Miracle-dz/UniFAR-FTUs huggingface dataset:
Bulanık Mantık ve Lojistik Regresyon Yöntemleri ile Ulaşım Ağlarında Geçki Seçim Davranışının Modellenmesi

Gecki secim problemi, bir cok parametrenin degerlendirilerek, bireysel faydanin en buyuklemesine yonelik karmasik bir sorun olup, olusturulacak modelin dogrulugu, bireysel gecki secim davranisinin gercekci olarak temsiline baglidir. Bu calismanin amaci, Denizli ilinde belirlenmis olan onemli bir yol agindaki gecki secim problemini, yapilan anket calismasi sonucu elde edilen gercek veriler kullanilarak bulanik olarak modellemektir. Bulanik Mantik modelinde, gecki secim davranisi uzerinde etkili olan en onemli dort parametre; yolculuk suresi, trafik guvenligi, tikanma olasiligi ve cevresel etki degerlendirmeleri dikkate alinmistir. Gecki secim davranisindaki belirsizlikleri modelleyebilmek amaciyla Bulanik Mantik kabullerinden yararlanilmistir. Gelistirilen Bulanik Mantik Gecki Secim modeli, lojistik regresyon modelleri ile karsilastirilmis ve gercek degerlere en yakin sonuclar BM modeli ile elde edilmistir.
Space-time receivers for CDMA systems

This paper discusses blind spatial channel estimation techniques for single user space-time CDMA receivers. The proposed receiver structure consists of beamformers in front followed by the generalized sidelobe canceler (GSC)-based time domain interference cancelers. We propose two spatial channel estimation techniques using the power method (PM): (i) the covariance method (CM) in which the data covariance matrix of the despread array output is applied to the PM to compute the spatial channel as its principal eigenvector and (ii) decision-directed and differentially-formed covariance matrix-based method (DDCM) which utilizes the decision feedback from the time domain filter to estimate the effective interference-free covariance matrix of the spatial channel using the differentially-formed covariance matrix of the array output. The simulation results show the both techniques can estimate the spatial channels reliably under the assumption of mild power control and DDCM could do so even in the "near-far situation", outperforming the conventional either only time-domain or space-domain receivers in BER performance in the Rayleigh fading channel.
TQM in Construction and Manufacturing Companies of Pakistan: A Case Study

The role of construction quality and continuous improvement is vital in the development of construction industry of developing countries. Construction quality and continuous improvement is linked with the adoption of quality management systems in construction companies. This paper highlights the importance of TQM (Total Quality Management) and presents the benefits of TQM gained by construction organizations in worldwide construction sector. It examines and contrasts the level of acceptance and execution of TQM in construction and manufacturing sector of Pakistan. The paper also identifies the barriers in adoption of TQM and advantages of implementing TQM in construction sector of Pakistan. In the end, the paper presents some suggestions and steps for the implementation of TQM in construction companies of Pakistan. The findings and recommendations of the study are not only beneficial for the construction sector of Pakistan but also these will be helpful to other developing countries having similar scenarios.
FACTORS SHAPING CAPITAL STRUCTURE: EVIDENCE FROM PRIVATE COMMERCIAL BANKS IN BANGLADESH

This study investigates how various determinants shape the capital structure of commercial banks in Bangladesh, employing panel data, structured from available secondary sources, covering 22 banks as samples from 61 scheduled banks for the period of 2011 to 2020, conducting Feasible Generalized Least Squared (FGLS) Regression Model. Several diagnostic tests have been conducted to ensure the robustness and stability of the model. The study results reveal that return on assets, earnings per share, asset growth, asset structure, investment structure, cost per loan assets, and loan loss provisioning considerably influence the capital structure or the leverage of commercial banks. On the contrary, the authors find no explicit evidence that bank size, liquidity, capital adequacy, and non-performing loan ratio have significant impacts on the capital structure of the banking industry of Bangladesh. The findings of this study advocate that return on assets, earnings per share, asset structure, and cost per loan assets as the dominant explanatory factors of capital structure. Besides, asset growth, investment structure, and loan loss provisioning affect less significantly on determining the capital structure of the banking industry. This study also brings the academicians, researchers, and analysts with corroborating new routes for exploring further research in this field.
Fabrication of low cost microwave circuits and structures using an advanced thick film technology

The explosive growth in applications for microwave circuits and systems is demanding new approaches to circuit technology to satisfy system demands. With applications such as phased array antennas, satellite communications and car collision avoidance radar, there is a high volume demand for microwave circuits. Established circuit technologies, primarily thin film, are too high in cost to meet these demands. What is needed is a lower cost technology which still offers high performance. Such a technology is described here. Advanced thick film materials are combined with photoprocessing techniques to provide outstanding circuit performance. Line resolutions of 12 /spl mu/m are available, together with via dimensions of 50 /spl mu/m. The electrical performance of the materials is also excellent, with very high conductivity lines and low loss, low dielectric constant dielectric materials. The paper briefly reviews this technology. The majority of the paper concentrates on describing examples of microwave components and their performance when fabricated using this technology. It is shown that it is possible to equal or even exceed thin film performance at frequencies up to at least 80 GHz using the conductor material on ceramic substrates. Particular attention is paid to novel microwave structures using this technology. A structure referred to as "microstrip on dielectric" is illustrated and performance figures are given. Due to the compact form of this structure, small size circuits with low material costs and hence low overall cost result. Test results on components fabricated using this approach are also given.
Effectiveness of community forest association and water resource users’ associations in discharging their statutory functions: A case of Kilungu catchment, Kenya | JBES

Catchment degradation has continued to occur globally albeit the presence of Community Forest Associations (CFA) and Water Resource Users Associations (WRUA). Similarly, Kilungu catchment area in Kenya is under the management of the Kenze (CFA) and upper Kaiti (WRUA). This paper examined Kenze CFA and Upper Kaiti WRUA activities by exploring their effectiveness in discharging their statutory functions. This was achieved by carrying out, an exploratory descriptive survey. Data was collected through questionnaires, focus group discussions, 10 key informants’ interviews and direct observations. Descriptive analysis was used. Information was presented in fig.s, tables and percentages. Results showed that upper Kaiti WRUA as more effective in catchment management at moderately (31%) and highly at (37%) as compared to CFA moderately (29%) and highly (5%). In terms of discharging of their statutory functions, Upper Kaiti WRUA was better at a rating of 27% (good) and 23% (very good) as compared to Kenze CFA which was rated at 3% (good) and 6% (very good). This study results implied that Upper Kaiti WRUA was more effective in all aspects of ensuring catchment management as opposed to CFA. In conclusion, a strategy of seizing the opportunities presented by the CFA of being empowered to perform all its activities as required by law with emphasis on the timely preparation and implementation of management plans and WRUA’s continuous improvement should be prioritized. The study recommends new initiatives that improve on the CFA and WRUA activities in order to effectively discharge on their statutory functions.
Analysis of all‐optical demultiplexing from 160/320 Gbit/s to 40 Gbit/s using quantum‐dot semiconductor optical amplifiers assisted Mach‐Zehnder interferometer

The performance of ultrafast all‐optical demultiplexer using quantum‐dot semiconductor optical amplifiers (QD‐SOAs) assisted Mach‐Zehnder interferometer (MZI) is analyzed. Through numerical simulations, a set of key parameters are optimized and all‐optical demultiplexing from 160/320 Gbit/s to 40 Gbit/s can be realized with fairly high performance. The results are useful for the system performance studies and practical application. © 2010 Wiley Periodicals, Inc. Microwave Opt Technol Lett 52: 1629–1633, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.25287
Changing freshwater contributions to the Arctic: A 90-year trend analysis (1981-2070)

The pan-Arctic domain is undergoing some of Earth’s most rapid and significant changes resulting from anthropogenic and climate-induced alteration of freshwater distribution. Changes in terrestrial freshwater discharge entering the Arctic Basin from pan-Arctic watersheds significantly impact oceanic circulation and sea ice dynamics. Historical streamflow records in high-latitude basins are often discontinuous (seasonal or with large temporal gaps) or sparse (poor spatial coverage), however, making trends from observed records difficult to quantify. Our objectives were to generate a more continuous 90-year record (1981–2070) of spatially distributed freshwater flux for the Arctic Basin (all Arctic draining rivers, including the Yukon), suitable for forcing ocean models, and to analyze the changing simulated trends in freshwater discharge across the domain. We established these data as valid during the historical period (1971–2015) and then used projected futures (preserving uncertainty by running a coupled climate-hydrologic ensemble) to analyze long-term (2021–2070) trends for major Arctic draining rivers. When compared to historic trends reported in the literature, we find that trends are projected to nearly double by 2070, with river discharge to the Arctic Basin increasing by 22% (on average) by 2070. We also find a significant trend toward earlier onset of spring freshet and a general flattening of the average annual hydrograph, with a trend toward decreasing seasonality of Arctic freshwater discharge with climate change and regulation combined. The coupled climate-hydrologic ensemble was then used to force an ocean circulation model to simulate freshwater content and thermohaline circulation. This research provides the marine research community with a daily time series of historic and projected freshwater discharge suitable for forcing sea ice and ocean models. Although important, this work is only a first step in mapping the impacts of climate change on the pan-Arctic region.
Internal Control System and Return on Assets of Manufacturing Companies Listed in Nigeria

Manufacturing companies in Nigeria has witnessed poor financial performance, subsequent failure and liquidation which can be traced to weak internal control system, internal fraud, and non-compliance with corporate governance standard, lack of transparency, creative accounting and insider trading. The financial performance of manufacturing companies has been called to question on several occasions. The study examined the effect of internal control system on return on asset of manufacturing companies listed in Nigeria. The study employed ex-post facto research design, a target population of forty-three (43) manufacturing companies quoted on Nigerian Stock Exchange was used and a sample of fifteen (15) companies was selected from the population. The data was gathered from audited financial reports of the sample manufacturing firms for a period of ten (10) years. The study employed descriptive method of analysis to describe the data while inferential statistics such as multiple linear regression technique was used to test the hypotheses using Stata software. Inferences were made at 10% level of significance. The study showed that Risk management has significant and positive effect on return on assets of manufacturing companies listed in Nigeria giving the F-statistics value of 4.865 with the probability value of 0.001 and Adjusted r of 0.180 showed that compliance with regulatory framework has statistical effect on return on asset, hence the null hypothesis of no significant effect of compliance with regulatory framework on the financial performance of manufacturing companies listed in Nigeria was rejected. Internal communication of information has statistical effect on financial performance of manufacturing companies in Nigeria giving the F-statistics value of 2.652 with the probability value of 0.036 and Adjusted r of 0.045, hence the null hypothesis was rejected. From the findings of the study, the study concluded that manufacturing companies that had invested on effective internal control systems have more improved financial performance as compared to those with a weak internal control system. The following recommendations were made based on the outcome of the study: Management should develop more effective monitoring systems through the internal control department to ensure compliance with regulatory frameworks. Management of companies should regularly upgrade their information and communication frameworks to enable them cope with the frequent changes in the global environment and as such improve their financial performance.
Machine Learning for Screening Microvascular Complications in Type 2 Diabetic Patients Using Demographic, Clinical, and Laboratory Profiles

Microvascular complications are one of the key causes of mortality among type 2 diabetic patients. This study was sought to investigate the use of a novel machine learning approach for predicting these complications using only the patient demographic, clinical, and laboratory profiles. A total of 96 Bangladeshi participants with type 2 diabetes were recruited during their routine hospital visits. All patient profiles were assessed by using a chi-squared (χ2) test to statistically determine the most important markers in predicting three microvascular complications: cardiac autonomic neuropathy (CAN), diabetic peripheral neuropathy (DPN), and diabetic retinopathy (RET). A machine learning approach based on logistic regression, random forest (RF), and support vector machine (SVM) algorithms was then developed to ensure automated clinical testing for microvascular complications in diabetic patients. The highest prediction accuracies were obtained by RF using diastolic blood pressure, albumin–creatinine ratio, and gender for CAN testing (98.67%); microalbuminuria, smoking history, and hemoglobin A1C for DPN testing (67.78%); and hemoglobin A1C, microalbuminuria, and smoking history for RET testing (84.38%). This study suggests machine learning as a promising automated tool for predicting microvascular complications in diabetic patients using their profiles, which could help prevent those patients from further microvascular complications leading to early death.
Elephant movements in different human land-uses in Chobe District, Botswana

We have a limited understanding of the effects that an increasing human population and urban and agricultural development are having on elephant movements in Botswana. Elephant movements are complex because they are influenced by a wide range of location-specific variables. This study aimed to investigate how elephants move through different human-dominated landscapes in the Chobe District, Botswana. The movements of four female elephants from the Chobe District were studied over a period of 13 months using GPS collars to follow them. Annual home ranges of the elephants were calculated using both the 100% minimum convex polygon (MCP) and 95% fixed kernel (FK) methods. Additionally, general estimating equation models were used to investigate which factors influenced the elephants’ distance moved, both hourly and daily. We found the elephants’ movement behaviour was dependent on the time of day and type of land use: whether agricultural areas, protected areas or wildlife management areas, trophy hunting blocks, and multi-use zones (e.g. game management areas). Overall, all of the elephants had smaller annual home ranges (~450-1,750 km2) than seen in other studies within southern Africa, and there was a difference in seasonal movements, between individuals. Additionally, contrary to previously published studies, the elephants made larger diurnal movements than nocturnal movements. Movements were significantly different between different land-use areas, suggesting that elephants could be developing different strategies to move through differing levels of human disturbance. It is vital for any wildlife management plan that the spatial movements of key conservation species are thoroughly understood, in order to formulate informed management decisions and create an integrated landuse management plan that enables both development and elephant coexistence. Additional
Fast and Accurate Transferability Measurement for Heterogeneous Multivariate Data

Given a set of heterogeneous source datasets with their classiﬁers, how can we quickly ﬁnd the most useful source dataset for a speciﬁc target task? We address the problem of measuring transferability between source and target datasets, where the source and the target have diﬀerent feature spaces and distributions. We propose Transmeter , a fast and accurate method to estimate the transferability of two heterogeneous multivariate datasets. We address three challenges in measuring transferability between two heterogeneous multivariate datasets: reducing time, minimizing domain gap, and extracting meaningful homogeneous representations. To overcome the above issues, we utilize a pre-trained source model, an adversarial network, and an encoder-decoder architecture. Extensive experiments on heterogeneous multivariate datasets show that Transmeter gives the most accurate trans-ferability measurement with up to 10.3 × faster performance than its competitor. We also show that selecting the best source data with Transmeter followed by a full transfer leads to the best transfer accuracy and the fastest running time.
Application of xgboost to time series forecasting by taking advantage of its powerful forecasting performance

xgboost [1] has the best forecasting performance among non-deep learning methods. However, it works well for interpolation problems and regression, but not for future forecasting of time series data that requires extrapolation. I think it is difficult to avoid this tendency even if we add explanatory variables in the background of the data. Possible explanatory variables include lags of a day or several days from the data, months, days, days of the week, holidays, and so on. In fact, the increase or decrease in data values due to these factors is quite possible and can serve as explanatory variables. However, even if you do this, you will not be able to capture the trend.
AN OPTIMAL MODEL FOR ENERGY EFFICIENCY SPECTRUM SENSING IN COGNITIVE RADIO NETWORKS

— Cognitive Radio Sensor Network (CRSN), which incorporates the ability of cognitive radio in wireless sensor networks. Sensor nodes generally operate on batteries and therefore have strict energy restrictions. As a result, energy efficiency is also a very critical problem in the CRSN. This document focuses on energy consumption due to spectrum detection. We also present an interval time strategy of adaptive spectrum detection, in which secondary users can adjust the following spectrum detection time interval based on the results of detection of the current spectrum (i.e. channel status). ) and also analyze the probability of false alarm. To find an optimal spectrum detection time interval, the user's operating model is introduced. Next, establish a mathematical model based on the Markov model
60 GHz CMOS pulse generator

A 60 GHz CMOS pulse generator (PG) is presented for the wireless transmission of uncompressed HDTV data, and is realised by only CMOS transistors. The CMOS PG was fabricated using a 90 nm CMOS process with nine metal layers. A carrier frequency of 62.5 GHz was obtained at a supply voltage of 1.15 V with an output power of −25 dBm. The power consumption was 11.5 mW at 1.5 GHz input frequency.
Emotion and Language in Philosophy

In this chapter, we start by spelling out three important features that distinguish expressives—utterances that express emotions and other affects—from descriptives, including those that describe emotions (Section 1). Drawing on recent insights from the philosophy of emotion and value (2), we show how these three features derive from the nature of affects, concentrating on emotions (3). We then spell out how theories of non-natural meaning and communication in the philosophy of language allow claims that expressives inherit their meaning from specificities of emotions—namely, from being felt, evaluative attitudes toward propositional or non-propositional contents (4). 1. Expressives vs. descriptives: three benchmarks Supposing that utterances (1)–(3) and (4)–(9) respectively refer to the same phenomena, compare groups A and B.
Multiscale entropic regularization for MTS on general metric spaces

We present an $O((\log n)^2)$-competitive algorithm for metrical task systems (MTS) on any $n$-point metric space that is also $1$-competitive for service costs. This matches the competitive ratio achieved by Bubeck, Cohen, Lee, and Lee (2019) and the refined competitive ratios obtained by Coester and Lee (2019). Those algorithms work by first randomly embedding the metric space into an ultrametric and then solving MTS there. In contrast, our algorithm is cast as regularized gradient descent where the regularizer is a multiscale metric entropy defined directly on the metric space. This answers an open question of Bubeck (Highlights of Algorithms, 2019).
An observational study of precipitation types in the Alaskan Arctic

The effects of various precipitation types, such as snow, rain, sleet, hail and freezing rain, on regional hydrology, ecology, snow and ice surfaces differ significantly. Due to limited observations, however, few studies into precipitation types have been conducted in the Arctic. Based on the high-resolution precipitation records from an OTT Parsivel disdrometer in Utqiaġvik, Alaska, this study analysed variations in precipitation types in the Alaskan Arctic from 15 May to 16 October, 2019. Results show that rain and snow were the dominant precipitation types during the measurement period, accounting for 92% of the total precipitation. In addition, freezing rain, sleet, and hail were also observed (2, 4 and 11 times, respectively), accounting for the rest part of the total precipitation. The records from a neighbouring U.S. Climate Reference Network (USCRN) station equipped with T-200B rain gauges support the results of disdrometer. Further analysis revealed that Global Precipitation Measurement (GPM) satellite data could well characterise the observed precipitation changes in Utqiaġvik. Combined with satellite data and station observations, the spatiotemporal variations in precipitation were verified in various reanalysis datasets, and the results indicated that ECMWF Reanalysis v5 (ERA5) could better describe the observed precipitation time series in Utqiaġvik and the spatial distribution of data in the Alaskan Arctic. Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) overestimated the amount and frequency of precipitation. Japanese 55-year Reanalysis (JRA-55) could better simulate heavy precipitation events and the spatial distribution of the precipitation phase, but it overestimated summer snowfall.