Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Nonsmooth Frank-Wolfe method for Stochastic Regret Minimization

The current best-known algorithm for convex constrained nonsmooth online stochastic regret minimization using a Linear Minimization Oracle (LMO, a la Frank-Wolfe) and a Stochastic First-order Oracle (SFO) achieves a regret of O ( K 3 / 4 ) , where K is the number of iterations [26]. We provide two novel single-loop nonsmooth Frank-Wolfe methods, P-MOLES & PD-MOLES, which achieve the nearly-optimal online stochastic (non-adversarial) regret of O ( √ K ln( K )) for this problem with a Lipschitz continuous function. Our methods only need a mild assumption that the function remains Lipschitz and can be queried on a slightly larger neighborhood around the constraint set. Further, the last-iterates of our methods are guaranteed to be ε -suboptimal feasible solutions just after using O ( ε − 2 ) LMO calls and O ( ε − 2 ) SFO calls. These ofﬂine oracle calls complexities are optimal, and compared to the state-of-the-art ofﬂine method, MOLES [48], P-MOLES & PD-MOLES have the added advantage of being single-loop methods which use only one LMO call and one SFO call per iteration. This kind of simplicity is much preferred in practice, especially in the online setting.
Tutorial_ Analysis of motor unit discharge characteristics from high-density surface EMG signals

Recent work demonstrated that it is possible to identify motor unit discharge times from high-density surface EMG (HDEMG) decomposition. Since then, the number of studies that use HDEMG decomposition for motor unit investigations has increased considerably. Although HDEMG decomposition is a semi-automatic process, the analysis and interpretation of the motor unit pulse trains requires a thorough inspection of the output of the decomposition result. Here, we report guidelines to perform an accurate extraction of motor unit discharge times and interpretation of the signals. This tutorial includes a discussion of the differences between the extraction of global EMG signal features versus the identification of motor unit activity for physiological investigations followed by a comprehensive guide on how to acquire, inspect, and decompose HDEMG signals, and robust extraction of motor unit discharge characteristics.
AN EMPIRICAL ANALYSIS OF THE DETERMINANTS OF BANK SELECTION IN PAKISTAN A Customer View

This study analyzes the major determinants of a bank selection by a customer in the banking industry of Pakistan. It is based on a survey of 358 customers of private, privatized and nationalized banks located in the city of Lahore (Pakistan). The findings of the study reveal that the most important variables influencing customer choice are customer services, convenience, online banking facilities and overall bank environment. The study aims to bridge the existing gap in local banking literature through identifying the important bank selection determinants and concludes with some policy implications which are expected to have an impact on the marketing efforts of Pakistani banks.
Investigating the Determinants of Renewable Energy Consumption in Malaysia: An Ardl Approach

It is vital for Malaysia to increase the consumption of renewable energy to reduce its dependence on dirty fossil fuels for electricity generation. This paper attempts to investigate the factors affecting renewable electricity consumption in Malaysia. Specifically, our study aims to explore the long-run relationship among renewable electricity consumption, economic growth, CO2 emissions, foreign direct investment and trade openness over the period 1980 to 2015. By employing autoregressive distributed lag (ARDL) bounds testing cointegration approach, we find that economic growth and foreign direct investment (FDI) are the major drivers for renewable electricity consumption. Trade openness, however, is found to have a negative impact on renewable electricity consumption in the long-run. Interestingly, the effect of CO2 emissions on renewable electricity consumption is not significant. Moreover, the vector error correction model (VECM) Granger causality test discovers the existence of a unidirectional causality relationship running from GDP to renewable electricity consumption, confirming the validity of conservation hypothesis in Malaysia. Some important policy implications are also discussed.
Use of Fura 2 Fluorescent Dyes as Indicator for Studying Calcium Distribution in Several Plant Tissues

Calcium (Ca) is an essential plant nutrient and is important in determining quality of fruits in storage. The analytical method presently known to determine Ca concentration in vegetables measures total Ca, and there is a need to develop methods that can determine the distribution of Ca within vegetable tissues. The objective of this study was to determine the ability of fluorescent probes to visualize Ca location and distribution in vegetable tissues. We examined three protocols using fluorescent dyes developed to detect Ca. The first tested Fura 2 acetoximetil (AM) probe in fresh cuts from grapes at different combinations of temperatures and incubation times. The second protocol was developed with the aim of lowering the natural autofluorescense. In the third protocol, the Fura 2 probe was used in tissues previously fixed in formalin, acetic acid, and alcohol solution (FAA). Tissues were observed under an epifluorescence microscope and, to compare and complement the observations, under a scanning electron microscope (SEM). No sign of fluorescence was observed in fixed and fresh tissue using the Fura 2 AM. In fresh cuts, there was autofluorescent interference, provoked mainly by chlorophyll, but also from the vascular system and tannins. The Fura 2 probe was introduced to vegetable tissues by utilizing a pH of 4.5, and a more intense signal was observed in tissues with greater Ca concentration. This signal was also associated with Ca crystals, which might have had some degree of hydrolysis at low pH. Under a SEM microscope, Ca oxalate crystals were clearly observed in those tissues. Our results show that Fura 2 probe can be used to detect Ca and its distribution in vegetable tissues.
EŞLİ PROGRAMLAMA ETKİNLİĞİNİN ORTAOKUL ÖĞRENCİLERİNİN PROGRAMLAMA BAŞARIL ARINA ETKİSİ

The aim of this study is to evaluating effectiveness of pair programming. The experimental period of the research is applied to 36 sixth grade students from a secondary school in Ankara at 2014 – 2015 spring semester. The research work has been designed and realized with the posttest experimental pattern with control group. Independent variable of the research is students being pair or alone in programming sessions. The two group take the same instruction and we just look for the effect of pair working. The dependent variable of the research is programming achievement of students. The students’ logical thinking abilities were used as control variable (covariate) to reduce bias on results. Group Assessmentof Logical Thinking was used to measure students’ logic al thinking ability. A programming achievement test has been developed to measure students programming success. For the test, expert opinion was received from three information technologies teachers. The test pre examined in different secondary school with 65 students which already taken Scratch programming course. On the single factor that arises from the posttest application of the performance variable that belong to the students working as pair or alone and using Group Test of Logical Thinking results as control variable ; ANCOVA test has been applied. All assumptions has been tested fort this analysis. According to the obtained findings, between the pair working students and alone working students there is no significant difference on the students’ program ming achievement.
GROWTH AND NUTRIENTS UPTAKE OF RICE AT EARLY SEEDLING STAGE AS INOCULATED WITH BACILLUS SPP

Utilization of plant growth promoting rhizo-bacteria (PGPR) potentially elevates crop productivity. Concurrently, our study was focused on isolating efficient PGPR strains from the rhizosphere of rice plants. This in order to assess its properties under both laboratory and glass house conditions accordingly. Five (5) bacterial isolates were screened out based on sets of qualitative tests. Among the bacterial isolates, UPMRB9 were selected due to higher production of plant growth promoting traits:-1) nitrogen fixation, 2) phosphate and potassium solubilization, 3) indole-3 acetic acid production as well, 4) siderophore and hydrolyzing enzyme production. The isolates were later identified based on 16S rRNA sequence by which known to be Bacillus tequilensis. Subsequently, this potential isolates were inoculated to rice seedlings under control environment (glasshouse conditions). The results amply that seedling biomass was 38.2% (BRR1 dhan67), 38.5% (Putra-1) and 33.9% (MR297) higher in compare to uninoculated control. Similar goes for seedling height at 22.5%, 20.2% and 20.0% higher whilst total chlorophyll content was 22.5%, 20.2%, 20.0% higher respectively. The relative increase of nitrogen for the rice variety BRRI dhan67, Putra-1 and MR297 were 34.38%, 99.65% and 52.22% accordingly; phosphorous was 442.7%, 104.9%, 140.7% accordingly and potassium was 41.5%, 45.8%, 153.7% accordingly. Therefore, the isolates of UPMRB9 could be considered as a potential bio-fertilizer source; yet further evaluations are necessary particularly on its performances under field environment.
A Deep Learning and Image Recognition System for Image Recognition

A BSTRACT . With the improvement of computer hardware and computing power, the powerful and automatic feature extraction capability of computers can effectively determine good features to improve the efﬁciency of model recognition systems. The purpose of this study was to apply a variety of binarization preprocessing algorithms and to implement an image recognition system using the GoogLeNet model, a convolutional-neural-network module based on deep learning. ImageNet, the largest image recognition database in the world, was used as the training dataset, and ﬁve types of gallery sets, namely cars, planes, horses, ships, and trucks, were chosen to carry out the experiments. This system attempted to use a variety of algorithms on gray-scale and binarized images; then, it trained three models based on GoogLeNet Inception classiﬁcation V1, Inception classiﬁcation V2, and Inception classiﬁcation V3, and attempted to improve the accuracy of the identiﬁcation of the original models. The system was implemented in two parts. The ﬁrst part used six methods to preprocess the images. The second part trained and tested the image data, and then, it used six matching modules to circle and label the image targets successfully. The results of the experiment showed that the preprocessed images could effectively improve the accuracy of module identiﬁcation
Determinants of Adaptation Measures to Climate Change by Arable Crop Farmers in Owo Local Government Area of Ondo State, Nigeria

This study examined determinants of adaptation measures to climate change by arable crop farmers in Owo Local Government Area of Ondo State, Nigeria. The study drew a sample of 120 crop farmers through a multi-stage sampling technique and the data obtained were analyzed using descriptive statistics and Tobit regression model. Result revealed that majority of the farmers perceived climate to be changing. The findings also revealed that agricultural systems (96.7%), household livelihoods (86.7%), protective measures (70.8%), soil conservation techniques (55.8%) and farming operation (41.7%) were the main adaptation measures employed by the farmers. Household size, education, farm size, income, experience and access to extension agents were the factors that were statistically and significantly affected the rate of utilizing adaptation measures using Tobit model. The main barriers limiting the farmers from fully adapting to climate change were inadequate funds (98%) and information to climate change (81%). It is therefore recommended that climate change adaptation advocacy should be intensified by creating more awareness on climate change couple with more innovative and effective adaptation measures that are accessible, available and affordable by the crop farmers. [Fatuase AI, Aborisade AS, Omisope ET. Determinants of Adaptation Measures to Climate Change by Arable Crop Farmers in Owo Local Government Area of Ondo State, Nigeria. World Rural Observ 2015;7(1):49-57]. ISSN: 1944-6543 (Print); ISSN: 1944-6551 (Online). http://www.sciencepub. net/rural. 7
Estimating Cambodia’s Economic Conditions by Dynamic Factor Model

This study constructed a coincident indicator (CI) as the unobserved state of the economy in Cambodia by combining principal components and a dynamic factor model (DFM). In the first step, it estimated the factor loadings (coefficients of the unobserved state variables) by ordinary least squares (OLS) and feasible generalized least squares (FGLS) methods using the state variable produced by the first principal component. In the second step, it estimated the unobserved state variables through the DFM by replacing the coefficients with their estimators in the first step. Doz, Giannone, and Reichlin (2011) introduced this hybrid approach for stationary data. The coincident indicator showed that Cambodia’s economy fell below its potential level between 2016 and 2017 and started recovering after mid-2017. By exploiting the coincident index, the study examined comovement between the foreign direct investment (FDI) inflow and the state of the economy by using the autoregressive distributed lags (ARDL) model. The result showed that an acceleration of the economic condition contributed to an increase in FDI inflow in the short-term for all models; the long-term coefficient became negative. One reason for this could be the diminishing marginal product of capital that made foreign capital investment less attractive.
WiDir: A Wireless-Enabled Directory Cache Coherence Protocol

As the core count in shared-memory manycores keeps increasing, it is becoming increasingly harder to design cache-coherence protocols that deliver high performance without an inordinate increase in complexity and cost. In particular, sharing patterns where a group of cores frequently reads and writes a shared variable are hard to support efficiently. Hence, programmers end up tuning their applications to avoid these patterns, hurting the programmability of shared memory. To address this problem, this paper uses the recently-proposed on-chip wireless network technology to augment a conventional invalidation-based directory cache coherence protocol. We call the resulting protocol WiDir. WiDir seamlessly transitions between wired and wireless coherence transactions for a given line based on the access patterns in a programmer-transparent manner. In this paper, we describe the protocol transitions in detail. Further, an evaluation using SPLASH and PARSEC applications shows that WiDir substantially reduces the memory stall time of applications. As a result, for 64-core runs, WiDir reduces the execution time of applications by an average of 22% compared to a conventional directory protocol. Moreover, WiDir is more scalable. These benefits are obtained with a very modest power cost.
Modeling, Simulation, and Experimental Evaluation of Particle Size Distribution in Stabilized Fluidized Bed Adsorption System

Fluidized beds containing solid particles of a wide size distribution is of significant practical importance. In such systems, the overall behavior depends on the opposing effect of mixing and classification. In the present work, the mixing and segregation behavior of liquid fluidized beds containing particles of different sizes is described mathematically. Particle size distribution (PSD) is studied in a glass column of 5 cm internal diameter and 250 cm length. Ion exchange resins were used as a solid phase with a particle size range of 50 to 650 µm. The bed was fluidized at constant and low water flow velocity and the particle size measurement was carried out at different locations over the column length by analytical scanning electron microscope. Particle size fractionation data obtained by Malvern Mastersizer-2000, version 5.4, was utilized in the solution of developed model equations to obtain PSD. It is apparent that the mixing model along with the classification model represents better results than any other model given by various researchers in the literature. The proposed model is in good agreement with the PSD data given by Malvern particle size analyzer.
The Market Microstructure of Illiquid Option Market s and Interrelations with the Underlying Market

Understanding and measuring determinants of bid-ask spreads is decisive to clarifying the efficiency of the microstructure of any exchange an d general market liquidity. This paper examines the market microstructure of a low liquidi ty, market maker driven option market, the relations to the underlying securities’ market and the challenges of pricing liquidity. Comparing empirical results with prior research we find suppo rt f r the “derivative hedge theory , in which option percentage spreads are inversely related to the ption market maker's ability to hedge his positions and this in proportion to associated cost s. We take the approach that option market makers’ costs represented by the bid-ask spread are det rmined from market activity and individual option characteristics. In a second step cross option market and underlying asset market characteristics are incorporated in the anal ysis.We model the bid-ask spread with order processing and delta hedging costs, inventory holdi ng costs and competition. We find that the option bid-ask spread positively depends on delta h edging costs and the bid-ask spread of the underlying security. Adverse to prior research we o bserve that larger option trading volume significantly reduces realized option bid-ask sprea ds. JEL Codes: C33, G13, G14, G24
How to Design Human Factors into a PSM System to Ensure Effectiveness and Deliver Risk Reduction Performance

This paper will present a practical application of a design process for developing and implementing effective process safety management (PSM) systems. Management system deficiencies are often the root causes leading to process safety incidents. Such deficiencies can be attributed to inadequately designed management systems, primarily since standards and regulations do not provide detailed specifications for their design. A methodology based on proven quality management principles will demonstrate how human factors can be incorporated directly into the design specification for a PSM system to assure effectiveness and deliver sustainable risk reduction performance. As such, they can have a dramatic impact on how individual management processes can be used to ensure that design, operational and maintenance activities are conducted in a safe and environmentally responsible manner. Applicable to both onshore and offshore facilities, this design methodology takes process safety beyond regulatory compliance and enables organizations to sustain performance for managing risk, reliability and resilience as part of an integrated operational risk management framework. It applies to both new and modified designs for engineered process systems, as well as individual management processes. Application of human factors to the management system design also allows for continual improvement in response to changes to regulations, technology, and operating practices. This paper will present a practical step-by-step procedure on “how to” incorporate human factors into the PSM system design, including: leadership, safety culture, human factors engineering and human-machine interfaces, employee engagement and empowerment, communications, etc. Examples will show how quality aspects for human factors are addressed in key management processes within the PSM system in order to improve risk reduction performance. GCPS 2016 __________________________________________________________________________
The Role of Socio-demographic Variables, Sexual Relationship, Marital Stability, Marital Communication and Conflict Resolution in Marital Satisfaction Among Married Individuals in Addis Ababa, Ethiopia

Intact and harmonious marital relationships are required not only for the mental health of the individual but also for children and thus, for the society in the broader sense. But unsatisfying and stressful marital relations lead to increased emotional disturbances and marital disruption. This study aimed to assess the role of socio-demographic, sexual relationship, marital stability, marital communication and marital conflict resolution in marital satisfaction among married individuals. The target population for this study was all heterosexual married individuals, legally bound by the state of marriage as husband and wife. Quantitative research design and a systematic sampling technique along with a simple random sampling technique were employed to select 326 households. Frequency and percentages, means, standard deviations, Pearson correlation, independent sample T-test, one-way ANOVA, and hierarchical multiple linear regressions were all used to compute sample statistic. In the hierarchical multiple linear regression analysis, from the socio-demographic variables, only age and occupation type predicted significantly married individuals’ marital satisfaction, b = -. 13, β = -. 08 and b = 7.37, β = . 09, respectively, p < . 05. The result implies that age has a negative impact whereas occupation type has a positive impact on the marital satisfaction of married individuals. Sexual relationships, marital stability, marital conflict resolution, and marital communication were significant predictors of marital satisfaction, with other variables held constant, at p < . 001. The most important predictors of marital satisfaction as the results of the study disclosed were sexual relationships followed by marital stability (b = .51, β = .28, and b = 1.04, β = .27, respectively, p < .001). Together all the significant independent variables in the model accounted for 74% of the variance in married individuals’ marital satisfaction and the model was significant, F (10,297) =45.83, p < . 001. This study adds a sound, contextual and specific knowledge to the existing marriage counseling practices and theories as well to enhance or reduce factors for married individuals’ marital satisfaction.
DATA PRIVACY PRESERVATION USING DATA PERTURBATION TECHNIQUES

-Data mining is the extraction of valuable knowledge from large data. Nowadays Data mining is done on Dynamic data rather than the traditional static data. The Data Mining techniques used today consider one main issue, the privacy of the critical and sensitive Data. There are various techniques involved in the privacy preservation of critical data. Data Perturbation is an important method to preserve privacy of data. Data perturbation is the data security technique that modifies the database to preserve the privacy and confidentiality. It is used for both data privacy and accuracy. In this paper we are going to discuss about the various perturbation techniques that can be used to preserve data privacy and discuss about the implications of the techniques.