Reviewerly/exHarmony huggingface dataset:
Subject, Objects and Types of Railway Forensics

Railway forensic examinations are one of the primary means to establish the circumstances in the detection and investigation of crimes connected to the safety of traffic and operation of railway transport or traffic accidents. This type of forensic expertise falls within the class of transport and technical forensic examinations together with aviation, auto-technical, and water-technical. The forensic and expert literature still has not developed any theoretical provisions concerning the subject of the railway forensics, its objects, tasks, as well as the methodology for conducting the study. The object of forensic expertise is an integral and defining feature of the generic and species identity of the expert study, a source of information about specific events. Based on the investigative and expert practice studied by the author, specialized literature, and the author’s formualtion of the subject of the examination under consideration the classification of objects of the railway forensic examinations is proposed, the types of this kind of forensic expertise are identified.
Unsupervised Online Grounding of Natural Language during Human-Robot Interactions

Allowing humans to communicate through natural language with robots requires connections between words and percepts.The process of creating these connections is called symbol grounding and has been studied for nearly three decades.Although many studies have been conducted, not many considered grounding of synonyms and the employed algorithms either work only offline or in a supervised manner.In this paper, a cross-situational learning based grounding framework is proposed that allows grounding of words and phrases through corresponding percepts without human supervision and online, i.e. it does not require any explicit training phase, but instead updates the obtained mappings for every new encountered situation.The proposed framework is evaluated through an interaction experiment between a human tutor and a robot, and compared to an existing unsupervised grounding framework.The results show that the proposed framework is able to ground words through their corresponding percepts online and in an unsupervised manner, while outperforming the baseline framework.
Review Paper on University Teachers Performance Appraisal

The purpose of the review paper is to summarize and analyze the previously published articles on the university teachers' performance appraisal.The researcher reviewed different articles on the title stated above.The primary aim of university performance evaluation system should be institutional improvement through quality assurance in every process of action.Teachers' job performance assessment criteria should be objective with complex judgment of work performance.The assessment should be based to improve credibility of performance assessment.Feedback from immediate supervisors, colleagues and students is helpful to strengthen the professional development of university teachers.
A Probabilistic Model with Commonsense Constraints for Pattern-based Temporal Fact Extraction

Textual patterns (e.g., Country's president Person) are specified and/or generated for extracting factual information from unstructured data.Pattern-based information extraction methods have been recognized for their efficiency and transferability.However, not every pattern is reliable: A major challenge is to derive the most complete and accurate facts from diverse and sometimes conflicting extractions.In this work, we propose a probabilistic graphical model which formulates fact extraction in a generative process.It automatically infers true facts and pattern reliability without any supervision.It has two novel designs specially for temporal facts: (1) it models pattern reliability on two types of time signals, including temporal tag in text and text generation time; (2) it models commonsense constraints as observable variables.Experimental results demonstrate that our model significantly outperforms existing methods on extracting true temporal facts from news data.
Design, assessment and evaluation of structural stabilization system for weather buoys using a moving foil

Abstract This paper proposes a novel, simple and high-efficient submerged structural stabilization system for a self-stabilizing buoy that provides a stable platform for oceanographic and meteorological sensors. The proposed stabilization system is a Seesaw-like Tuned Mass Damper (STMD) combined with a foil and is designed in a way to harvest the activation energy from incoming waves. A fixed rudder in the rear underside of the buoy, as well as physical properties of the buoy, help to keep its balance in yaw and roll directions while encountering lateral waves. Therefore, the orientational stabilization of the whole structure is achieved by controlling only the pitch deviation. The proposed model is then simulated in a marine dynamic analysis software. Two different shapes of a thin rod and a foil were proposed for the sliding mass (slider) of the STMD and their performances are investigated and compared to each other in two different modes of passive and active control. In the passive mode, different mass ratios were conducted for the thin rod-shaped slider (i.e., a ratio of the effective mass of the stabilizing system to that of the whole structure) and a mass ratio of 8% could suppress the pitch deviation up to 81.3% in the resonance condition. The same STMD system with a mass ratio of 2% suppresses the pitch deviation by only 7%. In the active mode, the STMD with a thin rod-shaped slider and a mass ratio of 8% exhibits only 49.1% suppression effect in a multiwave condition. However, by changing the shape of the slider to a foil while controlling its angle of attack (AOA) mechanically, the system with the mass ratios of 2% and 8% could suppress the pitch deviation of the buoy up to 69.4% and 79.1%, respectively.
A secured automated bimodal biometric electronic voting system

Insecurity, rigging and violence continue to mar electoral processes in developing nations. It has been difficult to enforce security and transparency in the voting process. This paper proposes a secure and automated bimodal voting system. The system uses three security layers, namely, a unique ID code, a token passcode that expires every five minutes and biometrics (iris and fingerprint). A scanner captures the fingerprint and iris of eligible voters. The fingerprint and iris images stored along with the corresponding particulars in a database. The software implemented is a .net managed code in C#. The result of this system shows the system is transparent, fast and fraud-free. The proposed method had a failure to enroll (FTE) and a failure to capture (FTC) of zero.
Evaluation of Eardrum Temperature and Autonomic Nervous Activity by VR Motion Sickness in Amusement Park’s VR Attraction

Using the Amusement Park’s VR Attraction (VR games emulates amusement park ride), pilot studies of 4 subjects were evaluated eardrum temperature and heart rate variability, assuming that temperature of the vestibular sensory receptor change when VR motion sickness occurs. The types of attractions are roller coasters, rotating swings, and rotating carts. As a result, when VR motion sickness occurred, increase of eardrum temperature was observed. The tendency of the increase of the eardrum temperature and the change of the autonomic nervous activity also differed by the difference of the VR attraction.
An Exploration of Target-Conditioned Segmentation Methods for Visual Object Trackers

Visual object tracking is the problem of predicting a target object’s state in a video. Generally, bounding-boxes have been used to represent states, and a surge of effort has been spent by the community to produce efficient causal algorithms capable of locating targets with such representations. As the field is moving towards binary segmentation masks to define objects more precisely, in this paper we propose to extensively explore target-conditioned segmentation methods available in the computer vision community, in order to transform any bounding-box tracker into a segmentation tracker. Our analysis shows that such methods allow trackers to compete with recently proposed segmentation trackers, while performing quasi real-time.
A probabilistic conversational agent for intelligent tutoring systems

The paper proposes a novel approach for a Conversational Intelligent Tutoring System, which combines Natural Language Processing techniques with dynamic Bayesian Inference for probabilistic student state estimation. Our aim is to develop and implement the probabilistic model for the discourse between the user and the Conversational Agent. Most of the already proposed tutoring systems interacting with the user via natural language use rather simple pattern matching rules to carry on the conversation. Even when the fuzzy pattern matching is employed, already existing approaches use these fuzzy values only to find a single best-matching rule, thus immediately discretising the result. Our proposed approach differs in this regard, as we would like to use the fuzzy values resulting from pattern matching as inputs for our probabilistic model. To be more precise, we would like to treat these values as observations for the state estimation in the dynamic Bayesian Network. Our approach is, not coincidentally, similar to the methods typical for state and action recognition. This paper focuses on the Natural Language processing aspect, while the probabilistic model is described in a separate work.
GENERIC LINEAR ARRAY SCANNER MODELING OF SPECTRAL IMAGING SYSTEMS CONTAINING LIMITED METADATA

Abstract. The National Geospatial-Intelligence Agency (NGA) designed the Generic Linear Array Scanner (GLAS) model for geopositioning images from both airborne and spaceborne linear array scanning systems, including pushbroom, whiskbroom, and panoramic sensors. Providers of hyperspectral imagery (HSI) historically have not populated products with high fidelity metadata to support downstream photogrammetric processing. To demonstrate recommended metadata population and exploitation using the GLAS model, NGA has generated example HSI products using data collected by NASA’s EO-1 Hyperion sensor and provided courtesy of the U.S. Geological Survey. This paper provides novel techniques for: 1) generating reasonably accurate initial approximations for GLAS metadata as a function of per-image metadata consisting of only timing information and the latitude and longitude values of the four corners of the image; and 2) identifying a vector of adjustable parameters and reasonable values for its a priori error covariance matrix that enable corrections to the metadata during a bundle adjustment. The paper describes applying these techniques to fourteen overlapping Hyperion images of the Alps, running a bundle adjustment as a function of tie points and optional ground control points, and demonstrating superior results to the previous polynomial based approach as quantified by the 3D errors at several ground check points.
Perancangan Kerangka Crowdsourcing Berbasis Wisdom Of Crowds Untuk Kamus Naskah Lontar (Takepan) Sasak Online

The online Lontar (Takepan) Sasak manuscripts currently available are not sufficient to be a reference for those who want to learn Sangsekerta because of the limited contribution and stagnation of their contributions. On the other hand, active speakers of Lontar (Takepan) Sasak manuscripts exposed to the internet are available in sufficient quantities. The wisdom of crowds-based crowdsourcing mechanism is expected to be a solution to the problem. This paper presents a draft framework of the Sasak Lontar (Takepan) online crowdsourcing dictionary system. The design of this framework is expected to be the basis for the development of the new Sasak Lontar (Takepan) online dictionary. DOI : 10.29408/jit.v3i2.2300
A Robust Video Compression Algorithm for Efficient Data Transfer of Surveillance Data

The compression models play an important role for the efficient bandwidth utilization for the streaming of the videos over the internet or TV channels.The proposed method improves the problem of low compression ratio and degradation of the image quality.The motive of present work is to build a system in order to compress the video without reducing its quality and to reduce the complexity of existing system.The present work is based upon the highly secure model for the purpose of video data compression in the lowest possible time.The methods used in this paper such as, Discrete Cosine Transform and Freeman Chain Code are used to compress the data.The Embedded Zerotree Wavelet is used to improve the quality of the image whereas Discrete Wavelet Transform is used to achieve the higher compression ratio.Finally quantitative analysis is performed on existing technique and through present technique through PSNR, CR and BER which clearly shows that present work is better that existing technique.
Weighting-based parallel local search for optimal camera placement and unicost set covering

This paper presents a weighting-based parallel local search algorithm (WPLS) for solving the optimal camera placement problem (OCP) and the unicost set covering problem (USCP). The neighborhood exploration of WPLS is parallelizable and hence can be accelerated using parallel computing architectures such as multi-core CPU or GPGPU.
Use Of Modern Information And Communication Technologies In The Learning Process

This article discusses in detail how to achieve the effectiveness of learning through the use of computer technology in the education system, how to facilitate the organization of the educational process, as well as how to increase and strengthen participants' interest in the lessons.The article describes in detail the meaning, purpose, content, methods, means of teaching ICT in the activities of educational institutions.
Compressing Knowledge Graph Embedding with Relational Graph Auto-encoder

Knowledge graphs (KGs) are extremely useful resources for varieties of applications. However, with the large and steadily growing sizes of modern KGs, knowledge graph embeddings (KGE), which represent entities and relations in KGs into 32-bit floating-point vectors, become more and more expensive in terms of memory. To this end, in this paper, we propose a general framework to compress the embeddings from real-valued vectors to binary ones while preserving the inherent information of KGs. Specifically, the proposed framework utilizes relational graph auto-encoders as well as the Gumbel-Softmax trick to obtain the compressed representations. Our framework can be applied to a number of existing KGE models. Particularly, we extend state-of-the-art models TransE, DistMult, and ConvE in this paper. Finally, extensive experiments show that the proposed method successfully reduces the memory size of the embeddings by 92% while only leading to a loss of no more than 5% in the knowledge graph completion task.
PUBLIC ACTIVITY OF THE STUDENTS OF PEDAGOGICAL EDUCATIONAL INSTITUTIONS IN KYIV IN 20-30s OF THE 20th CENTURY

In the 20–30s of the 20th century special attention was paid to the formation of the ideological worldview of students of education institutions, future teachers who were to shape the political consciousness of the younger generation with communist ideals. The ideological principles of the party were subordinated to the social activities of youth, in particular, in Kyiv pedagogical educational institutions. The article deals with the work of student clubs and student government bodies, various organizations. Since the mid-20s of the 20th century trade union organizations took over the functions of youth advocates, which were largely influenced by university administrations and controlled the social composition of students, who presented themselves as an exclusively peasant workers. Some of the students were embraced by work in the cells of voluntary societies, the government used to propagate their ideas of socialist construction and the ideological education of the masses. The most active were the cells of Tsoaviakhim, which oversaw the work of the rifle circles. Close to them were sports clubs. Universities also operated cells of MOPR, the Friends of the Children societies, the All-Ukrainian Society for Land Organization of Working Jews OZET, and the Friends of Radio. The ideological work among students was intensified by the student press, the production of “live and light newspapers” that covered the processes of building a higher school, the participation of youth organizations in the proletariat of institutes and technical schools, the life and attitude of students, their participation in cultural work etc. Most of the time, students took part in enriching work. In particular, they worked on various campaigns related to raising funds for the state’s economic needs, participating in fundraising to strengthen defense, days of industrialization, etc.
Process matters: from car owner experiences to automotive design proposals

Collecting and analysing user experiences, communicating discovered patterns, translating information into design proposals and materialising designed features is central to design driven research.This process immerses design teams into all aspects of users' experiences, helping them empathise with and scrutinise every detail until designers own the experiences and produce design proposals addressing end users' needs in unique ways leading to disruptive innovation.Design practice's strength is crystallising solutions into visualised and interactive proposals, presenting in-depth details of the look, feel and emotions they stimulate, and assisting decision making in product, service and business innovations.Existing research focusses on early stage collection of lived user experiences and final visualisation of the design proposal, yet seems to miss detailed discussion of the core bridging of user experiences and precise design proposals.We describe optimising a process supporting designers continuously switching between gathering user experiences and industry/market contexts when generating automotive design proposals.
Sharing a Secret Image in the Cloud Using Two Shadows

In this paper, we present a novel (2, 2) reversible secret image sharing scheme. Our scheme permits secret messages to be shared with two participants by splitting the marked encrypted image into two shadows. The secret messages can be reconstructed if two participants collaborate with each other. The proposed scheme chooses suitable binary blocks of a cover image in which to embed the secret message and divides those blocks into two shadow blocks by executing a logical operation with all of the other binary blocks, thereby producing two shadows. In the data extraction procedure, the secret messages and the cover image can be reconstructed by the logical operation of the corresponding binary blocks of the two shadows. A practical application is demonstrated by modeling our scheme as a reversible watermarking scheme in the Cloud. The experimental results indicated that the proposed method is reversible and that it can restore the image and watermark properly.
Intersubjectivity and Food Purchasing: Modeling the Intent to Buy

Aims: A previous study showed that Intersubjectivity Theory could explain how consumers could appreciate a food product when looking at the packaging and reading the brand. Two samples of subjects, English and French consumers, were individually presented first with a foreign language food product and then with a native language food product. Their reaction and perception were analyzed in the light of Intersubjectivity theory.&#x0D; However, the main limitation of the previous study addressed the psychosocial value carried by the foreign products: the product presented to French subjects had a sexual connotation and not this for the English. The present study intended to analyze this potential bias.&#x0D; Study Design: For the present study, a new sample of English subjects were individually presented with a foreign language food product having a sexual connotation. Reactions and perceptions were analyzed applying the protocol of the previous study and results were compared in order to analyze the aforementioned potential bias.&#x0D; Place and Duration of Study: Subjects were individually met in London in 2019 for the experiment.&#x0D; Methodology: Subjects were selected as in the previous study: volunteer, healthy adults, native English language (N=20, 60% male, average age: 35 years old, middle class). Their spontaneous reaction was observed and they had to fill in the questionnaire addressing intersubjective perspectives regarding the product. Answers were ticked on a Likert scale and data were compared with that of the previous study.&#x0D; Results: The results confirmed the previous study: the comparison of the percentage of responses per questions and of the mean scores showed no significant difference between previous and current studies. This showed that no bias was induced by the psychosocial value carried by the foreign product.&#x0D; Conclusion: The model developed on the basis of Intersubjectivity Theory explains the process of intent to buy in terms of positive coherence between the intersubjective dimensions. It also shows that analyzing the consumers’ direct perception of the product does not predict their intent to buy. These findings are of great importance for food producers and marketers.
Securing Data in Internet of Things (IoT) using Cryptography and Steganography Techniques

The Internet of Things (IoT) could also be a network of connected vehicles, physical devices, software, and electronic things that facilitates data exchange. The aim of IoT is to provide the IT-infrastructure for the secure and reliable exchange of "things." safety of this knowledge could be a difficult task; but, security challenges will be lessened with cryptography and Steganography techniques. These techniques square measure crucial once addressing user authentication and knowledge privacy. Within the planned work, the elliptic Variety Galois cryptography protocol is introduced and mentioned. During this protocol, a cryptography technique is employed to encode confidential knowledge that came from totally different medical sources. Next, a Matrix XOR coding Steganography technique is employed to embed the encrypted knowledge into an occasional complexes image. The planned work additionally uses associate optimization algorithmic rule is a known as adaptation Firefly tooptimize the option of canopy blocks among the image.Supported the results, varied parameters square measure evaluated and compared with the prevailing techniques.Finally, the info that's hidden within the image is recovered and is then decrypted.