Reviewerly/exHarmony huggingface dataset:
Evaluation of mRNA Markers for Estimating Blood Deposition Time

RNA analysis provide insight into diseases, molecular identification of body fluids and mechanisms leading to death and might develop into a valuable tool for identification of the cause of death in forensic pathology. Further potential uses are the determination of the age of wounds and the post-mortem interval. In this proof-of-concept pilot study clarifies and explains principles, applications and methods by offering a comprehensive and complete overview of using mRNA markers for estimating blood deposition time which can help to evaluate the time of the crime in forensic RNA work. The study presented in this thesis aimed to estimate the time passed since blood stains found in the crime scene by calculating the time of deposited blood using particular mRNA markers and unravelling one of the principles of at what time – when during the day or night a biological evidence was left at the scene – by applying the insights from circadian biology to some open forensic cases. By analyzing 4 candidate mRNA markers expression in peripheral blood samples collected from 29 health males. Blood samples were collected from healthy persons for the duration of the 24 hours’ day/night interval under four different groups, i.e. night/early, morning early morning/morning, morning/afternoon and afternoon/night. This study identified 2 mRNAs with statistically significant expression rhythms which are MKNK2 and PER 3. It’s found that, in general mRNA-based estimation of time categories was less accurate. The value of mRNA was demonstrated for blood deposition timing and introduced a statistical model for estimating day/night time categories based on molecular biomarkers, which shall be further validated with additional samples in the future.
RANCANG BANGUN SISTEM PAKAR KONSULTASI SISWA BERMASALAH DENGAN METODE FORWARD CHAINING BERBASIS WEB DI SMP MUHAMMADIYAH 1 WELERI

Problems that occur in students will be able to affect student learning processes. Even more problems that deviate from the prevailing social norms that can jeopardize the establishment of the system social. The design of this expert consulting system for problem students is based on the website using the method forward chaining with the aim to help analyze the causes of problems of students and subsequently the teacher counseling guidance to follow up on the results of student consultations. This expert system uses the Depth First Search (DFS) search technique and forward chaining as the inference method. The results of alpha and betha testing on the expert system indicate the expert system is feasible based on a questionnaire on alpha and betha testing.
Alternatives to Solar Power Plant Location Through GIS and AHP: Case of Karaman, Turkey

In meeting today's increasing energy needs, the use of renewable energy sources becomes widespread comparing with the thermal and nuclear power plants, which cause great harm to nature. While hydroelectric power plants are most common among renewable energy plants in Turkey, national policies towards increasing wind power plants and solar power plants are gaining momentum. Due to its geographical location, Turkey is more advantageous position compared to many other countries in terms of solar energy potential. The region receiving the most solar energy in Turkey is Southeastern Anatolia, followed by the Mediterranean and Eastern Anatolia. It is seen that the solar energy potentials of Antalya, Karaman, Mersin and Van provinces are higher than other provinces of Turkey. With the help of a well-known Turkey map on the solar potential of cities, it is possible to determine the advantageous cities which solar power plants (SPP) can be placed. However, there is a need for a multi-criteria decision-making method regarding where position solar power plants in these cities. With this work; according to the solar radiation values of Turkey, it is aimed to determine the alternatives for the most suitable SPP locations in Karaman Province, which has an important potential for the establishment of a solar power plant. Appropriate locations were determined by a multi-criteria and geographic information systems (GIS) supported method. Eleven criteria with data for the city of Karaman have been identified among the criteria mentioned in the related literature. The scores obtained from these criteria (in grids of 100x100 meters) are classified into five categories. The weighted scores were then standardized to a range of 1-5 with tools to reclassify in GIS environment. Reclassified weighted criteria were overlapped with Weighted Overlay Analysis to determine the most suitable regions for SPP investment.
Implementasi Kurikulum Berbasis KKNI Menuju Era Revolusi Industri 4.0: Telaah Literatur

Curriculum changes in tertiary institutions are routine activities that must be carried out in response to the development of Science and Technology, community needs, and the needs of graduate users. The curriculum currently used is the Indonesian National Qualification Framework or commonly abbreviated as KKNI. Namely the framework for qualifying work qualifications that juxtaposes, equalizes, integrates, the education and training sector as well as work experience in the context of providing work competency recognition in accordance with work positions in various sectors. The rapid development of information technology has influenced all aspects of life, including the business and accounting world. To that end, the curriculum of the accounting study program must harmonize with the development of the information technology. Namely the curriculum in accordance with the development of the Industrial Revolution 4.0. Various attempts have been made by several accounting study programs, including conducting workshops to review existing curricula, integrating the latest information technology materials into several (all) accounting courses currently available, training lecturers related to the latest information technology materials and adding eyes new lectures related to the latest information technology.
Exploring Gaps in DeepFool in Search of More Effective Adversarial Perturbations

Adversarial examples are inputs subtly perturbed to produce a wrong prediction in machine learning models, while remaining perceptually similar to the original input. To find adversarial examples, some attack strategies rely on linear approximations of different properties of the models. This opens a number of questions related to the accuracy of such approximations. In this paper we focus on DeepFool, a state-of-the-art attack algorithm, which is based on efficiently approximating the decision space of the target classifier to find the minimal perturbation needed to fool the model. The objective of this paper is to analyze the feasibility of finding inaccuracies in the linear approximation of DeepFool, with the aim of studying whether they can be used to increase the effectiveness of the attack. We introduce two strategies to efficiently explore gaps in the approximation of the decision boundaries, and evaluate our approach in a speech command classification task.
Security Of Dynamic Domain Name System Servers Against DDOS Attacks Using IPTABLE And FAIL2BA: Security Of Dynamic Domain Name System Servers Against DDOS Attacks Using IPTABLE And FAIL2BA

Availability, integrity and confidentiality are the main objectives of information security and server security. These three elements are links that are interconnected in the concept of information protection.Distributed Denial of Service (DDoS) is an attack to make online services, networks and applications not available by flooding data traffic so that services is unvailable or availability aspects disrupted. This attack resulted in huge losses for institutions and companies engaged in online services and web-based applications being one of the main targets of attackers to carry out DDoS attacks. Countermeasures that take a long time and large recovery costs are a loss for the institution or company that owns the service due to loss of integrity. NDLC (Network Development Life Cycle) is a method that has stages namely analysis, design, simulation, prototyping, implementation, monitoring and management. The NDLC method used aim for the results obtained focused and detailed. Snort IDS applied on the DDNS server functions to record when there is a DDoS attack. Implemention fail2ban as realtime preventation tool on the server by configuring based on the rules applied to fail2ban. The results showed  Snort IDS managed to detect DDoS attacks based on the rules applied to Snort IDS. Realtime prevention using Fail2ban successfully functions as a DDoS attack by blocking the attacker's IP Address.
Generative Max-Mahalanobis Classifiers for Image Classification, Generation and More

Joint Energy-based Model (JEM) of Grathwohl et al. shows that a standard softmax classifier can be reinterpreted as an energy-based model (EBM) for the joint distribution p(x,y); the resulting model can be optimized to improve calibration, robustness, and out-of-distribution detection, while generating samples rivaling the quality of recent GAN-based approaches. However, the softmax classifier that JEM exploits is inherently discriminative and its latent feature space is not well formulated as probabilistic distributions, which may hinder its potential for image generation and incur training instability. We hypothesize that generative classifiers, such as Linear Discriminant Analysis (LDA), might be more suitable for image generation since generative classifiers model the data generation process explicitly. This paper therefore investigates an LDA classifier for image classification and generation. In particular, the Max-Mahalanobis Classifier (MMC), a special case of LDA, fits our goal very well. We show that our Generative MMC (GMMC) can be trained discriminatively, generatively, or jointly for image classification and generation. Extensive experiments on multiple datasets show that GMMC achieves state-of-the-art discriminative and generative performances, while outperforming JEM in calibration, adversarial robustness, and out-of-distribution detection by a significant margin. Our source code is available at https://github.com/sndnyang/GMMC.
Grammatical Errors on EFL Students’ Final Project Writings

Making errors is an unavoidable part of learning a new language, especially for those who do not use that new language as their first medium of communication. Writing in a foreign language can be a considerably tough challenge for EFL learners, one of the problems is regarding the grammatical rules. This present study attempts to discover and analyze the grammatical errors found in EFL students’ final project writing. It employed a descriptive qualitative method using a textual analysis process by adopting the theory of Dulay et al regarding grammatical error analysis. (Dulay et al., 1982) classify grammatical errors into four; omission, addition, misformation, and misordering. Five students’ final projects with a total number of 2884 sentences became the object of this research. The final projects were taken from Politeknik Negeri Bandung (Polban) English Department graduates of 2018 and they were limited to the project of ‘Travel Writing’ only. Travel Writing was chosen due to the fact that it contains more various types of sentences, more complicated sentence structure, and higher level of language modification. The results of this study claim that all types of grammatical errors presented by Dulay et al are found in those five students’ final projects. Misformation is the most frequent error the students made in producing their travel writing products by 74% (380 out of 516 errors) while misordering is the least one by 1% (7 out of 516 errors). Theoretically, the findings can be a base for the next researchers to further analyze the cause of this error production. Meanwhile, practically the results can be used by curriculum makers as a guide to evaluate and develop new curriculum, syllabus, materials, and teaching methods which are more suitable for EFL students in order to communicate effectively and write skillfully. &#x0D; Keywords: error analysis, grammatical error, writing, travel writing&#x0D;
POSTER ART AND THE INNOVATIVE PRACTICES IN ART PEDAGOGY

The presented research highlights the innovative charge in the poster tasks as an essential part of the educational work in fine arts. With its essence of an artistic-aesthetic phenomenon with a strong public resonance, the poster focuses on the communicative functions of graphic design. It is in its field that students can express their attitude to all current problems of the present day. Modern technologies allow quick contact with the top achievements in poster art. The digital methods for polygraphic realization allow for the expeditious circulation of the students’ poster works and their introduction in the public environment. In the space of these pictorial tasks the art pedagogue creates preconditions for the teenagers to be more empathetic, more active and creative in their striving to join noble causes. This graphic genre would transform the negative impulses of society into a creative effort, which forms the self-confidence of students that from an object of multifaceted aggressive social influences they become a subject with an active position. The idea is that poster tasks are a reliable means of overcoming the inertia of layered methodological stereotypes.
A SOM-based Gradient-Free Deep Learning Method with Convergence Analysis

As gradient descent method in deep learning causes a series of questions, this paper proposes a novel gradient-free deep learning structure. By adding a new module into traditional Self-Organizing Map and introducing residual into the map, a Deep Valued Self-Organizing Map network is constructed. And analysis about the convergence performance of such a deep Valued Self-Organizing Map network is proved in this paper, which gives an inequality about the designed parameters with the dimension of inputs and the loss of prediction.
Forming an effective risk management system in cyberspace

The research focuses on cyberspace risk management and recommendations in line with the current agenda. The development of technologies for countering cybercrime contributes to the emergence of more sophisticated methods of destruction. The article provides an updated classification of cybercrimes based on the objects and methods of crime. As an object of research, the increasing cases of crimes committed in the European Union’s cyberspace have been chosen. The subject of the research is cyberspace risk management. The purpose of the study is to describe the phenomenon of cybercrime, study its characteristics, and develop recommendations to form a system for managing risks arising in cyberspace. When analyzing the object of research, the critical signs and features of cybercrime were identified. The consequences of cybercrimes using interviewing and observation methods are described. The systematization of historical facts of cybercrimes is carried out, and the experience of combating cybercriminals is summarized. A literary review of scientific and media publications on cybercrime was carried out. The main characteristics of security systems for electronic devices are presented, and establishing an effective risk management system in cyberspace is proposed. Because victims of cybercrime try not to disclose the details of the crimes, the sample of respondents is limited and only qualitative research methods have been used.
An Efficient Approach for Selecting QoS-Based Web Service Machine Learning Models Using Topsis

With the advancement of Service Oriented Architecture (SOA), web services have gained great popularity playing a vital role in performing daily transactions and information exchange based on the interaction of different applications within or outside through communication protocols, allowing to support the business requirements and data consolidation of any company. With the increase in the number of web services with the same functionalities, the problem that arises is that not all of them are efficient, which makes it difficult to make a decision to select the best ones that meet all the user’s requirements. The problem can be solved by considering the quality of web services to distinguish web services with similar functionality. The objective of this paper proposes several automatic learning models to classify web services in categories according to QoS attributes using a refined data set, then select the best model based on performance criteria through the TOPSIS method. The deductive method and exploratory research technique were applied to study the QWS dataset.
The Unity and the Struggle of Didactics and Autodidactics

The article describes the development of didactics and auto-didactics using the diachronic approach. The relation between didactics, as a major and traditional part of pedagogical science, and autodidactics, as its variety and alternative, is presented in the context of the law of unity and struggle of opposites, which is the "core" of dialectics. The validity of the general laws of dialectics and their relation to pedagogical science is argued. From a philosophical and pedagogical point of view, the basic principles are formulated, arising from the interdependence and contradiction in the didactics autodidactics system as factors for the sustainable development of education.
Data Extraction and Scratching Information Using R

Web scraping is the process of automatically extracting multiple WebPages from the World Wide Web. It is a field with active developments that shares a common goal with text processing, the semantic web vision, semantic understanding, machine learning, artificial intelligence and human- computer interactions. Current web scraping solutions range from requiring human effort, the ad-hoc, and to fully automated systems that are able to extract the required unstructured information, convert into structured information, with limitations. This paper describes a method for developing a web scraper using R programming that locates files on a website and then extracts the filtered data and stores it. The modules used and the algorithm of automating the navigation of a website via links are mentioned in this paper. Further it can be used for data analytics.
Science and humanities: clarification of differences and synthesis prospects

An attempt is proposed to overcome the tough opposition of the sciences and humanities. Both types of scientific knowledge have been realized in three ways of their presentation: factual descriptions, establishment of deterministic dependencies and the target context. Such a common platform allows us to specify their interaction. Thus, the results of psy­chophysiology studies of the brain demonstrate the potential of humanitarian concepts (nar­ratives, memory, self-awareness, freedom), which allows us to clarify the possibilities of in­terdisciplinary research and the “convergence” of humanitarian and natural-scientific knowledge in technological applications.
Is 'political correctness' threatening freedom of speech?

As a result of the culturalleft's long march through the institutions ... political correctness involving identity politics, privileging victimhood and virtue signalling dominate public policy and...
Finding a plan to improve recognition rate using classification analysis

With the emergence of the 4th Industrial Revolution, core technologies that will lead the 4th Industrial Revolution such as AI (artificial intelligence), big data, and Internet of Things (IOT) are also at the center of the topic of the general public. In particular, there is a growing trend of attempts to present future visions by discovering new models by using them for big data analysis based on data collected in a specific field, and inferring and predicting new values with the models. In order to obtain the reliability and sophistication of statistics as a result of big data analysis, it is necessary to analyze the meaning of each variable, the correlation between the variables, and multicollinearity. If the data is classified differently from the hypothesis test from the beginning, even if the analysis is performed well, unreliable results will be obtained. In other words, prior to big data analysis, it is necessary to ensure that data is well classified according to the purpose of analysis. Therefore, in this study, data is classified using a decision tree technique and a random forest technique among classification analysis, which is a machine learning technique that implements AI technology. And by evaluating the degree of classification of the data, we try to find a way to improve the classification and analysis rate of the data.
Incorporating Vision Bias into Click Models for Image-oriented Search Engine

Most typical click models assume that the probability of a document to be examined by users only depends on position, such as PBM and UBM. It works well in various kinds of search engines. However, in a search engine where massive candidate documents display images as responses to the query, the examination probability should not only depend on position. The visual appearance of an image-oriented document also plays an important role in its opportunity to be examined. In this paper, we assume that vision bias exists in an image-oriented search engine as another crucial factor affecting the examination probability aside from position. Specifically, we apply this assumption to classical click models and propose an extended model, to better capture the examination probabilities of documents. We use regression-based EM algorithm to predict the vision bias given the visual features extracted from candidate documents. Empirically, we evaluate our model on a dataset developed from a real-world online image-oriented search engine, and demonstrate that our proposed model can achieve significant improvements over its baseline model in data fitness and sparsity handling.
Threats to Libraries

Thesis/Purpose of the article – The present multitude of forms of communication requires diversified intermediation and promotion, and these seem now to be now the main functions of libraries. However, the basis of these endeavours is still print. A departure from supporting print media would result in a crisis in librarianship. In mediation there is a need to verify the content and support a critical reception, as well informational as non-informational. Direct services are essential, but so are remote services and the facilitation of interpersonal contacts. Research method – an analysis of the literature allows us to conclude that the overall library offer requires the supply of print media, delivery of digital media, and also the creation of conditions for direct contact between users. Without that, there will be no future for librarianship. Results and conclusions – The advantages of print are: wisdom, reflective concentration, non-informative (fictionalized) freedom. The possible elimination of print is therefore a serious intellectual and emotional threat. The advantages of digital communication are: multi-semioticity, informational; richness and extensive range – while its weaknesses are overinformation, shallow knowledge, and passivity of inspired thinking. Furthermore the related co-presence of smart articles phone users is only an appearance. Therefore, there is a need for the coexistence of print and digital communication and the facilitation of direct contacts between users. Libraries provide all of this in their offer. In turn, any departure from this, even partial, threatens librarianship with a fundamental crisis.
Pell coding and pell decoding methods with some applications

We develop a new coding and decoding method using the generalized Pell $(p,i)$-numbers for $p=1$. The relations among the code matrix elements, error detection, and correction have been established for coding theory when $p=i=1$. We give two new blocking algorithms using Pell numbers and generalized Pell $(p,i)$-numbers for $p=1$.