neurons. Arrays of sensors covering the entire scalp are now used to capture both temporal and topographic features of activity generated in multiple brain areas. The temporal information available with MEG compliments the excellent spatial resolution obtainable with other brain imaging technologies such as PET and fMRI. The majority of recent MEG studies have concentrated on the characterization of activity generated in relatively superficial fissural cortex. These brain areas are crucial for the initial processing of information from the senses and for the generation of movement. However, recent developments in MEG signal analysis now make possible the identification of responses from deep brain areas, such as hippocampus, thalamus and cerebellum. Many of these structures participate in a variety of higher cognitive functions, including learning and memory. The rational for and application of these new methods is demonstrated with whole-scalp MEG data recorded during the performance of a short-term memory task and tasks which interrogates the brain's ability to detect changes in the temporal pattern of stimulus presentation.
Closed loop control of 3D underactuated vehicles via velocity field tracking

A novel strategy to design time invariant motion controllers for underactuated mobile systems is applied to the position and attitude control of an underactuated 3D vehicle. The idea involves defining a velocity vector field such that an ideal, fully actuated system would exponentially achieve the control objective by simply following such field. A steering law for the given underactuated system is then designed such that it is exponentially stabilized parallel to the above mentioned velocity vector field. For the problem addressed, due to the use of polar like coordinates, this method yields a discontinuous control law. Both the design process and the resulting solution give a clear physical interpretation. Important practical requirements for approaching the target on a null curvature path, avoiding cusps in the whole path and moving in only one given forward direction, are easily satisfied within this framework.
On-line Resource Matching forHeterogeneous GridEnvironments

Inthis paper, wefirst present a linear programming basedapproach formodeling andsolving theresource matching problemin gridenvironments with heterogeneous resources. Theresource matching problem described heretakes into account resource sharing, job priorities, dependencies onmultiple resource types, and resource specific policies. Wethen propose awebservice style architecture foron-line matching ofindependent jobs withresources ina gridenvironment anddescribe a prototype implementation. Ourpreliminary performance results indicate thatthelinear programming based approach forresource matching isefficient inspeed and accuracy andcankeep upwithhigh jobarrival rates Dan important criterion foron-line resource matching systems. Also, thewebservice style architecture makesthesystem scalable andextendable. Itcanalsobeintegrated with other existing grid services inastraighiforward manner.
Neural network training using multi-channel data with aggregate labelling

The solution of classification problems using statistical techniques requires appropriately labelled training data. In the case of multi-channel data, however, the labels may only be available in aggregate form rather than as separate labels for each individual-channel. Standard techniques, using a trained model to classify each channel separately, are therefore precluded. We present a method of training neural network classifiers from aggregate labels. This technique allows the network to learn what significant events on individual channels result in the given labels. We apply this training method to two synthetic (but, in the second case, realistic) problems and compare the results with those from a classifier trained on the accurate channel labels, which would usually not be available. On previously unseen test data for the two problems 97.75% and 99.1% of feature vectors were classified correctly by a network trained on aggregate labels. These represent reductions of only 0.5% and 0.1% from classifiers trained on accurate labels for all channels.
Gene Expression Data Analysis Using Automatic Spectral MEQPSO Clustering Algorithm

In the field of Genetics, thousands of gene expression levels are measured simultaneously, using Microarray Technology. In this technology, Gene Clustering approach is used to discover the similarity of biological function within the genes. In this approach, many clustering algorithms are used. In this paper a new algorithm - Spectral MEQPSO for clustering gene datasets is proposed, based on MEQPSO and Automatic clustering algorithms. MEQPSO algorithm is a promising method in gene clustering, which provide an ability of stronger global convergence towards an optimal solution. By using Spectral algorithm, cluster number can be selected automatically during the cluster process, which reduces the overall time taken to cluster the genes.
Evaluation Theory, Models, and Applications

Tables, Figures, and Exhibits. Acknowledgments. About the Authors. Introduction. PART ONE: FUNDAMENTALS OF EVALUATION. 1 Overview of the Evaluation Field. 2 The Nature of Program Evaluation Theory. 3 Standards for Program Evaluations. 4 Personnel Evaluation: The Ghost in Program Evaluations. PART TWO: AN EVALUATION OF EVALUATION APPROACHES AND MODELS. 5 Background for Assessing Evaluation Approaches and Models. 6 Pseudoevaluations. 7 Questions- and Methods-Oriented Evaluation Approaches (Quasi-Evaluation Studies). 8 Improvement- and Accountability-Oriented Evaluation Approaches. 9 Social Agenda and Advocacy Approaches. 10 Eclectic Evaluation Approaches. 11 Best Approaches for Twenty-First-Century Evaluations. PART THREE: EXPLICATION AND APPLICATION OF SELECTED EVALUATION APPROACHES. 12 The Evaluation Case: An Evaluation of an Innovative Housing and Community Development Project. 13 Experimental Design. 14 Case Study Evaluations. 15 Daniel Stufflebeam's CIPP Model For Evaluation: An Improvement/Accountability Approach. 16 Michael Scriven's Consumer-Oriented Approach to Evaluation. 17 Robert Stake's Responsive/Client-Centered Evaluation Approach. 18 Michael Patton's Utilization-Focused Evaluation. PART FOUR: EVALUATION TASKS, PROCEDURES, AND TOOLS AND THE METAEVALUATION IMPERATIVE. 19 Identifying and Assessing Evaluation Opportunities. 20 First Steps in Addressing Evaluation Opportunities. 21 Designing Evaluations. 22 Budgeting Evaluations. 23 Contracting Evaluations. 24 Collecting Evaluative Information. 25 Analyzing and Synthesizing Information 26 Communicating Evaluation Findings. 27 Metaevaluation: Evaluating Evaluations. Glossary. Name Index. Subject Index.
Using Fuzzy Set Theory in an Optimization Setting

Fuzzy set theory has a strong track record of success in the field of Optimization under uncertainty. It offers a proper framework for coming to grips with situations where imprecision and complexities are in the state of affairs in an Optimization setting. This paper presents my personal views on the descriptive and prescriptive power of Fuzzy set Theory in letting informational and intrinsic imprecision be taken into account in an Optimization model. The paper is jam-packed with information on how and why I started doing research in this field, along with encouragements and inspiration I got from Professor L.A. Zadeh and H.J. Zimmermann.
Empirical Drain Current Model of Graphene Field-Effect Transistor for Application as a Circuit Simulation Tool

In this paper, an empirical model of dual gate graphene field-effect transistor (GFET) has been developed. The explicit form of drain current expression has been established analytically based on a drift-diffusion approach. The channel sheet charge density helps us to determine the quantum capacitance more accurately. The channel potential has been derived from the equivalent circuit. The improvement of carrier mobility has been included. The closed form expression is obtained with a few fitting parameters to explore the model characteristics. The model is also valid for single gate technology. The model has been verified against some pioneering experimental results reported in literatures. Model simulation agrees well with existing experimental data. We have also compared the results of the model obtained from NANOHUB online simulator for further verification. The characteristics of small signal parameters of this GFET model have been observed and cut-off frequency has been determined. The developed analytical GFET model is also found to be computationally efficient. It is observed that with ± 10% variation in top gate oxide thickness, maximum drain current and peak transconductance vary by (−11.53%/ + 14%) and (−25%/+31.25%), respectively. The double gate bilayer GFET model is implemented in Verilog-A and verified for a voltage amplifier in SPICE environment.