Reviewerly/exHarmony huggingface dataset:
Entrepreneurs with a Mission

Nigeria ranks first in the world in youthful entrepreneurship, with 40 per cent of young Nigerians engaged in early-stage entrepreneurial activity. With jobs scarce and often badly paid, a business on the side helps make ends meet. But it’s also a cultural attitude: entrepreneurial nous flows through this generation’s veins. New businesses tend to be focused on local and pan-African consumers and entrepreneurship is fuelled by social media. Instagram, WhatsApp and Facebook are used as tools to sell physical products and services. Social enterprises are growing, too, as acting with humanity becomes an important consideration for many young entrepreneurs across the continent. The typical Soro Soke generation entrepreneur is a creative disruptor, using their business to deliver solutions to the larger problems the continent faces. But being an entrepreneur on the continent still poses significant challenges. Nigeria has the highest volume of start-ups on the African continent, over 750, but misses out on all the top 10 rankings for categories that are critical to helping a business thrive.
Internet Usage and Academic Performance of Secondary School Students in Indonesia

Learners and teachers around the world extensively use the internet. Internet usage makes learners more motivated to look for information more frequently. Hence, the study sought to examine the impact of internet usage on the academic performance of secondary school students in Indonesia. The study employed a descriptive research design. The target population included principals, teachers and learners in secondary schools in Jakarta, Indonesia. The target population was 500 participants. The study used a stratified sampling technique to get the sample size. The study used questionnaires to collect the data. The analysis of the data was done using descriptive and inferential statistics. It was found that internet usage explains 26.1% of the variations in academic performance. The study findings showed that internet usage is positively and significantly related to academic performance (B=.2857, p=0.014). The study concluded that internet usage positively impacts learners' academic performance. The use of the internet opens doorways to a wealth of information, knowledge, and educational resources, increasing opportunities for learning in and beyond the classroom. The internet provides different content that students can use to learn or enhance their understanding. The study recommended that earning organizations make sure that appropriate internet services are provided in their respective libraries to make it possible for learners to fulfill their information needs. The schools need to help learners utilize the internet for positive academic achievement. Government should make sure that each learning institution has a cost-free ICT center so that children can learn and have earlier knowledge to understand the favorable and unfavorable elements of the internet. Keywords: Internet Usage, Academic Performance, Secondary School Students, Indonesia
Internal causes, difficulties and breakthrough paths of implementing classroom revolution in Applied Undergraduate Colleges and Universities

“Classroom revolution” is a comprehensive reform of the traditional classroom from the aspects of teaching methods, teaching contents, teaching means and teaching evaluation. It is the internal requirement of establishing a modern classroom teaching model and the inevitable trend of the development of modern educational technology. In practice, the implementation of the “classroom revolution” confronts difficulties and dilemmas in Applied Undergraduate Colleges and Universities. Starting from the exploration of the implementation background and practical significance of the “classroom revolution”, this study deeply analyzes the necessity of the “classroom revolution” in Colleges and universities, puts forward some methods and paths to break through the difficulties from the aspects of top-level design, teachers’ ability and consciousness, work incentive mechanism in view of the practical problems existing, and gives the specific methods of reform practice according to the practical requirement. Through this path, the goal of improving classroom value has been guaranteed.
Study About Image Capture Device Based on Internet of Things (IoT)Technology

Tracing stolen cattle in the NTB province's Lombok Tengah regency is done by following footprints and waiting at specific locations that are regarded the path to be crossed or the final destination of cattle theft, known as "Ngendeng" Ngendeng is carried out day and night from the time the livestock is declared missing until the livestock is found or the potential to be found is considered lost. The issue with Ngendeng's operations is that it puts people's lives in peril if there is a fight with thieves, as well as a decline in health for the inhabitants of Ngendeng. An Internet of Things (IoT) gadget for image capture was designed to replace the community's function in Ngendeng. The Research and Development (R&amp;D) approach is used in the development of gadgets to create goods and test their effectiveness. The Participatory Rural Appraisal (PRA) approach was utilised to trace the site of deployment of devices in each sub-district. As a result, the most often travelled point (high potential) has been identified for the placement of IoT-based image capture devices in an effort to minimize cattle theft in Lombok Tengah Regency. &nbsp; &nbsp
Research on the Effectiveness of Cyber Security Awareness in ICS Risk Assessment Frameworks

Assessing security awareness among users is essential for protecting industrial control systems (ICSs) from social engineering attacks. This research aimed to determine the effect of cyber security awareness on the emergency response to cyber security incidents in the ICS. Additionally, this study has adopted a variety of cyber security emergency response process measures and frameworks and comprehensively proposes a new organizational model of cyber security incident response. The corresponding measures are evaluated based on the MP2DR2 risk control matrix model to assess their practical value in the evaluation stage. This study found that after adding security awareness measures to response control measures, the influential value ranking of other control measures changed. The practical value of security awareness control measures was given a higher priority than that of other control measures. The research results highlight the importance of cyber security awareness and aim to inspire ICSs to place a higher priority on staff cyber security awareness in relation to cyber security incidents, which can effectively prevent the occurrence of cyber security incidents and make the field of industrial control application agency respond to incidents faster to restore the regular progress of all works.
Using CNN in Surveillance Videos for Recognizing Human Actions Based on Machine Learning in Examination

Video analytics is the process of processing a video, obtaining data, and analyzing the data to derive domain-specific information. In recent years, examining live surveillance films for recognizing events that occur within its coverage area has become increasingly important, in addition to analyzing any video for information retrieval. Face identification from recordings is easy when training models are used. Estimating skin colour aids hand detection. This study project aims to detect suspicious acts such as object exchange, new person admission, peeping into another's answer sheet, and person exchange using footage captured by a security camera during exam. People are paying greater attention to the fairness of exams these days, therefore detecting anomalous conduct to ensure examination order is important. Most of the current methodologies propose a fraudulent model. We extract the optical flow of video data in this system and present a 3D convolutional neural networks model to solve the problem. Face recognition, hand recognition, and detecting contact between the face and hands of the same person and that of distinct people are all required. The automation of suspicious activity detection' will aid in lowering the mistake rate associated with manual monitoring.
A Hybrid Movie Recommendation Algorithm Based on Optimized K-means Clustering

With the advent of the big data era, there is an increasing amount of information available on the internet, resulting in an explosion of information and information overload, making it impossible for users to access the information they want in a short period of time. In this regard, the recommendation system uses algorithmic deep mining of users' personal information and historical data to find out what they want and gives them a list of personal recommendations. The collaborative filtering algorithm looks for users with similar behaviour, the algorithm is not affected by new items and has a better recommendation accuracy in comparison. This paper analyses and compares content-based and user-based collaborative filtering algorithms and adds clustering algorithms to the algorithm's practical optimization process. The collaborative filtering algorithm suffers from poor recommendation accuracy, so the time-based interest calculation is added to optimize the similarity formula. Before calculating user similarity, the clustering algorithm is used to cluster users, aggregating users with similar behaviour interests into a class. Then PCA algorithm is used to reduce the dimension of project attributes, and finally the similarity was calculated by combining the optimized user data to obtain the final Top-N recommendation list. The experimental data were obtained using the public Movielens dataset, with 70% of the data used in the training set and 30% in the test set. The experiments show that the model is effective in extracting user features, while the recall and accuracy of the inference and storage techniques is improved. The hybrid optimization of the kmeans model with collaborative filtering is therefore a great contribution to the development of recommendation systems.
An Enhanced Information Retrieval-Based Bug Localization System with Code Coverage, Stack Traces, and Spectrum Information

Several strategies such as Vector Space Model (VSM), revised Vector Space Model (rVSM), and integration of additional elements such as stack trace and previously corrected bug report have been utilized to improve the Information Retrieval (IR) based bug localization process. Most of the existing IR-based approaches make use of source code files without filtering, which eventually increases the search space of the technique, thereby slowing down the bug localization process. This study developed an enhanced IR-based bug localization model as a viable solution. Specifically, an enhanced rVSM (e-rVSM) is developed based on the hybridization of code coverage, stack traces, and spectrum information. Combining the stack trace and spectrum information as additional features can enhance the accuracy of the IR-based technique by boosting the bug localization process. Code coverage analysis was conducted to remove irrelevant source files and reduce the search space of the IR technique. Then the filtered source files are preprocessed via tokenization and stemming from selecting relevant features and removing unwanted words. The preprocessed data is further analyzed by finding similarities between the preprocessed bug reports and source code files using the e-rVSM. Finally, scores for each source code and suspected buggy files are ranked in descending order. The performance of the proposed e-rVSM is tested on two open-source projects (Zxing and SWT), and its effectiveness is assessed using TopN rank (where N = 5, 10), Mean Reciprocal Rank (MRR), and Mean Average Precision (MAP). Findings from the experimental results revealed the effectiveness of e-rVSM in bug localization. In particular, e-rVSM recorded a significant Top 5 (80.2%; 65%) and Top 10 (89.1%; 75%) rank values on SWT and Zxing dataset respectively. Also, the proposed e-rVSM had MRR values of 80% and 54% on the SWT dataset and MAP values of 61.22% and 47.23% on the Zxing dataset.
Speech Recognition in E-Mail

Abstract: Speech recognition is one of the developing parts of AI and deep learning. Speech Recognition can be considered a predecessor of Voice recognition. SRE is based on speech recognition and helps send email by speaking and not by typing. Speech recognition involves PLP(Perceptual linear prediction), MFCC(Mel-frequency cepstral coefficients), and many other algorithms, which helps the software to distinguish the specific voice from the surrounding environment, make frequencies audible enough for human ears. DNN uses sound waves as data, to train the software. DNN uses Acoustic model, Pronunciation model, Language model, for speech-to-text, and text-to-speech. Keywords: Speech recognition, sound waves, audio, SMTP, e-mail server.
An Improved Ikeda System and Its Application in Image Encryption

Based on the enhanced Ikeda time delay system derived from modified nonlinear function, a multi-rounds image encryption scheme is proposed. It is constructed by adding arctangent functions to nonlinear terms. Not only is the stability condition of the improved system analyzed theoretically, but also the stability and chaos characteristics of the system are studied from the aspects of solution response, phase diagram by using numerical analysis method. And then, the current time response sequence and delay time sequence are used to scramble and replace the pixel sequence of the plain image, respectively. As a characteristic of encryption algorithm, when multi-rounds encryption is carried out, it is necessary to use the pixels of the previous encrypted image to update the control parameters of the system dynamically. Simulation results show that the cryptosystem has excellent encryption performance, and can resist various attacks.
Implementation Paper on Web Based Mid-Day-Meal Analysis

Abstract: The Mid Day Meal Programme (MDMP) is a welfare programme that is being operated through the country and involves millions of children, crores of public funds, and thousands of officials manning the programme. While there can no denying that the programme needs to be monitored with an eagle’s eye for lacunae, discrepancies and malpractices, it is equally imperative that each and every well-intentioned effort, however miniscule, needs to be appreciated, rewarded and publicized for the simple reason that man motivation is a simple but a highly effective tool that can rev up the gargantuan lumbering machinery involved in the implementation of MDMP to generate unprecedented results, as expected of this populist programme. Keywords: Mid-Meal, Government schemes, School, Children, Database connection
Effect of Strategic Management Practices on Organizational Excellence

Strategic management is one of the prominent topics widely adopted for research purposes all over the academic society. It was argued that strategic management could encourage the organization to be more goal-oriented. At the same time, other opinions stated that being strategic in the approach means the organization strategically runs and manages its sources, abilities, and the human factor in achieving better performance. Also, many scholars agreed with that idea, arguing that strategic thinking means being more empowered to utilize the right item in the right place to achieve performance excellence. From that idea, the present research sought to investigate the impact of strategic management methods on bringing the company to peak performance. The SM practices used in the present investigation were (Strategic Planning, Strategy Formulation, Strategy Implementation, and Strategic Control). The study's goal was achieved via a quantitative technique; for this purpose, an online questionnaire was posted to Google Forms, and 268 persons from senior management inside Jordanian SMEs answered it. The study's findings revealed that strategic management practices positively affect organizational efforts to achieve excellence. Strategic control is the most significant variable with a correlation of r = 0.806, followed by strategy execution with a correlation of r = 0.584. Other factors (formulation and planning) had a weak to medium link but looked important in bringing the organization to excellence. Based on these findings, the research suggested establishing coherence between the organization's objectives and the strategic plans established to have a successful operational strategy. The report also included further suggestions.
Food Board: A Restaurant Management System

Abstract: The Restaurant Management System provides necessary services for the typical fast food restaurant to manage all the day-to-day activities. The restaurant management system is there to help communication between all teams within a restaurant by minimizing the probability of human error and getting more efficient and effective information. This system has a built-in POS system with order management solutions and kitchen management to handle all the food production efficiently to get the orders to the customer Keywords: Restaurant Management, Menu, Pos, Billing, Kitchen
Analysis of the Effectiveness of the Digital Role on Manual Archive Management at the Binjai Branch Office of BPJS Employment

Archives are several important information documents that are collected so that they can be stored in a planned and orderly manner in a good and safe manner so that when one day in the future these documents can be found when needed. Based on the Decree of the President of the Republic of Indonesia Number 105 of 2004 regarding archive management, chapter I Article 1 explains that archives are defined as a collection of manuscripts made and accepted by Government Agencies and Private Agencies or individuals, in any form individually or in groups. in the context of implementing government activities as well as in the context of implementing national life. The archive data files will increase day by day, so that the data files can be neatly arranged, a proper management system is needed. So that it can be seen that the purpose of this study is to find out the advantages and disadvantages of implementing an archive management system both digitally and manually. So that it can show which system is more efficient to implement in managing archives at the BPJS Ketenagakerjaan office, Binjai Branch. As well as benefits The results of this study are expected to be used as input and information to be used as a reference in order to improve the performance of archive management in the work unit.
Real-time eyeglass detection using transfer learning for non-standard facial data

&lt;span&gt;The aim of this paper is to build a real-time eyeglass detection framework based on deep features present in facial or ocular images, which serve as a prime factor in forensics analysis, authentication systems and many more. Generally, eyeglass detection methods were executed using cleaned and fine-tuned facial datasets; it resulted in a well-developed model, but the slightest deviation could affect the performance of the model giving poor results on real-time non-standard facial images. Therefore, a robust model is introduced which is trained on custom non-standard facial data. An Inception V3 architecture based pre-trained convolutional neural network (CNN) is used and fine-tuned using model hyper-parameters to achieve a high accuracy and good precision on non-standard facial images in real-time. This resulted in an accuracy score of about 99.2% and 99.9% for training and testing datasets respectively in less amount of time thereby showing the robustness of the model in all conditions.&lt;/span&gt;
The Cloud Radiation Forcing Prediction Based on Textural Feature Extraction from Cloud Image

The intermittency and instability of the solar energy resource brings great challenge to the accurate forecasting of the surface solar irradiation. In this work, based on texture characteristics analysis of sky image collected by TSI combined with SVM model, a new methods for the forecasting of cloud radiative forcing was presented. First, the texture characteristics related to solar irradiation were extracted from sky images through image processing technologies, including contrast, entropy, grayscale and energy; Then regression model was built between image characteristics and irradiation reduction coefficient; Finally, the SVM model was used to forecasting cloud radiation forcing. The experiment results indicated that: the forecasting accuracy of the method based on texture characteristics tends to provide better a performance than traditional forecasting method and forecasting method based on cloud block movement prediction. It can provide important reference for the accurate forecasting of surface solar irradiation on complex climate conditions.
Stereovision-based method for free vibration measurement of a mine hoisting rope

Currently, there are no suitable means to measure the composite vibration response of mine hoisting rope. However, machine vision-based measurement technology is a potential way to solve this problem. Therefore, a non-contact and non-intrusive stereovision method is proposed to obtain the 2D vibration displacement of a moving hoisting rope. In this methodology, a novel 3D digital image correlation (DIC) method that combines digital image processing (DIP) algorithm with 2D-DIC algorithm is developed, and the method can simplify the procedure of rope target stereo matching in two synchronous image sequences. In order to confirm the correctness of the stereovision method, some free vibration responses of a rope are measured in a hoist experimental system. Test results demonstrate that the stereovision measurement technique can keep satisfactory consistency with the laser displacement sensor for vibration data identification. The method is verified to have high adaptability to different lighting conditions and be reasonable to measure the vibration parameters of dynamic mine hoisting rope.
Thyroid Ultrasound-Image Dataset

Thyroid Computer-Aided Diagnosis (CAD) systems have been developed to assist radiologists in improving efficiency, reliability, and diagnosis performance. Often the performance of these CAD systems is evaluated with different datasets that make it incomparable. A valuable thyroid ultrasound (US) dataset is presented in this work. This dataset consists of 2450 thyroid US images from 2018 to 2020 in Prospective Epidemiological Research Studies in Mashhad, Iran (PERSIAN), a large national cohort study. These US images have the ROI of thyroid nodules and the associated American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TIRADS) features by expert physicians provided in XML format. Dataset's images are categorized into five groups based on the ACR-TIRADS (Tirads1-Tirads5). The presented dataset is expected to be a valuable resource to develop and assess thyroid CAD systems to help radiologists better diagnose.