Miracle-dz/UniFAR-FTUs huggingface dataset:
Comprehensive analysis of different types of feature selection

Following the development of research on machine learning in general, feature selection, as a process utilized in machine learning, has also gained some attention. As a common process in machine learning, it would be normal to be enhanced on, just to increase the overall efficiency of the processing. However, to achieve that, one must gain a deep understanding of the topic itself first. In this paper, we will offer a general and comprehensive review and analysis for feature selection. Stating from three basic methods of feature selections: Wrapper, Filter, and embedded, we introduced how those methods work and analyze them as well. Then, we started introducing the steps necessary to perform feature selection: Generation Procedure, Evaluation Function, Stopping Criterion, and Validation Procedure. Finally, we would review and analyze a few recent developments and important concepts related to feature selection: MIC Formulation, Distance Correlation, Model-Based Ranking, Recursive Feature Elimination, and Laplacian score. Those are the methods that represent the recent development of feature selection. This paper is a useful review and reference for people who just started entering the field of feature selection and machine learning in general. It may help one understand some important concept from the ground in feature selection or machine learning in general.
Carbon-Oriented Expansion Planning of Integrated Electricity-Natural Gas Systems With EV Fast-Charging Stations

Under the pressure of climate change and the energy crisis, electric vehicles (EVs) have experienced a marked growth in many countries recently. However, the environmental benefits of EVs cannot be achieved if the charging power from the electricity grid is still mainly provided by fossil-fueled power plants. How to construct a low-carbon fast-charging system has become an emerging research topic. In this context, a novel carbon-oriented expansion planning model of the integrated electricity and natural gas system (IEGS) with EV fast-charging stations (FCSs) is proposed to determine the optimal alternatives, locations, and sizes for ecofriendly candidate assets, including roof-top photovoltaic (PV) panels and fuel cell (FC) units in each FCS, as well as renewable energy units and carbon capture and storage (CCS) systems in IEGS. To guarantee the carbon reduction performance of the planning scheme, the carbon emission cap of the EV charging system is specified by the planner and optimally allocated among multiple FCSs according to their carbon reduction abilities. Furthermore, the proposed model can not only consider the initial investment and operation costs but also take into account the expected adaptation cost to future scenarios that are generated in line with three uncertainties, namely, the traffic flow levels, conventional load levels, and renewable-based power generation levels. Finally, the proposed expansion planning method is illustrated by conducting numerical experiments in case studies.
A A review of bioactive compounds produced by endophytic fungi associated with medicinal plants

Interest in exploring endophytic fungi has increased in recent years, especially those associated with medicinal plants, reflecting the great potential of these microorganisms for the production of bioactive substances. Medicinal plants shelter a high diversity of endophytes that represent targets for use in biotechnological processes. These fungi synthetize several compounds that can be used in pharmaceutical, agricultural and other industries. Additionally, endophytes produce many bioactive metabolites involved in host-endophyte symbiosis, such as those that increase resistance to stressful conditions, alter physiological properties, and produce phytohormones, toxins, antimicrobial compounds and medicinal substances, immunosuppressants, antitumoral agents, and other biotechnological substances of interest, such as enzymes. In this review, information regarding plant interactions with endophytes is highlighted, contributing to a better understanding of this association, benefits and potential for biotechnological utilization.
Reflective rumination mediates the effects of neuroticism upon the fading affect bias in autobiographical memory

ABSTRACT Across three studies we explored neuroticism in relation to the fading affect bias, which refers to the greater fading of unpleasant compared to pleasant emotions in autobiographical memory. With increasing neuroticism, there was an increase in the frequency of unpleasant event rehearsal, which was then linked to less fading of negative affect. Study 2 showed this effect was specific to reflective rehearsal, with Study 3 clarifying the mediating effect was due to increased frequency of the reflective sub-type of rumination. We offer new insights into the effects of neuroticism on autobiographical memory and suggest that reflective rumination can be linked to retention of negative affect in individuals with high neuroticism, which can be interpreted as indicative of maladaptive emotional processing.
Phytochemical Screening of Rosmarinus officinalis L. as a Potential Anticholinesterase and Antioxidant–Medicinal Plant for Cognitive Decline Disorders

The inhibition of acetylcholinesterase (AChE) by cholinergic agents has been promoted as a potent strategy for treating and managing cognitive decline disorders. A wide range of natural products has long been used as potential sources or formulations of cholinergic inhibitors. Therefore, this study aimed to evaluate different Rosmarinus officinalis L. (R. officinalis) extracts for their AChE inhibitory activity using galanthamine as a standard AChE inhibitor. In this study, the ethyl-acetate extract (at a concentration of 250 µg/mL) exhibited the greatest inhibitory effect against AChE with significant inhibition of 75%, comparable to the inhibitor galanthamine with an inhibition of 88%. Kinetic analysis revealed that the extracts could induce a mixed type of inhibition, as observed in the case of galanthamine, with the highest increased Km and decreased Vmax values in the ethyl acetate extract. The antioxidant potential of the three extracts tested was found to be in the order of ethyl-acetate > ethanol > aqueous, with IC50 values of 272 µg/mL, 387 µg/mL, and 534 µg/mL, respectively. Ethyl-acetate was found to have the highest total phenolic content in all extracts. Further, in silico study showed structural binding characterization of rosmarinic acid and carnosic acid with human AChE enzyme. Rosmarinic acid showed strong binding and formed two hydrogen-bonding interactions with Ser-293 and Arg-296. In light of this, the ethyl-acetate extract of the plant may provide some novel potential pharmacological leads for treating and managing cognitive disorders such as Alzheimer’s.
The Impact of Restricted versus Liberal Early Fluid Volumes on Plasma Sodium, Weight Change, and Short-Term Outcomes in Extremely Preterm Infants

The optimal fluid requirements for extremely preterm infants are not fully known. We examined retrospectively the fluid intakes during the first week of life in two cohorts of extremely preterm infants born at 22–26 weeks of gestation before (n = 63) and after a change from a restrictive to a more liberal (n = 112) fluid volume allowance to improve nutrient provision. The cohorts were similar in gestational age and birth weight, but antenatal steroid exposure was more frequent in the second era. Although fluid management resulted in a cumulative difference in the total fluid intake over the first week of 87 mL/kg (p < 0.001), this was not reflected in a mean weight loss (14 ± 5% at a postnatal age of 4 days in both groups) or mean peak plasma sodium (142 ± 5 and 143 ± 5 mmol/L in the restrictive and liberal groups, respectively). The incidences of hypernatremia (>145 and >150 mmol/L), PDA ligation, bronchopulmonary dysplasia, and IVH were also similar. We conclude that in this cohort of extremely preterm infants a more liberal vs. a restricted fluid allowance during the first week had no clinically important influence on early changes in body weight, sodium homeostasis, or hospital morbidities.
Nutritional Quality of Wholegrain Cereal-Based Products Sold on the Italian Market: Data from the FLIP Study

The consumption of wholegrains (WG) is encouraged worldwide, but the lack of a common legal definition of such products leads to an unclear classification and identification on the grocery store shelf. In Italy, several products are generally sold as WG, but it cannot be determined if they are made entirely with all WG cereal(s) or if they are partially produced with WG ingredients (PWG). The aims of this study were to (a) survey the number of cereal-based food items formulated with WG, PWG, or refined (RG) present on the Italian market; and (b) analyse the nutritional quality, intended as nutrition facts, of WG products in comparison to PWG and RG. Nutritional information and declarations were retrieved from packs of 3040 products belonging to five different categories: breakfast cereals, biscuits, sweet snacks, bread, and bread substitutes. A descriptive analysis of the products and comparison of energy, macronutrients, fibre and salt among RG, PWG and WG products within each category was performed. In all categories, a major portion of the products did not contain WG ingredients. Results showed that the nutritional quality of RG, PWG, and WG products varied in relation to the product category and that WG inclusion cannot be always considered a marker of the overall nutritional quality of foods. Instead, it is necessary to evaluate the global product characteristics, and it is important to pay attention to differences between WG and PWG products that can be perceived by consumers as equivalent.
Feed Mismatch Due to Reflectors Revisited

An expression for the reflection coefficient in a feed resulting from scattering from a neighboring reflector is derived from the reaction theorem. This expression includes the influence of an external interfering source as well. An asymptotic formula for this reflection coefficient is derived, which simplifies for an arbitrary shaped symmetrical reflector. This formula is shown to be accurate to second order. For a paraboloid, this is identical to the one derived originally by Silver (1949) except for an additional 180° phase factor. The results are given for a parent parabola, one loaded with a cone at its vertex and another for a reflector that is shaped to minimize reflection while maintaining efficiency over a 20% bandwidth. The effect of an interfering on- axis source on the mismatch is described through an asymptotic approximation.
Cooperative detection algorithm of idle spectrum in cognitive radio

To improve the detection performance of sensing users for primary users(weak signals) in the cognitive radio,the optimal cooperative soft decision algorithm by many sensing users are adopted.In this paper,the thresholds of each sensing user are independent.Through theoretical analysis and simulation,the detection probability of optimal cooperative detection algorithm is better than both fusion rule and threshold decision fixed when the False Alarm probability of the fusion center is constant.The results also show that cooperative detection algorithm improves the detection performance of primary user as the attendees grow.When each sensing user adopts soft decision method,for the cooperation of two sensing users and sensing users,the performance of optimal cooperative detection algorithm has 0.5 dB improvement respectively.
INVESTIGATING THE IMPACT OF ORGANIZATIONAL FORGETTING ON IMPROVEMENT OF ORGANIZATIONAL PERFORMANCE

Organizational performance is an indicator of an organization's ability to achieve its goals. Nowadays, organizations that can acquire more organizational knowledge will be successful in their performance. Intentional organizational forgetting can help increasing of this knowledge. In this study, impacts of intentional organizational forgetting on organizational learning, capacity of knowledge management and ultimately, organizational performance has been investigated. Present study has been done by researching on staff of various banks (managers, assistant managers and other employees) that were selected randomly, in Kerman City. Results of this research suggest managers to develop their capacity of knowledge management in order to improve their organizational performance. The improvement will be gained when learning process has been done through intentional organizational forgetting.
CHARACTERIZING ANDROID PERMISSIONS AND ANALYZING THEIR PRIVACY-INTRUSION

OF THE THESIS Characterizing Android permissions and analyzing their privacy-intrusion by Kirty Prabhakar Vedula Thesis Director: Prof. Janne Lindqvist Several studies have examined Android apps use of permissions from a security pointof-view. However, privacy has been an increasing concern with the increasing number of apps and most users are still not aware of several privacy-intruding permissions. This research investigates a dataset of permissions for over 610,000 apps existing on the Google Play Store on how they can impact users of smartphones. The objective is to better understand the patterns in permissions from a users perspective. We report findings on thousands of reputed apps using users coarse or exact location. About 70% of such apps were free and the major categories were Entertainment and Games. We observe more than 90% positive correlation between the ratings and such permissions. We also analyze device-intrusion where few apps ask for permissions to let the app run in the background, tweak with hardware and deplete energy using rich-media ads. For example, several apps in News & Magazines category were found to consume energy for downloading even when the device is in sleep mode. More than 20,000 free apps were found to receive packet data anonymously. The thesis concludes with discussion on implications obtained by employing k-modes algorithm to cluster dangerous and safe apps.
EFFECT OF FARMYARD MANURE (FYM) DOSES AND DIFFERENT BIO-FERTILIZERS ON VEGETATIVE GROWTH, SEED YIELD AND ACTIVE CONSTITUENTS OF Plantago ovata FORSK PLANTS

The present investigation was carried out in the Experimental Station and Laboratory of the Vegetable Crops and Ornamental Plants Department, Faculty of Agriculture, Mansoura Univ., Egypt, during the two successive seasons of 2002/03 and 2003/04 to study the effect of farmyard manure (10, 20 and 30 m /fed.) and bio-fertilizers (Microbein, Phosphorein and Rhizobacterein) on Plantago ovata Forsk plants. The results indicated that FYM doses had a positive effect on plant height, number of tillers and spikes, dry weight per plant, seed yield per plant and plot as well as mucilage content and percentage when compared with each other. The best results were of plants which received the medium FYM dose (20 m /fed). The inoculating with Rhizobacterein bio-fertilizer gave the tallest plants, while the inoculating with Microbein gave the highest number of tillers and spikes, dry weight per plant, seed yield per plant and plot as well as mucilage content and percentage. The combined treatment of the medium FYM dose and Rhizobacterein inoculating gave the tallest plants, while the combined treatment of the medium FYM dose and Microbein gave the highest number of tillers and spikes, dry weight per plant, seed yield per plant and plot as well as mucilage content and percentage. Also, the combined treatment of the medium FYM dose and Phosphorein gave the heaviest 1000 seed weight.
Bioconversion of Glycosidic Precursors from Sour Guava (Psidium friedrichsthalianum Nied.) Fruit by the Oral Microbiota into Odor-Active Volatile Compounds

The ability of the human oral microbiota to hydrolyze the glycosidic aroma precursor extract isolated from sour guava (Psidium friedrichsthalianum Nied.) fruits was studied herein. The glycosidic extract (GP) was incubated with a mixture of the oral microbiota isolated from three individuals’ saliva to evaluate the hydrolytic capacity of oral bacteria in the generation of odor-active compounds. The oral microbiota was able to release 1-hexanol from GP, under both aerobic and anaerobic conditions. Additionally, the aroma precursor extracts showed a decrease in the growth of harmful oral bacteria (Streptococcus and Actinomyces). This effect can be considered beneficial to human health because these bacteria have been related to different diseases of the bucco-respiratory tract.
Research on the spatial behavior conflict in suburban village communities based on GPS tracking and cognitive mapping

ABSTRACT Suburban village tourism is supposed to promote happiness. However, as tourists swarm in, suburban village community spaces tend to become spaces of conflict between diverse groups. To balance development and protection, we need to understand such conflict. Spatial behavior conflict is an important index of the conflict between tourists and residents. This paper is a case study of the Shecun community. It obtains data via GPS tracking and cognitive mapping. By employing the spatial behavior conflict model and space syntax, it analyzes the spatial characteristics of the spatial behavior conflict. And lastly, it explores the paths to sustainable development in suburban villages. According to this empirical research, variations do exist in the spatial behavior conflict in Shecun community, whose spaces can be classified into five types based on their conflict intensity; and there is a positive correlation between the community space’s global accessibility and intensity of spatial behavior conflict.
Aplikasi Augmented Reality untuk Pengenalan Pola Gambar Satwa Menggunakan Vuforia

Abstrak Teknologi Augmented Reality merupakan penggabungan antara objek virtual dan objek nyata. Penggabungan tersebut menghasilkan informasi yang lebih banyak dan lebih lengkap. Jika Augmented Reality digunakan, maka informasi tentang satwa pada kebun binatang Gembira Loka Yogyakarta akan lebih cepat dan lebih banyak yang disajikan kepada pengguna aplikasi. Proses pembuatan aplikasi Augmented Reality membutuhkan data dan gambar satwa sebagai marker. Pengguna mengarahkan kamera handphone ke gambar marker dan melakukan proses pemindaian untuk pencocokan pola. Pengumpulan data menggunakan metode wawancara dan riset pustaka. Penelitian ini bertujuan mempermudah pengguna mendapatkan informasi yang lebih cepat dan lebih rinci tentang satwa yang ada pada kebun binatang Gembira Loka Yogyakarta, serta bagi pengelola database lebih rmudah mengelolah data satwa tersebut. Kata Kunci: augmented reality, kebun binatang, gambar satwa, pencocokan pola.
Machinery New Emerge Fault Diagnosis Based on Deep Convolution Variational Autoencoder and Adaptive Label Propagation

In the research field of mechanical equipment fault diagnosis, usually only the existing fault types are identified, and the new emerge class of the fault is ignored, however, the new emerge fault class may also occur actually. In order to solve the problem, a novel fault diagnosis model based on deep convolution variational autoencoder network and adaptive label propagation (DCVAN-ALP) is proposed. Firstly, the initial high dimensional features are constructed by using the double tree complex wavelet packet method as the input of the model. Secondly, the convolutional neural network architecture is applied to construct the variational autoencoder, and the local and non-local characteristics of samples are embedded into the loss function for training, which is considered to improve the identification of hidden layer features of the neural network. Finally, t-SNE and the improved label propagation algorithm are adopted to process the hidden features of the neural network, which can achieve the purpose of diagnosing the existing fault class and especially new emerge fault class. Experimental results show that the proposed model can effectively extract the fault characteristics of the vibration signal, and it also has a significantly higher recognition accuracy rate than other typical deep learning methods and traditional classifiers in diagnosing new emerge fault class.
Towards a Better Understanding of Machine Learning based Network Intrusion Detection Systems in Industrial Networks

: It is crucial in an industrial network to understand how and why a intrusion detection system detects, classiﬁes, and reports intrusions. With the ongoing introduction of machine learning into the research area of intrusion detection, this understanding gets even more important since the used systems often appear as a black-box for the user and are no longer understandable in an intuitive and comprehensible way. We propose a novel approach to understand the internal characteristics of a machine learning based network intrusion detection system. This approach includes methods to understand which data sources the system uses, to evaluate whether the system uses linear or non-linear classiﬁcation approaches, and to ﬁnd out which underlying machine learning model is implemented in the system. Our evaluation on two publicly available industrial datasets shows that the detection of the data source and the differentiation between linear and non-linear models is possible with our approach. In addition, the identiﬁcation of the underlying machine learning model can be accomplished with statistical signiﬁcance for non-linear models. The information made accessible by our approach helps to develop a deeper understanding of the functioning of a network intrusion detection system, and contributes towards developing transparent machine learning based intrusion detection approaches.
Determination of Optimal Location, Sizing and Power Factor of Grid-Connected Solar PV Plant

The increasing number of grid-connected solar PV plants today has brought great benefits to the power system. However, it has also created several technical issues that need to be addressed by planning engineers. Due to this reason, the optimization for interconnection of solar PV plants has attracted their attentions, in order to operate these plants safely and economically. In this paper, three key parameters which are the location, size and operating power factor of the solar PV plant are optimized. The proposed method considers the technical constraints of the network such as voltage limits, together with the intermittency of PV generation and system loads. Two case studies are simulated on a typical 11kV distribution system with 54 buses. Results show a reduction in system energy losses for the optimized values, without violating any power system requirements.