Reviewerly/exHarmony huggingface dataset:
Effectiveness of Quantum Computing in Image Processing for Burr Detection

Technology is developing at a dizzying pace to make our lives easier. Among other innovations, quantum computing, which is based on quantum mechanics, is evolving with the aim of solving all the problems that traditional computing is unable to solve. Quantum computing, unlike traditional computing, relies on qubits (quantum bits) that can be in superposition of the values 0 and 1, as well as other fundamentals, such as interference or entanglement. This paper analyses the use of quantum computing for image processing, testing the efficiency when quantum computers are employed. To do that, the Flexible Representation of Quantum Images model of image representation is implemented in a quantum simulator to solve a particular problem. Therefore, images of machined parts are processed in order to detect the edges of the mask what can determine the presence of burrs. Detecting burrs improves the surface finish and, in turn, the quality of industrial processes. The results of the proof of concept show that, although compared to traditional computing, quantum algorithms are not yet efficient enough to match or even surpass classical algorithms, they are promising.
Get Infinitely Rich! (while definitely going broke)

Click to increase image sizeClick to decrease image size Disclosure statementNo potential conflict of interest was reported by the author.Additional informationNotes on contributorsDan SwensonDan Swenson received a PhD in mathematics from the University of Minnesota in 2009. He is currently a professor of mathematics at Black Hills State University in Spearfish, South Dakota—just down the road from the town of Deadwood with its many casinos and slot machines. Dan enjoys playing, watching, and analyzing (mathematically) games and sports. He lives in Spearfish with his wife, Becky, and their dog, Bowie.
Rapid Fog-Removal Strategies for Traffic Environments

In a foggy traffic environment, the vision sensor signal of intelligent vehicles will be distorted, the outline of obstacles will become blurred, and the color information in the traffic road will be missing. To solve this problem, four ultra-fast defogging strategies in a traffic environment are proposed for the first time. Through experiments, it is found that the performance of Fast Defogging Strategy 3 is more suitable for fast defogging in a traffic environment. This strategy reduces the original foggy picture by 256 times via bilinear interpolation, and the defogging is processed via the dark channel prior algorithm. Then, the image after fog removal is processed via 4-time upsampling and Gaussian transform. Compared with the original dark channel prior algorithm, the image edge is clearer, and the color information is enhanced. The fast defogging strategy and the original dark channel prior algorithm can reduce the defogging time by 83.93–84.92%. Then, the image after fog removal is inputted into the YOLOv4, YOLOv5, YOLOv6, and YOLOv7 target detection algorithms for detection and verification. It is proven that the image after fog removal can effectively detect vehicles and pedestrians in a complex traffic environment. The experimental results show that the fast defogging strategy is suitable for fast defogging in a traffic environment.
The Impact of Information Technology on the Management of Small and Medium Scale Enterprise in Nigeria

The objective of this study is to examine the impact of Information Technology to the Management of Small and Medium Scale Enterprises in Nigeria with reference to Ramadan Press Limited, Bauchi, Bauchi State. The research design took both an inferential and a descriptive approach. A sample size of one hundred and thirteen (113) was drawn from the population. A 5 - point Likert scale was developed and validated to collect information from the respondents. The data collected was analyzed with basic descriptive statistics such as frequency and simple percentages. Chi-square analysis was also made. The core findings from the results obtained show that that Information Technology play significant role in the activities and operations of Small and Medium Scale Enterprises (SMEs), that Information Technology has impacted positively on the managerial practice of SMEs and that Information Technology has improved the performance of SMEs. Conclusion was drawn from the summary of the result. Various remarks and recommendations were proffered to the organization of study.
Social Media-Based Traffic Situational Awareness under Extreme Weather

Traffic information under extreme weather cannot be collected in a timely and accurate manner by traditional traffic information collection methods, due to various restrictions. Although recent evidence suggests that social media, such as Twitter, is a powerful supplement to traditional traffic information collection methods, which plays an important role in addressing the issue of traffic situational awareness, few studies take Chinese social media data as the object of analysis. To fill this gap, based on the social media data scraped from Weibo, which is the largest Chinese social platform in China, this study provides new insights into comparing the metrics of different machine learning classification algorithms. The results indicate that the long short-term memory (LSTM) classifier outperformed others and achieved 93.8%–95.8% accuracy.
Interpretation of Geothermal Magnetic Depths, Physicochemical Parameters and Heavy Metals Determination of Lamurde Hot-spring in the North-Eastern Benue Trough, Nigeria

An integrated interpretation of the magnetic data and the analysis of physicochemical parameters and heavy metals from Lamurde hot spring has been done for the first time. The temperature of the hot spring was measured to be at 44 °C while the normal surface temperature is 25 °C. Three prominent magnetic anomalies were found at bottom depths of 11.379 ± 0.253 km, 13.015 ± 2.120 km and 9.161 ± 1.200 km suggesting that the Lamurde hot-spring is heated at deep mantle (13.015 ± 2.120 km) and issued to the surface through either local or regional fault system or both. The physicochemical analysis gave pH (7.93 ± 0.06), total chlorine (125.0 ± 2.89 µg/L), total dissolved solids TDS (202.0 ± 2 ppm), hardness (64 ± 1.73 µg/L), alkalinity (210 ± 4 µg/L) and nitrate (1.3 ± 0.3 µg/L). In comparison with that of WHO standards, the results indicated that all the physicochemical parameters studied except for alkalinity fall within the permissible limits. Heavy metals were identified and analyzed in the sampled water: lead (0.1501 ± 0.0007 mg/L), chromium (0.0729 ± 0.0007 mg/L), nickel (0.1987 ± 0.1476 mg/L), cadmium (0.0115 ± 0.0003 mg/L), copper (0.0442 ± 0.0008 mg/L), arsenic (0.0456 ± 0.0003 mg/L), iron (0.8016 ± 0.0005 mg/L), cobalt (0.0274 ± 0.0004 mg/L), selenium (undetectable), manganese (5.31 ± 0.0361 mg/L) and zinc (0.1629 ± 0.0004 mg/L). The concentrations of heavy metals observed in the area with the exception of Zn, Cu and Se are all above the standards for drinking water. Their concentrations are in the order of Mn &gt; Fe &gt; Ni &gt; Zn &gt; Pb &gt; Cr &gt; As &gt; Cu &gt; Co &gt; Cd &gt; Se. These results suggest that the Lamurde hot spring is a potential zone for Mn, Fe, Ni, Zn and Pb deposit.
Analisa Algoritma C.45 Terhadap penentuan Rekomendasi Penerima Beasiswa SMP Swasta Methodist-8 Medan

Scholarships are financial assistance with the intention to be used as a means of continuing education that is taken and is usually given by foundations, companies and government agencies. Scholarships in the form of funds used to help underprivileged students in continuing their task of completing education. Therefore the scholarship must be on target to the recipient who is truly feasible and deserves to get it. The number of prospective recipients makes the selection process take a long time. In this case the use of data mining methods can be used as a solution to facilitate the selection process. The C4.5 algorithm is an algorithm that will be used in this study. The data used are the names of students, classes, parents' income, dependents of parents, and the average report card value. Data mining processing on a training data will produce a decision tree. The evaluation method carried out in this test was obtained by the accuracy value of 93.33 %, this could be proof that the C4.5 algorithm was accurate enough to provide scholarship recommendations.
The Python Bites Back

Just like other programming languages it has its fair share of gotchas that can trip up a Python newbie. In this chapter we will look at 14 of the most common mistakes and how to solve them.
Class Inheritance

Inheritance is a core feature of Object-Oriented Programming. It allows one class to inherit data or behaviour from another class and is one of the key ways in which reuse is enabled within classes.
Performance Analysis of Feature based Multiple Descriptors with Histogram Equalization for Image Mosaicing

Objectives: The main objective of the proposed work is to develop an image mosaicing model for combining the images of different individual images. In other way, the union of two images and to evaluate the performance of the model in terms of the number of run time in seconds and number of key features they use. Methods: In this work, the Histogram Equalization is a processing step required to make the mosaic invariant to intra image and inter image intensity variability. The detailed feature of the enhanced image is extracted using Scale-invariant feature transform (SIFT), Oriented Fast and Rotated Brief (ORB), Binary Robust invariant scalable key points (BRISK) feature descriptors techniques. The features including local and global are matched using K-Nearest Neighbor. Then, homography is performed using RANdom SAmple Consensus (RANSAC) algorithm to compute the camera motion. Finally, the image warping is performed using smoothing filter of size 40x40 to obtain the panorama image. Findings: The model is tested on various datasets using three different feature extractors popularly used in image mosaicing or image stitching algorithms SIFT, ORB and BRISK descriptors. It is observed that the ORB is the best feature extractor among the state-of-the-art feature extractors. The ORB with HE uses a minimum of 500 key features to match the images and generates panoramic images that are invariant to shift and rotation with the minimum run time of 0.0836 seconds. Novelty: The state-of-the-art models developed by the researchers suffer with good number of matching points of the input images to generate the image mosaicing. This issue is addressed in the proposed model using multiple descriptors SIFT, ORB and BRISK techniques. The ORB with HE will provide the minimum key features and enough good matches of features with the record of minimum runtime to obtain the panoramic images. Keywords: Mosaicing; Smoothing Filter; Histogram Equalization; Homography; Panorama Images
PENINJAUAN SISTEM POLDER GROGOL DALAM MENGHADAPI BANJIR

Floods that often occur due to high rainfall inflicts social problems and other social impacts on the community. Therefore. a capable drainage system is necessary which comprises drainage channels with adequate capacities as well as pumps with sufficient capacities and operational rules. The study focuses on hydrological and hydraulical analysis on the system of Polder Grogol, West Jakarta. The estimation of design flood discharge employs Soil Conservation Service method with 5 years return period for Semeru and Makaliwe channels. The results of hydraulical analysis shows both channels are still adequate in draining design flood discharge. However, the existing pumping system is no longer sufficient to keep the reservoir’s water level below the bottom of reservoir’s inlet channel. There are several options to lower the reservoir water level. In this study, the approach is to add a new pump with the capacity of 0,25 m3/s wihout changing the formation of existing pumps. The analysis results reveals the additional pump manages to lower the reservoir water level below the targeted elevation.&#x0D;
PELATIHAN PEMANFAATAN VLOG SEBAGAI MEDIA PEMBELAJARAN MENULIS DESCRIPTIVE TEXT DI SMPN 5 SRAGI KABUPATEN PEKALONGAN

Learning in endemic era is not inseparable from the use of technology to support teaching and learning process. The use of technology can be realized in the use of Vlog as a learning medium. Therefore, a workshop was needed for English teachers and the students in utilizing technology in the teaching learning process. This activity was aimed to: 1) facilitating workshop to the teachers on the use of vlog as teaching medium of descriptive text, and 2) providing training to the students in writing descriptive text based on the vlog they watched. The participants of this agenda were 33 people consisting of English teachers and seventh graders of SMPN 5 Sragi, Pekalongan regency. This activity was held in some stages, they were Vlog playback, presentation, writing practice, and feedback. The result of this workshop showed that the teachers got new experiences to innovate the teaching learning process, especially the use of learning media. Meanwhile, for the students, they felt enjoyable learning atmosphere. They could develop ideas for writing descriptive text assisted by learning media in the form of “Wonderful Black Canyon” Vlog.
DESIGN OF INFORMATION TECHNOLOGY GOVERNANCE IN THE INFORMATION TECHNOLOGY DIVISION OF PT PLN USING THE FRAMEWORK COBIT 2019

In order to support the company's main business objectives, PLN UP3 Manokwari has implemented Information Technology (IT) which is structurally managed and implemented by the information technology division. However, information technology management in the IT division has not yet implemented information technology governance. To support the ongoing management of information technology, the information technology division of PLN UP3 Manokwari still uses the system manually. Manual management of information technology has many risks, this causes the company's main business objectives to not be achieved optimally. The method used in this study refers to the 2019 COBIT framework. From data analysis, it is known that the level of capability of the selected IT governance process in this study is the process in the domain EDM03, APO03, APO12, APO13, BAI01, BAI03, BAI06, BAI07, BAI11 , and DSS05 are mostly still at level 2, while the capability level expected by companies is mostly at level 4. The results of this study are in the form of recommendations for improvements aimed at achieving the expected level of capability by companies and design of IT governance as a reference for the IT Division PT PLN UP3 Manokwari in managing better IT processes to support the achievement of the company's main business objectives.
Implementasi Program Literasi dalam Meningkatkan Minat Baca Peserta Didik di SDN Unggulan Bontomanai

This study aims to describe the form, implementation and impact of the literacy programme implemented at SDN Unggulan Bontomanai, Bontomarannu Sub-district, Gowa Regency. The research data was obtained from interviews with teachers, observations and distributing questionnaires to 29 grade V students. Based on the results of interviews and observations, it was found that the form of literacy programme used is reading-writing literacy and its application has three stages, namely the habituation stage, the development stage, and the learning stage. In the habituation stage, students are accustomed to reading or being read books other than textbooks, then discussion activities are carried out related to the books read. At the development stage, literacy implementation is carried out with the aim of consolidating students' interest in reading and increasing students' understanding. At the learning stage, students have been able to capture and re-explain the material provided well. The results of the questionnaire accumulation show that the literacy programme implemented at Bontomanai Primary School has a positive impact, such as reading becoming a student habit, the school library becoming more lively, and the way students think being creative, critical and innovative.
Integration of Technology in the Era of Information Enhancement in Advancing English Classroom Education

The degree of internationalization and openness has continuously increased along with the ongoing growth of the global economy. Higher-level English language instruction must also keep up with technological advancements and global growth. To significantly respond to the inclination of an improved English education system in the future, it is currently essential to construct a multi-source knowledge base on English methodology for education and assessment index system. The development of English teaching has been better facilitated by actively absorbing significant education perceptions from foreign successful teaching models. In the present English education and learning procedure, it is essential to modify the conventional teaching strategy, change the past educational ideas, contribute greatly to forming a global and versatile training course, and significantly gather thoughts for outstanding education from international examples for excellent teaching. The post-test average for the experimental class is 81.50 points, compared to 78.60 points for the control class; the excellence rate for the teaching method is 39%, and the pass rate is 100%, whereas the post-test average for the controlled group has an outstanding rate of 33%. An 88.8% pass rate was achieved. Further investigation reveals that the post-test outcomes of the experimental class have improved in both the passing and excellent rates. After the exam, the experimental class's kids' test results significantly outperformed those of the control group. The pupils' general performance has considerably improved.
Impact of Effective Communication on Institutional Performance: Case Study in Higher Learning Institutions

Effective communication is crucial for institutional success as the globe becomes a smaller and more interconnected community. In recent times, Information technology has significantly improved how employees and employers interact with each other. Effective and efficient communication is achieved when institutions adopt new and faster technologies that improve the performance of employees. This research empirically tests the impact of effective communication on institutional performance in the educational sector, specifically in Bayelsa Medical University, Yenagoa, Bayelsa State. Questionnaires were administered to sample respondents which comprised of Principal officers, Deans, Directors, Heads of Departments, academic and senior non-academic staff. ANOVA and factor analysis were used to assess the structural relationship between the variables at a 5% level of significance.&#x0D; A total of 180 respondents (25 academic staff and 155 non-academic staff members) from fourteen (14) different departments/units participated in this study. The findings of this study revealed that effective communication via the studied variables has a significantly positive effect on employee performance Four key variables (Communication Process (t = 4.003, β = 1.786, p = 0.00); Culture/Climate (t = 3.316, β = 1.483, p = .001); Verbal and Non-verbal Cues (t = 1.990, β= .832, p = .047); and Communication Techniques (t = 5.092, β = 1.808, p = .000)) were determinants of employee effective communication in an institution. The findings revealed that effective communication process were significantly related to organizational performance.&#x0D; The researchers recommends that every institution should make an effort to incorporate effective communication into its management strategies, as doing so will help reduce organizational conflict, clear up misunderstandings, and improve cordial relationship between management and workforce.
Stimulating mathematical communication with SPECOMATSO technology development based on digital literacy

Mathematical communication is crucial in inclusive mathematics teaching and learning to convey mathematical symbols. However, teaching mathematical symbols to deaf students in inclusive classrooms has been a persistent challenge due to the lack of specialized sign language for mathematical expressions. Media, such as SPECOMATSO technology, can serve as a bridge to address this issue. This research focused on developing valid and practical SPECOMATSO technology to strengthen students’ literacy and facilitate the delivery of mathematical symbols, which previously posed difficulties for teachers in inclusive settings. The research combined the Alessi Trollip and V-waterfall models, encompassing seven development stages: analysis, design, implementation, unit testing, integration testing, system testing, and acceptance testing. The research instruments included observation and interview guidelines, a product validation questionnaire, and a student response questionnaire. This study produces SPECOMATSO technology that is valid and practical for learning plane geometry and angles in mathematics. Although this development still needs improvement in fixative abilities, such as storage and editing functions, it is expected to strengthen digital literacy and stimulate mathematical communication among deaf students who face challenges related to their limited auditory capabilities.
EvolveFNN: An interpretable framework for early detection using longitudinal electronic health record data

Abstract The extensive adoption of artificial intelligence in clinical decision support systems necessitates a significant presence of ML models that clinicians can easily interpret. Therefore, we developed an RNN-based interpretable method, combining the fuzzy concepts and recurrent units, to train accurate and explainable models on high-dimensional longitudinal electronic health records data. Through supervised learning, our method allows the identification of variable encoding functions and significant rules. To demonstrate its performance and capabilities in classification and rule discovery, we first tested it on a simulation dataset. The proposed methods achieved the best model performance, and the rules learned are almost identical to what we used to generate the synthetic data. Furthermore, we showcased a pilot application that proved its potential in the early detection of cardiac event onset. We constructed a prediction window of length from 30 days to 180 days and a 360-day retrospective observation window to evaluate our algorithm. Our proposed algorithm EvolveFNN with GRU unit achieved an AUPRC of 0.695 and an AUROC of 0.682 and EvolveFNN with LSTM unit achieved an AUPRC of 0.696 and an AUROC of 0.684 when the prediction window size is 180 days. The proposed algorithm obtained a comparable model performance to vanilla GRU models and remains relatively stable when the prediction window size changes. Examining the rules generated by our EvolveFNN model with the GRU unit, we found that the extracted rules align with clinical practices and existing literature. This provides potential risk factors not explored before in the population, such as chloride. To assess the generalizability of the algorithm, we conducted experiments on the MIMIC-III benchmark dataset for in-hospital mortality prediction. The results showed our proposed algorithms achieved model performance comparable to the top-performing GRU model and surpassed other approaches by providing transparent decision reasoning. In conclusion, our approach, EvolveFNN, can effectively train accurate, interpretable, and reliable models using large longitudinal electronic health records datasets, thereby offering valuable insights for clinicians.