Reviewerly/exHarmony huggingface dataset:
Design And Implementation Of A Geospatial Dashboard For Crime Analysis And Prediction

&lt;div&gt;Dashboard has been around for a long time, and many have been developed as a governing and monitoring tool in city management, such as crime monitoring. However, the majority of crime dashboards function as a visualization tool and few of them has been specifically developed for crime analysis and prediction.&lt;/div&gt;&lt;div&gt;This thesis focuses on the development of geospatially-enabled crime dashboards with spatial analysis capabilities for supporting crime analysis and prediction. A prototype has been designed and implemented to support the understanding of crime events for crime reduction efforts. This dashboard will assist policy makers and leaders in crime fighting by visualizing basic statistical information of crimes, revealing their spatial and temporal patterns, identifying crime clusters, and analyzing relationships between crimes and other factors. Based on the criteria developed in this thesis, the prototype confirmed its ability of enhancing the understanding of crime events.&lt;br&gt;&lt;/div&gt;
Camera and projection models

Chapter Contents: 4.1 Mathematical preliminaries 4.2 The pinhole camera model 4.3 Intrinsics of the pinhole camera 4.4 Projection matrices 4.4.1 Mathematical derivation of projection matrices 4.4.2 Characteristics of the projection matrices References
A Case Report on Malaria

Introduction: Malaria is caused by the parasitic protozoan Plasmodium. It is a vector-borne disease which is transmitted from person to person via bites from infected mosquitoes. Following a mosquito bite the parasites multiply in the liver and subsequently infect red blood cells. It is a mosquito-borne illness. Fever or flu symptoms include shivering chills, headaches, and muscle pains. Anemia, jaundice, nausea, and diarrhea are some of the symptoms of malaria.&#x0D; Main Symptoms and Important Clinical Findings: A 24-year-old woman was admitted in. Acharya vinoba bhave rural hospital with chief complaint of stomach pain as her primary complaint. Then after several days Fever, pain, fatigue, headache occur. Several diagnostic evaluations done which shows total Red blood cells count: 4.8 million cu mm; white cell count: 11.810 cells mm3; lymphocytes: 11.2% platelets drop on smear, RBCs are moderated.&#x0D; The Main Diagnoses, Therapeutic Interventions, and Outcomes: 24 years old women admitted in Acharya vinoba bhave rural hospital with the chief complaint of stomach pain, fever, fatigue, headache and after all investigation she has diagnosed as malaria. Doctor manage with Iv fluids, cap. Doxycycline 100 mg, tab.dolo 650 mg, tab.larigo 650 mg, emset 4 mg injection Once a day, she was also given the Calcium Tab. Her condition has improved as a result of the treatment. The fever and agony had subsided.&#x0D; Conclusion: My patient was admitted to Acharya vinoba bhave rural hospital with a known case of malaria and a fever and discomfort complaint. Her condition improved after she received proper therapy.
Protecting Against Malicious Code Injection in Reviews on Web Applications

Malicious code injection is done by the attackers or hackers mainly in reviews, these are the fake user identities that are created by the attackers, through sending continuous links to some user till the user clicks on that link. When user clicks the link, that particular users identity will be stolen by the attackers which is done like the phishing, generally these reviews which are maliciously injected are mixed with the original users review of the product in a website. To identify these malicious injection attacked reviews, in this paper the Naive Bayes Classifier (NBC) algorithm is used. Then to eliminate the unwanted disturbed data in the website the Natural Language Processing technique is used. The Natural Language Processing (NLP) technique, which removes unwanted data by understanding the text or words in review. Then the length of the reviews in the given sample dataset is reduced for easy understanding by using the Principal Component Analysis (PCA) algorithm which reduces the dimensionality of the reviews. Then user input review is compared with the sample dataset and classified as good review and bad review and also detected as malicious or not by using the Naïve Bayes Classifier algorithm which is used for the classification of the objects.
Etiquetadores morfosintácticos para corpus en español

In languages of rich inflectional morphology such as Spanish, the automatic treatment of the internal information contained in words is essential. In the first place, the characteristics and problems of morphological taggers are addressed. Their function is to detect PoS, lemma and grammatical features for each word. The formal variation of words is responsible for its 405computational complexity. Any tagger has to recognize and generate only grammatical forms. Two serious problems are the “unknown” words (usually neologisms) and the multiwords (lexical units formed by more than one word). The full listing of words, associated with their linguistic information, produces many homographs: the same wordform can have several morphosyntactic analyses. A disambiguation component to resolve homography is necessary for any tagger, which performs the selection of the appropriate analysis, according to the syntactic context of appearance. All current taggers use a statistical model for disambiguation, based on corpora hand-annotated by linguists. In the second part of the chapter, the different options that a corpus user faces will be dealt with. The performance of automatic taggers depends basically on the tagset (descriptive tags provided by the program) and the semantic domain or language register for which the disambiguation model is trained. Therefore, the choice of the most appropriate tagger for our corpus depends on these two factors. The best-known Spanish taggers and their use within corpus tools are analyzed in this chapter.
Auto-mobile Search Engine

The majority of people are looking for vehicles. To find their desired vehicle, people search on the most popular websites. The sellers post their ads on multiple sites to reach out to a larger audience. This means buyers have to find their desired vehicle on multiple sites to compare the prices because buyers always look for lower prices. This search needs to visit and find ads on multiple vehicle entertaining websites, which requires much time. In this paper, we are proposing a unique “Automobile Search Engine” (ASE) which grabs all the automobile ads posted on different websites. Our solution will give a single search for automobile ads. The user can get all the ads based on his/her search criteria. ASE will find all the ads for different websites and will display the results. The user can then compare the searched ads on one single view. ASE supported Multi Thread Crawler.
The Design and Implementation of Blockchain-Assisted User Public-Private Key Generation Method

The rapid development of network technology has brought new challenges to data security. As the first gateway of a certain mobile internet system, access authentication is an essential step that guarantees the internal security of the network. However, there are some problems in traditional cryptosystem-based authentication mechanisms, such as certificate management problem and centralized key escrow problem. Centralized storage of user information is restricted by the server, the security of the server is not within the user’s control, the stability of the server cannot be guaranteed, and personal privacy on the server may be leaked. In this paper, we focus on the private key escrow problem caused by the Private Key Generator (PKG) in Identity-Based Cryptosystems (IBC) mechanism and propose a Blockchain-assisted user public-private key generation scheme (BAKG) which introduces the blockchain to improve the robustness and reliability of key management. In BAKG, the user’s private key is determined by itself through combining the partial private keys from different PKGs, which prevents the risk of private key exposure caused by a single PKG. Meanwhile, based on the theory of the Combined Public Key (CPK) algorithm, we have designed a feasible blockchain-based key generation logic and developed a prototype authentication system based on the above concept. We further analyze the security of BAKG and the analytical results show that BAKG can meet various security requirements. In addition, according to the performance evaluation results, BAKG has good performance in both read/write consensus and different key length calculations, which means it has good potential for lightweight authentication applications.
A Bayesian Network-based Quantum procedure for Failure Risk Analysis

&lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;p&gt;Studying the propagation of failure probabilities in interconnected systems like that of electrical distribution networks is traditionally performed by means of Monte Carlo simulations. In this paper, we propose a procedure to create a model of the system in a quantum computer using a restricted representation of Bayesian networks. Some examples of this implementation on sample models are presented using Qiskit and tested using both quantum simulators and IBM Quantum hardware. Results show a correlation in the precision of the results when considering the number of Monte Carlo iterations alongside the sum of shots in a single quantum circuit execution. &lt;/p&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt;
Professional Identity of Applicants and Students in the System of Higher IT Education of Ukraine

The article considers the methodological problem of forming the professional identity of entrants and students in the transition to a knowledge society.It is shown that the choice of profession takes into account the dynamics of professional development of the individual, associated with the formation of his professional identity and the process of professional selfdetermination.The analysis of the factors influencing the choice of profession by young people was studied on the example of IT professions.The article lists the most popular IT professions in 2021.In accordance with the trends of interaction between IT education and the IT industry, the trends in the development of higher education in Ukraine and their impact on the formation of professional self-awareness of young people are described.The authors consider the professional identity of the individual as one that develops as a result of his work or educational activities.The paper analyzes the factors that contribute to the formation of the professional identity of applicants.The article proves that the choice of university entrants is a factor influencing their professional self-determination.The choice of the educational program by the entrants is considered as a factor of their professional self-realization, and the formation of the individual educational trajectory of the student is considered as a factor of realization of the "I-concept" at the level of determining professional preferences of entrants.The article analyzes the dynamics of change in the professional identity of entrants and students on the example of training in the speciality "Software Engineering" at different stages of becoming a competent specialist.The dynamics of the development of a student's professional identity from student identification "Istudent" to European identity as a condition of integration into the European community is shown.
Measurement of software quality based on international standards

Quality is one of the factors that ensure the commercial success and safety of using the software. Quality is understood as conformity the explicit and implicit requirements of various stakeholders. It is necessary to ensure a joint understanding between developers and users, engineers need to understand the meaning of the concept of quality, characteristics and importance of quality for the developed or maintained software. Measurements are the basis for quality assurance. They are the main tool for managing the life cycle of software products, assessing the implementation of plans and monitoring. To quantify quality, it is necessary to measure the characteristics of the software. Standardization provides unification of requirements for quality, its measurement and assessment. The use of standards has many potential benefits for any organization, especially in key areas such as measuring the quality of software products, information and measurement systems. Recognized international standards organizations have published the ISO/IEC 25000 series of standards for systems and software quality requirements and evaluation (SQuaRE), which is gaining widespread practical application. The paper discusses a series of the SQuaRE international standards, analyzes the relationship between the quality model, quality characteristics, quality measures and a new concept, i.e., a quality measure element of the software, presents the measurement of quality based on these standards.
Learning Memory Propagation And Matching For Semi-Supervised Video Object Segmentation

Abstract This paper studies the task of semi-supervised video object segmentation (VOS). Multiple works have shown the outstanding performance of the memory retrieval method based on matching, which performs temporal and spatial pixel-level matching, but does not pay attention to the temporal relationship of the frames. To this end, we propose a memory propagation and matching (MPM) method, combining the propagation-based method and matching-based method simultaneously, to reduce some wrong matching and maintain the consistency between adjacent frames and make the model more robust to occlusion and object disappearance and reproduction. Inspired by the remarkable effect of recurrent neural network (RNN) based methods in video tasks, we proposed memory propagation (MP) module which uses Convolution Gate Recurrent Unit (ConvGRU) for memory propagation, and the memory refinement is carried out when the target frame is segmented. At the same time, MPM matches the target frame with the first frame and the previous adjacent frame. The multi-object matching (MOM) module calculates the probability matrix of each pixel belonging to each object, so that the MPM model can effectively distinguish different objects. Experiments show that the MPM model has achieved J&amp;F 82.8% on DAVIS 2017 Validation dataset and J&amp;F 80.1% on YouTube-VOS dataset.
Teknik Data Mining menggunakan Algoritma Decision Tree (C4.5) untuk Prediksi Seleksi Beasiswa Jalur KIP pada Universitas Muhammadiyah Kotabumi

Smart Indonesia Card Scholarship (KIP) is an educational scholarship provided by the government for equivalent SMA/SMK/MA alumni who have good academic potential and wish to continue their studies to a higher
Redesign Web Sekolah Metode User Centered Design

The web is indispensable as a medium for school promotions to attract interest and information about schools. This website will be used to make it easier for both teachers, students, and guardians of students. The problem we often face is that the appearance of the website is unattractive and less informative. Starting from unattractive colors, news and information are not updated. It is necessary to redesign the school web to provide an attractive and informative appearance. The method in this research uses User Centered Design (UCD) starting from Plan, Design, Prototype and review. This study aims to produce a website for SMK Negeri 1 Perhentian Raja that is informative and liked by users
Consistent 3D Hand Reconstruction in Video via self-supervised Learning

We present a method for reconstructing accurate and consistent 3D hands from a monocular video. We observe that detected 2D hand keypoints and the image texture provide important cues about the geometry and texture of the 3D hand, which can reduce or even eliminate the requirement on 3D hand annotation. Thus we propose ${\rm {S}^{2}HAND}$, a self-supervised 3D hand reconstruction model, that can jointly estimate pose, shape, texture, and the camera viewpoint from a single RGB input through the supervision of easily accessible 2D detected keypoints. We leverage the continuous hand motion information contained in the unlabeled video data and propose ${\rm {S}^{2}HAND(V)}$, which uses a set of weights shared ${\rm {S}^{2}HAND}$ to process each frame and exploits additional motion, texture, and shape consistency constrains to promote more accurate hand poses and more consistent shapes and textures. Experiments on benchmark datasets demonstrate that our self-supervised approach produces comparable hand reconstruction performance compared with the recent full-supervised methods in single-frame as input setup, and notably improves the reconstruction accuracy and consistency when using video training data.
Enhanced Algorithms for Steganography Based on Least Significant Bit and Secret Image Compression

the data can be secured using various methods, such as cryptography, watermarking, and steganography. For secure communication, an image is utilized as the cover in image steganography. Hiding the secret image requires a large number of bits, thus you need a larger number of pixels in the cover, and this reduces imperceptibility. In this paper, large capacity is hidden in less space inside the cover. The secret image is compressed by only one of the two compression methods, the first is applied Huffman encoding and in the second method, the secret image is compressed to approximately half its size. The second method results in a higher Peak Signal-to-Noise Ratio (PSNR) rating and greater robustness. The tent chaotic map is used to obtain random locations. The secret image is hidden using the Least Significant Bit technique (LSB) in the cover pixels corresponding to resulting locations of the chaotic map in the last bit, two, or three randomly, which provides a high level of security. The complete method is carried out in MATLAB, and the results are analyzed, which shows greater protection for hidden information. According to the quantitative results, our proposed technique gets the highest PSNR between 44.00 and 47.986.
University Teaching Management Information System Based on Intelligent Data Mining

To stimulate students’ interest in learning and design a simple teaching system, a college teaching management information system based on intelligent data mining is proposed. The hardware of the system first designs the intelligent data mining application server and then designs the database server to store a large amount of data. In the design of college teaching management information system software, the data mining database of the management system and two user modules for teachers and students are designed. The design of the college teaching management information system is realized by combining hardware and software. Through the system test, it is verified that when the number of login is 1500, the system response time is less than 12s. The system meets the design requirements, has good performance and runs well.
Complex Pattern Recognition using Feedback Algebraic Activation Function

Various researches on the Wisconsin breast cancer dataset in the prediction of benign and malignant were proposed in this work. The various classification models were used in the literature survey in which logistic regression give the better accuracy of 95.41%. But in machine learning model, the linear relationship between the features may lead to over fitting in that model. The neural network is a fully connected layer to find and understand the nonlinear combinations of the features in the dataset. To reduce the over fitting and improves the accuracy of the model, the Neural Network with Feedback Algebraic Activation (FAA) function is introduced and applied to the hidden layer in the network . In this, the error will be added as a feedback to the network and uses the keras callbacks and keras tuner for selecting the optimal parameters and produces the better results with the accuracy of 95.91% compared with all other activation functions in the neural network.
ORTHODONTIC FORCE DIFFERENCE ON ACTIVE COMPONENTS ACTIVATION OF REMOVABLE ORTHODONTIC APPLIANCES (PERBEDAAN BESAR GAYA ORTODONTI PADA AKTIVASI KOMPONEN AKTIF PERANTI ORTODONTI LEPASAN)

Orthodontic treatment is performed by moving the malposition teeth into a good position in the dental arch with a removable or fixed orthodontic appliance. In this regard, the removable orthodontic appliance has an active component to transmit the orthodontic force that will result in orthodontic tooth movement. The orthodontic force used must be optimal in the sense of being able to produce tooth movement without causing side effects that endanger the periodontal tissue. It is necessary to activate the active components of the appliance, which in orthodontic treatment can be done several times until the desired tooth position is achieved. This study aims to explain the differences in orthodontic force in activating active components of removable orthodontic appliances. The research method was an experimental laboratory. A total of 24 removable orthodontic appliances used in this study were divided into two groups. The first group has a Z spring or single cantilever spring active component, and the other group has a labial bow. Each active component is activated by opening the loop by 1mm, 1.5mm, and 2mm, and in each activation, the magnitude of the force generated is measured using a tension gauge. Data analyzed by Mann Whitney (p&lt;0.05). The result showed different activations carried out in this study resulted in significantly different forces with p=0.029. The force generated in each activation increases as the loop opening increases. Based on that results, it can be concluded that there is a significant difference in the force magnitude generated by the activation of the removable orthodontic appliance active component.
What are cognitive illusions?

In this introductory chapter, I describe what constitutes the domain of cognitive illusions and how cognitive illusions can be characterized. Much debate has evolved around the classical “heuristic and biases” approach, also involving the accusation of producing more or less artificial biases. I discuss these arguments in detail including the question of which normative standard to apply and conclude that cognitive illusions span a wide range of phenomena from simple “tricks” up to hard-wired and unavoidable systematic errors. Next I discuss potential explanations, especially dual-process models and simple information-processing strategies. Finally, I take a look at the impact of cognitive illusions in applied contexts outside the lab and how the adaptive value of cognitive illusions can be judged. Most researchers probably agree that cognitive illusions can be seen as the (mostly bearable) costs of an otherwise highly functioning and efficient cognitive system.
The mistery of gravity simple

Every time you jump, you experience gravity, It pulls you back down to the ground, without gravity you’d float off into the atmosphere. We see gravity at work in our lives every day and we see the evidence, but the mystery is still there. Even with several well-received theories attempting to explain why a book falls to the ground they’re still just theories and the mystery of gravity is still unexplained. Maybe the song recurring in internet is wrong, maybe we do not want to change our mind or may be the confidence of living on the same Earth and the attitude of looking at the same sky produced a hindrance to follow the intuitions of our best masters, to perceive the suggestions derived by their unexplained experiments and to make use of available data. In the present paper we start from the free fall Galileo experiment joined with Plank black body model and thanks to available nuclear data and to Fermi radioactive beta decay theory, we prove that it is possible to build a new theory for Gravity that is consistent with Newton model, does not suffer the complexity of Einstein in the description of the gravitational field and can explain some of the question marks present in natural phenomena and in books of physics.