Reviewerly/exHarmony huggingface dataset:
Use of exploit for vulnerability detection of Linux Servers

At present, any computer equipment connected to the Internet is exposed to various threats, and the risk to which the servers are exposed when providing services in the cloud is no stranger. One way to prevent it is to act early, detecting the potential vulnerabilities that can be exploited by the attackers. In this way the probability of success of the attacks made is reduced. This article shows techniques for the detection of vulnerabilities with the use of exploit on Linux servers, making use of ethical hacking practices; since the use of these servers is in great demand by software developers and architects, whether it is because of the open source license it has, the ease of use and implementation of different services in these servers, and the security issue. For this, different phases were developed called recognition, port scanning, enumeration of services, vulnerability scanning, obtaining access and maintaining access. They are necessary to carry out each of the phases for their execution. The results obtained with the use of exploits were satisfactory for the detection of vulnerabilities of the different services that work on a linux server; With this information you can reduce the risks to which these servers are exposed, providing different services and working with valuable information.&#x0D; Resumen. En la actualidad cualquier equipo de cómputo conectado a internet está expuesta a diversas amenazas, y no es ajena el riesgo a los que están expuestos los servidores al brindar servicios en la nube. Una manera de prevenirlo es actuar anticipadamente, detectando las vulnerabilidades potenciales que pueden ser aprovechadas por los atacantes. De esta manera se disminuye la probabilidad de éxito de los ataques realizados. El presente artículo muestra técnicas para la detección de vulnerabilidades con el uso de exploit en servidores linux, haciendo uso de las prácticas de hackeo ético; ya que el uso de estos servidores tiene mucha demanda por los desarrolladores y arquitectos de software, sea por la licencia open source que tiene, la facilidad de uso e implementación de distintos servicios en estos servidores, y el tema de seguridad. Para esto se desarrollaron diferentes fases llamadas reconocimiento, escaneo de puertos, enumeración de servicios, escaneo de vulnerabilidades, obtener el acceso y mantener el acceso. Son necesarios realizar cada una de las fases para la ejecución de las mismas. Los resultados obtenidos con el uso de exploits fueron satisfactorios para la detección de vulnerabilidades de los diferentes servicios que funcionan en un servidor linux; con esta información se puede reducir los riesgos a los cuales están expuestos estos servidores que brinda diferentes servicios y trabajan con información valiosa.
THE EFFECTIVENESS OF TASK BASED LEARNING MODEL ON WRITING NEWS ITEM TEXT AT XI GRADE MAN 3 PADANG PANJANG

This research aimed at describing the effectiveness of TBL model on writing especially on news item text. The research design used was pre-experimental research with one group model. The population of this research was the entire XI grade of MAN 3 Padang Panjang. The sample of this research was one class; XI Science students. To determine the sample, the researcher used purposive sampling technique. To gain the data, this research used pre-test and post-test. The comparison of pre-test and post-test result is 43.57%, the mean of pre-test is 46 % and it increases to 80.47% to the post test one. Then, hypothesis showed that t-count is higher than t-table (8.74 > 1,761). It means task based learning model (TBL) has significant effectiveness on writing news item text. To conclude the result of this research, it can be stated that TBL model have been successful to be effective method and successful to increase students achievement in writing news item text. This research is recommended for teacher to use TBL in teaching writing especially on news items text.Keywords: News item text, task based learning model, writing
A Study about the Relative Importance Evaluation on Practical Arts Education Curriculum - using Analytic Hierarchy Process (AHP) -

교과내용에 대한 교사들의 중요성 인식은 교수수행에 영향이 크기 때문에 교과내용에 대한 중요도를 규명하는 것은 의미가 있으므로 이 연구에서는 AHP기법을 이용하여 초등교사와 예비교사를 대상으로 실과교육과정 각 영역과 핵심개념에 대한 중요도 인식을 분석·비교하여 실과교육이 추구하는 목표달성과 효율적인 교수수행을 위한 기초자료를 제공하고자 하였다. 연구 결과에 따르면 실과 교육과정 영역에서 초등교사와 예비교사 모두 ‘인간발달과 가족’의 영역을 상대적으로 가장 중요하게 인식하였다. 복합가중치를 포함한 전체평가요소에 대한 상대적 중요도에서 1위는 ‘가족관계’로 동일하게 인식하고 있는 것으로 나타났으나 ‘인간발달’에서는 초등교사는 전체 9위인데 반하여 예비교사는 전체에서 3위로 중요하게 인식하는 것으로 나타났다. ‘생활안전’은 초등교사와 예비교사 모두 전체에서 2위로 중요하다고 인식하는 것으로 나타났으며 ‘수송기술 효율성의 이해’가 전체에서 12위로 동일하게 가장 낮은 등수로 인식하는 것으로 나타났다. 이처럼 등수에서 다소차이가 있기도 하나 대부분의 평가요소의 상대적 중요도 인식에서는 초등교사와 예비교사가 유사하게 인식하는 것으로 나타났다. 실과교과 내용의 중요도 인식을 함양하기 위하여 각 하위요소에 적합한 교사교육 프로그램개발, 실습지원 확대 등의 다양한 방안을 마련해야 할 것이다.It is necessary to clarify the importance of teachers to the content of the curriculum because awareness of the importance of the content has a significant impact on the class. In this study, the perception of the importance of each area in the field of practical education was compared to that of primary and prospective teachers using AHP. The purpose of the study was to provide basic data for achievement of goals and efficient classes pursued by practical education. The results of the study are as follows. Of the total areas, the human development and family”area was found to be relatively the most important. In terms of relative importance to the overall rating element, it was found that the 1st ranking was recognized as a family relationship. However, the human development”factor was found to be recognized as the ninth place for primary teachers, and the third place for pre-service teachers. The “living safety”was found to recognize that both primary and pre-service teachers are important in second place. It has been shown that “understanding of transportation technology efficiency”element is recognized equally as 12th. Although there are such slight differences in equivalence, recognition of the relative importance of most factors has shown that primary and pre-service teachers are similarly aware. In order to foster awareness of the importance of practical contents, the government should prepare various management strategies such as developing teacher education programs and expanding hands-on support.
"MODELING OF PEDAGOGICAL SITUATIONS – METHOD FOR FORMING PROFESSIONAL COMPETENCE FACILITIES OF PHYSICOTECHNOLOGICAL PROFILE"

The pedagogical activity of a physics teacher at school will be successful provided that during its preparation an organic link is established between pedagogical theory and pedagogical practice. One way to establish aconnection is to simulate pedagogical situations that arise in the actual practice of professional activity of a physics teacher. The educational-methodical task can be considered: as a problematic situation and as a refl ection in the mind of the teacher of the contradictions and problems identifi ed in the situation, as well as a meaningful and formulated goal of further actions. In solving educational and methodological problems in the theory and methods of teaching physics students carry out specially designedcreative pedagogical tasks that ensure their readiness for professional activity.Key words: pedagogical situation, professional competence, student, future specialist in physiological and technological profi le.
Integer Quantum Hall Effect

Modern Condensed Matter Physics brings together the most important advances in the field of recent decades. It provides instructors teaching graduate-level condensed matter courses with a comprehensive and in-depth textbook that will prepare graduate students for research or further study as well as reading more advanced and specialized books and research literature in the field. This textbook covers the basics of crystalline solids as well as analogous optical lattices and photonic crystals, while discussing cutting-edge topics such as disordered systems, mesoscopic systems, many-body systems, quantum magnetism, Bose–Einstein condensates, quantum entanglement, and superconducting quantum bits. Students are provided with the appropriate mathematical background to understand the topological concepts that have been permeating the field, together with numerous physical examples ranging from the fractional quantum Hall effect to topological insulators, the toric code, and majorana fermions. Exercises, commentary boxes, and appendices afford guidance and feedback for beginners and experts alike.
The Impacts of Multiplier Cut Information on Market Liquidity : Based on the KOSPI200 Futures

KRX simultaneously cut the contract size of the KOSPI200 futures and options in halves on March 27, 2017. This is the first change which can influence the trading volume in the Korea futures market. We examine the effects of this change on liquidity using the intervention analysis with dynamic response functions. The results of this study are summarized as follows.BR Total trading volume has a significant increase indicating the abrupt and permanent response subsequent to the multiplier split. Such increase is attributed to the increase in the order of foreign, individual, and institutional investors. In the proportion, individual and institutional investors have a significantly initial increase without lasting effect whereas no significant change in foreign investors is observed. Moreover, individual investors are likely to enter the futures market more than institutional investors.BR The multiplier cut is not effective to attract voluntary participation from new or existing traders with lesser capital. As a result, the intention of financial authorities could not be achieved to revive a stagnant market. Beyond our purpose, we do not verify the effect of the multiplier change on the KOSPI200 options.
GA-Deep Neural Network Optimization for Image Classification

Deep neural network (DNN) has been used to solve many pattern recognition tasks specifically for classification of images, sounds and texts.This is due to the ability of DNN model to extract high level representation of features.However, a deep neural network is built up from a set of hyperparameters that need to be tuned in order to obtain the highest performance and at lower computational time.In this paper, the hyperparameters that are tuned is the combination of number of hidden layers and the number of neurons in each layer.Nevertheless, the challenge arises when choosing the suitable tuning method for this model.The aim of this study is to evaluate and compare the tuning methods of a conventional grid search (GS) method with a population-based searching method, known as genetic algorithm (GA).The comparison is made based on the performance of DNN model for classifying MNIST handwritten digits, in terms of the classification accuracy and the time taken to complete the task.The MNIST handwritten dataset is divided into 3 sets, 54000 images in training set, 6000 images in validation set and 10000 images in testing set.The results show that GA and GS methods achieved a comparable classification accuracy of 98.23% and 98.27%, respectively.However, GA method took only half of the time to search for the optimized combination, when compared to GS method, which is only 4.19 hours compared to 8.59 hours, for the same search space area.
Study of the Experimental Course Scheduling System Based on MIP Model

In order to solve the complicated problem of the course scheduling, the experimental course scheduling system based on the mixed integer programming (MIP) model was designed.This paper introduces the implementation process of the system in detail from four aspects: system function, system overall design, MIP model design and database design.
RETRIEVAL PERFORMANCE OF ARABIC LIGHT STEMMERS

Despite the fact that stemming greatly improves Arabic information retrieval performance, yet no standard stemmer emerges in the field of Arabic IR due to some limitations and shortcomings. Among the recurring problems is that the stemmer can reduce unrelated words to the same stem as well as fall short to reduce related words to a common stem. Many studies have suggested Arabic algorithms to address the problem associated with stemming. This paper aims to review the state of the retrieval performance of Arabic Light stemmers based on the main objectives achieved, causes for retrieval success and failure, retrieval measure, the affixes, and methodologies. The results showed that light 10 has better retrieval performance compared to other reviewed Arabic light stemmers.
Deep Transfer Learning With Field-Based Measurements for Large Area Classification

Classification of Electro-Optical (EO) datasets using Deep Neural Networks (DNNs) has lead to high-performance supervised learning algorithms. However, DNNs require a large amount of labeled data for training which often have limited availability in ecological studies. Up-to-date classification of vegetation in sensitive Arctic ecosystems continue to be a challenge. In an ecosystem undergoing rapid change, capturing the dynamics of vegetation requires the existing maps of vegetation (such as Alaska Existing Vegetation Type (AKEVT), circa 2000) to be updated based on frequent field based observation of vegetation. A method is needed to transfer the knowledge gained from field-collected observations to a larger area using DNNs. Transfer learning is a machine learning technique where a model trained on one task is re-purposed on another similar task. This paper seeks to train DNNs using field-collected observations and apply transfer learning to apply the knowledge gained to update existing vegetation map at larger scale. We test two DNN methods, (1) a deep multilayer perceptron (MLP) model and (2) siamese MLP network that uses a structure to rank similarity between inputs and can be used for training datasets with few samples and show good performance with limited datasets (e.g. few-shot learning). The results show ~90% accuracy (using the field observations for evaluation) when transfer learning is applied to a siamese network, compared to ~45% accurate when a MLP is trained on the AKEVT and evaluated on the field observations. The approach show promise for improving and update the existing vegetation maps over large areas using limited field-based observations.
Perfect zero knowledge for quantum multiprover interactive proofs.

In this work we consider the interplay between multiprover interactive proofs, quantum entanglement, and zero knowledge proofs - notions that are central pillars of complexity theory, quantum information and cryptography. In particular, we study the relationship between the complexity class MIP*, the set of languages decidable by multiprover interactive proofs with quantumly entangled provers, and the class PZK-MIP*, which is the set of languages decidable by MIP* protocols that furthermore possess the perfect zero knowledge property. Our main result is that the two classes are equal, i.e., MIP* = PZK-MIP*. This result provides a quantum analogue of the celebrated result of Ben-Or, Goldwasser, Kilian, and Wigderson (STOC 1988) who show that MIP = PZK-MIP (in other words, all classical multiprover interactive protocols can be made zero knowledge). We prove our result by showing that every MIP* protocol can be efficiently transformed into an equivalent zero knowledge MIP* protocol in a manner that preserves the completeness-soundness gap. Combining our transformation with previous results, we obtain the corollaries that i) all languages that can be solved in non-deterministic double exponential time have zero knowledge MIP* protocols and ii) all co-recursively enumerable languages (which include undecidable problems as well as all decidable problems) have zero knowledge MIP* protocols with vanishing promise gap.
Synthesized AI LMI-based Criterion for Mechanical Systems

This paper proposes a novel artificial intelligence sythethized controller in the mechanical system which has high speed computation because of the LMI type criterion. The proposed membership functions are adopted and stabilization criterion of the closed-loop T-S fuzzy systems are obtained through a new parametrized LMI (linear matrix) inequality which is rearranged by machine learning membership functions.
Can Artificial Intelligence Improve Screening Mammography's Track Record?

Even among expert radiologists, accuracy varies when interpreting screening mammograms. Artificial intelligence (AI) has shown promise in the setting
Spent my Sunday morning bookmarking the last ...

Spent my Sunday morning bookmarking the last two weeks of professional reading. Upload to my server, create link as a bookmark on @withknown, add some
Changing landscape of social networking services in Indian libraries

Today, in this modern world, the strongest media for communicating among people is Social Media. We are becoming more and more dependent on Social Media for sharing information (including personal information), data, pictures, watching videos, making shopping, getting news, forwarding messages and so on. Academic Libraries must harness the power of this most powerful media to stay connected with its users and provide information at shortest possible time. Academic Libraries should also facilitate communication among the scholars for sharing the information through this media. This paper presents the usage of social networking sites (SNSs) by the students and faculty for sharing information in universities of Haryana. The study is a questionnaire-based survey on the usage of SNSs among the students and faculty members of the selected universities of Haryana. The data of the study were collected through questionnaires, which were personally distributed to the identified population, i.e. undergraduate and postgraduate students, research scholars and faculty members by the researcher. The survey was based on a sample of 700 questionnaires; of which, 560 questionnaires were received, having a response rate of 80.0 per cent. The study showed that all the respondents were found to be aware of and making use of such applications in their academic affairs. It was revealed from the study
RPLIDAR Integration Module for Obstacle Avoidance Robot

ABSTRACTThis paper presents the project development of Obstacle Avoidance Robot, an Automated Guided Vehicle (AGV) in example, which use a LIDAR (Light Detecting and Ranging) as a sensor for obstacles detection.RPLIDAR as LIDAR sensor is integrated with Raspberry Pi 2 becoming a sensing module.The programming is done by using Python and Arduino sketch.There are other types of sensor which also be used as an obstacle detector such as ultrasonic sensor, limit switches and a few other sensors.Any information regarding the obstacle detected will then transmitted by the Raspberry Pi to Arduino Mega.Based on information received the Arduino Mega then commanding the AGV to move the robot with the avoiding obstacles abilities.The integration module successfully developed to control the AGV trajectory to move forward direction only.The studies on the AGV behavior in facing the obstacle while moving have been done, as a result it will varying the speeds of the wheel which make the AGV turning and avoiding the obstacle.The result may be implemented in any other of AGV with differential drive system.
Pelican: Power Scheduling for QoS in Large-scale Data Centers with Heterogeneous Workloads

Given the high cost of building and operating large-scale data centers in terms of the power budget, it is crucial to maximize available power resources for overall quality of service(QoS). In this paper, we present a power scheduling system, Pelican, for large-scale data centers to increase overall QoS by over-provisioning the number of servers for heterogeneous workloads. We adopt a two-level design that separate power scheduling mechanism and power controlling policy without affecting the already over-complicated job scheduler. Our power controller leverage both priority and performance as key indicators to control the power of a server, which improves QoS while significantly reducing the risk of power violations.We implemented and deployed our Pelican in a real overprovisioned production data center at Baidu Inc. Our evaluations show that we are able to utilize 12.7% more computing resources without any violation and achieve 11.5% offline service throughput gain while not affecting the latency of online services so as to improve overall QoS.
PROFESSIONAL COMPETENCE OF FUTURE SPECIALISTS IN INFORMATION AND COMMUNICATION TECHNOLOGIES: QR CODING IN STUDENT LEARNING

The article explores modern information and telecommunication technologies, which are the basis of information processes in education. The fundamentals of improving the quality of student training from the point of view of the development of a vocational education system are investigated. The authors explore the definition of an innovative educational environment. It is proved that professional IT education is the basis for improving its quality level and has certain advantages over other types of knowledge, providing flexibility due to modern technological features, including the use of QR coding information.
Finding monotone patterns in sublinear time.

We study the problem of finding monotone subsequences in an array from the viewpoint of sublinear algorithms. For fixed k ∊ N and e > 0, we show that the non-adaptive query complexity of finding a length-k monotone subsequence of f : [n] → R, assuming that f is e-far from free of such subsequences, is Θ((log n)^ ⌊log_2k⌋ ). Prior to our work, the best algorithm for this problem, due to Newman, Rabinovich, Rajendraprasad, and Sohler (2017), made (log n)^O(k^2) non-adaptive queries; and the only lower bound known, of Ω(log n) queries for the case k = 2, followed from that on testing monotonicity due to Ergun, Kannan, Kumar, Rubinfeld, and Viswanathan (2000) and Fischer (2004).
FACTOS EFFECTING PERFORMANCE MANAGEMENT SYSTEM: AN EMPIRICAL ANALYSIS WITH REFERENCE TO HEALTH CARE INDUSTRY AROUND HYDERABAD METRO

In this empirical research we are reporting the results of a survey carried out in Healthcare Industry in the Metro city of Hyderabad, whether the performance appraisal management system is effected by the independent factors performance management, improved employee performance and impact of performance appraisal system on employee performance.The authors surveyed 750 staff working in various healthcare centres including hospitals, training centres consisting of 435 men and 315 women employees, to evaluate the how the said factors effect the performance management system in healthcare industry.The reliability statistics Cronbach Alpha, Kaiser-Meyer-Olkin Measure of Sampling Adequacy and Bartlett's tests of sample adequacy, principal component analysis and multiple linear regression analysis carried out.The Cronbach alpha measured at for performance management 0.870 factors for improvement of employee performance 0.776 and factors for Impact of performance appraisal system on organization is 0.742.The KMO-Bartlett tests reveal a strong relationship among the study variables and Bartlett's test of Sphericity is significant (P<0.001) for all the three factors indicating the correlation matrix is not an identify matrix.The multiple regression analysis reveals the three factors significantly influencing the performance management system in healthcare industry in the Metro of Hyderabad.