Miracle-dz/UniFAR-FTUs huggingface dataset:
OBJECT TRACKING IN VIDEO USING CONVOLUTIONAL NEURAL NETWORK: A SURVEY

: Object detection and object tracking is active Research field in computer Science.it is more use in real world application in military, video surveillance and security. This paper presents an in-depth review on advances in convolutional neural network mostly used in object decoction and tracking approach a large form of algorithm usually cited in research literature. learning. the CNN is Achieve best performance tracking system No of recent advance in different aspect are greatly analyzed. In this survey paper, some main problems with accessible are presented. This paper concludes with interesting future and analysis direction
An Immersed Lagrangian-Eulerian Method for Fluid-Structure Interaction

This paper introduces a sharp interface method to simulate fluid-structure interaction (FSI) involving arbitrary rigid bodies immersed in viscous incompressible fluids. This approach, which we refer to as an immersed Lagrangian-Eulerian (ILE) method, integrates aspects of partitioned and immersed FSI formulations by solving separate momentum equations for the fluid and solid domains, as in a partitioned formulation, while also using non-conforming discretizations of the moving fluid and structure, as in an immersed formulation. A Dirichlet-Neumann coupling scheme is used, in which the motion of the immersed solid is driven by fluid traction forces evaluated along the fluid-structure interface, and the motion of fluid along that interface is constrained to match the solid velocity, so as to enforce the no-slip condition. We introduce a penalty approach that weakly imposes the no-slip condition along the fluid-solid interface. In the coupling strategy, a separate discretization of the fluid-structure interface is tethered to the volumetric solid mesh via stiff spring-like penalty forces. Our fluid-structure interaction scheme relies on a recently developed immersed interface method for discrete geometries, which enables the accurate determination of both velocities and stresses along the fluid-structure interface. The effectiveness of this straightforward FSI methodology is extensively tested against benchmark computational and experimental studies in two and three spatial dimensions, including for geometries with non-smooth features. Unlike commonly used partitioned methods, which can suffer from so-called added mass effect instabilities, our methodology avoids subiterations between fluid and solid solvers or complex handling of the fluid pressure, and it retains stability for models involving extremely low, nearly equal, equal, and high solid-fluid density ratios.
Recurrent neural networks use discourse context in human-like garden path alleviation

Garden path sentences highlight the role of preceding linguistic context in parsing. Compare the following sentence (from [2]) with its unambiguous form: ​The horse raced past the barn fell ​vs. ​The horse that was raced past the barn fell​ . Readers experience confusion (known as a garden path effect; GPE) at the verb ​fell in the first sentence, having expected ​raced to be a main verb rather than the verb in a reduced relative clause (RC). The GPE is alleviated when raced ​is in an overt RC, as in the unambiguous second sentence. Recurrent neural network (RNN) language models (LMs) assign lower probability to ​fell in the reduced version compared to the overt version (analogous to a GPE; [3, 6]). Human GPEs can be alleviated by changing the discourse context to accommodate conversational implicatures of the RC [1, 4, 5]. In this work, we simulate [4] and [5] with RNNs, showing that similar discourse factors mitigate RNN GPEs, providing stronger empirical support for RNN use in modeling human behavior.
Identifying Consumer-Welfare Changes when Online Search Platforms Change Their List of Search Results

Online shoppers are guided by search platforms: consumers type a search phrase into the platform’s query box, and the platform chooses how products appear in response. While search platforms may choose responses that help consumers find products more efficiently, they may also have incentives to mislead consumers. For example, search platforms may organize responses to favor their own products over third-party products that better suit consumer needs. This paper uses a search-platform experiment to determine how to measure the effects of search responses on consumer welfare. In my model, the search platform has two different search algorithms, and the algorithm used for each consumer is assigned randomly. I apply the model in a study of users of an online travel agency. The data—from a data-mining competition sponsored by Expedia—contain an experiment that fits my model’s framework: Expedia treated some users with randomly ordered product listings and others with products ranked as Expedia saw best. I measure how consumer welfare changes across the two algorithms. I find that under the random listing, the welfare of the users of the online travel agency is lowered by an average of $8.84 per user relative to Expedia’s own ranking system. I also simulate the welfare harm from a counterfactual search response that removes the top five products from all search results and find the welfare lowered by an average of $20.51 per user. Thus, platforms may create value for consumers by providing useful product orderings, but they can also substantially harm consumers by hiding products.
Relationship between Performance Expectancy and Use of New Media in Scholarly Communication by Academic Staff in Public Universities in Kenya

Scholarly communication is integral to the research process and to the development of knowledge. Traditionally, research has been published in print journals which continue to be the preferred channel, especially in developing countries like Kenya. Lately, the academic publishing industry is grappling with disruption brought about by digital media. Scholarly communication is changing with the growth of new media technologies and these changes are impacting on all members of the academic community and on how they go about creating and maintaining scholarship. The aim of this study was to examine the influence of performance expectancy on the use of new media in scholarly communication by university academic staff in Kenya. The study used the unified theory of acceptance and use of technology (UTAUT) as a theoretical basis to conduct empirical research testing of the influence of performance expectancy on the use of new media technologies in scholarly communication by university lecturers. This was a quantitative survey research. The study population comprised of university lecturers in public universities in Kenya. The target population for the survey was drawn from lecturers from five selected universities which included University of Nairobi, Kenyatta University, Moi University, JKUAT and Egerton University. A self-administered questionnaire was distributed to the lecturers in the five universities for data collection. Findings of the study were analysed using Statistical Programmes for Social Sciences Version 22. A bivariate analysis of the factors associated with use of new media in scholarly communication revealed that performance expectancy had a significant relationship (p 0.000) with acceptance and use of new media technologies in scholarly communication. Further, a logistic regression model showed that performance expectancy (p 0.007) was found to be statistically significant when all other variables were controlled for.
Nutritional Status, Oxidant/Antioxidant and Inflammatory Markers in Scholar Athletes Adolescents

In the last two or three decades, physical activity (PA) has gained increasing recognition as being essential for maintaining good health and improving quality of life for all ages. To evaluate the nutritional status, oxidant/antioxidant, and inflammatory markers, in sports adolescents, a cross sectional study has done in west Algeria. A total of 110 athletes adolescents from special sport classes, aged 11-17 years, were compared to a non athletes group (n=60). Blood pressure, anthropometric and serum parameters were measured. Daily energy intake (DEI) was estimated using 24 hours recall, followed by a 3-days record. Energy expenditure (EE) was evaluated by the International Physical Activity Questionnaire-short form (IPAQ-S). Oxidant/antioxidant and inflammatory markers were determined. An increase in body weight and height (ppppppP P P In spite of inadequate DEI in athletes adolescents, beneficial effect of sport is observed by lowering serum TG concentrations. However, more research in this area is warranted to clarify sport nutrition needs to provide better and healthy nutritional guidance to young athletes.
OVER-EXPRESSION OF AN ISOFORM OF THE DELTA-12 FATTY ACID DESATURASE (FAD2-4) IN TRANSGENIC COTTON PLANTS

Embryogenic cell lines of Gossypium hirsutum L. , variety Coker 312, were transformed with a construct designed to over-express one of its own isoforms of fatty acid desaturase FAD2-4. In cotton, FAD2-4 is part of a multi-gene family and this isoform is expressed mostly throughout plant development, albeit at somewhat lower levels than FAD2-3. FAD2 introduces the second double bond into fatty acids (converting oleic acid to linoleic acid) and so represents a potential control point for polyunsaturated fatty acid content. We predict that up-regulating FAD2 activity in cotton plants will increase the proportion of polyunsaturated fatty acids in membranes and may impact tolerance of plants to cooler temperatures, which may be especially beneficial for early planting. Here we report the generation of transgenic plants and the initial biochemical characterization of these plants. Several independent transgenic cotton plants were produced via Agrobacteriumbased transformation. Out of 11 confirmed primary transgenic plants, four plants were fertile and yielded T1 seeds. T1 seeds were analyzed for total protein and oil content using non-invasive, time-domain (TD) NMR. Transgenic seeds (T1) showed increased protein content compared to wild type (Coker 312). The fatty acid composition of cotton seed oil is about 26% palmitic acid (16:0), 15% oleic acid (18:1) and 55% linoleic acid (18:2), and this seed fatty acid composition was relatively unchanged in transgenics, although a slight increase in 18:2 was noticed in three lines. On the other hand, the fatty acid composition of young leaves from T0 plants showed substantial differences in polyunsaturated fatty acid composition compared to wild type. These transgenic materials will be advanced and used in tests for germination and growth in cool temperatures.
Neural Networks and Decision Trees for Intrusion Detections: Enhancing Detection Accuracy

Many artificial intelligence methods were applied to enhance security in computer networks. These methods seem to be mainly based on neural networks and decision trees. Nevertheless, and according to literature, some of them are still suffering from some weaknesses. This is the reason why we focused in this study on the enhancement of two approaches: Iterative Dichotomiser 3 ID3 and multilayer perceptron (MLP) algorithms. The aim of this study is to use appropriate attributes of the KDD dataset, in order to obtain better detection rates. Simulations were conducted using WEKA and Tanagra tools. The results show that our contributions (ID3 and MLP) are competitive with other solutions in terms of detection accuracy.
COORDINATED ACTIVE POWER CONTROL BETWEEN SHUNT AND SERIES CONVERTERS OF UPQC BY USING BESS

This article presents a novel conception of co-ordinating active power distribution among shunt and series converters of unified power quality conditioner (UPQC) for distributed generation purposes amid PID regulator. Generally, the UPQCs are utilized to alleviate mutually voltage and current power quality troubles. However, these UPQCs are furthermore utilized for distribute active power in accumulation to its power quality enhancement by amalgamate distributed generation (DG) at the DC link of back to back linked converters. But, only the shunt converters are utilized to bear the entire active power from the DG resources and the series converters are utilizing to knob only voltage associated power quality troubles. So, the shunt converter is encumbered profoundly and the series converter is kept at rest in steady state cases. The extra reliance on the shunt converter also decreases the dependability of the whole organism. This projected control approach is utilized to bear active power through mutually series converter and shunt converter flush at the steady state situations. The projected technique advances the exploitation of the converters and also the consistency of the system. The usefulness of the projected control approach is verified by evaluate with the unadventurous control algorithm, where only the shunt converter is utilized to bear active power. Keywords—Distributed Generation; unified power quality control (UPQC); PID Controller
Thermosetting Resins 2018

The curing behaviour of a novel composite matrix formulation based on bisphenol A epoxy resin, an anhydride curing agent, and a tertiary amine accelerator is investigated. The curing kinetics are studied using both isothermal and dynamic differential scanning calorimetry (DSC) experiments. The cure kinetics of the thermoset resin are best described by a modified autocatalytic model, where good agreement between experimental and predicted model results is obtained during the initial stages of the cure reaction.
Progress of studies on traditional chinese medicine based on complex network analysis

Traditional Chinese medicine (TCM) is a distinct medical system that deals with the life–health–disease–environment relationship using holistic, dynamic, and dialectical thinking. However, reductionism has often restricted the conventional studies on TCM, and these studies did not investigate the central concepts of TCM theory about the multiple relationships among life, health, disease, and environment. Complex network analysis describes a wide variety of complex systems in the real world, and it has the potential to bridge the gap between TCM and modern science owing to the holism of TCM theory. This article summarizes the current research involving TCM network analysis and highlights the computational tools and analysis methods involved in this research. Finally, to inspire a new approach, the article discussed the potential problems underlying the application of TCM network analysis.
Fisher Effect and the Relationship between Nominal Interest Rates and Inflation: The Case of Nigeria

This research study carries out empirical investigations of the Fisher effect and the long-run relationship between nominal interest rates and expected inflation in Nigeria making use of annual data covering a period of half of a century. Fisher (1930) postulation is that nominal interest rates should reflect the expected rate inflation rates movements on one-for-one basis. Applying the Nigerian data covering the period between 1961 and 2009, this study uses the 3-month treasury bill rates to proxy for nominal interest rates while the 12-month moving average headline inflation serves as the expected inflation. Apart from the descriptive analyses of the sample data, the econometric approaches which the study employs are the ordinary least square (OLS) regression, the Engle-Granger ADF residual-based cointegration, the Johansen maximal likelihood cointegration and Granger causality test. Testing the data, using the augmented Dickey-Fuller (ADF) unit root test method, it was found out that nominal interest rate and expected inflation were non-stationary in levels but in first differences. This suggests that the OLS regression may be spurious even as the result rejects a full fisher effect in Nigeria. The results of the cointegration tests imply that there is no long-run cointegration relationship between nominal interest rates and inflation in Nigeria. The Granger causality tests report that expected inflation does not Granger cause nominal interest rates in Nigeria, but a one-way directional movement running only from nominal interest rates to inflation. The problem of high inflation identified in the history of Nigeria prompted the recommendation for the adoption inflation targeting policy for the country and other countries in this category while the interest rate should be set in line with the dictates of the economy.
XII , Issue ( 2 ) 2009 EVA Reconsidered for the Greek Capital Market By

The present study examines the explanatory power o f one value based performance measure (Economic Value Added) and thre e other traditional accounting measures (Earnings Per Share, Return On Investment, Return On Equity) in explaining stock market returns in the f ramework of Athens Stock Exchange for the period 1996-2005. Methodology is b a ed on studies performed for the same capital market by Maditinos, Theriou a nd Ševi ć (2005; 2006), Maditinos, Ševi ć and Theriou G (2007), Maditinos, Ševi ć, Chatzoglou and Theriou (2007) and Maditinos, Ševi ć, Theriou and Demetriadis (2007). Results show EPS to provide the greatest value relevance in xplaining stock market returns consistent with that of previous studies. M oreover, the explanatory power of the pair wise combinations of EVA with each trad itional accounting performance measure is also examined. The pair wise combination of EVA with EPS grants for a significant increase of the explan atory power, compared to EPS explanatory power examined alone (from 2.9 to 7.6 p er cent), in explaining stock market returns, consistent again with the previous findings.
Robust and Efficient Integrated Antenna With EBG-DGS Enabled Wide Bandwidth for Wearable Medical Device Applications

A compact wearable symmetrical e-slots antenna operated at 2.4 GHz was proposed for Medical Body Area Network applications. The design was printed onto a highly flexible fabric material. The final design topology was achieved by the integration of symmetrical e-slots antenna with an Electromagnetic Band-Gap (EBG) and Defected Ground Structure (DGS). The use of EBG was to isolate the body and antenna from each other whereas the DGS widened the bandwidth. This combination forms a novel and compact structure that broadens bandwidth. This broadened bandwidth makes the structure robust to deformation and loading in the human body. The design achieved a measured impedance bandwidth of 32.08 %, a gain of 6.45 dBi, a Front to Back Ration (FBR) of 15.8 dB, an efficiency of 72.3% and a SAR reduction of more than 90%. Hence, the integration of symmetrical e-slots antenna with EBG and etched DGS is a promising candidate for body-worn devices.
Analysis the Performance of Chemical and Physical Additives to Reduce Shrinkage of Drinking Water Treatment Sludge (DWTS)

Water is one of the basic human needs and the country has the main responsibility to confirm their citizens’ provision to safe water. Most of the countries in the world supply treated water to the country through water treatment plants. In drinking water treatment plants, solid sludge is generated at the end of the water treatment process as a waste product which is now becoming a global problem. In previous studies, shrinkage was identified as the major problem of drinking water treatment sludge (DWTS), accrued when use it as a raw material. This study was conducted to analyze the performance of both chemical and physical additives, to identify the possible additive to overcome the shrinkage of DWTS. In the study eight mixtures were prepared by adding Styrene Acrylic Binder as the chemical additive and sand and sugarcane fiber as physical additives separately and together and volumetric shrinkage of each mix was measured weekly. According to the results of this study it was concluded as, shrinkage of DWTS can be reduced by adding physical additives. Physical additives perform more effectively than chemical additives in the reduction of shrinkage of DWTS. Further studies are required to find the optimum mixing ratios of physical additives to optimize the performances.
Investigating Path Loss Effect in Wireless Sensor Networks

--In Wireless communication, the average received power decreases logarithmically with distance. The main factor responsible for this is path loss, which represents signal attenuation as a positive quantity measured in dB. In this paper, we investigate the effects of noise level on various parameters such as Bit Error Rate (BER), Packet Success rate (PSR), Transmit Energy and total energy required to transmit each information bits successfully. In this paper, energy metric is also derived which helps to calculate the optimal transmit energy.
Multi-modality sensor fusion for gait classification using deep learning

Human gait has been acquired and studied through modalities such as video cameras, inertial sensors and floor sensors etc. Due to many environmental constraints such as illumination, noise, drifts over extended periods or restricted environment, the classification f-score of gait classifications is highly dependent on the usage scenario. This is addressed in this work by proposing sensor fusion of data obtained from 1) ambulatory inertial sensors (AIS) and 2) plastic optical fiber-based floor sensors (FS). Four gait activities are executed by 11 subjects on FS whilst wearing AIS. The proposed sensor fusion method achieves classification f-scores of 88% using artificial neural network (ANN) and 91% using convolutional neural network (CNN) by learning the best data representations from both modalities.
Evaluating the Validity of Environmental Kuznets Curve Hypothesis: Empirical Evidence from Nigerian Economy

In this paper, the relationship between economic growth and environmental degradation is examined with primary objective of verifying the applicability of the Environmental Kuznets Curve Hypothesis in Nigeria. The empirical model followed the Grossman-Krueger traditional model with some improvements due to the introduction of technological progress and international trade as part of the predictors. The level of environmental degradation was measured using per capita carbon dioxide emissions. The Autoregressive distributed lag (ARDL) model/bounds cointegration test formed basis for the data analysis. It was observed from the results that the growth-carbon dioxide emissions nexus depicts and invested U-shape. This aligns with the hypothesis of the Environment Kuznets Curve. It was further found that technological progress is helpful in reducing environmental degradation and by so doing improves environmental quality. On the basis of the findings, it is recommended that government should pursue sustainable growth policies that offer opportunities for rapid and sustained economic growth without detrimental effects on the environment quality.
Grassroots – A Scalable and Robust Information Architecture

We propose a novel architecture, Grassroots , for collecting, disseminating, and querying information about the physical world. The Grassroots architecture consists of a massive number of individual agents called dataﬂies , which move around, collect, summarize, and query information about their immediate physical environments. We make use of this architecture in developing a system for collecting and disseminating real-time traﬃc information. Such a system would prevent traﬃc congestion from building up. Today a number of commercial solutions exist for disseminating traﬃc information (e.g., Traﬃc.com, Metrocommute, EtakTraﬃc). However, these solutions are plagued by prohibitive deployment and maintenance cost that prevents widespread deployment. As a result, these solutions cover select highways while leaving out major fractions of the highways. In this paper we present our vision of a low cost, highly scalable zero-infrastructure system for collecting and disseminating information about traﬃc conditions. Our goal is to devise a system that can cover the entire road network of US. We describe the proposed architecture for the system, and evaluate it using realistic model of transportation network and realistic traﬃc conditions.