Miracle-dz/UniFAR-FTUs huggingface dataset:
EFFECTIVENESS OF DIGITALIZATION IN HRM: AN EMERGING TREND

Increasing use of digital tools in Human Resource practices by employers has grabbed the attention of researchers, academicians, and strategists all over the world. Several studies have been done which described the application of information technology in various practices of human resource and justified its impact on organizational effectiveness. The study aims at providing an analysis of the most relevant contributions related to the use of digital tools in HR and its advantages to employers which enable them to grow their organizations into dynamic and high-performance organizations. The study focuses on the recent literature on effectiveness of digitalization in HR and provides some conclusions and directions for future research.
Real-Time Object Detection in Occluded Environment with Background Cluttering Effects Using Deep Learning

Detection of small, undetermined moving objects or objects in an occluded environment with a cluttered background is the main problem of computer vision. This greatly affects the detection accuracy of deep learning models. To overcome these problems, we concentrate on deep learning models for real-time detection of cars and tanks in an occluded environment with a cluttered background employing SSD and YOLO algorithms and improved precision of detection and reduce problems faced by these models. The developed method makes the custom dataset and employs a preprocessing technique to clean the noisy dataset. For training the developed model we apply the data augmentation technique to balance and diversify the data. We fine-tuned, trained, and evaluated these models on the established dataset by applying these techniques and highlighting the results we got more accurately than without applying these techniques. The accuracy and frame per second of the SSD-Mobilenet v2 model are higher than YOLO V3 and YOLO V4. Furthermore, by employing various techniques like data enhancement, noise reduction, parameter optimization, and model fusion we improve the effectiveness of detection and recognition. We further added a counting algorithm, and target attributes experimental comparison, and made a graphical user interface system for the developed model with features of object counting, alerts, status, resolution, and frame per second. Subsequently, to justify the importance of the developed method analysis of YOLO V3, V4, and SSD were incorporated. Which resulted in the overall completion of the proposed method.
Genetic Algorithm Based Automatic Layer Selection of Transfer Learning for Object Detection

A method for automatic re-learning layer selection based on a genetic algorithm is proposed to solve the difﬁculty of conventional transfer learning of deep learning-based object detection models. The ge-netic algorithm of the proposed method can select the re-learning layers automatically in the transfer learning process instead of a trial-and-error selection of the conventional method. A transfer learning experiment from the COCO dataset to the Global Wheat Head Detection (GWHD for short) dataset was performed using ﬁne-tuning and the proposed method, and the results were compared. Using the training data and the validation data of the GWHD, we compare the mean average precision of the models trained by the conventional and the proposed methods, respectively, on the test data of the GWHD. It is conﬁrmed that the model trained by the proposed method has higher performance than the model trained by the conventional method. The average of mAP of the proposed method, which automatically selects the re-learning layer ( ≈ 0.603), is higher than the average of mAP of the conventional method ( ≈ 0.594). Furthermore, the standard deviation of results obtained by the proposed method is smaller than that of the conventional method, and it shows the stable learning process of the proposed method.
Body-Biased VCO Tunes 12 To 16 GHz

This body-biased voltage-controlled oscillator provides reasonably good phase- noise performance over a broad tuning range with relatively low power consumption and low jitter timing noise in the time domain. Voltage-controlled oscillators (VCOs) are an integral part of frequency synthesizers using phase-locked loops (PLLs) and clock and data recovery (CDR) circuits. 1 Phase noise is one of the most critical characteristics of the wireless communication systems and it is based on static behavior in the device oscillation. 2 In wireless communication systems, wide bandwidths with reliable phase noise performance is extremely critical; hence the phase noise performance has been improved by number of novel VCO structures. 1-6 In this article, a novel dynamic-threshold (DT) metal-oxide-semiconductor (MOS) (DTMOS) technique has been applied to increase the operating bandwidth of a VCO by reducing the threshold voltage (VT) of a PMOS load transistor to achieve faster transitions and higher operating frequencies. The three-stage VCO has a center frequency of 14 GHz with tuning range of 12 to 16 GHz and phase noise of -101 dBc/Hz offset 100 kHz from the carrier. In this novel VCO design, the reduction of threshold voltage VT results in an exponential increase in the static power. This is a drawback in silicon-based technologies, 3 but having dynamic control over VT can be a benefit in some oscillator designs. It helps overcome supply variations and noise injection, 4 and eliminate parasitic capacitors in the transistor (gate-source, gate-base, and gate-drain capacitances CGS, CGB, and CGD, respectively)— and device body effects when the PMOS transistor is turned off. This control can lead to broadband VCO tuning. The DTMOS approach works best with a low voltage supply; as a result, it is ideal for high-frequency applications requiring a low-voltage supply.
MODELLING COASTAL WETLAND STABILITY

The size and number of coastal wetlands in the Great Lakes have been rapidly declining over the past century, but only in the past two decades have people begun to understand the complex environmental and biological benefits of these fresh water marshes. Recently, bioengineering techniques have been adapted as an integral functioning part of shore protection schemes. Constructed wetlands are prime examples of additions to shore protection schemes that provide ancillary benefits such as water quality improvements and the provision of a buffer zone and a rich biologically diverse sanctuary for terrestrial and aquatic species. The focus of most wetland studies has been related to biological aspects and, to a lesser degree, their hydrology. Little research has been conducted from a coastal science and engineering perspective, especially with regard to wave-exposed shoreline vegetation. This paper describes a recent study undertaken to examine common Great Lakes emergent shoreline aquatic plants in order to as.
CLASSROOM ENVIRONMENT AND ACADEMIC ACHIEVEMENT

The study is aimed to determine the relationship between classroom environment and the academic achievement. The respondents were 55 third year Radiologic Technology students enrolled in Cebu Doctors’ University. They were made to rate their classroom environment by answering the Classroom Environment Assessment Tool formulated by the researcher. The final grades of the students in each major course were used to determine the level of academic achievement. The study utilized the descriptive correlational design to determine the relationship between the classroom environment and the academic achievement. It was found out that there was a significant correlation between the physical environment and the students’ academic achievement in Computed Tomography Scan. The result showed that as the quality of the physical environment increased, the academic achievement of the student also increased. There was a significant correlation between the emotional climate and the Nuclear Medicine students’ academic achievement. The findings suggest that the physical environment slightly influenced the academic achievement of the students in Radiologic Technology.
The performance impact of implementing Web-based e-procurement systems

As Web-based e-procurement has become an important business avenue for the improvement of inter-organisational process efficiency, its implementation for purchasing direct materials nevertheless implies establishing collaboration mechanism among supply chain participants based on the adopted Internet based infrastructure. However, the value of Web-based procurement to the supply chain participants remains an arduous task for researchers. This study proposes a Web-based e-procurement impact model based on supply chain orientation, which includes both operational and strategic impacts. Specifically, the strategic dimension is about partner relationship, and the operational efficiency dimension includes supplier performance, buyer performance, process integration, and process automation. To prove the proposed model's contribution, a questionnaire survey was conducted on 137 firms in Taiwan who have all participated in e-procurement related projects. The results verify that the electronic execution of purchasing activities improves both the operational efficiency dimension and the strategic dimension. Furthermore, partnership has a positive impact on supplier performance and buyer performance.
Learning Fast-Inference Bayesian Networks

We propose new methods for learning Bayesian networks (BNs) that reliably support fast inference. We utilize maximum state space size as a more ﬁne-grained measure for the BN’s reasoning complexity than the standard treewidth measure, thereby accommodating the possibility that variables range over domains of different sizes. Our methods combine heuristic BN structure learning algorithms with the recently introduced MaxSAT-powered local improvement method (Peruvemba Ramaswamy and Szeider, AAAI’21). Our experiments show that our new learning methods produce BNs that support signiﬁcantly faster exact probabilistic inference than BNs learned with treewidth bounds.
Modified Widman Flap Surgery: At A Glance

There are numerous surgical procedures of which modified Widman flap is a standard procedure for open debridement. It was given by (Widman 1918, Ramfjord & Nissle 1974, Ramfjord 1977). It is classified as access flap operation as the main goal of this is to provide access and visibility to the periodontally involved tissues. It is characterized by precise incision, partial flap reflection with an atraumatic procedure. The main aim is to provide healing (regeneration or long junctional epithelium formation) and not necessarily pocket elimination. Post-operative pain and swelling are minimal as the as the alveolar bone is partially exposed. This article gives an outline about the history, indications, contraindications, advantages, disadvantages, procedure and the healing.
THE IMPACTS OF THE INDUSTRIAL REVOLUTION 4.0 ON THE ISSUE OF EMPLOYMENT AND REQUIREMENTS FOR UNIVERSITIES ON THE TRAINING OF VIETNAMESE HUMAN RESOURCES

The industrial revolution 4.0 with new technologies has changed the production platform and the nature of many industries. In addition to the emergence of new occupations, the world has also witnessed the loss of certain specific, repetitive jobs and increasingly demanding types of quality human resources. Therefore, the research about the impact of the fourth industrial revolution on jobs and the necessity for training high quality human resources in universities is a meaningful and necessary. The paper first analyzes the positive and negative impacts of the industrial revolution 4.0 on the jobs, followed by some recommendations for universities in identifying key training areas, future-oriented training fields, especially the training programs associated with the technology 4.0, and strengthening cooperation between universities and enterprises in training human resources, at the same time, developing soft skills for students to meet the human resources for the digital era.
The influence of non-governmental organizations (NGOs) on the development of voluntary sustainability accounting reporting rules

Purpose –The purpose of this paper is to show the impact that non-governmental organizations (NGOs) have on the evolution of Global Reporting Initiative (GRI). GRI is a sustainability report disclosed by business organizations to meet the demands and interests of various stakeholders. These stakeholders’ needs have influenced GRI and its guidelines. Design/methodology/approach – The methodology for this paper is library-based archival research. It is qualitatively and analytically descriptive of prior academic research and published literature on the subject. Findings – Sustainability accounting rulemaking has evolved overtime resulting in proliferation of reporting rules. These rules have improved the extent and scope of environmental and economic performances that businesses disclose in GRI. Originality/value – GRI has provided the foundation for integrated reporting (IR). Both GRI and IR have ecological and functional dimensions. Sustainability is functionally inherent in the accounting principle of materiality, when disclosed in external reporting. The ongoing concern of business assumes an organization is systemic and operates as a living entity only when it can provide sustainable performance that benefits stakeholders and society.
Use Case: Smart Contract for Lease Agreements using Blockchain Technology

- A blockchain Technology is a peer to peer distributed ledger counterfeit by consensus, combined with a system for smart contracts. Its uses peer to peer network architecture to connect each other, without a central authority. Blockchain has established from many industries, researchers and government bodies. This paper aims to present the Blockchain and smart contract for a specific domain which deals with real estate for solving issues like avoiding Third-parties, Brokerage service, Trusty Transaction, Settlement in between landlord and Tenant, etc. A complete overview and designing of Decentralized application with smart contract is obtainable and then implementing use case for leasing/ renting residential and business buildings is examined.
Computer Vision-based Monitoring and Safety Early Warning System for Gymnasiums

In order to ensure that the security team can timely and effectively deal with the emergency and all the competitions of the 2022 Beijing Winter Olympic Games went on smoothly, this paper focuses on how to apply multi-person pose estimation to the security ﬁeld with the support of target detection, pose feature classiﬁcation and behavior recognition algorithm. The main approach is to combine OpenPose key pose estimation with SVM classiﬁer to develop the monitoring and safety early warning system for the dangerous behaviors of the audience. By identifying the key joint points of the human body, extracting motion characteristics and making use of the trained classiﬁer, the system can automatically pull the alarm when audience has abnormal behaviors such as throwing objects towards athletes, so that the security team can quickly deal with the emergency.
A COMPARISON OF NEONATAL THYROID PARAMETERS OF CORD BLOOD AND NEWBORN VENOUS BLOOD AMONGST NEW-BORNS OF AVMC

Background: Hypothyroidism may be congenital or may be acquired which might or may not have a delayed onset. Incomplete thyroid development and decreased thyroid hormone biosynthesis is a result of congenital hypothyroidism. Screening is usually missed in areas where testing is not done and is the reason for new cases of hypothyroid cases. India has a higher incidence of neonatal hypothyroidism. Aim: To evaluate whether cord blood can be used as a primary thyroid screening tool. Method: The study was taken up in the department of pediatrics of a tertiary teaching hospital. A total of 200 babies were taken for the study during the whole study period. The cord blood at the time of delivery and 48-hour serum blood was collected and sent to the lab for thyroid profile estimation. Results: The study consisted of 106 males and 94 female infants. Among the 200 subjects, 167 were term babies and 33 were preterm. The mode of delivery was 77.5% had lower segment cesarean section and the remaining 22.5% were normal deliveries. The mean birth weight was 2.810 kgs. The mean TSH 6.99±4.81, the mean T3 level was 80.43±39.06 and the meanT4 level among the subjects was 10.90±4.59. The systemic venous blood was collected after 48 hours for thyroid profiling. The mean TSH was 4.65±4.03, the mean T3 level was 114.205±38.27 and the mean T4 level among the subjects was 13.89±5.60. On comparison of cord blood, TSH and systemic venous blood TSH association were noted which was statistically significant. Association was between cord blood T3 and 48-hour venous blood was present and statistically significant. Cord blood for T4 and venous blood for T4 association was seen and statistically significance present. Conclusion: from the present study, it can be suggested cord blood can be used as a marker for thyroid screening tool.
Kriging-based heuristic optimization of a continuous concrete box-girder pedestrian bridge

The structural optimization aims to determine the best solutions for the project objectives while guaranteeing the structural constraints. The heuristic algorithms follow an intelligent process in which the design variables are modified for the purpose of optimizing the objective function and verify the constraints. Methodologies like metamodel-based design optimization or surrogate-based optimization carry out a pseudooptimization applicable to structures. The kriging method provides a response surface from the sample that can be optimized. In this paper, conventional heuristic optimization and kriging-based heuristic optimization are applied to the same case study. This case involves a continuous box-girder pedestrian bridge. The comparison of the methodologies shows the advantages and disadvantages of both methodologies. Furthermore, a major compression of both processes gain a better understanding of the methods and the most suitable cases.
RF bandwidth capacity and SCM in a radio-over-fibre link employing optical frequency multiplication

We demonstrate the feasibility of generating two 24 Mbps 64-QAM radio signals simultaneously at 17.3 GHz and 17.8 GHz after 4.4 km of multimode fibre in an OFM radio-over-fibre link for wireless multistandard support at the antenna site. (2 pages)
PETROLOGY AND STABLE ISOTOPE SYSTEMATICS OF MIGMATITES IN PINKHAM NOTCH, NEW HAMPSHIRE

Migmatite is a textural term used to describe very heterogeneous metamorphic rocks consisting of intermingled light-colored material (leucosomes), dark-colored material (melanosomes) and intermediate material (mesosomes). The obvious question is how do these rocks form, and under what conditions? Since Tuttle & Bowen’s (1958) experiments in the Granite System, the conventional wisdom has been that migmatites form as a result of anatectic partial melting processes (e.g., Winkler, 1979). However, leucosomes from many migmatites—including those in New Hampshire—do not have granitic minimum melt composition, containing quartz and albitic plagioclase but no K-feldspar (although muscovite is usually present; Dougan, 1979; Eusden, 1988; Allen, 1992). It is now generally recognized that other processes besides anatectic partial melting can play a role in forming migmatites, including sub-solidus differentiation, metasomatism, and injection of melt derived elsewhere (Ashworth, 1985; Olsen, 1985).
COVID-19 vaccine acceptability, determinants of potential vaccination, and hesitancy in public: A call for effective health communication

BACKGROUND: Coronavirus disease rapidly spreads across the entire world in < 2 months and gravely jeopardizes the regular human routine. The medical fraternity recommends a vaccine as one of the best solutions to save the universe. However, to be effective, the population should reflect an encouraging attitude to accept it. The study aimed to measure vaccine acceptability and reason for hesitancy among the public. MATERIALS AND METHODS: Eight hundred and forty one adults visiting a tertiary care hospital responded to a pretested validated questionnaire on vaccine acceptability and hesitancy. The Chi-square test and independent t-test, followed by multinomial logistic regression, were used to analyze the findings. RESULTS: Overall, 53.4% (n = 445) of participants interested to take vaccine, 27.2% (n = 229) were not sure, and the remaining 19.4% (n = 163) did not intent to vaccinate. Gender (P = 0.013), information on the vaccine (P = 0.022), chances to get coronavirus disease in the next 6 months (P < 0.001), awareness on India COVID-19 vaccine (P < 0.001), Indian manufacturing company of vaccine (P < 0.001), family history of the laboratory-confirmed case (P < 0.001), and health status (P = 0.011) found a significant association with intention to vaccination (a response “yes” vs. “no” and “not sure”). Reasons for vaccine hesitancy included specific antivaccine attitudes and beliefs, a concern of fear and phobia, lack of information, and safety issues on the vaccine. CONCLUSIONS: This institute-specific survey revealed that approximately every 4 in 8 people were not sure to take the vaccine, and one in five people refused to be vaccinated. The study recommends using target-based health education to understand and address vaccine-specific concerns to enhance vaccine coverage, and boost confidence among the population.
Rotated multidimensional modulation for spatial multiplexing systems

In this paper, we consider a spatial multiplexing (SM) system combined with rotated multidimensional QAM mapping, which can improve system reliability without spending additional power or bandwidth consumption under fast Rayleigh flat fading channels. Based on the pairwise error probability of the spatial multiplexing system, we construct a rotated multidimensional QAM scheme. To reduce the complexity of maximum likelihood decoding subject to increase in the modulation dimension, sphere decoding has been employed. We note that various levels of QoS can be immediately achieved by changing the dimension, and it is a useful feature to implement adaptive modulation under varying channel conditions.