Miracle-dz/UniFAR-FTUs huggingface dataset:
Recommendation, Customer Satisfaction, Online Shopping Experience, Trust, and Word-of-mouth Affecting Consumer Online Shopping Decision in China

The purpose of this research study was to investigate recommendation, customer satisfaction, online shopping experience, trust, and word-of-mouth (WOM) affecting consumer online shopping decision China. The closed-end questionnaires were applied for collecting data from 150 online consumers in China. The majority of respondents were females with the age between 21-30 years old. Most of them completed high school /vocational colleges, worked as company employees, and had monthly income less than 8,000 RMB. More than 82% of the respondents had an online shopping experience in the past one month. The results revealed that online shopping WOM, online shopping trust, online shopping experience, and recommendation were the significant factors that affected customers’ online shopping decision in China at the significant level of . 05. On the other hand, customer satisfaction did not affect customers’ online shopping decision in China.
AN ASSESSMENT OF THE EFFECT OF INNOVATION AS MEDIATOR TO BUSINESS NETWORKING AND PERFORMANCE RELATIONSHIP: EVIDENCE FROM ZIMBABWEAN SMES

The aim of this study was to improve the understanding of the mediating role of innovation on the business networking and business performance relationship. The study adopted a quantitative approach to gather 154 usable questionnaires from SMEs in Zimbabwe. The results revealed a statistically significant relationship between business networking and performance and also the mediating role that innovation plays between the business networking and performance relationship. The study makes a contribution to the existing literature on management and SME by assessing the mediating role of innovation in the relationship between business networking and business performance in the SME sector of a Sub-Saharan African country
Optimization Model for Sustainable Renovations in Buildings

Buildings consume a substantial amount of energy and adversely affect the global climate and environment. According to the US Department of Energy (DOE), buildings account for 39% of total primary energy consumption and 71% of the electricity consumption. The construction and operation phases constitute the largest proportion of the total energy end-use worldwide (Ma et al. 2012). An innovative and comprehensive set of sustainable materials aiming at the envelope of buildings excluding the roofs is employed to define the renovation alternatives in order to ameliorate the sustainability status of the buildings. The model is comprised of a NSGA-II multi-objective optimization algorithm integrated into a simulation engine. Simulation runs are performed to compute the objective function values and transfer them to the optimization algorithm. A hybrid fuzzy simulation-based optimization model is developed to select the optimum renovation alternatives. The model simultaneously minimizes annual energy consumption and capital cost of an existing office building based on a multi-objective optimization problem. Fuzzy set theory is assigned to the objective functions to address the uncertainty associated with calculation of energy consumption and capital cost values. Conclusively, the model is implemented on a sample case to substantiate the capabilities of the developed model. The case study is a one-story office building with a double skin facade on the south facing facade in Montreal. The results illustrate nine Pareto optimal points and demonstrate that the generated optimum solutions are capable of causing an average of 35% decrease in the annual energy consumption compared to the conventional building scenario.
RF Fingerprints Prediction for Cellular Network Positioning: A Subspace Identification Approach

Cellular network positioning is a mandatory requirement for localizing emergency callers, such as E911 in North America. Although smartphones are normally equipped with GPS modules, there are still a large number of users with cell phones only as basic devices, and GPS could be ineffective in urban canyon environments. To this end, the RF fingerprints based positioning mechanism is incorporated into LTE architecture by 3GPP, where the major challenge is to collect geo-tagged RF fingerprints in vast areas. This paper proposes to utilize the subspace identification approach for large-scale RF fingerprints prediction. We formulate the problem into the problem of finding the optimal subspace over Stiefel manifold, and redesign the Stiefel-manifold optimization method with fast convergence rate. Moreover, we propose a sliding window mechanism for the practical large-scale fingerprints prediction scenario, where recorded fingerprints are unevenly distributed in the vast area. Combining the two proposed mechanisms enables an efficient method of large-scale fingerprints prediction in the city level. Further, we validate our theoretical analysis and proposed mechanisms by conducting experiments with real mobile data, which shows that the resulted localization accuracy and reliability with our predicted fingerprints exceed the requirement of E911.
Optical Geolocation for small Unmanned Aerial System

This paper presents an airborne optical geolocation system using four optical targets to provide position and attitude estimation for a sUAS supporting the NASA Acoustic Research Measurements (ARM), where the goal is to reduce nuisance airframe noise during approach and landing. A large precision positioned microphone array captures the airframe noise for multiple passes of a Gulfstream III aircraft. For health monitoring of the microphone array, the Acoustic Calibration Vehicle (ACV) sUAS completes daily flights with an onboard speaker emitting tones at frequencies optimized for determining microphone functionality. An accurate position estimate of the ACV relative to the array is needed for microphone health monitoring. To this end, an optical geolocation system using a downward facing camera mounted to the ACV was developed. The 3D positioning of the ACV is computed using the pinhole camera model. A novel optical geolocation algorithm first detects the targets, then a recursive algorithm tightens the localization of the targets. Finally, the position of the sUAS is computed using the image coordinates of the targets, the 3D world coordinates of the targets, and the camera matrix. A Real-Time Kinematic GPS system is used to compare the optical geolocation system.
Reinforcement Learning to Create Value and Policy Functions Using Minimax Tree Search in Hex

Recently, the use of reinforcement-learning algorithms has been proposed to create value and policy functions, and their effectiveness has been demonstrated using <italic>Go</italic>, <italic>Chess</italic>, and <italic>Shogi</italic>. In previous studies, the policy function was trained to predict the search probabilities of each move output by Monte Carlo tree search; thus, a number of simulations were required to obtain the search probabilities. We propose a reinforcement-learning algorithm with game of self-play to create value and policy functions such that the policy function is trained directly from the game results without the search probabilities. In this study, we use <italic>Hex</italic>, a board game developed by Piet Hein, to evaluate the proposed method. We demonstrate the effectiveness of the proposed learning algorithm in terms of the policy function accuracy, and play a tournament with the proposed computer <italic>Hex</italic> algorithm DeepEZO and 2017 world-champion programs. The tournament results demonstrate that DeepEZO outperforms all programs. DeepEZO achieved a winning percentage of 79.3% against the world-champion program MoHex2.0 under the same search conditions on <inline-formula><tex-math notation="LaTeX">$13 \times 13$</tex-math></inline-formula> board. We also show that the highly accurate policy functions can be created by training the policy functions to increase the number of moves to be searched in the loser position.
Inertial measurement unit-based pose estimation: Analyzing and reducing sensitivity to sensor placement and body measures

Introduction Inertial measurement units have been proposed for automated pose estimation and exercise monitoring in clinical settings. However, many existing methods assume an extensive calibration procedure, which may not be realizable in clinical practice. In this study, an inertial measurement unit-based pose estimation method using extended Kalman filter and kinematic chain modeling is adapted for lower body pose estimation during clinical mobility tests such as the single leg squat, and the sensitivity to parameter calibration is investigated. Methods The sensitivity of pose estimation accuracy to each of the kinematic model and sensor placement parameters was analyzed. Sensitivity analysis results suggested that accurate extraction of inertial measurement unit orientation on the body is a key factor in improving the accuracy. Hence, a simple calibration protocol was proposed to reach a better approximation for inertial measurement unit orientation. Results After applying the protocol, the ankle, knee, and hip joint angle errors improved to 4 . 2 ∘ , 6 . 3 ∘ , and 8 . 3 ∘ , without the need for any other calibration. Conclusions Only a small subset of kinematic and sensor parameters contribute significantly to pose estimation accuracy when using body worn inertial sensors. A simple calibration procedure identifying the inertial measurement unit orientation on the body can provide good pose estimation performance.
A Comparative Study on the Implementation of Block Cipher Algorithms on FPGA

Advanced Encryption Standard(Rijindael) is a widely used algorithm for data security, but there are many notable block cipher algorithms which have not been widely adopted for usage. The algorithms such as Blowfish, Serpent, Twofish and RC6 were the top finalist of the AES contest but are not widely used. They have strong security features compared to that of AES and cryptanalysis of these algorithms are still difficult. These algorithms are realized on FPGA to carry out a comparative study on the timing, functional blocks and area requirements. This study helps understand different aspects of the algorithms and identify suitable applications with given limitations where they can be applied.
IMPLEMENTASI MODEL PBL (PROBLEM BASED LEARNING) UNTUK MENINGKATKAN HASIL BELAJAR DAN KEMAMPUAN BERPIKIR KRITIS SISWA

This research was aimed to improve the students’ learning achievement and critical thinking ability through problem based learning (PBL) model, the method which was applied in this research was classroom action research. It consisted of two cycles and each cycle consisted of planning, implementing, observing, and reflecting. The data was taken by giving the students test, it was in form of multiple choice test. The was used to know the students learning achievement to know students critical thinking, essay test was used. The finding of the research show that there was improvement from cycle to cycle. (1) at the first cycle: the percentage score of students mastery was 63.16% ; the mean score of the students critical thinking ability was 51.31 ; (2) at the second cycle : percentage score of the students mastery was 85% ; mean score of the students critical thinking ability was 72.08 and catagorized into critical and between 62.59 – 81.25. based on the finding, it can be concluded that problem based learning (PBL) model can improve the students learning achievement and critical thinking ability.
Marketing's Influence within the Firm

Although there is increased interest in marketing's changing role within the firm, there is little empirical research that measures the influence of marketing or links marketing's role to situational factors. Drawing on contingency and institutional theories of intraorganizational power, the authors address the following question: In what circumstances does the marketing subunit have higher levels of influence? Results from a survey among U.S. and German companies indicate that (1) the marketing subunit still has substantial influence, (2) marketing's influence is related systematically to determinants other than individual managers’ characteristics, and (3) institutional factors account for variance not explained by the determinants more commonly used in contingency theories in marketing. This implies that organizational dimensions are the result not only of adaptation to environmental conditions, but also of unique historical aspects that become institutionalized within the firm.
An investigation of capital investment and accounting information: evidence from Jordan

The study goal is to investigate the effect of cash specific accounting information on the capital investment decisions. To this end, the researcher used a prepared questionnaire to selected companies in Jordan. The main result of the study has shown that there is a significant effect of three kinds of accounting information, which are related to expected cash flows: 1) data on scrapped assets at the end of investment, 2) information on money coming in and out, and 3) information on cash saving by tax (outflows). Capital investment decisions show an increased consciousness by companies and have an importance of accounting information effect. This will significantly extend in the progress of capital investment decisions in companies. The main recommendation was to use the information on accounting, such as cash flows obtained from the asset at the end of their life. Also, information on cash coming in and out of companies, and information on cash saving by outflows (tax) have a significant effect on decisions related to capital investment.
A 0.2-V Energy-Harvesting BLE Transmitter With a Micropower Manager Achieving 25% System Efficiency at 0-dBm Output and 5.2-nW Sleep Power in 28-nm CMOS

This paper reports an ultralow-voltage (ULV) energy-harvesting bluetooth low-energy (BLE) transmitter (TX). It features: 1) a fully integrated micropower manager (<inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>PM) to customize the internal supply and bias voltages for both active and sleep modes; 2) a gate-to-source-coupling ULV voltage-controlled oscillator (VCO) using a high-ratio (5.6:1) stacking transformer to improve the phase noise and output swing; 3) an ULV class-E/F<sub>2</sub> power amplifier (PA) with an inside-transformer LC notch to suppress the HD<sub>3</sub>, and finally 4) an analog type-I phase-locked loop (PLL) with a reduced duty cycle of its master-slave sampling filter (MSSF) to suppress the jitter and reference spur. The TX prototyped in 28-nm CMOS occupies an active area of 0.53 mm<sup>2</sup> and exhibits 25% system efficiency at 0-dBm output at a single 0.2-V supply. Without resorting from any external components, both the output HD<sub>2</sub>–49.6 dBm) and HD<sub>3</sub>–47.4 dBm) comply with the BLE standard. The FSK error is 2.84% and the frequency drift in a 425-<inline-formula> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula> data packet is <5 kHz under open-loop modulation. The use of negative-voltage power gating suppresses the sleep power of the entire TX to 5.2 nW.
Investigating the Islamic and Conventional Mutual Fund Performance: Evidence From Malaysia Equity Market

The phenomena of financial crisis (2007-2008) shows a significant breakdown of US$16 trillion in conventional financial industry. This provides an opportunity for Islamic capital market to drive the global asset growth investments to investors. Previous studies signal mixture results on Islamic mutual fund (IMF) and conventional mutual fund (CMF) performance. This study aims to analyze the performance of 200 IMFs and CMFs from 2007 to 2015. The sub-sample period of 2007 to 2015 will be compared to the era of financial crisis from 2007-2008. Findings show all types of mutual funds are performed throughout 2007 until 2015. The results provide information that would benefit the investors and market players in asset funds selection.
Variational Sparse Coding

Unsupervised discovery of interpretable features and controllable generation with highdimensional data are currently major challenges in machine learning, with applications in data visualisation, clustering and artificial data synthesis. We propose a model based on variational auto-encoders (VAEs) in which interpretation is induced through latent space sparsity with a mixture of Spike and Slab distributions as prior. We derive an evidence lower bound for this model and propose a specific training method for recovering disentangled features as sparse elements in latent vectors. In our experiments, we demonstrate superior disentanglement performance to standard VAE approaches when an estimate of the number of true sources of variation is not available and objects display different combinations of attributes. Furthermore, the new model provides unique capabilities, such as recovering feature exploitation, synthesising samples that share attributes with a given input object and controlling both discrete and continuous features upon generation.
CORPORATE SOCIAL REPORTING IN MALAYSIA: A POLITICAL THEORY PERSPECTIVE

This study explores the influence of the government in the development Corporate Social Reporting (CSR) in the Malaysian context. It explains CSRdisclosure in annual reports of public listed companies using a political economy theory perspective. An examination of 201 annual reports ofMalaysian companies reveals the influence of the government in CSR disclosure. Generally, the reporting practice of the companies sampled support political economic theory since both variables used in this study, government shareholding and dependence on the government, were found to be significant. The findings indicate that the government has a potential to play a significant role in spearheading CSR practice more intensively, as companies that are dependent on the government or with significant government shareholding are institutionalized by the government’s aspiration and vision with respect to social and environmental issues. The findings reveal that employee and environmental themes are the most commonly disclosed information by those companies. Keywords: Corporate social responsibility, political economy theory, voluntary disclosure, Malaysia, CSR, government
Accrual and real earnings management in both state-owned and privately-owned Egyptian companies

This study aims to explore the difference between the level of both types of earnings management; Accrual Earnings Management (AEM) and Real Activity Earnings Management (REM)) between state and privately owned Egyptian companies. Using a sample of non-financial state and privately owned companies over the period from 2010 to 2017, with 1030 firm–year observations. The results reveal that there are no significant differences in the level of both AEM and REM using the two proxies; sales manipulation and discretionary expenses; between state and privately owned firms. This result could be attributed to the Egyptian government’s attempt to eliminate the differences between state-owned and private owned companies, especially in recent years.
Neural machine translation system for the Kazakh language

“Development and research of the Kazakh language neural machine translation system” is a 3-year-long project funded by the Science Committee of Ministry of Education and Science of the Republic of Kazakhstan. The project is being executed by the team of the Laboratory of Intelligent Information Systems at the Research Institute of Mathematics and Mechanics of al-Farabi Kazakh National University. Duration of the project: January 2018 – December 2020.
Seeds of change: How current structure shapes the type and timing of reorganizations

Research Summary This article develops theory on how an organization's structure affects future reorganizations. I highlight that a firm's structure shapes not only the locus of decision‐making power (i.e., centralization and decentralization) but also the employees' interaction structure. I develop microlevel theory that connects the firm's structure to the interactions among its employees—for instance, its influence on the time employees spend adjusting their behavior after a reorganization. This theory predicts that some structures are more likely than others to promote a reorganization to occur sooner. I use a unique, hand‐collected data set of reorganizations in the cell‐phone manufacturing industry to test and find directional support for this theory. Managerial Summary I examine the effect of a firm's current structure on its corporate reorganization decisions, which are defined as the addition and/or removal of business units. I posit that the way employees are grouped into those business units may affect both the type and timing of subsequent reorganizations; the reason is that employees of similar (resp. different) backgrounds should need less (resp. more) time to achieve effective collaboration. Using data on the reorganizations of cell‐phone manufacturing firms during 1983–2008, I find directional support for the theory. This result implies that managers may need to watch closely any reorganization that shifts the firm toward more heterogeneous interaction structures—because its implementation may well require additional time.
Independent directors and corporate investment: evidence from an emerging market

Purpose The purpose of this paper is to examine whether independent directors reduce corporate overinvestment and improve investment efficiency in an emerging market. Design/methodology/approach First, the author developed a research model in which corporate investment is a function of Tobin’s Q, the proportion of independent directors in the board and an interaction between them. Second, the author divided the full sample into groups of firms with a low- and high-financial constraint to compare the effects of independent directors between financially unconstrained and constrained firms. Findings With a full sample of 1,281 observations collected from 193 firms listed in Ho Chi Minh Stock Exchange during the period from 2009 to 2017, the author find that the proportion of independent directors is negatively related to firm investment but its interactive term with Tobin’s Q is positively related to corporate investment. These findings imply that independent directors can help firms reduce overinvestment and improve investment efficiency. Moreover, the research findings indicate that these effects of independent directors are stronger for financially constrained firms. Originality/value The extant literature shows that independent directors are an effective mechanism to reduce agency problems in firm decisions and operating performance. However, there has been no research on the role of independent directors in corporate investment policy.
DEVELOPMENT OF DRY PORT MODE OF LOGISTICS TRANSPORTATION CHOICES

This paper is aims to find out the preferred behavior of logistic business actors for using dry-port with rail-transport. The methodology of research was conducted by field survey randomly to logistic entrepreneurs in big cities at around Java with rail-network facilities, find the behavior of dry-port users for train reaching is less of numbers expectation, the remaining ispreferring use transport by road. This research limitation just taking respondents as many as 214 respondents, each of participants is considered to have same of knowledge about dry-port on transportedthem owned of goods, and expect of respondents to be representative the population. Finally founded the tendency of logistic business actors in Java to choose road/truck-transport in goods distribution activities, so have opportunity to use trains is still open, but it takes understanding and hard work to convince logistic actors.