Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Approach to Mammogram Classification using Spatio-Temporal and Texture Feature Extraction using Dictionary based Sparse Representation Classifier

Cancer is a chronic disease and increasing rapidly worldwide. Breast cancer is one of the most crucial cancer which affects the women health and causes death of the women. In order to predict the breast cancer, mammogram is considered as a promising technique which helps to identify the early stages of cancer. However, several schemes have been developed during last decade to overcome the performance related issues but achieving the desired performance is still challenging task. To overcome this issue, we introduce a novel and robust approach of feature extraction and classification. According to the proposed approach, first of all, we apply pre-processing stage where image binarization is applied using Niblack’s method and later Region of Interest (ROI) extraction and segmentation schemes are applied. In the next phase of work, we developed a mixed strategy of feature extraction where we consider Gray Level Co-occurrence Matrix (GLCM), Histogram of oriented Gradients (HoG) with Principal Component Analysis (PCA) for dimension reduction, Scale-invariant Feature Transform (SIFT), and non-parametric Discrete Wavelet Transform (DWT) features are extracted. Finally, we present K-Singular value decomposition (SVD) based dictionary learning scheme and applied the Sparse representation classifier (SRC) classification approach and performance is evaluated using MATLAB tool. An extensive experimental study is carried out which shows that the proposed approach achieves classification accuracy as 98.13%, Precision as 97.58%, Recall as 98.36%, and F-Score 97.95%. The performance of proposed approach is compared with the state-of-art techniques which shows that the proposed approach gives better performance.
Assessment of the Perdew–Burke–Ernzerhof exchange-correlation functional

In order to discriminate between approximations to the exchange-correlation energy EXC[ρ↑,ρ↓], we employ the criterion of whether the functional is fitted to a certain experimental data set or if it is constructed to satisfy physical constraints. We present extensive test calculations for atoms and molecules, with the nonempirical local spin-density (LSD) and the Perdew–Burke–Ernzerhof (PBE) functional and compare our results with results obtained with more empirical functionals. For the atomization energies of the G2 set, we find that the PBE functional shows systematic errors larger than those of commonly used empirical functionals. The PBE ionization potentials, electron affinities, and bond lengths are of accuracy similar to those obtained from empirical functionals. Furthermore, a recently proposed hybrid scheme using exact exchange together with PBE exchange and correlation is investigated. For all properties studied here, the PBE hybrid gives an accuracy comparable to the frequently used empirical .
The Effect of Performance & Conformance Innovation Towards Product Life Cycle Through Customer Relationship Management

The research on The Effect of Performance Innovation,Conformance Innovation with the mediation of Customer Relationship Management (CRM) toward Product Life Cycle (PLC) on Batik Madura SMEs is intended to analyze the linkage of those research variables. The research population is all Batik Madura SMEsat Madura Island. The sampling technique uses a proportional sampling technique in 4 (four) districts on Madura Island, namely, Sumenep, Pamekasan, Sampang, and Bangkalan District as many as 200 respondents. While the analysis technique uses Partial Least Square. Based on the results of primary data analysis, it was revealed that both performance and conformance innovation significantly affect the product life cycle and also mediate the effect of Customer Relationship Management (CRM) toward the product life cycle. However, customer relationship management does not affect directly the product life cycle. Of course, it is necessary to synergizethose innovationsto extend the product life cycle of Madura Batik.
Effect Of Alum On The Proximate Composition Of Raw African Breadfruit ( Treculla africana )

The proximate composition of breadfruit seed parboiled with various alum concentrations of 0%, 0.4%, 1.2% and 2% were evaluated respectively. Results showed that moisture content increased (18.35%, 18.65%, 20.55%). Crude protein decreased with alum concentration (17.63, 16.18, 15.91 and 15.68). Crude fibre increased steadily (1.55, 2.95, 2.98, 3.40). Ash and crude fat showed no significant difference. Keywords : Breadfruit (Ukwa) parboiling process, Alum, Proximate composition. Journal of Agriculture and Social Research Vol. 7 (1) 2007: pp. 77-81
β-Glucosaminidase Activity as an Index of Nitrogen Mineralization in Soils

Abstract N-Acetyl-β-d-glucosaminidase (NAGase, EC 3.2.1.30) is one of three enzymes that catalyze the hydrolysis of chitin. This hydrolysis is important in carbon (C) and nitrogen (N) cycling in soils because it participates in the processes whereby chitin is converted to amino sugars, which are major sources of mineralizable N in soils. This study investigated the relationship between N mineralization indexes and activity of β-glucosaminidase in soils from six agroecological zones of the North Central region of the United States. Nitrogen mineralization was studied by using short-term laboratory incubations under aerobic and anaerobic conditions and by hydrolysis of soil organic N by steam distillation with chemical reagents. Enzyme activity was assayed at its optimal pH value. The amounts of N mineralized by all the biological and chemical methods studied were significantly correlated with β-glucosaminidase activity, with r values of 0.73*** and 0.76*** for the amounts of released by steam distillation with PO4-B4O7 for 4 or 8 min, respectively; of 0.69*** and 0.74*** for the amounts of released with Na2B4O7 for 4 or 8 min, respectively; of 0.47*** for the amounts of inorganic N produced under aerobic incubation; of 0.80*** for amounts of inorganic N produced by incubation under anaerobic conditions of field-moist soils; and of 0.86*** for anaerobic incubation of air-dried soils. There was a significant correlation between β-glucosaminidase activity and organic C (r = 0.56***), total N (r = 0.60***), and fixed of the soils (r = 0.79***). The amounts of inorganic N released by the methods, with the exception of those under aerobic incubation, were significantly (P < 0.001) correlated with organic C and total N contents of the soils, with r values ranging from 0.65*** to 0.78*** and from 0.62*** to 0.80*** for organic C and total N, respectively.
Reset Moving Horizon Estimation for Quantized Discrete Time Systems

This article addresses reset moving horizon estimation for multiple output discrete-time systems with quantized measurements. A new state reset estimator is designed based on a one-dimensional noisy measurement to overcome underestimation or overestimation of the system state, and an iterative algorithm is proposed to deal with multiple output systems. It is shown that with the proposed reset algorithm, the state estimation error is improved in the presence of over or under estimation, and the boundedness of the estimation error is established. The proposed algorithm also achieves a better estimate than the existing one for systems with a scalar measurement in the static case. A simulation of a moving vehicle is provided to demonstrate the advantage of the developed approach.
Improved Direction-of-Arrival Estimation and its Implementation for Modified Symmetric Sensor Array

In this paper, we propose a modified symmetric sensor array for the estimation of uncorrelated and coherent sources by reconstructing the modified Toeplitz matrices. The rank of these matrices only corresponds to DOAs and the coherency present between the signals cannot affect it. Uniform linear array (ULA) and symmetric ULA do not make the correct estimation of DOAs near the array endfires. The proposed algorithm deciphers this problem by exploiting two extra sensors placed at both the ends of the modified symmetric ULA. Although the new method is computationally simple since it does not use the process of peak searching and does not depend on the coherency between the signals. The efficacy of the proposed method is exemplified by both computer simulations and practical realization. Firstly, computer simulations are presented for various conditions, and then a practical possible concept is explained. Finally, the new method is implemented using an advanced TMS320C6678 digital signal processor (DSP). Both simulated and practical experiments verify the efficacy of the new method.
Improving the Combination of Satellite Soil Moisture Data Sets by Considering Error Cross Correlation: A Comparison Between Triple Collocation (TC) and Extended Double Instrumental Variable (EIVD) Alternatives

Satellite-derived geophysical variables provide valuable information about the earth’s functioning, but there are errors that limit their direct uses. Linearly combining two or more data sources is a simple and efficient method to reduce the uncertainty between the truth and observations. However, calculating the optimal weight for such a linear combination generally needs a reference “truth” that is rarely available in practical applications. To address this limitation, a triple collocation (TC) technique is often used to estimate data error by using a data triplet without the truth. The TC-based error variances are then applied to calculate the optimal weight calculation with an assumption of independence between errors. However, ignoring the error cross-correlations (ECCs) can lead to inaccurate optimal weight for a linear combination and hence may degrade the performance of calculations using merged products. Recently, an extended double instrumental variable (EIVD) method has been proposed to estimate ECC using only three products like TC. In this study, we examined the performance of an EIVD-based linear combination approach through two applications using synthetic data and actual satellite-derived soil moisture (SM) products. For direct comparison, the TC-based linear combination was also implemented using the same data sets. The verification showed that the EIVD-based products are generally better than the TC-based products and result in statistically significant differences in correlation coefficients. While the results here are based on SM, the proposed method is potentially applicable for reconstruction of other data sets that seldom have suitable references in large-scale regional settings.
Optimization of nanoscale phenomena in AlGaN for improved UV emitters

We have developed AlGaN films deposited by plasma assisted molecular beam epitaxy (PA-MBE) that can possess enhanced internal quantum efficiency (> 30%) due to the presence of nanometer scale compositional inhomogeneities (NCI-AlGaN) within a wider bandgap matrix that inhibit nonradiative recombination through the large defect densities (> 1010cm-2) in these materials. Time- and temperature-dependent studies of the UV photoluminescence from these NCI AlGaN films as a function of growth conditions have been performed with the goal of optimizing the emission efficiency. Measurements of radiative and nonradiative lifetimes in conjunction with modeling indicate that the NCI AlGaN inherently combines inhibition of nonradiative recombination with reduction of radiative lifetime, providing a potentially higher efficiency UV emitter active region.
Data Processing Approaches on SPAD-Based d-TOF LiDAR Systems: A Review

With the rise of advanced driver assistance systems (ADAS), range sensors and their data processing methods are becoming more and more important. Light detection and ranging (LiDAR) sensors are attracting attention due to their unique advantages in terms of radial distance resolution and detection range. However, the study of LiDAR data processing is usually divorced from the LiDAR sensor measurement process itself. This leads to critical measurement information being overlooked. This paper seeks a breakthrough to improve the performance of single-photon-avalanche-diode-based direct time-of-flight LiDAR systems by reviewing the data processing stages and corresponding processing approaches for LiDAR measurements, starting from photon incidence and ending with high-level feature recognition. Firstly, we propose a LiDAR system model based on data generation and transfer. The data forms in such a LiDAR system are mainly classified into timestamps, time-correlated histograms, point cloud data, and high-level properties. Subsequently, data processing methods applied to each of these data forms are analyzed. A number of hardware solutions closely related to data transmission and control are also included in the discussion. The principles, limitations, and challenges of these methods are discussed in detail and the criteria for evaluation of time-correlated histograms in ADAS are proposed. Finally, the research gaps in data processing are summarized, and future directions for research development are presented.
Adoption of the Electronic Document Records Management System within the Public Sector in Namibia: Exploring the Challenges and Opportunities

The concept of records management aided by information and communication technologies (ICTs) has recently been embraced by many institutions across the globe. For example, organisations that have implemented the Electronic Document and Records Management System (EDRMS are deemed to be better equipped to handle both internally and externally generated records. These organisations are said to operate at higher level in terms of efficiency and effectiveness than those that still rely on manual filing. However, despite the well documented benefits that come With the adoption of ICTs for records management, some departments within the public sector in Namibia, such as the Ministry of Home Affairs, Homeland and Security as well as the Office of the Prime Minister are still heavily reliant on manual filing of documents. It is against this background that this study explored factors hindering the adoption of EDRMS in the Office of the Prime Minister (OPM). The study adopted a qualitative research approach to collect, analyse, and interpret data. The data collecting instruments included open-ended questionnaires, face-to-face interviews and observation of the study respondents. Data was analysed using the Atlas.ti tool. The study found that insufficient training of staff on electronic records management, lack of user needs analysis and lack of user involvement before the introduction of the system all contributed to resistance of the EDRMS adoption in the OPM. The study recommends that the OPM must provide adequate training to its employees on electronic records management and on the EDRMS in particular. The OPM should also make provision for the adoption of a change management strategy plan in order to get user buy-in for the new electronic system to be embraced.
Encapsulation and Release of Moxifloxacin Hydrochloride in Chitosan–Dextran Sulphate Microcapsules

Abstract In the present work, multilayer microcapsules of size 350 nm were prepared with layer-by-layer assembly of oppositely charged chitosan and dextran sulphate on silica template. The monodisperse silica particles (310 nm) with fine spherical shape were successfully synthesized by Stober's method. Dissolution of silica particles in HF leads to the formation of hollow capsules. The resulting capsules were found to be able to effectively load moxifloxacin hydrochloride in the interior of the capsules under modest conditions without addition of other reagents, as demonstrated by scanning electron microscopy. Parameters affecting loading and release such as pH and initial concentrations were investigated. Release studies were performed in in-vitro mode with a semi-automatic release protocol, with different pH solutions in water and phosphate buffered saline. The size of silica particles was analysed by dynamic light scattering method. Scanning electron microscopy and energy dispersive X-ray spectroscopy measurements proved the surface morphology and purity of the hollow capsules from the core material. The kinetics of drug release mechanism was studied using Peppas and Higuchi models.
Supervisory Control of Fair Discrete-Event Systems: A Canonical Temporal Logic Foundation

This paper studies the linear-time temporal logic (LTL) control of a class of fair discrete-event systems (DESs). It is motivated by the curious extent in which the use of LTL can be strengthened and differentiated in control theory development. Over a fair DES model, a marker-progressive supervisory control problem is formulated in LTL. The problem formulation admits a more flexible specification of multiple markers to distinguish different DES tasks, and seeks to find a supervisor—a passive control function by convention for specified temporal safety—such that a fair DES under its control is guaranteed to make constant progress to these markers. The problem is studied in terms of DES marker-controllability—a new controllability concept formulation of temporal safety for constant marker progress. This new formulation sheds light on how event fairness in DESs coachieves such marker progress with supervision that exists. It is shown that a solution supervisor may be found by canonical LTL verification. Three examples are provided for illustration.
Kinetic, equilibrium and thermodynamic studies for the sorption of metribuzin from aqueous solution using banana peels, an agro-based biomass

Banana peels were employed for the removal of metribuzin from aqueous solution. Sorption in the batch mode was optimized regarding pH, contact time, sorbent dose, initial pesticide concentrations, and temperature. The sorption data were fitted to pseudo-first-order, pseudo-second-order, intraparticle diffusion, Elovich, and liquid film diffusion model, the pseudo-second-order exhibiting best fit (R2 = 0.9803). Of the four most common sorption isotherm models (Langmuir, Freundlich, Tempkin, and Dubinin–Radushkevich), the data followed the Langmuir isotherm with highest correlation. The maximum adsorption capacity was found to be 167 mg g−1. Gibbs free energy, enthalpy, and entropy showed that the sorption was exothermic and spontaneous.
An Integrated Visual Odometry System for Underwater Vehicles

Underwater navigation is always a challenging problem because of electromagnetic attenuation. The traditional methods involve beacons, inertial sensors, and Doppler velocity log, but they have many shortcomings, such as high cost and lengthy setup time. In order to solve underwater navigation problems at low cost, an integrated visual odometry system has been developed and discussed in this article. In this method, two inertial sensors provide acceleration and attitude of the vehicle, and an underwater sonar is used to provide the distance between the vehicle and the seabed, whilst in the visual odometry section, an optical flow algorithm has been applied for tracking feature points. With the depth provided by the sonar, 3-D position of feature points can be calculated. Linear motion of the vehicle is then predicted through these feature points in dual frames. Finally, nonlinear optimization is used to correct the attitude of the vehicle using visual information. In the proposed algorithm, the vehicle trajectory can be estimated in absolute scale by using a single camera; computational complexity is reduced dramatically compared to other visual odometry methodologies; and this algorithm allows the approach to work in sparse texture conditions. The results from practical experiments demonstrate that the method is effective and it is also a low-cost solution.
The use of intellectual property protection mechanisms by publicly supported firms

ABSTRACT Technology-based firms use intellectual property protection mechanisms (IPPMs) to appropriate the returns to their research investments. The empirical literature has generally focused on the use of IPPMs by private sector firms to appropriate the returns to their privately financed R&D-based technologies. To date, studies have not considered the use of IPPMs by private sector firms whose research is publicly financed. We identify empirically a number of significant covariates with the use of a portfolio of formal IPPMs consisting of patents, copyrights, and trademarks. However, our multivariate empirical analyses show that caution is needed in generalizing about such covariates when discussing any one particular formal IPPM.
Assessment of Water Quality in the Elbe River at Low Water Conditions Based on Factor Analysis

An assessment of water quality measurements during a long-lasting low water period in the Elbe River is presented. Weekly samples were taken from May to December 2003 at a sampling site in the middle part of the Elbe River. For multivariate data analysis, 34 parameters of 46 samplings were considered. As a result of this analysis, 78% of the variance of the data set is explained by five factors. They can be assigned to the following latent variables: season (37.5%) > tributaries (12.7%) > re-suspension (10.4%) > discharge (9.4%) > complexation (8.5%). For the investigated sampling site, two key processes were identified as dominating factors on the water quality during low water conditions. First, seasonal phytoplankton development caused changes in redox conditions with consequences for re-solution of pollutants from sediments. Second, tributaries have a higher impact on the main stream, due to changes in mixing processes. Therefore, in addition to flood investigations, monitoring strategies, and management plans should be developed in order to survey changes in water quality during low water conditions.
Co-production in BDS: The evidence from the Sri Lankan Microfinance Sector

Microfinance Institutions (MFIs), in addition to the provision of microcredit, also provide business development services (BDS) to owner managers in order to develop micro enterprises. BDS are non-financial services such as business training and access to information that help owner managers of microenterprises to develop businesses. In this respect, counsellors and trainers in MFIs co-produce BDS with owner managers. Co-production is the joint efforts of two parties, who together determine the output of their collaboration. The objective of this study therefore is to examine how co-production works in a BDS setting. A multiple case study method was used to carry out the study. Six MFIs were selected as cases and in-depth interviews were held with counsellors, trainers and managers to collect the data. The findings reveal that the expertise of counsellors, trainers and owner managers are the inputs for co-production. The outputs of co-production are twofold: MFI specific outputs and owner manager specific outputs. While MFI specific outputs are identified in better loan repayments rates, enhanced client satisfaction, and increased client retention, the owner manager specific outputs are denoted by better business knowledge, better sales, and profits. MFIs use counselling and training as modalities to co-produce BDS. There are a number of factors that affect the variability in coproduction including the readiness of counsellors and trainers, with a number of BDS provided under each modality. Therein, the findings of this study are beneficial to microfinance practitioners and policy makers. Furthermore, the findings also contribute to the knowledge domain of microfinance.