Reviewerly/exHarmony huggingface dataset:
The Effect of Blockchain Technology in the Initial Stages of Auditor Investigation in the Halal Supply Chain

Each country in Asia will apply a halal assurance system (HAS) to get a halal certificate and logo. The problem with HAS in Asia is that every country has its own halal standard rules. This problem raises a trade dispute because imported products cannot enter another state market due to different halal standards. So, we need the same halal standards for every country in Asia, one of which requires transparency in each country's HAS. However, the HAS documentation process currently has several shortcomings, such as document fraud and transparency during internal and external audits. This chapter aims to discuss blockchain technology's development in solving internal audit problems to improve its performance, and blockchain technology can improve efficiency, transparency, and traceability of original documents, thereby enhancing the overall halal certification process. And it is hoped that this research will be taken into consideration for those who will make the same halal standards for every country in Asia.
The Annotation Type of Video Case System Built for Pre-Service Teachers in Teaching Skills Training

Abstract The training program of teaching skills is one of the key elements for pre-service teachers who cultivated in school. Due to the advantages of vivid, image video case are admired greatly by teaching classes teachers, and then, there are many video cases support systems for pre-service teachers emerged. However, they have some common problems which are not conducive to training pre-service teachers’ teaching skills, including listing integrated instructional videos and a small amount of video review. Base on this situation, the author built a training case system for pre-service teachers, which can add annotations on fragments, search, evaluate, and share the content as a whole, by using the advanced network and informational technologies, the aim is to help pre-service teachers expand the time and space on training teaching skills, and improve the research efficiency and effects on training.
Improving UAV Object Detection through Image Augmentation

Ground-image based object detection algorithms have had great improvements over the years and provided good results for challenging image datasets such as COCO and PASCAL VOC. These models, however, are not as successful when it comes to unmanned aerial vehicle (UAV)-based object detection and commonly performance deterioration is observed. It is due to the reason that it is a much harder task for the models to detect and classify smaller objects rather than medium-size or large-size objects, and drone imagery is prone to variances caused by different flying altitudes, weather conditions, camera angles and quality. This work explores the performance of two state-of-art-object detection algorithms on the drone object detection task and proposes image augmentation 1 procedures to improve model performance. We compose three image augmentation sequences and propose two new image augmentation techniques and further explore their different combinations on the performances of the models. The augmenters are evaluated for two deep learning models, which include model-training with high-resolution images (1056×1056 pixels) to observe their overall effectiveness. We provide a comparison of augmentation techniques across each model. We identify two augmentation procedures that increase object detection accuracy more effectively than others and obtain our best model using a transfer learning 2 approach, where the weights for the transfer are obtained from training the model with our proposed augmentation technique. At the end of the experiments, we achieve a robust model performance and accuracy, and identify the aspects of improvement as part of our future work.
Evaluating the Risk of Disclosure and Utility in a Synthetic Dataset

Social cues, such as eye gaze and pointing fingers, can increase the prioritisation of specific locations for cognitive processing.A previous study using a manual reaching task showed that, although both gaze and pointing cues altered target prioritisation (reaction times [RTs]), only pointing cues affected action execution (trajectory deviations).These differential effects of gaze and pointing cues on action execution could be because the gaze cue was conveyed through a disembodied head; hence, the model lacked the potential for a body part (i.e., hands) to interact with the target.In the present study, the image of a male gaze model, whose gaze direction coincided with two potential target locations, was centrally presented.The model either had his arms and hands extended underneath the potential target locations, indicating the potential to act on the targets (Experiment 1), or had his arms crossed in front of his chest, indicating the absence of potential to act (Experiment 2).Participants reached to a target that followed a nonpredictive gaze cue at one of three stimulus onset asynchronies.RTs and reach trajectories of the movements to cued and uncued targets were analysed.RTs showed a facilitation effect for both experiments, whereas trajectory analysis revealed facilitatory and inhibitory effects, but only in Experiment 1 when the model could potentially act on the targets.The results of this study suggested that when the gaze model had the potential to interact with the cued target location, the model's gaze affected not only target prioritisation but also movement execution.
SKILLS OF PROFESSIONAL SELF-IDENTIFICATION AS THE CENTRAL MOMENT IN THE FORMATION OF PROFESSIONAL AND PERSONAL QUALITIES IN STUDENTS AT A UNIVERSITY

The period of study at a higher professional educational institution is of great importance for the individual, since it is at this time that they begin to take an active part in industrial relations, demonstrate a meaningful, mature perception of their future specialty, supported by a formed system of values and clear motivation. In this article, attention is focused on the phenomenon of professional self-identification. Professional self-identification changes the entire student's value system, forms a new personality in them, based on a number of values which become an integral part of a person. Each student becomes a specialist who must be able to perform all assigned tasks at the enterprise. It is their competitiveness that determines their development as a person and becoming a professional in the field. Self-identification helps to better reveal a person, get advanced experience in mastering one's profession, working skills. A set of qualities are formed that help develop skills and gain knowledge. When doing practical work, the initial level of self-identification changes. Today, the problem of self-identification of future specialists is urgent. The article describes the process of the formation of professional and personal qualities of students at University, examines the essence of the concepts of “self-identification”, “professional self-identification”, reveals the conditions for their formation. The stages and factors of the formation of the skill of professional self-identification are also shown. It is concluded that the skills of professional self-identification are the main moment in the formation of professional and personal qualities and should be formed in students precisely within the walls of a university.
ATR: Auto-Tuning Configurations of Redis via Ensemble Learning

Redis is one of the most popular in-memory cache databases at present and it has many performance-related configuration parameters. Because of the complexity to explore the configuration space, there is an urgent need of a method that can automatically adjust configuration parameters to quickly and accurately improve the performance of Redis. In this article, we propose ATR: a novel approach to auto-tune the configuration parameters for a given Redis application. The core of ATR is to take Redis configuration parameters as input and to establish an accurate performance prediction model. Then we use the model as a basis to search for configuration parameters with better performance. By systematically comparing various modeling techniques and optimal search algorithms, we employ an ensemble learning algorithm to build the performance model and leverage genetic algorithm to search the optimal configuration parameters. In order to evaluate ATR, we build a Redis cluster with 10 nodes and test the performance by 6 representative applications from YCSB benchmark suite. The experimental results show that compared with the default configuration, ATR increases the throughput by 79% at the maximum, with an average of 48%. ATR reduces the latency by 16.6% at the maximum, with an average of 9.49%.
Fast Jump Point Search Based Path Planning for Mobile Robots

We propose a method to improve the performance of JPS for path planning on static grid map, including a fast neighbor pruning method and a symmetry-breaking heuristic function. First, we adopt a new and effective method to identify jump points quickly through bit operations at a single time. Second, we adopt a symmetry-breaking heuristic function to pruning redundant jump points by adding angle information and node sequence number in order to further speed up path planning search. We conducted simulation experiments on grid maps of different specifications and obstacle ratios to verify the effectiveness and feasibility of the proposed algorithm, comparing with JPS. The experimental results show that our improvement has more advantages on grid maps of different specifications and obstacle ratios, both in terms of search time and number of jump points.
Comparison of frameworks for creating web services using the Axis2/C and gSOAP examples

Main purpose of this paper was to compare two frameworks (Axis2/C and gSOAP) that implement the SOAP protocol, a protocol for the exchange of structured messages in a computer environment. The paper describes experiments showing the level of SOAP performance depending on the components of each framework and the methods of their implementation, such as: parsing, serialisation, working with various message formats, the effectiveness of protocol, the efficiency of message processing models, etc. After the practical part was completed, performance studies of each of the frameworks were carried out, the collected data helped to define a more efficient and faster tool for transferring data between the server and the client.
TRENDS IN THE DEVELOPMENT OF INFORMATION TECHNOLOGIES IMPLEMENTED IN THE EDUCATION SYSTEM

All spheres of society are moving to informatization - the widespread use of information systems and technologies. For several years, different countries of the world have been engaged in the implementation of information systems in educational activities, which allowed us to form a significant experience in using technologies in pedagogical work when teaching students and schoolchildren. Thanks to the exchange of practical knowledge between the countries, a large number of information products were created that solve different problems in educational activities, which formed the basis of a new layer of information. Today, the education system uses the ideas of various fields of science and technology, both in the form of individual developments, and a set of tools of various directions, depending on the choice of the specifics of the issue being solved. The article shows that today in pedagogical practice the use of information technologies occurs through their modernization and adaptation to the current Russian realities. The article reflects the dynamic development of the education system and the role of informatics and computer technology in this. The main difficulties of the transition of the education system are identified-limited financial resources, as well as the rapid obsolescence of information products, which requires their regular updating. In this case, the optimal solution for improving the quality of the pedagogical process is to introduce additional opportunities provided by new information technologies. The priority direction of the development of information technologies for the conditions of the education system is the formation of a system that ensures the separate operation of various modules for the ease of integrating new functions into the educational process.
Decision support system for neglected elderly social assistance recipients using the Weighted Product method

Abstract Among the people of Indonesia is an aging society, with an elderly population of around 20 million people, or 8% of the total population. The data is the governments concern to provide assistance proposals. In the process of proposing assistance, this is still done by checking one by one the documents of prospective beneficiaries and matching them with existing criteria. This method requires quite a long time and makes an error because of subjectivity. The purpose of this study was carried out to implement the Weighted Product (WP) method into a decision support system that can determine the priority proposals for recipients of neglected elderly social assistance. RUP (Rational Unified Process) used in the software development method. The final results of this study obtained a decision support system that can assist in the process of determining the ranking of recipients of abandoned social assistance proposals by using the WP method that gets an accuracy of 76.74%.
Overcoming Data Sparsity in Predicting User Characteristics from Behavior through Graph Embeddings

Understanding user characteristics such as demographic information is useful for the personalization of online content promoted to users. However, it is difficult to obtain such data for each user visiting the website. Since demographic data for some users can be collected, their behavior can be used to predict the attributes of unknown users. Through online news consumption, we can infer the attributes of users from the articles they view. Most existing models take a supervised learning approach to this modeling task. However, by representing the user-URL interactions with a network, we can convert it to a semi-supervised learning problem and learn embeddings for users. Graph embeddings have become popular in recent years, with research mainly focusing on algorithmic developments. However, while we have an intuitive understanding of the problems they may overcome, such as data sparsity, this problem remains unexplored in the domain of demographic prediction using behavior. In this paper, we first investigate the effectiveness of using user embeddings generated from network representation learning for prediction by comparing its performance with other traditional feature sets, including content and item-based features. We find that the embeddings can represent a user generally on two prediction tasks, (1) gender prediction (classification) and (2) age prediction (regression). Second, we explore the advantages of using these embeddings over the other methods in two cases of data sparsity, where (1) the training and testing sets of users are temporally split and (2) the user labels are imbalanced. In both these cases, the embeddings outperform the baseline.
Improvised Distributed Data Streaming Scheduler in Storm

Apache Storm is one of the most widely used platforms for processing of data streams due to its properties of being distributed, highly scalable, and fault-tolerant. It provides real-time processing, is fast and stateless, and uses master–slave architecture with ZooKeeper. In the Hadoop ecosystem, Apache Storm is the one that fills the present real-time functionality and provides strong coupling with many tools and technologies. In Storm framework, the Storm default scheduler is commonly used to schedule the task or data to be processed, whose basis for scheduling the task is the time quanta or time slots, which leads to increase in context switches and longer response time. In Storm default scheduler, the workload of a topology equally distributed among worker processes or Java virtual machine (JVM) all over the cluster using a simple round-robin algorithm without considering any priority or criteria. The proposed algorithm addresses the above-specified issues. An improvised the custom Storm scheduler was developed where the scheduling is based on the workload, which is calculated based on the total memory utilized per task and the total processing unit utilized per task, thereby resulting in lesser context switches and faster response time of distributed streaming applications.
Testing identity of collections of quantum states: sample complexity analysis

We study the problem of testing identity of a collection of unknown quantum states given sample access to this collection, each state appearing with some known probability. We show that for a collection of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>d</mml:mi></mml:math>-dimensional quantum states of cardinality <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>N</mml:mi></mml:math>, the sample complexity is <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>O</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:msqrt><mml:mi>N</mml:mi></mml:msqrt><mml:mi>d</mml:mi><mml:mrow class="MJX-TeXAtom-ORD"><mml:mo>/</mml:mo></mml:mrow><mml:msup><mml:mi>&amp;#x03F5;</mml:mi><mml:mn>2</mml:mn></mml:msup><mml:mo stretchy="false">)</mml:mo></mml:math>, with a matching lower bound, up to a multiplicative constant. The test is obtained by estimating the mean squared Hilbert-Schmidt distance between the states, thanks to a suitable generalization of the estimator of the Hilbert-Schmidt distance between two unknown states by Bădescu, O'Donnell, and Wright \cite{Badescu2019}.
A Study on the Performance Analysis of MILITARY Culture Innovation

Purpose: This study was conducted to evaluate and analyze whether the military culture innovation;which has been being promoted since 2014;is doing well through a survey of Army soldiers on A Survey on the Feel-ings of Military Culture Innovation. In particular;a qualitative performance analysis of military culture innova-tion was conducted through a survey on the awareness and satisfaction of soldiers who are experiencing mili-tary culture innovation in personally. Method: In this work;we selected suitable questions for the study through factor analysis of the SPSS pro-gram and conducted the study in two main ways on selected questions. The first is to conduct an analysis of the performance of military culture innovation through the average of the selected detailed questions for each part on the five implementations of military culture innovation. Second;we divided the officers and soldiers among the survey respondents to see if the results of their survey on the level of military culture innovation showed a difference;and analyzed whether the difference was significant through the SPSS program s independent sam-ple T test. Results: The results of the analysis conducted using selected questions through factor analysis are as follows: First;as a result of the analysis of the feeling of military culture innovation;we produced positive results that we are somewhat satisfied with all five implementations. Second;there was a significant difference between the officer group and the soldier group in terms of the sense of military culture innovation. Conclusion: This study was conducted using the most survey results among the performance analysis of mili-tary culture innovation that has ever been done;so the reliability is very high. In addition;it is of great value in that it analyzed quality performance based on the feelings and thoughts of soldiers who are experiencing mili-tary culture innovation directly;not performance analysis relying on quantitative results. Through this;we hope that it will help to accurately diagnose the current military culture innovation and find constructive improve-ments in the future.
Word Segmentation for Gujarati Handwritten Documents

In this fast-evolving world, documents in numerous regional languages are finding a prominent place on the internet. This is evident from the increasing use of regional languages on hoardings of advertisements, boards of various stalls and shops, and even essential government instructions are found in regional languages. With the growing reach of the internet, the least privileged are also getting an opportunity to explore the world. Hence, more than a technological requirement, it has become a moral responsibility to put to the test research at the grass root levels in serving the ones who have remained aloof for a while. This work is a preliminary step in exploring the efficiency of various conventional techniques like morphology operations, connected components analysis, and finding contours in segmenting Gujarati handwritten words from scanned documents. The results obtained from the collected data are encouraging.
Geology, mineralization and short wave infrared alteration mapping of the <scp>Khan Altai Au deposit, Mongolia</scp>

Abstract Khan Altai Au deposit is located near the N margin of the Neoproterozoic‐Cambrian Lake terrain in SW Mongolia, about 5 km from its contact with the Proterozoic‐Archean Baydrag craton, and 18 km SE of the Khantaishir ophiolite, which was emplaced in the Late Cambrian. The host rocks are strongly deformed and metamorphosed to lower greenschist facies, and of uncertain age. They comprise a sequence of rhyolitic volcaniclastics and porphyritic flows interbedded with laminated siltstone, basaltic andesite and faulted against dolomite. Low‐grade gold mineralization (up to 2 ppm Au) is hosted mainly in rhyolitic volcanics and extends over an area of about 1,100 × 160 m with a vertical extent of about 200 m. It is associated with disseminated pyrite (2–10% by vol) but includes high‐grade zones (up to 183 ppm Au over 1 m) related to cm‐wide quartz‐native Au‐pyrite veins. The Au mineralized zone also encompasses VMS mineralization (currently of minor extent), characterized by massive pyrite‐sphalerite lenses and quartz‐chalcopyrite stringer zones. A larger VMS deposit (Ereen Budagt, about 10 Mt sulfide ore) is found 6 km to the SSE in a similar geological setting. The main alteration assemblage is quartz‐white mica‐albite, but with minor carbonate, chlorite, epidote‐actinolite and pyrophyllite‐diaspore‐dickite alteration. Gold mineralization is related to zones of strong tectonic foliation and formation of phengitic white mica, with an outward zonation to high Al white mica. Pyrite is typically euhedral, and exhibits concentric growth zones, as well as quartz pressure shadows to enclosing foliation, consistent with syngenetic growth during metamorphism and deformation. Other sulfides include arsenopyrite, sphalerite and possible marcasite. Preliminary LA‐ICPMS mapping shows pyrite rims are enriched in Au, As, Co, Cu, Ni, Pb, Ag, Mo and Se, the pyrite core is enriched in Co, Bi, Te, and rhyolitic host rock is enriched in K, Ba, V and Tl. Whole rock geochemistry of basaltic andesite to rhyolite, shows N‐MORB characteristics for basaltic andesite, as well as a subduction signature for all rocks, and high MgO (~8%), TiO 2 (~1%) and low Ni, Cr content in basalt, compatible with a back arc tectonic setting.