Reviewerly/exHarmony huggingface dataset:
Deep Learning Approach for Identifying and Classifying Cancer Types Using BPSO and GAN

One of the most dangerous and dreadful diseases in the world is cancer. In 2020, it was found that over 10 million people will die due to cancer. Main causes of cancer are either due to inherited genetics or environmental and lifestyle factors. The risk of cancer increases significantly with age, their type and many cancers occur more commonly in developed countries. Early detection of cancer plays an important role, as it increases the possibilities of betterment. Latest improvement of artificial intelligence techniques in terms of productivity and precision and also optimization algorithms have largely smoothed out the human genomics study. So, we propose an RNA-Sequence analysis method for identifying and classifying cancer types, which uses Binary Particle Swarm Optimization using Support Vector Machine (BPSO-SVM) as feature selection tool and Generative Adversarial Network (GAN) along with different classical augmentation techniques to avoid overfitting by increasing the size of dataset and a deep learning network as the last phase for classification and thus helps in increasing accuracy.
Elongation of curvature-bounded path

The elongation of curvature-bounded paths to an expected length is fundamentally important to plan missions for nonholonomic-constrained vehicles in many practical applications, such as coordinating multiple nonholonomic-constrained vehicles to reach a destination simultaneously or performing a mission with a strict time window. In the paper, by applying the properties of the reachability set of curvature-bounded paths, the explicit conditions for the existence of curvature-bounded paths joining two oriented points with an expected length are established. These existence conditions are numerically verifiable, allowing readily checking the existence of curvature-bounded paths between two prescribed oriented points with a desired length. In addition, once the existence conditions are met, elongation strategies are provided to get curvature-bounded paths with the expected length. Finally, some examples of minimum-time path planning for multiple Dubins vehicles to cooperatively achieve a triangle-shaped formation are presented, illustrating and verifying the developments of the paper.
Efficient Data Storage Security Analysis Using Randomized Algorithm in Cloud

Database re-appropriating is a common circulated registering perspective that empowers data owners to misuse its on-request accumulating and computational assets. The guideline challenge is keeping up the data arrangement concerning entrusted parties. We propose a combination of triple randomized algorithms namely 3DES, AES, Blowfish. The data owner can select between the encryption methods which is suitable. As each of the algorithms takes a different block size as input and also has various key sizes. Another issue that arises is the redundancy of data. When many copies of identical data are stored, the storage size decreases, and large storage space is required. Here data reduplication technique, which is used to identify duplicate files using the hash code value method for better storage space.
Digital Currency Illegal Behavior Detection Based on Mutual Information Prior Loss

In recent years, with the rapid development of digital currency, digital currency brings us convenience and wealth, but also breeds some illegal and criminal behaviors. Different from traditional currencies, digital currency provides concealment to criminals while also exposing their behavior. The analysis of their behavior can be used to detect whether the current digital currency transaction is legal. There is a problem that most digital currency transactions are in compliance with laws and regulations, and only a small part of them uses digital currency to conduct illegal activities. It belongs to the problem of sample imbalance. It is quite challenging to accurately distinguish which transactions are legal and which are illegal in the massive digital currency transactions. For this reason, this study combines the mutual information and the traditional cross-entropy loss function and obtains the loss function based on the mutual information prior. The loss function based on the mutual information prior is that the bias of the category prior distribution is added after the output of the model (before the softmax), which makes the model consider category prior information to a certain extent when predicting. The experimental results show that the use of the loss function based on mutual information prior to the detection of digital currency illegal behavior has a good effect in SVM, DNN, GCN, and GAT methods.
Multiquadratic rings and oblivious linear function evaluation

The Ring Learning with Errors (RLWE) problem has been widely used for the construction of new quantum-resistant cryptographic primitives. Most of the existing RLWE-based schemes make use of power-of-two cyclotomic rings due to their good performance and simplicity. This talk explores the replacement of power-of-two cyclotomic rings by multiquadratics. We show that for polynomials with $n$ coefficients, the cost of the polynomial operations can be reduced from $\mathcal{O}(n \log{n})$ multiplications to $\mathcal{O}(n)$ multiplications and $\mathcal{O}(n \log{n})$ additions. Finally, we discuss the benefits that these rings can bring about when implementing the OLE (Oblivious Linear Function Evaluation) primitive, which is a basic block used in many Secure Multiparty Computation (MPC) protocols.
Optimasi Augmented Reality Sebagai Media Pembelajaran Interaktif Alat Musik Gamelan Jawa Tengah

Education is basically a process of maturing students through the development of abilities and skills that exist in themselves so that they can be of quality so that the abilities and skills they have can play a role in building themselves and the surrounding community. One of the subjects that practice the abilities and skills of students is the Cultural Arts. Art and culture is a material taught in middle school. At SMP N 1 Sumpiuh, Arts and Culture teaches the traditional music of Central Java, Gamelan. So far the supporting media used by teachers to teach are still inadequate because of the limited amount of Gamelan. This is considered less effective in teaching Gamelan practice. The purpose of this study is to create an interactive media for learning the musical instrument of Gamelan in Central Java in the form of an Augmented Reality-based application to help the introduction of Gamelan in Cultural Arts material. The system development method used is the MDLC method. From the results of the beta test using a questionnaire against 15 respondents and produced a value of 89.33% with the category of strongly agree. The results of this study are augmented reality optimization as an innovative learning media for Central Java gamelan music instruments
A(n) Assumption in machine learning

The commonly used statistical tools in machine learning are two-sample tests for verifying hypotheses on homogeneity, for example, for estimation of corpushomogeneity, testing text authorship and so on. Often, they are effective only for sufficiently large sample (n> 100) and have limited application in situations where the size of samples is small (n < 30). To solve the problem for small samples, methods of reproducing samples are often used: jackknife and bootstrap. We propose and investigate a family of homogeneity measures based on A(n) assumption that are effective both for small and large samples.
Hand Tracking and Detection Using Python and OpenCV

Man, always strived to do things differently using artificial technology which is trending in the present-day scenario. One among such wonderful ideas there born this gesture recognition and finger counting. In this, see how a human hand will be detected when and how to finger counting takes place. Hand gestures play a vital role in human-computer interaction. In this article, presented a method for hand recognition, detection and the finger count will be done and displayed. Moreover, it is not only meant for fun and entertainment but can also be used in our daily life for various applications. The proposed method is a very efficient method and easy to use for Human-computer interaction. The logic present behind its detection is new and showing robustness over the existing method.
Semantic Templates for Generating Long-Form Technical Questions

Question generation (QG) from technical text has multiple important applications such as creation of question-banks for examinations, interviews as well as in intelligent tutoring systems. However, much of the existing work for QG has focused on open-domain and not specifically on technical domain. We propose to generate technical questions using semantic templates. We also focus on ensuring that a large fraction of the generated questions are long-form, i.e., they require longer answers spanning multiple sentences. This is in contrast with existing work which has predominantly focused on generating factoid questions which have a few words or phrases as answers. Using the technical topics selected from undergraduate and graduate-level courses in Computer Science, we show that the proposed approach is able to generate questions with high acceptance rate. Further, we also show that the proposed template-based approach can be effectively leveraged using the distant supervision paradigm to finetune and significantly improve the existing sequence-to-sequence deep learning models for generating long-form, technical questions.
A method for generating various style Chinese fonts in the absence of training data (S)

In recent years, the generation of arbitrary style fonts has drawn broad attention.At present, the common idea of most methods is to train the model through a large number of text samples of a specific style, so that the model can learn the font style, and then automatically generate all the text of the style.However, in the case of insufficient sample data, almost all the current methods fail.In this paper, we investigate how to generate arbitrary style Chinese fonts automatically, especially when the sample data of specific style is insufficient.In order to solve the problem, we propose a new frame.The method can be used to generate the fonts of Chinese ancient calligraphers whose relics are rare.The experimental results show the effectiveness of the new frame.
ZERO WASTE COLLABORATIVE SHOP DI BANJARBARU

Waste is a problem that has become a never-ending topic to get talked about all over the world. Indonesia alone has produced 67 tons of waste only in 2019 by the percentage of organic waste dominating more than half of the total waste. The issuance of a presidential regulation on waste management coupled with a law that regulates sustainable economic policies became the reason why the Zero Waste Collaborative Shop in Banjarbaru gets to design. So the problem that needs to be solved is how to design a Zero Waste Collaborative Shop that can accommodate the interactions between the environment, society, and economy so the three of them could integrate with the surrounding community? Zero Waste is a philosophy that is used as a lifestyle to encourage the cycle of resources so a product can be used sufficiently, and not excessively while the rest of the waste can be reprocessed. The design of the Zero Waste Collaborative Shop will have three problems, which are environmental, social, and economic issues. Therefore, the locality was chosen as the method to assist the Stacking the System concept which is expected to be the solution to these problems.  The results of this paper are formulating the concept of planning the commercial space by stacking the permaculture systems, circular economy, and community collaboration, with the outcomes in the form of 1) The implementation of the reuse principle in former office buildings that are not maintained so that it will have new functions 2) Analyzing the climate data surrounding the site so that it is following the needs of the site location 3) Utilizing the permaculture ethical principles, that respect natural resources such as land, water, sun and wind 4) Mapping the utility flow schemes as a model for commercial space 5) Providing space for surrounding communities in the application of Zero Waste to everyday life
The Effect of Artificial Intelligence (Microbit) in Raising the Motivation Towards Learning Programming Among the Students of Educational Technology at King Abdulaziz University in Jeddah: أثر الذكاء الاصطناعي المايكروبت (Microbit) في رفع الدافعية نحو تعلُّم البرمجة لدى الطالبات في مقرر تقنيات التعليم بجامعة الملك عبد العزيز بجدة

The research seeks to know the effect of Artificial Intelligence (Microbit) in raising the motivation towards learning programming among the students of educational technology at King Abdulaziz University in Jeddah. The sample consisted of (14) students, and the research followed the quasi-experimental method for one experimental group. Also, a pre-measurement and post-measurement was done by using the motivation measure towards learning programming. The results of the research confirmed that there were statistically significant differences at the level of significance (0.001) between the results of students for their motivation towards learning programming before and after the use of the (Microbit) in favor of post-measurement. The research also recommended the importance of employing artificial intelligence techniques in curricula and academic projects for its effective role in making the education process active, improving the performance of male and female students and raising their motivation. As well as, preparing educational institutions and centers, and training teachers to work using artificial intelligence techniques, especially the Microbit device.
LibGuides: Library / Open Access Database Tools and Tips: Intro to Library Databases

Most databases have common elements which help streamline your research and save time. This How-To guide shares tools and tips for using the library databases at ACC.
AN ANALYSIS OF SPEECH ACT IN THE CONCESSION SPEECHES

The purpose of this study is to explain the various forms of speech acts used in concession speeches. Concession speech is a term used in politics to describe speeches given by losing candidates after an election and after the overall vote, the result is known. The data of this study were taken from four types of concession speeches delivered by losing American candidates in the form of concession speeches: John McCain (2008), Mitt Romney (2012), Hillary Clinton (2016), and Donald Trump (2021). The method used in this study is a qualitative descriptive method because it uses words rather than numbers as a reference for the data to be studied, and it implies obtaining results for collecting the data included in the data sources and analyzing them to detect differences in concessions, speaking actions and Pragmatic discourse analysis approach to speech. The theory used is derived from the theory of Searle (1976), Cutting (2003), Holmes (2013), Leech (1947). The results show (1) five types of speech acts, namely representative (fact, statements, describing, and conclusion), expressive (thanking, congratulating, praising, and wishing) directive (inviting, requesting, suggesting, and ordering), and commissive (promising, offering), (2) the language function of each type of speech acts according to the context used by the concession speech, such as expressing gratitude, working together in building America, etc. (3) the most widely used in concession speech are expressive speech acts (thanking and praising) and representative speech acts (statements). The results of this study indicate that the losing candidate's sportsmanship supports the winning candidate and the various words used to say the same thing contributes to the development of English vocabulary.
A method for outlier detection based on cluster analysis and visual expert criteria

Outlier detection is an important problem occurring in a wide range of areas. Outliers are the outcome of fraudulent behaviour, mechanical faults, human error, or simply natural deviations. Many data mining applications perform outlier detection, often as a preliminary step in order to filter out outliers and build more representative models. In this paper, we propose an outlier detection method based on a clustering process. The aim behind the proposal outlined in this paper is to overcome the specificity of many existing outlier detection techniques that fail to take into account the inherent dispersion of domain objects. The outlier detection method is based on four criteria designed to represent how human beings (experts in each domain) visually identify outliers within a set of objects after analysing the clusters. This has an advantage over other clustering‐based outlier detection techniques that are founded on a purely numerical analysis of clusters. Our proposal has been evaluated, with satisfactory results, on data (particularly time series) from two different domains: stabilometry, a branch of medicine studying balance‐related functions in human beings and electroencephalography (EEG), a neurological exploration used to diagnose nervous system disorders. To validate the proposed method, we studied method outlier detection and efficiency in terms of runtime. The results of regression analyses confirm that our proposal is useful for detecting outlier data in different domains, with a false positive rate of less than 2% and a reliability greater than 99%.
Presupposition of Slogan in the Jakarta Post Advertisement

ABSTRACT This study aimed at identifying the types of the presupposition on the slogans of the advertisements in the Jakarta post. Slogan is the words employed to describe the virtues of products or services. Presupposition is one of the indispensable things in a communication, especially in the advertisement. Mostly the presupposition is frequently employed by the advertiser to convey a message about product or service since it possesses some virtues in the advertisement. Yule’s theory (1996) and Lam (2009) were used to identify the presupposition found. The research method employed was the qualitative method. From the data analysis, some types of presupposition were found 5 types of presupposition, namely 6 existential presuppositions, 6 factive presuppositions, 6 lexical presuppositions, 1 structural presupposition, 2 non-factive presuppositions Keywords: Pragmatics, presupposition, advertisement, slogan
APPLICATION OF DIFFERENTIATED AND INDIVIDUALIZED TEACHING IN UPPER GRADES OF PRIMARY MATHEMATICS TEACHING

The paper deals with the problem of application of differentiated and individualized mathematics teaching, in upper grades of initial mathematics classes. We will try to answer some very important questions of modern mathematics teaching, dealing with differentiated and individualized teaching both in acquiring new knowledge and in repeating, practicing and determining mathematical content, and see what is necessary to achieve the conditions for good differentiation and individualization in the teaching process. Contemporary education and society-imposed life needs, impose new education needs and goals daily. Mathematics is an extremely favourable subject for achieving new education goals, enabling students to acquire critical thinking, life-long education, and enable the students to adequately cope with every problem situation. Mathematics teaching modern methodology, as a priority of differentiated teaching, must include the principle of individualization. In primary school, in the upper grades of primary mathematics classes, the utmost respect for the principle of individuality is justified by the fact that the students’ possibilities, abilities and interests within the class have already been differentiated, so during differentiated classes, the focus will primarily be on active involvement of all students in the teaching process. In individualized teaching, the focus is on an individualized approach that emphasizes the special and certain abilities of an individual, which is emphasized in the very teaching process. Differentiated teaching takes into account the differences between students and specific structures within a class, while striving to optimally demonstrate the mathematical abilities of each student, while individualization, as a higher degree of differentiation among students, strives to achieve the adoption of mathematics education by each student individually according to the student’s abilities. The application of differentiated and individualized teaching in the upper grades of primary mathematics teaching, primarily develops abstract and critical thinking in students, leads to increased motivation, development of thought operations, independence, originality, which than leads to creative and productive expression of students' abilities and better and lasting acquisition of knowledge. In this way, every student develops a love for mathematics and a desire to independently solve the problems, and breaks down stigma and prejudices about mathematics as being abstract and difficult, which, with its problems, is understandable only to some students, while for others, it remains unattainable.The aim of this paper is to underline the importance of applying differentiated and individualized mathematics teaching in the upper grades of primary mathematics classes, so that each student can achieve his/her maximum in mathematics, in accordance with his/her abilities, possibilities and interests, with good and professional teacher support.
A Privacy by Design Methodology Application in Telecom Domain

Telecommunication has been considerably developed over the last decades, notably through optical fiber submarine cables and wireless connections offering voice and data wide range services. Telecommunication infrastructures are the necessary backbone that make possible any voice and data exchange. Unfortunately, these infrastructures are still suffering from various vulnerabilities and continue to be target of specific cyber-attacks. Some of these attacks could lead to service deniability, integrity and privacy loss. Against this fact, it’s also established that telecom service providers, as the owner of this infrastructure,can have access to huge data,                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            even personal data related to customer and  to their employees. Basically, this personal data is related directly to the customer’s and employee’s identity, geolocation, interest areas and contact circle, etc.,  when it comes to the use of this personal data, the privacy concerns become a big challenge for telecom service providers due to heavy impact that can induce. Given the personal data protection criticality in telecom domain, privacy by design PbD should be incorporate. Then, this article aims to apply in telecom service providers ISPM methodology Information System Privacy Methodology which focuses on PbD implementation in enterprises architecture, specifically in information systems taking into account all technical and organizational aspects.