Miracle-dz/UniFAR-FTUs huggingface dataset:
An innovative maturity model to assess supply chain quality management

Purpose – This paper aims to presentand discuss an innovativematurity model (MM) to assess supply chain quality management (SCQM). The SCQM MM can be used to guide organizations in the development and improvement of quality in their supply chains (SCs). Additionally, this paper intends to better understand that integration and its impacts on organizational performance. Design/methodology/approach – The proposed MM was developed based on an exhaustive literature reviewofthemostrelevantMMsdevelopedintheareasofqualitymanagement,supplychainmanagementand otherrelevantdomains. Findings – The proposed MM consists of a matrix with 100 criteria organized in five organizational dimensions and five maturity levels, embracing the most relevant SC issues and describing a progressive path towards a state of full maturity. Originality/value – It is an innovative tool useful for both academic experts and practitioners to integrate quality management across the SC, thus promoting and improving organizational performance from an integrated and sustainable perspective.
A Review of Big Data Resource Management: Using Smart Grid Systems as a Case Study

Big data has recently been a prominent topic of research due to the exponential growth of data every year. This massive growth of data is causing problems with resource management. The available literature does not address this problem in depth. Therefore, in this article, we aim to cover the topic of resource management for big data in detail. We addressed resource management from the perspective of smart grids for a better understanding. This study includes a number of tools and methods, such as Hadoop and MapReduce. Large data sets created by smart grids or other data-generating sources may be handled using such tools and approaches. In this article, we also discussed resource management in terms of various vulnerabilities and security risks to data and information being transmitted or received, as well as big data analytics. In summary, our comprehensive study of big data in terms of data creation, processing, resource management, and analysis gives a full picture of big data.
North American Free Trade Agreement Truck Highway Corridors: U.S.-Mexican Truck Rivers of Trade

The dramatic growth in trade between the United States and Mexico from $12.39 billion to $56.8 billion of U.S. exports and $17.56 billion to $73 billion of U.S. imports between 1977 and 1996 and the implementation of the North American Free Trade Agreement (NAFTA) have focused attention on the impact that the truck-transported portion of this trade has on U.S. highways. State and federal highway administrators are concerned with the planning implications this additional unexpected traffic may have on the transportation infrastructure. Public advocacy groups want additional highway funds to promote one NAFTA highway corridor over others in an effort to stimulate additional economic development. Most of these groups advocate a north-south route through the United States between Canada and Mexico that follows the alignment of an existing federal highway number. Research conducted by the U.S. government under the 1991 Intermodal Surface Transportation Efficiency Act has failed to define NAFTA highway corridors adequately, leaving policy makers with little concrete information with which to combat the rhetoric of the trade highway corridor advocacy groups. A report is provided on research critical to the needs of both highway administrators and corridor advocacy groups, namely, the location of U.S.-Mexican trade highway corridors and the trade truck density along these corridors.
Shwas: A Smartphone based Augmentative and Alternative Communication (AAC) System which Converts Breath into Speech

To make Augmentative and Alternative Communication (AAC) devices accessible to everyone, I present Shwas. AAC device is used by people suffering from developmental disabilities like cerebral palsy, intellectual impairment, autism, ALS, etc. The life expectancy of such people is expected at 20 years below average, mainly due to absent or inadequate communication. The AAC devices which are available now are expensive and heavy. This paper presents a novel technique of communication using the smartphone. Shwas is a smartphone application which converts the breath of the user into speech. The application uses breath input in the form of Morse code and converts it into audible speech or visible text which can then be used for communication.
An Adaptive Reclosing Scheme Based on Phase Characteristics for MMC-HVDC Systems

To improve the reliability of power supply, reclosing schemes are required after transient faults, which commonly occur in overhead line based high voltage DC (HVDC) systems. However, in the event of permanent faults, the auto-reclosing scheme may cause a severe strike. To avoid the severe impacts caused by permanent faults, the fault type should be discriminated before activating the reclosing scheme. Therefore, an adaptive reclosing scheme based on phase characteristics is proposed in this paper. Firstly, the modulation of a periodic voltage by actively controlling the hybrid DC circuit breaker (DCCB) is introduced. Then, a cascaded π equivalent model and its decoupling algorithm are presented to analyze the frequency-domain characteristics of the measured impedance of the coupled overhead lines. From the frequency-domain characteristics, the frequency of the periodic detecting voltage is determined to analyze the phase features of the measured impedance at primary frequency. The permanent or transient faults can thus be accurately identified by using these different phase characteristics, with negligible influence on the healthy lines. In addition, the proposed scheme is robust to various fault resistances, leading to improved reliability. The effectiveness of the proposed scheme is verified in PSCAD/EMTDC.
A survey of faults on induction motors in offshore oil industry, petrochemical industry, gas terminals and oil refineries

The report presents a survey of the reliability of squirrel cage motors on board drilling, production and other platforms offshore, together with cage motors in the petrochemical industry, gas terminals and refineries onshore. Most of the activity in this connection is related to the North Sea that offers a tough environment for motors. The collected data have been treated statistically, and the faults sorted according to supply and motor data, driving conditions, maintenance and so on. Comparisons between this survey and a survey from the IEEE have been carried out. The report also pays some attention to methods for monitoring of machinery and detection of faults. <<ETX>>
International Journal of Science and Business

Machine Learning is a significant technique to realize Artificial Intelligence. The Random Forest Algorithm can be considered as one of the Machine Learning’s representative algorithm, which is known for its simplicity and effectiveness. It is also can be defined as a Decision Tree-Based Classifier that chooses the best classification tree as the final classifier's classification of the algorithm via voting. Random Forest is the most accepted group classification technique because of having excellent features such as Variable Importance Measure, Out-of-bag error, Proximities, etc. Currently, it is in the new classification, intrusion detection, content information filtering, and sentiment analysis that is why there is an extensive range of applications in image processing. In this paper, the construction process of Random Forests and the study status of Random Forests would primarily be introduced in terms of capacity enhancement and performance indicators. The use of Random Forest in different fields such as Medicine, Agriculture, Astronomy, etc. is often mentioned. IJSB Literature review Accepted 24 January 2021 Published 27 January 2021 DOI: 10.5281/zenodo.4471118
DESIGN AND ANALYSIS OF THE CMOS COMPATIBLE PRESSURE SENSOR USING FLIP CHIP AND FLEX CIRCUIT BOARD TECHNOLOGIES

Graduate Assistant, Ph.D candidate In this study, a silicon base piezoresistive pressure sensor using flip chip and flex circuit packaging technologies is studied, designed and analyzed. A novel designed pressure sensor using flip chip packaging with spacer is employed to substitute the conventional chip on board or SOP packaging technology. Subsequently, a finite element method (FEM) is adopted for the designing of the sensor performance. Thermal and pressure loading is applied on the sensor to study the system sensitivity as well as the thermal and packaging effect. The performance of novel packaging pressure sensor is compared with that of the conventional one to demonstrate the feasibility of this novel design. The findings depict that this novel packaging design can not only maintain well sensor sensitivity but also reduce the thermal and packaging effect of the pressure sensor.
Stator current harmonics and their causal vibrations: a preliminary investigation of sensorless vibration monitoring applications

This paper presents an initial study into the relationship between vibration and current harmonics of electric motors, including the effect of externally induced vibrations. This relationship was investigated experimentally on both new motors, on a vibration stand, and a motor with bearing wear. Both theory and experimental results show that a change in the RMS value of the stator current is directly related to the change in vibration magnitude, for a known vibration frequency. The paper shows this result both for a new motor with an externally induced vibration and for a motor with vibration caused by progressive bearing wear.
Selection of inspector for visual inspection

SUMMARY This paper presents a statistical method for selecting the best inspector for visual inspection having the highest defect-finding ability among k(≥2) prospective inspectors. A sample containing known number of defects are submitted to each of k prospective inspectors. As the sample size is increased, sampling variation decreases so that we have a better chance of selecting the truly best inspector, but at the same time the cost of sampling is also increased, The problem is how to determine the sample size required for selecting the best inspector with specified probability P*. This problem is formulated from the indifference zone point of view with an application of the loss function which takes into consideration the opportunity cost of making a wrong selection and the cost of sampling. Minimax solution is obtained under the restriction that the best inspector is to be selected with the specified probability P*. The selection procedure is applied to the visual inspection of car body painting.
Robustness Compensation Control of Simulation Loading System Based on Secondary Regulation

This study investigated a mathematical model which was built for a simulation loading system based on secondary regulation. Because the loading system was complicated in structure and some other factors, the control performance was not ideal. Therefore, a dynamic robust compensating controller was designed for the system. The robust compensator could improve the control system by adding the return-to-zero factor and low pass filter on the basis of PID control. This study used MATLAB to simulate the general PID control and the robust compensation control. The results of simulation showed that when the equivalent rotary inertia and damping coefficient changed, the control performance decreased. When using the dynamic robust compensation control, the influences caused by parameter variations were reduced greatly, the system robustness and control accuracy are improved.
Reiteration as an Instance of Lexical Cohesion in theQur'anic Discourse: The Case of At-Takweer Surah

As one of thecohesive devices in the development of discourse, “reiteration”has been considered as an effective textual strategy involving any unit of atext, such as morphemes, words, phrases, clauses, or sentences, as various means ofachieving emphasis, clarity, continuity, multiplicity, or textual integrity. Reiteration can even be extended as a method of contributing to the progress anddevelopment of ideas. But, if used unskillfully, it could simultaneouslyproduce redundancy, monotony, or even banality. Several studies have indicated that reiteration of words and utterances is one of the distinctive textual features of The Holy Qur'an(cf. for instance, Abdul-Raof, 2006, Saffarzaddeh, 2004). The present study hasaimed to investigate different forms of reiterationand the types of function they serve in The Qur'anic discourse, in general, and in a single Qur'anic Surah (i.e., At-Takweer), in particular. Our intention has been to examine not only the cohesive functions that reiterations as instances of lexical cohesion serve, but also to investigate the rhetorical effects produced as a result of reiterating utterances in the entire discourse
Forward osmosis: understanding the hype

Abstract The scientific interest in forward osmosis has increased dramatically over the last decade. The hype has resulted in a high scientific production, but research activities seem to go in all directions, and the real benefits of the process are not always well understood. This paper aims to give some directions based on the current state of the art. Without going into details about the process itself, the current research lines and their background are described. While some of these are important, others – notably the search for alternative draw solutions – have become the Holy Grail of forward osmosis. The further analysis of the process is based on suggested applications and uses the observations made on contemporary research topics in the field. At first, direct application of forward osmosis for potable water production is considered. This leads back to the research challenges of the reverse draw solute flux, concentration polarization, and the regeneration of the draw solution. Special attention is given to desalination, as forward osmosis is often incorrectly denoted as a desalination technology. It can be used in the context of desalination; however, the question remains in which applications this is of interest. Combining desalination and wastewater treatment is one such interesting application, which is further described in this paper for some types of wastewater found in the literature. In the last part, the paper emphasizes the need to develop processes in which the challenge of the draw solution is intrinsically solved. The foremost example of such application is the one for which forward osmosis was developed four decades ago: the use of impaired water sources diluted through a forward osmosis membrane by using a concentrated fertilizer solution to provide osmotic pressure. This application was suggested four decades ago but was never applied on any scale. Process economics and an insufficiently developed technology may have been the basis of this failure. However, a renewed focus on such applications would allow forward osmosis to come to its real potential and contribute to solving the global water challenge.
Window-temperature measurements on a high-power gyrotron with an internal, quasi-optical converter

Window-temperature measurements on a double-disc sapphire window have been performed during a series of high-power, long-pulse tests of a 110 GHz, internal-converter gyrotron using a 10-/spl mu/m, infrared camera. Details of the infrared-imaging setup will be discussed and the results obtained will be presented. From these measurements, loss-tangent and film-coefficient values used in calculations can be verified.
Survey on the usage of total quality management tools and techniques in Indian service industries: an empirical analysis

This study focuses on the state of usage of quality tools and techniques in Indian service industries. To achieve this objective, a comprehensive instrument was constructed and distributed to select Indian service companies. The usage of quality tools and techniques was surveyed and then analysed. The study sample consists of a group of 172 selected Indian service companies from various industries like healthcare, information and communication technology (ICT), banking, and hospitality. The survey findings revealed that usage of tools and techniques for quality improvement in Indian service companies is low and majority of the Indian service industries implement easiest and simple to use quality tools and techniques. The survey also showed some areas for further improvement like usage of advanced and complex quality tools such as 5-’S’, Pareto analysis, Kaizen activities, and business process reengineering (BPR) which are barely used. Further, some managerial implications and future scope of this study are also reported at the end.
Association of Neuregulin Levels and Neuregulin-1 Polymorphism with Short-term Morbidities in Preterm Neonates

Background Premature birth is linked to neonatal morbidity and mortality worldwide. Neuregulin (NRG) is a trophic factor from the growth factor (GF) of a transmembrane polypeptide, encoded by four different genes, including NRG-1 which acts as an endogenous protector in fetal development. Decreased levels of NRG-1 affect several organs. The relationship between NRG-1 polymorphism and the outcome of neonatal development has been widely studied. There are no studies that have assessed NRG-1 levels and NRG-1 rs35753505 C/T polymorphism in preterm neonates, as well as its association with short-term morbidities in Indonesia.Methods This cross-sectional study was conducted on preterm neonates with the gestational age of 32-36 weeks in Medan, North Sumatera, Indonesia, from December 2017 to December 2018. It aimed to evaluate the association of NRG-1 levels and NRG1 polymorphism with short-term morbidities. Samples were obtained from cord blood specimens. Enzyme-linked immunosorbent assay (ELISA) was used to determine NRG-1 levels, and NRG-1 polymorphism was sequenced by polymerase chain reaction (PCR). Observations in preterm neonates were made during the first 72 h to assess short-term morbidities.Results During the study period, 48 cord blood specimens from preterm neonates were found eligible for analysis. Preterm neonates with low NRG-1 levels had a 10-times higher risk of developing short-term morbidities. The presence of CC and CT genotypes increased the risk of developing short-term morbidities 13.33 times (P=0.003) and 6.19 times (P=0.019), respectively. The presence of the C allele in subjects' genotype increased the risk of short-term morbidities 4.04 times (P=0.001), compared to those with T allele.Conclusion As evidenced by the obtained results, preterm neonates with low NRG-1 levels had a higher risk of developing short-term morbidities. Furthermore, there was a significant association between NRG-1 rs35753505 C/T polymorphism and short-term morbidities.
Cloud Security using Supervised Machine Learning

Cloud computing is gaining significant attention, however, security is the biggest hurdle in its wide acceptance. Users of cloud services are under constant fear of data loss, security threats and availability issues. Recently, learning-based methods for security applications are gaining popularity in the literature with the advents in machine learning techniques. However, the major challenge in these methods is obtaining real-time and unbiased datasets. Many datasets are internal and cannot be shared due to privacy issues or may lack certain statistical characteristics. As a result of this, researchers prefer to generate datasets for training and testing purpose in the simulated or closed experimental environments which may lack comprehensiveness. Machine learning models trained with such a single dataset generally result in a semantic gap between results and their application. There is a dearth of research work which demonstrates the effectiveness of these models across multiple datasets obtained in different environments. We argue that it is necessary to test the robustness of the machine learning models, especially in diversified operating conditions, which are prevalent in cloud scenarios. In this work, we use the UNSW dataset to train the supervised machine learning models. We then test these models with ISOT dataset. We present our results and argue that more research in the field of machine learning is still required for its applicability to the cloud security.
Governance Mechanisms for Federated Digital Platform Ecosystems

This paper defines governance factors and mechanisms for complex, federated digital platform ecosystems, characterized by a variety of interaction models among various stakeholders that have different motivations and incentives to participate in an ecosystem. The proposed governance framework is compared with the recent research in platform ecosystem governance design, and further structured into five areas to allow for a coherent policy acquisition and modelling across the platform consortium. The proposed governance framework addresses both data-and service-driven policy mechanisms, including emerging mechanisms caused by the recent changes of public policies created to balance ethical frameworks of platform companies, transparency reporting, fairness and algorithm transparency, responsibility, etc. Furthermore, a holistic federated governance architecture to be implemented for the enforcement of major governance mechanisms is presented in the paper. The motivation to explore the governance mechanisms for federated digital platform ecosystems, relates to the design and implementation of an innovative, federated industrial platform ecosystem currently developed in the European H2020 Research and Innovation Programme.
Extraction of Different Types of Geometrical Features from Raw Sensor Data of Two-dimensional LRF

This paper describes extraction methods of five different types of geometrical features (line, arc, corner, polynomial curve, NURBS curve) from the obtained raw data by using a two-dimensional laser range finder (LRF). Natural features with their covariance matrices play a key role in the realization of feature-based simultaneous localization and mapping (SLAM), which can be used to represent the environment and correct the pose of mobile robot. The covariance matrices of these geometrical features are derived in detail based on the raw sensor data and the uncertainty of LRF. Several comparison are made and discussed to highlight the advantages and drawbacks of each type of geometrical feature. Finally, the extracted features from raw sensor data obtained by using a LRF in an indoor environment are used to validate the proposed extraction methods.