Reviewerly/exHarmony huggingface dataset:
Effects of workplace satisfaction, job satisfaction and skills fitness on characteristics of workplace learning participation in university

이 연구는 한국직업능력개발원 한국교육고용패널(KEEP) 12차(2015년)년도 조사 데이터를 사용하여 표본의 인구통계학적 특성 및 (대학 재학 중) 현장실습 참여특성이 (첫 번째 일자리 임금근로자의) 직장만족도, 직무만족도, 수준적합도에 미치는 영향 관계를 실증적으로 분석하였다. 연구 결과는 다음과 같다. 첫째, 직장에서의 업무, 의사소통·인간관계, 근무시간 및 환경 등 직무에 대한 만족도는 대학 재학 중 현장실습 자체가 취업 및 업무능력에 유익할수록(도움이 될수록) 높게 나타났다. 둘째, 현재 직장에서 요구하는 기술과 능력, 교육수준이 내 수준에 비해 보다 적합하다고 느끼는 수준적합도는 전문계고 출신 학생들이 일반계고 출신 학생들보다 높고, 남성이 여성에 비해 높은 것으로 나타났다. 셋째, 직장의 복지후생, 임금, 개인발전 가능성 등 직장에 대한 만족도는 일반계고 출신 학생들이 전문계고 출신 학생들보다 높게, 그리고 정규직이 비정규직 보다 높게 나타났다. 넷째, 현장실습의 선택방법, 전공 관련성, 참여기간, 참여유형에 따라 직장만족도, 직무만족도에는 유의미한 차이는 발견되지 않았다.With the 12th year data of the high school students cohort within Korea Education and Employment Panel(KEEP), this study examined relationships how workplace satisfaction, job satisfaction and skills fitness were impacted by demographic characteristics and participation characteristics of workplace learning. The results are as follows. First, tasks in the workplace, communication·human relationships, working hours and environment, etc., job satisfaction showed higher when the fieldwork itself was designed to help in employment and work ability. Second, skills fitness feeling more suitable than one s own level showed that the skills, abilities and educational level requiring in your current job were higher students from vocational high school than general high school. And also skills fitness indicated that men were found to be higher than women. Third, welfare benefits, wages and personal development potential of the workplace, etc., workplace satisfaction were higher students from general high school than vocational high school, and also skills fitness indicated that men were found to be higher than women. And also skills fitness showed that regular workers were found to be higher than non-regular workers. Fourth, according to selection method, major relevance, duration of participation, and type of participation. significant differences weren’t found between job satisfaction and workplace satisfaction.
Projective aesthetics as a possible world

The notion of “projective aesthetics” is considered in this paper for the first time as a variant of the recourse to praxis that characterizes contemporary aesthetics and its “aesthetic involvement” (A. Berleant). Projective aesthetics involves the use of methodologies of a new type:  “schizoanalysis” (in Deleuze’s and Guattari’s terms), “conceptivism” (as devised by M. Epstein) and “projectivism”. The emphasis is put on the principle of “rhizome” and on the features of so-called “culturonics”, a way of thinking “through projects” in the cultural sphere. Projective aesthetics implies a way of philosophizing about art and aesthetics which is defined by a functional orientation in terms of a process of aestheticization and artification, and, accordingly, of projectivity. The connection between projective aesthetics and the peculiarities of modern communicative aesthetics is also examined, together with the need for creating a philosophical glossary of artistry and modern art, meant as a relevant project for aesthetics. In the text, a special place is also given to a number of projects implemented in the process of teaching philosophical aesthetics, as related to beauty as well as with the direct participation of students in filling out the contents of the above-mentioned glossary.
Robust face recognition method based on similarity fusion

In the open-set face recognition tasks, the face features change greatly due to different ages, camouflage, and large angle. It further leads to weak robustness of recognition methods and low recognition accuracy. To this end, this paper proposes a new robust face recognition method based on similarity fusion. The target identity is further identified by learning the associated feature between the target and the comparison libraries. This paper defines the concept of similarity vector and designs the associated learning layer (AL layer). The similarity vectors are input into the associated learning layer to learn the representation of the target associated features. The robustness of the algorithm is weak due to noise in the associated features. Targeting this challenge, this paper designs the association fusion layer (AF layer) and proposes an improved association enhancement fusion algorithm (AEFA). The AEFA calculates the weight vectors based on the mean and variance of multiple associated features. Further, they are used to calculate the redistribution associated features. Finally, the redistribution associated features are merged into one enhancement feature. Based on the CASIA-Web dataset, this paper further selects faces with different ages, camouflage and large angles as experimental data. The experimental results show that compared with the SphereFace algorithm, the top1 accuracy of this method is improved by 7.45% and 10.89% in the face@1000 dataset and face@2000 dataset respectively. The experiment also proves that the proposed method is more robust.
MRI Image Reconstruction Through Contour Interpolation

Magnetic Resonance Image reconstruction is a promising guidance strategy for acquiring volumetric information from various cross sections of same medical image data. In the field of medical science, visualization of internal anatomy of organs is very important and crucial for proper treatment of any disease. Medical image reconstruction model can help doctors in better visualization of human body organs thus making it easier and convenient for doctors in accurate diagnosis and in therapeutic process. This paper proposed a contour based interpolation technique that will reconstruct an MRI brain dataset for better visualization of patient’s anatomy in order to open up new avenues for the doctors for better analysis of the disease. Main focus was to reconstruct and visualize 3D volumetric brain images which will be helpful for visualizing, manipulating, and quantitatively analyzing human brain anatomy.
A Survey on Various Techniques for Personal Movie Recommendation

Recommendation system plays an important role in helping users to find appropriate products and contents they usually want. There are various recommendation techniques for recommending items to users. These recommendations can be optimized to be more accurate by means of optimization algorithms. This paper focuses on survey of such recommendation techniques and optimization algorithms in the personalized movie recommendation domain. The comparative evaluation of recommendation techniques is also done. This paper gives an insight into recommendation system, various recommendation techniques and optimization algorithms. Collaborative filtering technique along with time varying multiarmed optimization algorithm will give most appropriate recommendations.
Mineralogical and geochemical studies of ironstones around Koton karfi, part of southern Bida Basin, north central Nigeria

The combination of mineralogical and geochemical data of sedimentary rocks can reveal the nature of rocks and the tectonic settings of the sedimentary basin. Ironstone deposits cap plateaux around Koton Karfi requiring detailed studies. The survey area is bounded by longitudes 6°48ʹ00ʺ E to 6°52ʹ48ʺ E and latitude 8°05ʹ00ʺ N to 8°10ʹ46ʺ N covering an area of about 96.8 km2. The stratigraphic successions in the study area consist of the basal Lokoja Formation, overlain by the Patti Formation and capped by the Agbaja Formation. The basal Lokoja Formation is a sequence of matrix supported conglomerates and sandstones overlying the Pre–Cambrian Basement. 21 rock samples were collected from the study area. Geochemical analysis of the samples was carried out using x-ray fluorescence. Mineralogical analysis determined the mineral compositions and modal percentages of minerals in the samples. 20 elements and 19 oxides were revealed and they include Al2O3, SiO2, Fe2O3, P2O5, CaO, K2O, V2O5, Cr2O3, Eu2O3, NiO2, ZnO, La2O3, BaO, SrO, CuO, Nd2O3, Re2O7 and PbO. The mineralogical study shows the presence of two petrographic varieties namely the ooidal pack-ironstone and detrital mud-ironstone. The core of the ooids is made up of pseudomorphs of goethite after siderite and hematite after Itabirite.
PENGARUH METODE MIND MAPPING TERHADAP PEMBELAJARAN MENULIS TEKS EKSPOSISI PADA SISWA SMP

This research is motivated by the difficulties faced by students when writing exposition texts, one of which is that there are still many students who complain in developing ideas to make a writing and lack of students' understanding of the exposition text structure. To overcome this problem, we need a learning method that has never been applied to students, namely the mind mapping method. Mind mapping method can increase students to write exposition text, because it can store material easily into the brain and can easily be expressed again. In this study, researchers used the experimental method by collecting data in the form of initial tests (pre-test) and final tests (post-test) with a sample of 30 MTs students. Based on the data obtained, the comparison of the results of learning exposition text writing with a mind mapping method can affect the learning process. Evidence states that the comparison results obtained by students are quite significant, before using mind mapping methods obtain an average of 73.2 and after using the mind mapping method obtain an average of 81.36. So, writing learning using the mind mapping method can be used in the classroom in learning exposition text writing.
Application Settings and Error Handling

Before Play 2.6, the practice was to use a global object to define application-level configurations and processing logic like filtering, error handling, etc. This approach was deprecated in Play 2.5.x and dropped since Play 2.6.x. The recommended approach since Play 2.6.x is to use dependency injection. Hence I won’t go into the details of the approach followed prior to 2.6.x and instead will direct your attention to the dependency injection approach. I will give you an example at the end of this section so that you are aware how it was done before, which will be helpful if you’re migrating an older Play framework project to the newer version.
REVOLUTIONARY DEVELOPMENT IN INFORMATION TECHNOLOGY THROUGH FDI

Information Technology has played a wider role in Foreign Direct Investment. The under developed countries needs resources to increase their balance of payments. Generally, the State Government and Central Government has taken many Initiatives measures to improve the information technology market. Domestic savings cannot compensate the world level target market to overcome that information technology is concentrating both with foreign and domestic level market. IT industry is a revolutionary changes with possibilities of all the e-govt measures through e-health e-education, e-agriculture etc., In global map IT industry is filing income tax returns, applying for passports, online railway ticket, net banking by clicking a mouse. Information Technology can change world level market and it can make the person to meet in place with all categories of people. Through the development of IT sector the investors opportunities can be increased through generation by generation.
Development of a game application for a custom eight-processor device with a tangible interface

The article briefly discusses functions that are often used in modern gadgets, such as a shared working space in different devices, and features, such as a gyroscope and accelerometer, as well as an example of a non-standard device that uses this functionality. This device is a smart toy with a tangible interface and is an analogue of a portable console, with the ability to launch not only gaming applications. The second section describes the design of the hardware-software complex of a non-standard eight-processor device with a tangible interface. The third section describes the structure of the package, which the hardware modules exchange with each other to ensure synchronization. The method of messaging and the lifetime of messages are described. The fourth section describes the commands used when exchanging messages between the platform and the running application. The list of commands used by the platform and applications is determined. In order to determine the topology of the network of cube modules, an example of the operation of the messaging mechanism not only between the platform and the application, but also between the modules is considered. The fifth section, using the developed application for this complex as an example, taking into account its features and limitations, describes the process of interaction between its parts. An example of working with the main menu of the device is also given. The methods of user interaction with a tangible interface are described.
In the vaults: Bitcoin Futures and storage insurance

Blockchain technology and the trading of Bitcoin were introduced in October 2008 in the famous paper by Satoshi Nakamoto. Since then, a number of other cryptocurrencies have been created. However, Bitcoin remains the most prevalent.Financially settled Futures contracts using Bitcoin were introduced in December 2017 by the Chicago Mercantile Exchange (CME). Another large exchange, Intercontinental Exchange Inc (ICE), started trading in physically settled Bitcoin Futures through its Bakkt unit in October 2019, highlighting similarities between bitcoins and commodities, and making the concept of warehousing not only relevant but critical. This, in turn, triggered a large number of offers for storage insurance by companies like Lloyd’s, Aon, ING and other large insurers. In this article, we present some features of cryptocurrency spot and Futures markets and explain why storage devices ensure the existence of a convenience yield introduced by Working (1949) in the Theory of Storage. Then, we discuss the insurance contracts recently proposed. Finally, we infer from the spot-forward relationship the specific ‘benefit’ component priced by the market for having physical (versus financial) Bitcoins readily available.
Design Patterns based on Deep Learning analyzing Distributed Data

Data silos in many system landscapes complicate the creation of comprehensive information. Distributed Ledger Technology enables trust between assets via a distributed, secure and immutable storage of transactions. Deep Learning realizes intelligence to make decisions, conduct them and analyze their results based on the gathered data. In order to counteract the limitations of current system landscapes, an integrative implication of both Distributed Ledger Technology and Deep Learning is needed. Many considerations arise during the design of information systems integrating the named technologies. Transparency over the training and deployment of various Deep Learning methods on a distributed data landscape needs to be achieved. Using both a literature review and a qualitative research approach, this paper describes the development of design patterns and their selection criteria with different dimensions taken into consideration. The evaluation phase comprises of semi-structured interviews with experts from different disciplines. The result of this paper guides stakeholders in the selection of a suitable technical solution.
Teletrafic models based on dual systems with hyperexponential and erlang distributions

This paper presents the results of studies on queuing systems (QS) H 2 /E 2 /1 and E 2 /H 2 /1 with second-order hyperexponential and Erlang input distributions. Considered QS are of type G/G/1. The use of these higher-order distribution laws is hindered by increasing computational complexity. For such second-order distribution laws, the classical method of spectral decomposition of the solution of the Lindley integral equation for G/G/1 systems makes it possible to obtain a solution in closed form. The article presents the obtained spectral decompositions of the solution of the Lindley integral equation for the considered systems and the formula for the average waiting time in the queue. The adequacy of the results is confirmed by the correct use of the classical method of spectral decomposition and the results of numerical simulation. For practical application of the results obtained, the probability theory moments method is used. Systems of the G/G/1 type are widely used in the theory of teletraffic when modeling data transmission systems. For example, according to the average waiting time in the queue, packet delays in packet switching networks are estimated when they are modeled using QS.
IMPLEMENTASI DAN PENGUKURAN KUALITAS WEBSITE OBJEK WISATA MENGGUNAKAN METODE WEBQUAL. 4.0 STUDI KASUS PULAU SIMEULUE ACEH

Simeulue is one of the regions in Indonesia which is located at the tip of the island of Sumatra whichhas a variety of cultures, tourist attractions and culinary that is very attractive to foreign tourists and local tourists. However, the beauty of this island is not yet realized or known by tourists, only some of them who already know and see directly the island of Simeulue, because of that the need for an application system based on travel websites. The purpose of this research is to design a website-based application system and measure the quality of the website. In carrying out the process of measuring quality using the Webqual 4.0 method, in this method there are three indicators in measuring quality, namely, usability, information quality and service interaction quality. In designing this system using the Hypertext Preprocessor (PHP) programming language. Based on the results of the analysis of the study using 3 (three) indicators above are having an average value located at intervals of 3 ≤ x ≤ 4 or with a standard deviation value, UQ: 0.577, IQ: 1,317, SIQ: 0.808 which states that the website is very useful and very useful for tourists in accessing information and determining tourist attractions on the island of Simeulue.
Anomaly Detection by Using Artificial Intelligence

Nowadays, anomaly detection is a well-known and widely utilized computational technique used to detect novelty, anomalous and unusual behavior for a statistical problem. It possesses the capability to capture error by pre-indicating a threshold based on the condition, standard and requirement of the system. According to various researches, the technique of anomaly detection is used in numerous field which includes medical illness detection, detecting bank fraud, and network system log monitoring and telecommunication fraud detection to analyze the pattern and behavior of the data in order to detect the occurrence of novelties. Similar as the application of the other examples from the research, the anomaly detection technique is also suitable to be used on part failure detection of machine in the production line of manufacturing company. In this project, there is a collaboration with a global leading electronic manufacturing service providing company which used machine with high precision to operate the component mounting and assembling process. It is a fact that not all machines are perfect and there is an occurrence of certain amount of error in the machines. Hence, the anomaly detection technique is suggested to be applied on this situation to enhance the situation in the production line. The main objective of the system development is to ensure the detection of faulty events that will occur in the machines. The secondary objective of the research is to create an anomaly detection system to forecast the faulty event occurrence via machine learning of AI while the other objective is to smoothen the operation of the production line by reducing the time to detect error for trouble shooting of the machine. This anomaly detection system will be developed based on the method of machine learning. In this research project, raw datasets will be obtained from reliable source as the data to be analyze will be the data log file of the machine production line of the company. A few algorithms will be written in codes to learn the pattern of the training data and will be able to determine and identify the occurrence of anomalous events when more new data is fed.
Pengembangan Sistem Informasi Manajemen Lembaga Penelitian UNM

The focus of this research is the development of an integrated management information system for UNM research institutions. The aim of this research is to develop an integrated information system to improve and assist the performance of UNM research institutions. This type of research is research and development (Research and Development), with the System Development Life Cycle (SDLC) method. The planned research will develop an integrated management information system that can be implemented to support performance at UNM research institutions.
Multi-Robot Navigation and Exploration in Graphs with Entrance-Dependent Identification of the Edges

We propose two multi-robot algorithms to enable navigation in graph environments where numerical ports identify edges incidents to each node. This identification, however, varies dynamically according to the entrance edge used by the robot to reach the node. A new exploration algorithm called ECEP writes information on the nodes that can later be used by the new navigation algorithm NCEP to properly navigate to any given neighbor. Both algorithms require minimal memory space from the agent and from each node. Simulations showed that it requires an average exploration time O(G/k), for k robots. Both were also successfully implemented on robots with simple hardware.
Handicapped Wheelchair Movements Using Discrete Arabic Command Recognition

Automatic Speech Recognition (ASR) is an effective and widespread method used to interpret the human voice into commands.Over the past few decades and due to the great evolution in data science, the processing of speech has been embedded in various new technologies.The benefits of such evolution motivated us to develop a discrete voice system for controlling the wheelchair movements for Arab people with physical impairment (handicapped people).The wheelchair via voice system was able to recognize seven isolated words in the Arabic language.The approach uses the CMU-Sphinx4 ASR for evaluating the effectiveness and the accuracy of the recognition system.A corpus was built, and then the system was trained on 70% of this corpus and tested using the rest of 30%.The experiments reveal that the recognition rate of the proposed approach is 96%.The average level of accuracy of the real experiment and corpus-based testing experiment reached 94%.
An Edge-based Multiple Total Variation model

Regularization methods are one of the important methods of image restoration. A general regularization framework based on truncation is high efficient in contrast preservation. However, the position information of each pixel is not used in the truncation process. In order to use the position information of each pixel, an edge-based multiple total variation (EMTV) model is proposed by introducing the edge indicator function and the binarization function. Computationally, we employ the alternating direction method of multipliers (ADMM) to solve the EMTV model. Simulation experiments show that the proposed model outperforms many the most advanced image restoration models in Peak Signal-Noise Ratio, Structural Similarity Index and visual quality.
Cloud Resource Scheduling Method Based on Hybrid Particle Swarm Optimization

As a new computing model, cloud computing delivers infrastructure resources such as computing and storage of data centers to users in the form of services by applying virtualized technologies. Users can access the resources of the data center on their own needs, which provides a better service to users. This paper mainly improves the particle swarm optimization algorithm by introducing a hybrid particle swarm optimization (HPSO) algorithm. Experiments showed that the improved algorithm can reduce the total time consumption and total cost of the task.