Miracle-dz/UniFAR-FTUs huggingface dataset:
Fusion of shallow and deep features for classification of high-resolution remote sensing images

Effective spectral and spatial pixel description plays a significant role for the classification of high resolution remote sensing images. Current approaches of pixel-based feature extraction are of two main kinds: one includes the widelyused principal component analysis (PCA) and gray level co-occurrence matrix (GLCM) as the representative of the shallow spectral and shape features, and the other refers to the deep learning-based methods which employ deep neural networks and have made great promotion on classification accuracy. However, the former traditional features are insufficient to depict complex distribution of high resolution images, while the deep features demand plenty of samples to train the network otherwise over fitting easily occurs if only limited samples are involved in the training. In view of the above, we propose a GLCM-based convolution neural network (CNN) approach to extract features and implement classification for high resolution remote sensing images. The employment of GLCM is able to represent the original images and eliminate redundant information and undesired noises. Meanwhile, taking shallow features as the input of deep network will contribute to a better guidance and interpretability. In consideration of the amount of samples, some strategies such as L2 regularization and dropout methods are used to prevent over-fitting. The fine-tuning strategy is also used in our study to reduce training time and further enhance the generalization performance of the network. Experiments with popular data sets such as PaviaU data validate that our proposed method leads to a performance improvement compared to individual involved approaches.
ANN Control Based Variable Speed PMSG-Based Wind Energy Conversion System

Mtech student EEE Department, Koneru Lakshmaiah Education Foundation, Green fields , Vaddeswaram , Guntur, Ap , India koneru Lakshmaiah Education, Foundation, Green Fields, Vaddeswaram, Guntur, Ap, India koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Guntur, Ap ,India koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Guntur, Ap, India *Email: Praveenkumarmtech.b@gmail.com
The Moderating Effect of Enterprise Risk Management on the Relationship between Audit Committee Characteristics and Corporate Performance: A Conceptual Case of Jordan

The moderating effect of Enterprise Risk Management (ERM) on the relationship between Audit Committee (AC) characteristics and corporate performance under Jordanian context remains a challenge that is yet to be resolved. Jordan plays a significant role on Middle East economy, and recently attracted the attention of the investors. Audit committee characteristics have a significant effect on corporate financial and risk decision-making practices in Jordan. The fundamental AC role is to supervise the corporate’s financial reporting practice, review of financial reports, auditing practice, internal accounting controls, and risk management practices. Hence, the risk management committee (RMC) and AC can potentially moderate the relationship between risk management disclosure and firm performance. Several results of the previous literature were found fraternized, unclear, and inconsistent regarding the ERM effect on firm performance or its effect on AC characteristics in general context, while the literature on Jordan context remain very scarce inaccessible. Therefore, this paper, with regards to existing literature, conceptualized that ‘ERM’ moderates the relationship between AC size, number of AC meeting, AC independence, accounting expertise in the AC, Muslim directors in the AC, and corporate performance.
Identification of the evolutionary divergence in DHDPS and DHDPR

i Acknowledgements . ii Abbreviations . iii Table of Figures. v List of Tables . vii Chapter 1 – Introduction . 1 1.1 Overview . 1 1.2 DAP Pathway . 1 1.3 Importance of Lysine . 4 1.3.1 Industrial Production . 4 1.3.2 Importance in Nature . 5 1.4 Applications and Aims . 6 1.4.1 Applications . 6 1.4.2 Aims . 7 Chapter 2 – Methods and Materials. 8 2.1 Materials . 8 2.1.1 Chemicals . 8 2.1.2 Equipment . 8 2.2 Purification . 8 2.2.1 Plasmid Selection . 8 2.2.2 Protein Purification . 8 2.3 Size Exclusion Chromatography . 11 2.3.1 Qualitative Size Exclusion Chromatography . 11 2.3.2 Quantitative Size Exclusion . 11 2.4 SDS-PAGE Gel . 11 2.5 Analytical Ultracentrifugation. 12 2.6 Kinetic Assays of DHDPR . 12 2.7 Small Angle X-ray Scattering . 13 2.8 Differential Scanning Fluorimetry . 13 Chapter 3 – DHDPS . 15 3.1 Background . 15 3.1.1 Quaternary Structure and Mechanism . 15 3.1.2 Key Residues . 17 3.1.3 Dimeric Interfaces . 19 3.1.4 Lysine Inhibition Mechanism . 22 3.1. 5 DHDPS as a Drug Target . 23 3.2 Evolutionary Differences . 24 3.3 SMO DHDPS Sequence Analysis . 25 3.3 Transformation, expression and purification of SMO DHDPS . 27 3.4 Analytical Ultracentrifugation. 27 3.5 Small Angle X-ray Scattering . 29 3.6 X-ray Crystallography . 35 3.7 Differential Scanning Fluorimetry . 36 3.8 Conclusions . 38 3.8. 1 Proposed Evolutionary Pathway . 38 3.8. 2 Summary . 40 Chapter 4 – Algal DHDPR Enzymes . 41 4.1 Background . 41 4.1.1 Quaternary Structure . 41 4.1.2 Mechanism . 42 4.1.3 Domain Dynamics . 43 4.1.4 Nucleotide Binding Loop . 44 4.1. 5 Substrate Binding Loop . 46 4.1. 6 Dimer Interfaces. 48 4.2 Evolutionary Divergence. 50 4.2.1 Quaternary Structural Differences . 50 4.2.2 Nucleotide Utilisation . 50 4.3 Phylogenetic Analysis . 51 4.4 Sequence Alignment . 54 4.5 Enzyme Kinetics . 58 4.6 Quantitative Size Exclusion Chromatography . 64 4.7 Small Angle X-ray scattering . 67 4.8 Summary . 72 Chapter 5 C. reinhardtii DHDPR . 73 5.1 Overview . 73 5.2 Purification and Expression . 73 5.3 Analytical Ultracentrifugation. 74 5.4 Enzyme Kinetics . 75 5.5 Small Angle X-ray Scattering . 77 5.6 Differential Scanning Fluorimetry . 81 5.7 Conclusions . 86 5.7. 1 Proposed DHDPR Evolutionary Lineage . 86 5.7. 2 Summary . 87 Chapter 6 – Conclusions . 88 Chapter 7 – References . 89
Building a Herbal Medicine Ontology Aligned with Symptoms and Diseases Ontologies

The use of traditional medicine is increasing rapidly in many societies due to its efficiency and affordability. The locally available herbs are basically used in the treatment of symptoms and diseases. Herbal Medicines have proved effective in many cases and outperformed the chemical drugs. Subsequently, the need arose to develop an herbal repository containing the taxonomy hierarchy that represents the structured knowledge of herbs and could be integrated in many medical applications that use the herbs in the treatment in an accurate and effective way. Today, Medical ontologies have become the most efficient way for representing declarative knowledge about diseases, symptoms, medications, and diagnosis. Many ontologies have been elaborated in the few past years for some well-known traditional medicine like the Chinese, African and Korean traditional medicine. Few of these existing ontologies tried to relate traditional medicine ontologies with known “modern” medical ontologies. Linking traditional medicine ontologies with medical ontologies can benefit in the treatment process where herbs can be used effectively. In this paper, we are proposing a new ontology to be used for the herbal medicine. We are also introducing an algorithm to align our ontology with the symptoms ontology SYMP and with the diseases ontology DOID. The MeSH ontology is the source of our herbal concepts. Journal of Digital Information Management We are actually using this ontology in an educational expert system that prescribes herbs for the treatment of casual symptoms. In addition, new herbal blends can be suggested, and conflicting herbs effects can be detected through this system. A simple e-health portal has been developed to interact with the expert system. Subject Categories and Descriptors I.2. 1 [Applications and Expert Systems]; Medicine and science: J.3 [Life and Medical Sciences]; Medical information systems General Terms: Ontology, Medical Information Systems, Medical Information Processing
Deep convolutional neural network based antenna selection in multiple-input multiple-output system

Antenna selection of wireless communication system has attracted increasing attention due to the challenge of keeping a balance between communication performance and computational complexity in large-scale Multiple-Input MultipleOutput antenna systems. Recently, deep learning based methods have achieved promising performance for large-scale data processing and analysis in many application fields. This paper is the first attempt to introduce the deep learning technique into the field of Multiple-Input Multiple-Output antenna selection in wireless communications. First, the label of attenuation coefficients channel matrix is generated by minimizing the key performance indicator of training antenna systems. Then, a deep convolutional neural network that explicitly exploits the massive latent cues of attenuation coefficients is learned on the training antenna systems. Finally, we use the adopted deep convolutional neural network to classify the channel matrix labels of test antennas and select the optimal antenna subset. Simulation experimental results demonstrate that our method can achieve better performance than the state-of-the-art baselines for data-driven based wireless antenna selection.
ADAPTIVE POTENTIAL TO CAMOUFLAGE MISMATCH: PLASTIC AND EVOLUTIONARY RESPONSES TO A CLIMATE CHANGE STRESSOR

Understanding whether organisms will be able to adapt to the myriad of human-induced stressors currently endangering their existence is an urgent priority. Multiple species distributed across the northern hemisphere seasonally moult from brown summer coat to white winter coat to maintain camouflage against snowy landscapes. But snow cover duration is decreasing due to climate change resulting in camouflage mismatch. White animals mismatched against dark snowless background suffer higher predation rates and adaptive responses will be critical for species persistence in the altered environments. We took advantage of a historical dataset to test for adaptive responses to climate change in a widespread, colour moulting mammal, the mountain hare (Lepus timidus). We repeated historical (1950s) field studies of moult phenology in Scotland and tested whether
Semi-analytical solution for buckling of SMA thin plates with linearly distributed loads

Buckling analysis of shape memory alloy (SMA) rectangular plates subjected to uniform and linearly distributed in-plane loads is the main objective in the present paper. Brinson\'s model is developed to express the constitutive characteristics of SMA plate. Using the classical plate theory and variational approach, stability equations are derived. In addition to external in-plane mechanical loads, the plate is subjected to the pre-stresses caused by the recovery stresses that are generated during martensitic phase transformation. Ritz method is used for solving the governing stability equations. Finally, the effects of conditions on the edges, thickness, aspect ratio, temperature and pre-strains on the critical buckling loads of SMA plate are investigated in details.
A novel automated approach of multi-modality retinal image registration and fusion

Biomedical image registration and fusion are usually scene dependent, and require intensive computational effort. A novel automated approach of feature-based control point detection and area-based registration and fusion of retinal images has been successfully designed and developed. The new algorithm, which is reliable and time-efficient, has an automatic adaptation from frame to frame with few tunable threshold parameters. The reference and the to-beregistered images are from two different modalities, i.e. angiogram grayscale images and fundus color images. The relative study of retinal images enhances the information on the fundus image by superimposing information contained in the angiogram image. Through the thesis research, two new contributions have been made to the biomedical image registration and fusion area. The first contribution is the automatic control point detection at the global direction change pixels using adaptive exploratory algorithm. Shape similarity criteria are employed to match the control points. The second contribution is the heuristic optimization algorithm that maximizes Mutual-Pixel-Count (MPC) objective function. The initially selected control points are adjusted during the optimization at the sub-pixel level. A global maxima equivalent result is achieved by calculating MPC local maxima with an efficient computation cost. The iteration stops either when MPC reaches the maximum value, or when the maximum allowable loop count is reached. To our knowledge, it is the first time that the MPC concept has been introduced into biomedical image fusion area as the measurement criteria for fusion accuracy. The fusion image is generated based on the current control point coordinates when the iteration stops. The comparative study of the presented automatic registration and fusion scheme
Integrating climate change adaptation into community planning using a participatory process: The case of Saebat Maeul community in Busan, Korea

Climate change is certain, given the sufficient evidence for it. Thus, it needs to be integrated into the process of spatial and community planning to empower communities so they can adapt to it. This study addresses the critical gap in the literature on community planning and climate change adaptations by creating planning methodologies based on the participatory method, and simulating application of the process to the Saebat Maeul community in Busan, Korea. In the Saebat Maeul community, the study area, people have struggled with urban flooding, which is related to the poor sewer system and heat waves. Green infrastructures were used as the main tools to mitigate the negative impacts of climate change. The suggested community plan includes physical and socioeconomic measures, such as new parking structures with green roofs and pervious pavement, drainage facilities that reduce flooding, repairs to homes with cool roofs, and installation of rainwater harvesting facilities to lower the impact of heat waves. If planners have proper knowledge about climate change and if they guide the participatory planning process (thus reflecting local knowledge and suggestions), we concluded that it is possible to consider climate change adaptations within the context of spatial and community planning.
Industrial Employment Trends in Nigeria: Workforce Issues, Impacts and Ideas

The labour market and workforce in Nigeria are experiencing massive pressure changes, both in quantity of entrants but also in the composition of its new entrants. With higher enrolment in engineering and fewer in technical education, disruption in the manpower mix is clearly evident. This paper explores the issues and trends in workforce demographics in Nigeria, with focus on employment trends, workforce trends and the consequences of oversupply of graduates. The changing skills and composition of the informal sector is discussed. The paper wraps up with policy implications for the emerging trends identified. The paper concludes that the present situation of the Nigerian labour market, though dire is marked by certificates for employment and not skills for employment. Consequently, people are overschooled but undereducated. Thus, leaving a dearth of skills and a vacuum that is filled by workers from other countries. A stagnating labour market and formal economy has opened up a lot of young Nigerian graduates to the informal sector changing the composition of the informal sector all over the nation. It is recommended among others that Government should encourage its private sector businesses to develop activities that require graduate level skills and they need to attract new firms with these types of activity.
Motives and Commitment of Entrepreneurs in Hospitality/Tourism Firms in Port Harcourt

This aim of this study is to provide both theoretical and empirical insights on entrepreneurs’ motives and commitments in the hospitality and tourism industry in Nigeria, using simple descriptive statistics and complemented with interviews. The study adopted an exploratory research methodology to explore the phenomena of motives and commitment, using descriptive statistics, particularly mea, and standard deviation to present the extent of occurrences in the study subject. The study is based on a sample of 120 entrepreneurs who are owners of small restaurants in Port Harcourt, Rivers State. The results show that entrepreneurs in the hospitality industry are mostly motivated by family related factors such as family tradition, family situation, family line of business, and family prestige. Societal factors are more prominent in the list than both personal and income, financial considerations. The least considered factor that motivates a business start-up is finance or income. The results also suggest that although, entrepreneurs are highly committed to starting and growing their own businesses and are willing to do anything that will help achieve this objective including significant personal sacrifices, they are however, not willing to compromise their family lives.
THERMODYNAMIC ASSESSMENT OF CHEMICAL AND ELECTROCHEMICAL STABILITY OF IRON SILICIDES

The phase and chemical equilibria in the Fe – Si system at 298 K were considered. The comparison between the available thermodynamic information on the solid solubility of silicon in bcc-iron at low temperatures was performed with and without consideration of the α-phase long distance ordering. The standard Gibbs energy of formation for non-stoichiometric iron silicide was estimated. The possible maximum solid solubility of Si in bcc-Fe at 298 K was estimated. The thermodynamic activities of the components in this saturated solution were calculated. The state diagram of the Fe – Si – O system at 298 K was plotted and the characteristics of their invariant conditions were calculated. The solid solubility of Fe2SiO4 in Fe3O4 and of SiO2 in Fe2O3 at 298 K was estimated. The activity – pH diagrams for the aqueous Fe (II) and Fe (III) species were constructed. The potential – pH diagram of the Fe – Si – H2O system at 298 K, air pressure of 1 bar and activities of ions in solution, equal to 1 mol l was plotted. Basic chemical and electrochemical equilibria in this system were considered. The thermodynamic analysis of chemical and electrochemical stability of the Fe – Si system alloys was performed.
Output characteristics of LCC-S compensation network and its optimal parameters design in IPT system

A main circuit of inductive power transfer system based on LCC-S compensation network is built up. The resonant conditions for realising constant current (CC) output and constant voltage (CV) output with loads independent are revealed. By analysing the leakage inductance equivalent circuit of the LCC-S resonant network, the relation between efficiency with frequency, coupling coefficient and loads are revealed. An optimal parameter tuning for working at the maximal efficiency state in both CC mode and CV mode is designed through changing frequency and adjusting the coupling coefficient. The theoretical analyses are confirmed by simulation results.
L’analyse des récits d’expériences de persévérance scolaire d’élèves du secondaire du nord-ouest d’Haïti

Cet article aborde la lutte contre le decrochage en tentant de cerner les differents facteurs qui contribuent a la perseverance scolaire d’eleves du secondaire dans un contexte socioeconomique defavorise, ou les risques de decrochage sont omnipresents. Il se base sur les recits et observations d’experiences de perseverance scolaire recueillis dans le cadre d’une recherche realisee en Haiti aupres de 12 eleves haitiens vulnerables, mais performants, au secondaire. L’etude, menee selon une approche ethnographique et faisant appel a trois modes de collecte des donnees, privilegie une forme d’analyse des recits permettant de comprendre le role de l’eleve en tant qu’acteur et de mettre au jour des moyens pour soutenir la perseverance et la reussite scolaires. Elle met en relief l’importance du sens de la responsabilite, de la capacite a apprendre et de l’estime de soi comme facteurs de la perseverance et de la reussite scolaires.
Micrometeorological impacts of offshore wind farms as seen in observations and simulations

In Europe, offshore wind farms have a capacity of 16 GW, with 71% installed at the North Sea. These wind farms represent an additional source of turbulence and may influence the stratification of the marine boundary layer. We present aircraft measurements and simulations showing an impact on temperature and humidity at hub height in the order of 0.5 K and 0.5 g kg−1 even 60 km downwind of a wind farm cluster. We extend these simulations to explore a realistic future scenario, suggesting wakes in potential temperature and water vapor propagating more than 100 km downwind. Such impacts of wind farms are only observed in case of a strong stable stratification at rotor height, allowing wind farms to mix warmer air downward.
The Relationship Between Cognitive Distortions, Self-compassion, and Insomnia Severity

The goal of this study was to examine the relationships between cognitive distortions, self-compassion, and insomnia severity. Individuals were assessed using the Inventory of Cognitive Distortions (ICD), Self-Compassion Scale (SCS), and Insomnia Severity Index (ISI). Data were analyzed using a sample of 67 participants, ranging in age from 18 to 74. A simple linear regression analysis was conducted to test the hypothesis that cognitive distortions would be predictive of insomnia severity. The results were not significant. A multiple regression analysis was used to test the hypothesis that the specific cognitive distortions of fortunetelling, labeling, and jumping to conclusions would be predictive of insomnia. The hypothesis was not supported. Lastly, a correlation analysis was used to test the hypothesis that self-compassion would be inversely correlated with insomnia. The results revealed that the correlation coefficient between these variables was not significant. Though research has demonstrated a relationship between negative beliefs about sleep and insomnia, the results of this study indicated that although certain negative sleep beliefs align with specific distortions, cognitive distortions overall and the distortions evaluated were not predictive of insomnia. Additionally, though past research has demonstrated a significant relationship between self-compassion and sleep quality, a direct relationship between insomnia and self-compassion was not found. Based on these results, future research is necessary, with a larger, more diverse sample, to further assess these relationships.