Miracle-dz/UniFAR-FTUs huggingface dataset:
Empirical evaluation on discounted Thompson sampling for multi-armed bandit problem with piecewise-stationary Bernoulli arms

The Multi-Armed Bandit problem is a problem in reinforcement learning that focuses on how to solve the exploration-exploitation dilemma. The dilemma is, given a set of options (known as arms) that you could try many times, how to balance between gathering information through experimenting with the available arms (exploration) or maximizing profit by choosing the seemingly best arm at that time (exploitation). The Multi-Armed Bandit problem is centered around determining which arm to choose at every round. Multi-Armed Bandit has gained its popularity as a more dynamic approach to a randomized trial, with its goal is to experiment with each available arm while still maximizing profit gained. An example of Multi-Armed Bandit in real life is in determining which film artwork should be shown to a visitor that would attract the visitor to watch that particular film. Bernoulli distribution with parameter θ is chosen to model the response of the visitor after seeing the artwork. Non-stationary condition on θ can be implemented to accommodate various trends in film artworks. Some artworks might be good at a certain month, but they could not be preferred in the next month. The non-stationary condition in this study is modeled through piecewise-stationary. We implemented a discounted Thompson sampling policy that used Bayesian method to determine which arm to choose at each round. Multiple simulations were conducted on various conditions to empirically test the policy’s performance on various conditions. Evaluation was based on the cumulative regret. Based on these simulations, discounted Thompson sampling policy achieved relatively lower cumulative regret in tackling the stationary and piecewise-stationary conditions, compared to some well-known policies such as Epsilon Greedy, SoftMax, Upper Confidence Bound, and Thompson Sampling.
Effects of flame retardants on liquid oxygen compatibility of epoxy resin containing binaphthyl based on combination of mechanical impact testing and theoretical analysis

The epoxy resin containing binaphthyl (BEBN) was synthesized, and the curing process of BEBN by amidogen curing agent was investigated. The hexabromocyclododecane, antimony trioxide, decabromodiphenyl oxide, and aluminum hydroxide were added to the BEBN in order to improve the compatibility of BEBN with the liquid oxygen. The compatibility of cured BEBN was evaluated by mechanical impact according to ASTM D–2512–95 standard. The microstructure and the surface element compositions of the specimen before and after the mechanical impact were investigated and analyzed by scanning electron microscopy and X-ray photoelectron spectroscopy, respectively. The mechanical impact results confirmed that the compatibility of BEBN with liquid oxygen was related to the oxidation reaction, and the compatibility was significantly improved after adding the flame-retardant additives, specially the combination of the inorganic and organic additives.
Projected Food-grain Production and Yield in India: An Evidence from Statewise Panel Data Investigation during 1977-2014

Purpose : This study examines the impact of climatic change on food-grain production and yield using state-wise panel data during 1977-2014 in fifteen Indian states. Accordingly, it estimates the projected food-grain production and yield by the years of 2040, 2040, 2060, 2080 and 2100. Finally, it provides the effective practical and effective policy suggestions to reduce the climate change impact on food-grain farming based on existing studies. Research Method : Regression coefficients of food-grain production and yield with climatic and non-climatic factors are estimated using Cobb-Douglas production function model. Marginal impact analysis method is used to examine the projected food-grain production and yield. Findings : Empirical results infer that most climatic factors have a negative impact on food-grain production and yield in different weather seasons. Projected results are suggested that food-grain production is expected to be declined by 5.25%, 6.64%, 8.03% and 9.57% by 2040, 2060, 2080 and 2100 respectively. Food-grain yield is likely to be decreased by 1.05%, 1.96%, 2.87% and 5.07% by the aforesaid years. Research Limitations : This study could not capture impact of inter-states disparities in socio-economic condition of farmers, geographical conditions, agriculture policies and public spending on agriculture and rural development on food-grain production and yield. It also could not include factors such as solar radiation, sun intensity, wind speed and heat wave in empirical investigation. Originality/ Value : It compiles state-wise panel of food-grain production and yield as dependent variables, and climatic variables and non-climatic factors as explanatory variables during 1977-2014. It examines the projected food-grain production and yield.
Deep Learning Hybrid with Binary Dragonfly Feature Selection for the Wisconsin Breast Cancer Dataset

Breast cancer is the world’s top cancer affecting women. While the danger of the factors varies from a place, lifestyle, and diet. Treatment procedures after discovering a confirmed cancer case can reduce the risk of the disease. Unfortunately, breast cancers that arise in low and middle-income countries are diagnosed at a very late stage in which the chances of survival are impeded and reduced. Early detection is therefore required not only to improve the accuracy of discovering breast cancer but also to increase the chances of making the right decision on a successful treatment plan. There have been several studies tending to build software models utilizing machine learning and soft computing techniques for cancer detection. This research aims to build a model scheme to facilitate the detection of breast cancer and to provide the exact diagnosis. Improving the accuracy of a proposed model has, therefore, been one of the key fields of study. The model is based on deep learning that intends to develop a framework to accurately separate benign and malignant breast tumors. This study optimizes the learning algorithm by applying the Dragonfly algorithm to select the best features and perfect parameter values of the deep learning model. Moreover, it compares deep learning results against that of support vector machine (SVM), random forest (RF), and k nearest neighbor (KNN). Those classifiers are chosen as they are the most reliable algorithms having a solid fingerprint in the field of clinical data classification. Consequently, the hybrid model of deep learning combined with binary dragonfly has accurately classified between benign and malignant breast tumors with fewer features. Besides, deep learning model has achieved better accuracy in classifying Wisconsin Breast Cancer Database using all available features.
Primary and ultimate biodegradation of anionic surfactants under realistic discharge conditions in river water

Some levels of even the most highly biodegradable compounds escape sewage treatment and enter rivers and streams as components of effluent. Rapid biodegradation in the stream lowers a chemical`s concentration, prevents its dispersion through the environment, limits exposure of aquatic organisms downstream, and minimizes any potential for bioaccumulation. The biodegradation kinetics of representative anionic surfactants were determined under conditions simulating the mixing zone below a treatment plant outfall. {sup 14}C-1 C{sub 14} alkyl sulfate (AS), {sup 14}C-(ethoxylate) C{sub 14}E{sub 3} alkyl ethoxylate (AE), {sup 14}C (ethoxylate) C{sub 14}E{sub 3}S alkyl ethoxylate sulfate (AES) and {sup 14}C-(ring) C{sub 12} linear benzenesulfonate (LAS) were dosed at 75 {micro}g/l into river water amended with 1% activated sludge liquor to approximate a mixing zone. Evolution of {sup 14}CO{sub 2} was monitored over time, and periodically samples were flash frozen, lyophilized, extracted, filtered and analyzed by Rad-TLC. Incorporation into biomass was determined by quantifying the radioactivity associated with the extracted solids on the filter. Primary degradation of all four surfactants exhibited first-order kinetics, and half-lives ranged from 0.4 to 11.0 hrs. The time needed for ultimate degradation, defined as mineralization or incorporation into biomass, to reach 50% ranged from 0.7 to 19 hrs. These datamore » demonstrate the power of this approach for understanding the fate of chemicals in river water. Furthermore, this work shows that loss of parent and consequently loss of toxicity can occur very rapidly under realistic conditions generating kinetic data, which can be used directly with few assumptions to model exposure concentrations downstream. « less
The effects of information technology and operation performance on service supply chain management practices with moderating effect of capital owners

The objective of this study is to analyze and review the influence of government regulations and information technology on the operational performance of local television stations in East Java with service supply chain management practices as the mediator variable and capital owner’s intervention as the moderator variable. The data of exploratory research was collected through questionnaires distributed to twenty-nine local televisions stations, selected through saturated sampling method from a population of local television stations in East Java, and was analyzed using structural equation modeling. The finding of this study reveals that government regulations and information technology significantly influence the operational performance of local television stations with service supply chain management (SCM) practices as the mediator variable, which means that better government regulations and better information technology are analogous with the importance for the improvement of local television stations operational performance. Capital owner intervention weakens service SCM practices on operating performance and has a direct and immediate effect on reducing the operational performance of local television stations. The practical implications of this study signify the understanding that service SCM practices is an important concept in enhancing the operational performance. Capital owner’s intervention weakens service SCM practices on operating performance of local television stations.
A portable shifted excitation Raman difference spectroscopy system: device and field demonstration

In this paper, we present a portable shifted excitation Raman difference spectroscopy (SERDS) system applied in outdoor experiments. A dual-wavelength diode laser emitting at 785 nm is used as excitation light source. The diode laser provides two individually controllable excitation lines at 785 nm with a spectral distance of about 10 cm−1 for SERDS. This monolithic light source is implemented into a compact handheld Raman probe. Both components were developed and fabricated in-house. SERDS measurements are performed in an apple orchard, and apples and green apple leafs are used as test samples. For each excitation wavelength, a single Raman spectrum is measured with 50 mW at the sample. Strong background interference from ambient daylight and laser-induced fluorescence obscure the Raman signals. SERDS efficiently separates the wanted Raman signals from the disturbing background signals. For the Raman spectroscopic investigations of green leafs, one accumulation with an exposure time of 0.2 s was used for each excitation wavelength to avoid detector saturation. An 11-fold improvement of the signal-to-background noise is achieved using SERDS. The results demonstrate the suitability of the portable SERDS system for rapid outdoor Raman investigations. Copyright © 2016 John Wiley & Sons, Ltd.
Estimation of stature from hand length of an individual in central India population

Anthropometry is a important parameter in medico- legal investigation, in which stature has vital importance in identification of individual. Estimation of stature is important when fragments or remnants or parts of body are found on crime scene. So, the aim of this study is to develop a regression formula to indicate relation between height and hand length of individuals of both sexes. The study was conducted on 159 healthy individuals (75 males and 84 females). Prior permissions were taken from Institutional ethics Committee and written informed consent from all subjects were taken prior to data collection. Linear regression equation was derived using SPSS 23 software. There was a linear correlation between height and hand length. Pearson correlation coefficient found significant at P value – 0.01 (P value The study will significant to medico-legal experts in estimating stature from remnants of upper limb. Keywords: Anthropometry estimation of stature height hand length establishment of identity.
Multi‐sensor particle filtering with multi‐step randomly delayed measurements

This paper develops particle ﬁltering for multi-sensor systems with randomly delayed measurements, where the general case that random delay can be multi-step rather than one-step or two-step is considered. Moreover, different sensors can have different delay steps and delay probabilities. Random delays are assumed to be mutually independent for different sensors and modelled by a separate sequence of random variables obeying discrete dis-tributions. Since random delay leads to the actual measurements being dependent rather than independent given states, and this dependence becomes more complicated with the increase of random delay step, a new formula of the local likelihood density is proposed and then a new weighting scheme is adopted in particle ﬁltering to deal with these difﬁculties. The proposed method is applied to two examples to testify its effectiveness and superiority.
Promoting Energy Efficiency and Proportional Fairness in Densely Deployed Backscatter-Aided Networks

Recently, energy-efficient ambient backscatter communication has emerged as a promising technology to build up self-sustainable wireless networks. However, the limited transmission range and rate restrict the communication capability of a single backscatter node. To ensure network coverage and connectivity, the nodes in ambient backscatter-aided wireless networks (AmBWNs) have to be densely deployed. Unfortunately, the fickle and sporadic nature of the energy source and carrier in AmBWNs would lead to unreliable and unstable transmissions. We argue that the network throughput can be significantly improved if we can take full advantages of both stable active transmission and energy-saving backscattering. However, it is challenging to jointly determine nodes’ transmission mode to enhance the throughput and energy efficiency. Moreover, the fairness in terms of traffic load at each node of AmBWNs is not thoroughly considered in the existing research. The improper load allocation would hinder the network throughput and even cause network partition if some bottleneck nodes deplete the energy. In this article, a novel metric is defined to measure the aggregate energy efficiency of neighboring nodes, capturing the beneficial interaction of active links and backscatter links. Subsequently, we address the aggregate energy efficiency maximization problem constrained by Gini threshold. The Gini coefficient is used to adjust the load in proportion to the delivery capacity of each node, achieving proportional fairness in the dense AmBWN. The simulation result shows that the well-designed metric can improve the energy efficiency by 11 times and the throughput by 86%.
Lithological mapping using Landsat 8 Oli multispectral data in Boumalne, Imider, and Sidi Ali Oubork, High Central Atlas, Morocco

The recognition of geological formations, from a lithological point of view, as well as their tectonic character always remain a major challenge for any precise geological study, in this work we will see the great importance of the application of remote sensing (Landsat OLI, DEM) to realize lithological maps of great interest as well as the realization of detailed lineament maps with the statistics of the performed measurements, the application of some indicated techniques showed a good discrimination of the lithology of geological formations (Fig.8 ,Fig.10,Fig.11),better results and interpretations are also obtained for lineaments affecting the whole area by using the CP1 and DEM methods (Fig.5,Fig.6). Topographic map and geological maps of JBEL SAGHRO DADES and TODGHA MADER (1/200000) gained from ministry of energy and mines, direction of geology (1975), are used for validation of the obtained results by eliminating of artificial structures (roads) and geological layer boundaries. All data sets were pre-processed and projected in the Universal Transverse Mercator (UTM Zone 29 North) projection system and the WGS84 datum using GIS tools (ArcGIS 10.2).
Modeling human-like longitudinal driver model for intelligent vehicles based on reinforcement learning

The driver model is the decision-making and control center of intelligent vehicle. In order to improve the adaptability of intelligent vehicles under complex driving conditions, and simulate the manipulation characteristics of the skilled driver under the driver-vehicle-road closed-loop system, a kind of human-like longitudinal driver model for intelligent vehicles based on reinforcement learning is proposed. This paper builds the lateral driver model for intelligent vehicles based on optimal preview control theory. Then, the control correction link of longitudinal driver model is established to calculate the throttle opening or brake pedal travel for the desired longitudinal acceleration. Moreover, the reinforcement learning agents for longitudinal driver model is parallel trained by comprehensive evaluation index and skilled driver data. Lastly, training performance and scenarios verification between the simulation experiment and the real car test are performed to verify the effectiveness of the reinforcement learning based longitudinal driver model. The results show that the proposed human-like longitudinal driver model based on reinforcement learning can help intelligent vehicles effectively imitate the speed control behavior of the skilled driver in various path-following scenarios.
A Comparative Study on Application of Unmanned Aerial Vehicle Systems in Agriculture

Presently in agriculture, there is much ample scope for drone and UAS (Unmanned Aircraft System) development. Because of their low cost and small size, these devices have the ability to help many developing countries with economic prosperity. The entire aggregation of financial investments in the agricultural area has increased appreciably in recent years. Sooth to say, agriculture remains a massive part of the world’s commercial growth, and due to some complications, the agriculture fields withstand massive losses. Pets and destructive insects seem to be the primary reasons for certain degenerative diseases. It minimizes the potential productivity of the crops. For increasing the quality of the plants, fertilizers and pesticides are appropriately applied. Using UAVs (Unmanned Aerial Vehicles) for spraying pesticides and fertilizing materials is an exuberant contraption. It adequately reduces the rate of health dilemma and the number of workers, which is quite an impressive landmark. Willing producers are also adopting UAVs in agriculture to soil and field analysis, seed sowing, lessen the time and costs correlated with crop scouting, and field mapping. It is rapid, and it can sensibly diminish a farmer’s workload, which is significantly a part of the agricultural revolution. This article aims to proportionally represent the concept of agricultural purposed UAV clear to the neophytes. First, this paper outlines the harmonic framework of the agricultural UAV, and then it abundantly illustrates the methods and materials. Finally, the article portrays the outcome.
Hepcidin: An emerging hormone in iron homeostasis: A review

Hepcidin, is a peptide hormone, which is a key regulator of systemic iron homeostasis and its unbalanced production contributes to iron disorders is derived from liver. Hepcidin was discovered by Krause and coworkers in the year 2000. The name ‘Hepcidin’ was given, from the place of synthesis in liver hepatocytes (hep-) and its antimicrobial activity (-cidin). The gene encoding hepcidin is expressed in various organs like liver, heart, lungs, brain, spinal cord, intestine, stomach, pancreas, adipocytes, skeletal muscles, testis and macrophages. Hepcidin is a 25 amino acid peptide hormone which inhibits entry of iron into the plasma compartment from the three main sources of iron: dietary absorption in the duodenum, the release of recycled iron from macrophages and the release of stored iron from hepatocytes. This blocking of iron flow is achieved by Hepcidin functios by causing degradation of iron receptor, via an iron transporter ferroportin. Hepcidin production is tightly regulated by (1) increased plasma and liver iron as a feedback mechanism to maintain stable body iron levels, (2) decreased by erythroid activity to ensure iron supply for erythropoiesis and (3) increased by inflammation as a host defense mechanism to limit extracellular iron availability to microbes. Hepcidin levels reflect the integration of signals involved in iron regulation and it directly controls iron absorption and bioavailability in circulation. Its measurement is a useful clinical tool for the management of iron disorders in the body. Recent evidence shows that the deficiency of hepcidin may cause iron overloading even in the much milder common form of hemochromatosis, from mutations in the HFE gene. The discovery of hepcidin and its role in iron metabolism could lead to new therapies for hemochromatosis and anemia of inflammation.
Cellular response of biodegradable AZ31 magnesium alloy stent in artery

Because of the increasing incidence of coronary artery disease, the use of cardiovascular stents is gradually increasing. In percutaneous coronary intervention, advantage of bioresorbable stent is that the stent does not remain in the human body after completing the necessary mechanical support to ensure the blood vessel open, and finally degrades into harmless molecules. Compared with bare stents, which require long-term retention in the body, the incidence of restenosis in stent or late stent thrombosis was lower. Current biodegradable stent mainly include polymers, biodegradable stents and metal alloy stent. Magnesium-based stent degradation and its copolymers are used in the application of biological absorbable stents and attract the attention of researchers.
A 30–36 GHz Passive Hybrid Phase Shifter With a Transformer-Based High-Resolution Reflect-Type Phase Shifting Technique

This brief presents a passive hybrid phase shifter consisted of a 5-bit switch-type phase shifter (STPS) and a 4-bit high resolution reflection-type phase shifter (RTPS). The STPS as the main body of the circuit utilizes the bridged T-type and high-pass/low-pass phase shifting cells. A novel high-resolution RTPS is proposed as a supplement of the STPS to improve the phase resolution and minimize the phase error. In the RTPS, a novel reflective load, which contains a transformer and a 4-bit digital-controlled switched capacitor array, is adopted. The transformer in the RTPS can weaken the variation of the reflection coefficient resulted by a large-capacitance switched capacitor array, which makes the control of the phase shifting more convenient and accurate at millimeter-wave (mm-wave) frequency. A proof-of-concept prototype was implemented in 55 nm CMOS technology. Measured results show that the root-mean-square (RMS) phase error of the proposed phase shifter in a step of 2.8° is 0.69 – 2.19° at 30 – 36 GHz, and less than 1.1° from 30 to 34 GHz. An average insertion loss (IL) of 12.6 – 14.6 dB is achieved. The core circuit occupies 0.24 mm2 without DC power consumption.