Reviewerly/exHarmony huggingface dataset:
Advanced Security System using YOLOv3

In this paper, authors considered the problem of Security system with high budget. The Security System proposed here is used to detect the objects or humans using YOLO. It can detect any kind of objects using deep learning based object detector in different positions and ranges from the camera. Here authors will apply a cascade of background subtraction and object detection that will describe the unauthorized zone and figure out the intruders by streaming each frame from the raspberry pi to laptop. The system is designed with the application of advanced computer vision algorithms that includes deep learning, object detection, and classification. Authors have proposed a system to provide advanced security using a resource constrained device known as Raspberry pi. The proposed system is capable of detecting objects and generates alerts also to provide advanced security system. Instead of limited resources on board, system is capable of doing complex computing via using Intel movidious NCS-2. Intel NCS-2 is a TPU that will perform all the complex computing on Raspberry pi like implementation of CNN and Deep learning modules.
Enhancing Performance of Operationalized Machine Learning Models by Analyzing User Feedback

Machine learning (ML) models that have been put into production must be actively monitored and maintained to ensure that the models continue to satisfy performance quality requirements. User feedback is often a very good indicator of whether the model is performing as per user expectations. We contend that monitoring ML models through user feedback, and promptly addressing the issues mentioned in the feedback will help to ensure long-term success of deployed ML models. However, the problem of incorporating user feedback for maintaining ML models has not been adequately studied. In this paper, we first motivate the importance of this problem by highlighting the benefits of incorporating user feedback. The paper discusses the challenges of effectively harnessing user feedback for enhancing performance of deployed ML models. Furthermore, we present a novel approach for analyzing user feedback to identify incompleteness of training datasets or differences between distributions of training datasets and actual workload. Our approach compares the user feedback and training data of deployed ML models to find the above mentioned deficiencies in the training dataset. And we determine a priority order to fix the issues. We also present experiments to demonstrate the effectiveness of the proposed approach.
Charting a Course for “Complexity”: Metamodeling, Ruliology and More

This is the first of a series of pieces I’m planning in connection with the upcoming 20th anniversary [1] of the publication of A New Kind of Science [2] (September 23, 2021).
Research on performance evaluation of industry-university-research collaborative innovation in industrial colleges

Today, with rapid developments in higher education in China, the Ministry of Education has repeatedly reiterated the need to further deepen the integration of industry and education and the collaborative innovation of industry, university, and research. The development of industry colleges is facing both opportunities and great challenges. This paper summarizes the development status and research status of industry colleges of local undergraduate universities in China, and finds that there are few studies on operational performance evaluation, but evaluation is an indispensable part of the long-term operation of the mechanism. The research group visited 28 industry colleges in 7 local undergraduate universities in Jiangsu, Zhejiang, and Fujian and had an in-depth understanding of their operating conditions and potential problems, so as to construct a scientific and reasonable performance evaluation index system, and obtained the weight of indicators at each level through analytic hierarchy process. This paper aims to generate positive incentive benefits for industry colleges through performance evaluation, provide basis for the transformation and development of industry colleges, fundamentally improve the running effect of industry colleges, enhance the cultivation quality of application-oriented talents, and help local undergraduate colleges to transform their application-oriented development.
Prototype for Multimedia Content Delivery based on Non-Transmittable Codewords Enhanced Viterbi Algorithm

The paper provides a prototype for multimedia content delivery with reduced channel code rate from conventional Non-Transmittable Codewords Enhanced Viterbi Algorithm. The code rate reduction was simulated using VB.NET Viterbi simulator available at College of Informatics and Virtual Education-University of Dodoma. The study approximates Uplink and downlink speeds limits of the prototype using High Speed Packet Access Evolved technology by assuming all other parameters remain constant. The uplink and downlink of the prototype is clearly presented. The code rate of 1/3 was obtained by simulating different 8-bits patterns. This code rate of 1/3 enabled reduction of encoder output bits from 48-bits to 24-bits, therefore, few bits would be sent to the network and bandwidth conservation is attained. This makes the prototype to be the good choice for low network bandwidth channel. In addition, the reduced code rate will reduce the expenses of user internet bundles, because number of MBs to be charged will be smaller. This prototype for multimedia delivery over network has three benefits, high data transmission reliability due to adopted NTC Enhanced Viterbi, minimum network bandwidth utilization and satisfied uplink and downlink access speed.
Lifelong learning for robust AI systems

Existing artificial intelligence (AI) agents are most successful on narrow, well-defined tasks, where training data are plentiful, well-labeled, and match the deployment scenarios. It is also possible to train an AI agent to do multiple tasks (such as identifying IEDs from image data as well as recognizing faces), given sufficient time to craft the training regime and network architecture. However, data and time are often in short supply -- multi-domain operations involve rapidly shifting and adaptive compositions of capabilities, against adversaries that will likely be adapting on the fly. We suggest that to be robust in such scenarios, AIs need to be capable of learning in the field with opportunistically-available data, limited human oversight, and limited or no access to ground truth. These challenges also apply to reinforcement learning agents, with the additional challenge that for such agents, bad decisions cascade and pose a further difficulty in learning new tasks on the fly. We present an overview of the challenges in enabling AI systems for multi-domain operations, current algorithmic approaches for developing lifelong learning agents, and potential techniques for evaluating them.
Object Detection Based on Feature Balance Pyramid in UAV Imagery

Compared with images taken from the ground perspective, small objects account for a large proportion of aerial UAV images and the image perspective changes greatly, which affects the target detection effect of aerial UAV images. In this paper, the Yolov5 algorithm is improved to adapt to UAV object detection. Given a large number of small objects in aerial images, the feature balance pyramid structure is added to improve the loss of low-level features and improve the detection effect of the small object. In the feature balance pyramid, Pixel un-Shuffle is used to adjust the scale of the feature, which preserves the low-level feature information and reduces the computational cost. The cross self-attention module is proposed to improve the balanced feature map and improve the positioning accuracy of the small object. The Angle of view of aerial images varies greatly. In this paper, the deformable convolutional network is added to the backbone network of Yolov5 to enhance the feature extraction capability of the model for multi-view objects. Experimental results show that on the visdrone data set, the improved algorithm improves the average accuracy (mAP) by 1.4 percentage points compared with the original algorithm.
QİDA RESEPTLƏRİNİN KOMMERSİYA SİRRİ KONTEKSTİNDƏ MÜHAFİZƏSİ

The article examines the protection of recipes with intellectual property rights in the context of trade secrets, as well as the legislation and judicial practice of foreign countries, in addition to national legislation. In connection with the topic, in the judicial practice of foreign countries, in addition to the requirement of confidentiality in the treatment of recipes, it was determined to take into account the requirement of innovation, and commented on this approach. The article also examines the right of consumers to information in terms of trade secrets and cases of obtaining trade secrets by legal means. Key words: food, recipe, trade secret, intellectual property rights, secrecy Kərimova Türkan Bəyəndik qızı QİDA RESEPTLƏRİNİN KOMMERSİYA SİRRİ KONTEKSTİNDƏ MÜHAFİZƏSİ Xülasə Məqalədə yemək reseptlərinin əqli mülkiyyət hüquqları ilə mühafizəsi kommersiya sirri kontekstində tədqiq edilmiş, milli qanunvericiliklə yanaşı, xarici dövlətlərin qanunvericilik və məhkəmə təcrübəsi də araşdırılmışdır. Mövzu ilə əlaqədar xarici dövlətlərin məhkəmə təcrübəsində yemək reseptlərinə münasibətdə gizlilik tələbilə yanaşı, yenilik tələbinin də nəzərə alınması müəyyən edilmiş və bu yanaşmaya münasibət bildirilmişdir. Həmçinin məqalədə kommersiya sirri aspektində istehlakçıların məlumat almaq hüququ və kommersiya sirrininin qanuni vasitələrlə əldə etmə halları da araşdırılmışdır. Açar sözlər: qida, resept, kommersiya sirri, əqli mülkiyyət hüquqları, gizlilik
How an Expansion of Data Integration Processes is Proving to be the Turning Point on the Path Towards a New Era of Geosciences

Disclaimer Text and Data Mining. Any automated analytical technique aimed at analysing text and data in digital form in order to generate information including - but not limited to - patterns, trends and correlations (so-called Text and Data Mining) may only be applied if it is done by a research organisation or cultural heritage institution solely for the purpose of (non-commercial) scientific research as mentioned in Clause 3 of Directive (EU) 2019/790 (the Digital Single Market Directive) and Clause 15n of the Dutch Copyright Act [Auteurswet]. Text and Data Mining for commercial purposes is not allowed; all rights in this respect are reserved pursuant to Clause 4 paragraph 3 of the Digital Single Market Directive and Clause 15o paragraph 1 of the Dutch Copyright Act.
CENTRAL AFRICAN REPUBLIC: Bitcoin Adopted

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 59, Issue 4 p. 23840B-23842A Policy and Practice CENTRAL AFRICAN REPUBLIC: Bitcoin Adopted First published: 02 June 2022 https://doi.org/10.1111/j.1467-6346.2022.10573.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume59, Issue4June 2022Pages 23840B-23842A RelatedInformation
Real-Time Application for Deaf and Dumb: Bidirectional Communication Using Learning Methods

In this world, we have more than 466 million deaf dumb peoples. Normal peoples are communicating with voice, likewise deaf and dumb people are communicating by the use of sign language. Generally, without knowing the language, one cannot talk to other people in the world, similarly without knowing the sign language normal people cannot talk to deaf and dumb people. Within themselves, deaf and dumb people will communicate using sign language, which normal people cannot understand, but still hearing is one way to understand the people, so expression and gesture are also a way to understand thoughts of deaf and dumb people. To find a solution for this problem, either normal person needs to learn the sign language or we need to create a platform which will convert the sign language to voice and voice to sign language. Though we have many different types platform, still it not efficient so we need to use the advanced method which recognizes the input much efficiently. Since we are using gesture and voice as an input, this will act as bidirectional way communication. The focus of this work is to create a bidirectional-based system to identify sign language gestures from the sign language images and converting that to voice output. Since we are developing the application to computer and android, it should have two-way communication so that both can act as input and output node. For efficient voice input and output, we are using android mobile.
Longitudinal Study through Maximum Peak Age and Maximum Peak Velocity from Youth Physique Using Nonlinear Regression Equation

The purpose of this study was to investigate and analyze the maximum peak age(MPA) and maximum peak velocity(MPV) by using a polynomial expression with value of function from youth physique using nonlinear regression equation. For the completion of this study through longitudinal study, we sorted with BMI on youth physique in C city, Gyeonsangnam-do. Total of 959 students(553 males and 406 females) participated in this study. We collected data for 12 years from 1st grade(age 6) attending the elementary school in 2001 to 12SUPth/SUP grade(age 17) attending the high school. We used SPSS PC/Program(version 25.0) and sort three groups (underweight, normal, obesity). We also differentiated height and weight from male and female students with Origin Lab software (version Pro) by calculating the value of function through polynomial fitting and drew the graph. The results are followings. First, for the development and growth from the height of male students, it showed that MPA(age 11.78) and MPV(6.51cm/year) in the underweight group were the highest than other groups whereas MPH(maximum peak height)(154.43cm) was the highest than other groups in the obesity group. Second, for the development and growth from the height of female students, it showed that MPA(age 10.01) and MPV(4.83cm/year) in the underweight group were the highest than other groups in the underweight group whereas MPH(144.84cm) was the highest than other groups in the normal group. Third, for the development and growth from the weight of male students, it showed that MPA(age 12.75) was the highest than other groups in the underweight group. MPW(maximum peak weight)(58.81kg) and MPV(6.17kg/year) in the obesity group were the highest than other groups. Lastly, for the development and growth from the weight of female students, it showed that MPA(age 9.49), MPW(43.97kg) and MPV(5.01kg/year) in the obesity group were the highest than other groups.
E-only theses submission and preservation workshop

This workshop will provide participants with an opportunity to discuss issues relating to the deposit and archiving of e-only theses; and create a forum for promoting inter-institutional collaboration and knowledge exchange.
Applications of dynamic hypergraph visualization

We present a set of applications of dynamic hypergraph visualization. Dynamic hypergraphs can be used to represent connections between two or more entities that occur in time intervals. Visualizing dynamic hypergraphs can help analyzing the evolving connections in groups of entities. We report different domains where the data can be modeled as a hypergraph and some patterns that can be identified in the specific domains.
Crown lengthening procedure based on cone beam computed tomography measurements

This case report describes about a patient's desire and visualization of a pleasant smile for whom esthetic crown lengthening is indicated due to excessive gingival display.The Cone Beam Computed Tomography (CBCT) scan was used as a measurement using smile design principle which provided a reference for flap surgery and osteotomy procedure.A 6 months post-surgery follow up was obtained.
Design principles for music technology education support: Just-in-time learning in the recording studio using mobile technologies

Popular music education involves engaging students with using a range of music technologies found in recording studios, through utilization of multiple hardware and software devices to enable the recording process. Student users can struggle to keep up with the volume of knowledge required to operate these environments to their full potential. Providing just-in-time learning resources to support these students could improve student learning through augmenting gaps in their knowledge. Just-in-time learning is the provision of active learning opportunities that engage learners with skill development as part of the working process. This approach to supporting music technology education was trialled within a programme teaching popular music. The research found that students welcomed the provision of just-in-time learning opportunities delivered through a mobile phone application and that this suited their learning approach in the recording studio. This article suggests that mobile learning resources can benefit the curriculum of programmes working with music technology. The study was conducted using a design-based research methodology with students within a conservatorium teaching popular music. This popular music programme heavily utilized the recording studio as a learning and teaching tool, requiring students to engage with music technology routinely. Thirty students from all year levels of the undergraduate programme participated in the research project through surveys and focus groups. The research involved iterative cycles of mobile application design and testing over an eighteen-month period. Previously, a pilot study identified that students felt that on-demand learning opportunities delivered through mobile devices would be beneficial to their learning. The research from the design and testing of the mobile application evolved a series of design principles, which could be used as a guide for developing just-in-time resources to support music technology education.
Secure Database Authentication from Vulnerability Detection using Encryption Mode of Standardization

As the digital era is drastically increasing in the upcoming years, the security breach is also getting increased. The vulnerability or flaw occurs due to the malicious attack over the data. The security breach of the data has to be checked as it occurs due to the vulnerability state. Vulnerability or theft cause the data losses the integrity over the data. Data confidentiality loss occurs due to the security implications in the website. The website of the organization such as e-commerce sector has to be monitored as the intruder tries to attack the confidential information from the webpage by phishing technique. The illegitimate website which is trapped by the intruder which compromises the confidential information of the user and the credential information such as credit card, account details etc. In this paper, the novelty research is to risk the minimal factor by encrypting the credential information using the encryption mode of standardization. Encryption algorithm which is highly efficient in nature which can be used to minimal the risk factor of the intruder attack. The intruder tries to maliciously attack on the credentials of the data. Some of the malicious attack such as attacking the code, SQL server, cross-site scripting attacks, phishing, spoofing attack occurs on the website. These malware attacks maliciously attack the network mechanism. To secure the authentication, the encryption standard is used to secure the credentialed of the data by securing the data in an efficient way. If the data security is preserved then the minimal range of risk factor procures. By using the AES 256 standard scheme, the data security SQL server and cloud infrastructure can be secured. For the vulnerability prediction, the data mining is used for the classifying the exploitation based on the analysis.
Health Monitoring System

This paper illustrates a system that uses IoT to monitor a patient’s body 24/7 per day, seven days a week. The Health Monitoring System’s goal is to make health staff’ and individual users’ jobs easier, as well as to save time and money. Patient monitoring systems are gaining in popularity among academics and patient caretakers these days. Every 15 seconds, this system may measure physiological parameters from the patient’s body. This system is in charge of collecting the patient’s pulse, body temperature, and heart rate and sending the data to an IoT Cloud platform through WIFI-Module, where the patient’s health status is maintained. It allows a medical specialist or approved person to keep track of a patient’s health on a cloud server, where the specialist or authorized person may keep track of the patient’s status at all times. The study’s proposed outcome is to provide patients with appropriate and effective health care.
The Effects of Rainfall and Relative Humidity on Solar Radiation Intensity during Dry Season in Port Harcourt Metropolis-Quantitative Approach

In this study, we investigate the effects of independent weather variables of rainfall and relative humidity on the dependent weather variable of solar radiation intensity in Port Harcourt. This can be accomplished using appropriate instrumentation to measure the magnitudes of solar radiation intensity, rainfall, and relative humidity, and then using a Multistrand data analysis approach to determine their relationship and evaluate the integral influence of the independent variables on the dependent variable. This research is carried out in Rivers State University, which is located in Port Harcourt city local government Area. Port Harcourt city is a coastal part of Nigeria which is located in the Niger Delta region of Nigeria. Solar radiations are electromagnetic radiations that range from 0.25 to 4.5µm in wavelength. These radiations include the visible light, ultraviolet and near infrared (IR) radiation as shown in Fig.3 of the electromagnetic spectrum. The energy quantum from the solar radiations is called the photon. Data were collected in three months of dry season on daily basis at 5 minutes interval using appropriate instrumentations in Rivers State University NECOP Weather Station and analyzed with respect to their daily and weekly averages. It was observed that changes in amount of rainfall (mm) and relative humidity (%) negatively influence the magnitude of solar radiation intensity (W/m2) during the dry season that is from November through January. Nevertheless, the effect of rainfall (mm) on the solar radiation intensity (W/m2) was more obvious compared to the relative humidity (%) and this might be caused by the dryness of air during the dry season. It was also observed that there was no significant difference in solar radiation intensity (W/m2) for the different weeks in course of the effect of relative humidity in particular during the dry season. The findings of the study should be stored in the data banks of the aviation, agricultural, manufacturing, and meteorological industries, as well as government environmental ministries and agencies, for effective planning and execution of policies for long-term growth.