Reviewerly/exHarmony huggingface dataset:
Scrum Watch: a tool for monitoring the performance of Scrum-based work teams

Agile Methods propose an approach for developing software based on an iterative and incremental life cycle model, in which needs and solutions evolve through collaboration between multi-functional and self-organized teams. As such, agile practices in work teams are gaining much momentum. To meet the demanding level of projects, agile software development also has to keep up with several challenges. In this context, software industry has chosen to use several tools to ease development and communication between different teams&amp;rsquo; members. However, these tools generate overwhelming volumes of data that hamper decision-making by project managers. To address this issue, we present Scrum Watch , a tool-based approach that focuses on generating, through cloud-based technologies, graphic elements and reports that assist project managers with information to support decision making. Results obtained from an undergraduate Systems Engineering course through a capstone project confirm the feasibility of the proposed approach, which exploits the benefits of the availability and visualization of process and product metrics.
A Prediction Model to Prevent Phishing Attacks on E-Mails Using Data Mining Techniques

The current study presents a design and implementation of a prediction model that prevents phishing attacks on emails using data mining techniques. Hereby, we collected appropriate data sets in order to identify the characteristics of the infected emails, which allow a phishing attack to be successful from three significant sources, being Monkey.org, Enron.org, and PhishTank.com. For the design and implementation of the model, we used the CRISP-DM methodology in order to generate the detection model based on the characteristics that recognize an email as phishing. Likewise, we developed a descriptive analysis using Decision Trees, Bayesian Networks, and Random Forest as data mining algorithms, whose most precise has been Random Forest. Once the email was detected as infected, the algorithm quarantines the email. Subsequently, it sends a notification message through WhatsApp. Finally, we evaluated the model in a controlled environment. The results demonstrate the functionality of the model since it achieved a precision score greater than 97.28% in the detection of phishing emails.
The use of digital games in the professional training of social pedagogues: realities and perspectives

The article presents the possibilities of using digital games in the process of professional training of social educators. It was found that for the development of digital game-centered learning it is necessary to combine the efforts of public, private, charitable and public institutions and organizations that prepare for game design, training, organize exhibitions, competitions, festivals, which is the main direction of modern education as an important component. Competencies of the 21st century were talked about. It is determined that the use of computer games enhances the freedom of experiment, identity and social rewards, deepens personal experience by developing three basic needs for training motivation: competence (student feels the process of acquiring new knowledge and skills); autonomy (the student feels control over the educational process); interconnectedness (the student feels the connection with colleagues during the educational process). It is proved that the use of digital games in the professional training of social educators is an innovative and promising vector for the modernization of the educational process in modern higher education institutions as a whole.
From authority data, to linked open data and Wikidata : A case study of a Hebrew manuscript catalogue

The international conference #DHJewish - Jewish Studies in the Digital Age will bring together more than 60 scholars and heritage practitioners to discuss how the digital turn affects the field of Jewish Studies. The conference is organised by the [Luxembourg Centre for Contemporary and Digital History (C²DH).](https://www.c2dh.uni.lu/) [For more information, and a PDF download of the program, please see also here.](https://www.c2dh.uni.lu/events/dhjewish-jewish-studies-digital-age) In order to meet other participants and for informal chats in the breaks, join us in our [wonder.me room](https://www.wonder.me/r?id=73a12756-8d93-4871-9374-143253bfbf59).
Intelligent camouflage pattern generating in internet of things

Artificial Internet of Things (AIoT) has facilitated many aspects of people's daily lives and greatly promoted the development of military technology. Due to the rapid development of multiple Internet of Things (IoT) devices. The application of AIoT to daily lives and military come true. In our AIoT system, the key part is artificial camouflage pattern generating. In this paper, a new method for generating the camouflage pattern is proposed. In our algorithm, the loss function is designed based on the statistic information of nearby surroundings and traditional camouflage pattern. The statistic information is extracted from the feature maps of convolution neural network. The new camouflage pattern is synthesized by minimize the loss function. A color mapping method is designed. This color mapping method is design for the color mapped from the background to the camouflage pattern. Our method is more flexible than traditional methods and can integrate better with the surrounding environment. Experiments show that this method can effectively generate camouflage patterns similar with background in textures and colors. Besides, our method can well save the texture of traditional artificial designed camouflage pattern.
Screening: A Pitfall in Statistics

Scientists often propose hypotheses based on patterns seen in data. However, if a scientist tests a hypothesis using the same data that suggested the hypothesis, then that scientist has violated a rule of science. The rule is: test hypotheses with independent data. This rule may sound so obvious as to be hardly worth mentioning. In fact, this mistake occurs frequently, especially when analyzing large data sets. Among the many pitfalls in statistics, screening is particularly serious. Screening is the process of evaluating a property for a large number of samples and then selecting samples in which that property is extreme. Screening is closely related to data fishing, data dredging, or data snooping. After a sample has been selected through screening, classical hypothesis tests exhibit selection bias. Quantifying the effect of screening often reveals that it creates biases that are substantially larger than one might guess. This chapter explains the concept of screening and illustrates it through examples from selecting predictors, interpreting correlation maps, and identifying change points.
Occurrence of Geothermal Features Based on Surface Roughness and Geobotanical Analyses derived by ALOS-2 PALSAR-2 and Sentinel-2 Images

Geothermal energy as renewable, reliable, and environmentally friendly is one of the most important energy resources. Based on government regulation about the National Energy Policy, the use of geothermal energy must reach 23% by 2025. This regulation is in line with the goal of the 7th of Sustainable Development Goals (SDGs). In order to achieve the government’s targets, a preliminary assessment on a wide scale by minimizing time consumption is necessary. Remote sensing technology utilizing radar and optic sensors promises as an alternative solution for preliminary surveys. The occurrence of geothermal system could be characterized by surface features associated with thermal system near the surface. Geothermal features originated from sub surface hydrothermal fluids to surface through fractures or pores in the rock formations. The chemical composition of the fluid composed by hot and acidic constituent affects the surrounding environment such as host rocks and vegetation. In this study, surface roughness and geobotanical analyses were used as indicator of geothermal features occurrence. The ALOS-2 PALSAR-2 and Sentinel-2 images were selected to calculate surface roughness and geobotanical anomalies including NDVI, GNDVI, SAVI, and RDVI, respectively. Combining ALOS-2 PALSAR-2 and Sentinel-2 images, we could characterize the occurrence of geothermal features by surface roughness more than 17.2 cm and the vegetation index less than 0.2. Accuracy of obtained occurrence map has been calculated about 71.43% with a predicting error rate of 28.57%. The likely prediction zones agreed to the up flow and discharge zones of geothermal system in selected study area.
The development of cognitive independence of students in the context of higher music and pedagogical education

This article deals with the actual problems of the development of the cognitive independence of students in the conditions of higher musical and pedagogical education. The influence of the development of cognitive independence on the quality of professional training of a future teacher is noted. Various approaches to the interpretation of the concept of “cognitive independence” in the psychological and pedagogical literature are analyzed. The structural components of cognitive independence are considered and the search for effective ways of its development with an integrative model of musical-theoretical training of students of a pedagogical university is carried out.
Becoming a Virus: Self-Organization of the Masses in Recent Decades

According to our usual understanding of a virus, it is a parasite that spreads by forcing the host to make copies it. Cultural analogies to that concept have already given us the notion of a computer virus, a media virus or meme, and ideas as viruses infecting and propagating within the human brain, etc. But could the concept of a virus provide a useful analogy to political and social phenomena? The authors show how such an analogy illuminates the features of modern mass politics that remain obscure as long as political action is thought of in terms of identity, ideology, or private interest. The theoretical basis for regarding social and political phenomena as viruses is that the class of viruses is by nature analogous rather than homologous. This means that scientists can come to different conclusions about the origin of viruses and that several different theories may all be correct. Nevertheless, the term “virus” is meaningful precisely because of the analogy between all the entities called viruses. The core of this analogy is that all viruses use the same set of tricks (artificuim) to realize their essence (potentia). Viruses are parasitic on the organic machinery of other living beings, turning their malfunctions into their own reproductive system. That process also has a cognitive dimension because viruses learn only over succeeding generations. Viruses then live and act not as individual carriers, but only as procreating, mutating, learning multitudes. Their potentia is precisely analogous to the power of the multitudes, which Michael Hardt and Antonio Negri have discussed. It is a power which constitutes a new political order and simultaneously impoverishes the present one. The article explains the meaning of this analogy as it applies to the fate of the political and social institutions of late modernity.
CondenseNeXtV2: Light-Weight Modern Image Classifier Utilizing Self-Querying Augmentation Policies

Artificial Intelligence (AI) combines computer science and robust datasets to mimic natural intelligence demonstrated by human beings to aid in problem-solving and decision-making involving consciousness up to a certain extent. From Apple’s virtual personal assistant, Siri, to Tesla’s self-driving cars, research and development in the field of AI is progressing rapidly along with privacy concerns surrounding the usage and storage of user data on external servers which has further fueled the need of modern ultra-efficient AI networks and algorithms. The scope of the work presented within this paper focuses on introducing a modern image classifier which is a light-weight and ultra-efficient CNN intended to be deployed on local embedded systems, also known as edge devices, for general-purpose usage. This work is an extension of the award-winning paper entitled ‘CondenseNeXt: An Ultra-Efficient Deep Neural Network for Embedded Systems’ published for the 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC). The proposed neural network dubbed CondenseNeXtV2 utilizes a new self-querying augmentation policy technique on the target dataset along with adaption to the latest version of PyTorch framework and activation functions resulting in improved efficiency in image classification computation and accuracy. Finally, we deploy the trained weights of CondenseNeXtV2 on NXP BlueBox which is an edge device designed to serve as a development platform for self-driving cars, and conclusions will be extrapolated accordingly.
Drone Assisted Targeting for Direct Fire Engagements

Abstract The goal of the project is to develop a drone and recovery station system capable of tracking a target and round fired from a tank. Key aspects of the project include maintaining a level platform through the shot, performing accurate localization, and reacting to movements in the tank turret. The goal is for the design to be able to operate in GPS-denied and light-denied environments. After significant testing and research, the drone will be placed 10 meters behind and 20 meters above the tank muzzle and the recovery station will be placed on the rear of the tank. The drone will perform localization using visual-inertial odometry (VIO) and will react to movements in the tank turret by using a filtered IMU to send up the tank’s azimuth. All communication will be transmitted over WiFi and the video from the camera will be livestreamed on the recovery station laptop. In this semester, key areas of focus will be validating the VIO algorithm, developing a method for aligning the drone with the tank turret, establishing communication over WiFi, and then conducting final testing.
Research on Energy Saving Distribution in Cloud Computing Environment

Abstract With the huge increase of cloud infrastructure and the continuous expansion of cloud computing scale, the consumption promotion role of IT resources has been increasing, which has greatly hindered the development of IT industry. Energy consumption has become an important factor restricting the development of cloud computing. How to reduce energy consumption and improve the efficiency of energy utilization in cloud computing has become a new problem. At present, most of the cloud computing task scheduling algorithms are also carried out in job scheduling, which does not consider the allocation and energy consumption of resources. Therefore, the rational allocation of resources is an effective way to improve the efficiency of energy utilization and energy utilization. In this paper, the concept of resource waiting and resource consumption is proposed. It is considered that resource allocation is an effective way to improve the efficiency of platform software. In this paper, the resource space time energy consumption of intelligent energy is defined. The optimal ratio of known energy consumption to 0 and the resource needed for resource tasks and tasks is called map / task allocation and resource allocation. In this paper, the best resources than W test and wait for the relationship between the specific energy and resource; then, to verify that the map / mountain ice task division rationality by experiment; then the experimental data to verify the R2 algorithm can reduce the energy consumption of resources, improve the utilization rate of node resources, optimizing the energy efficiency of Map/Reduce task. The proposed resource ratio model and resource W method can be applied to existing map reduction system, which is of theoretical significance and practical value for improving and optimizing energy efficiency in cloud computing models.
Normative Harmonization of Multinational EEG Norms

Prior image deraining works mainly have two problems: (1) they do not generalize well to various datasets; (2) too much detail information is lost in the heavy rain area of the rain image. To overcome these two problems, we propose a new two-stage Adversarial Residual Refinement Network (ARRN) to deal with heavy rain images. Specifically, for the first problem, we first introduce a new implicit rain model to model a rain image as a composition of a background image and a residual image. Based on the proposed implicit model, we then propose the ARRN which consists of an image decomposition stage and an image refinement stage. For the second problem, a new attention Wasserstein Generative Adversarial Networks (WGAN) loss in the refinement stage is introduced to force the network to focus on refining heavily degraded areas. Comprehensive experiments demonstrate the effectiveness of the proposed approach.
Poster: Educational Effects of PBL Education in Collaboration with Company

Many higher education institutions in Japan are actively introducing PBL (Project Based Learning) programs to develop basic skills for students to enter the workforce. However, PBL programs have the problem that it is difficult for faculty members to manage the class and set the evaluation criteria for students. Furthermore, for many topics, students’ problem-solving conclusions are weak and may not provide sufficient educational effects. To solve these problems, in our attempt, we limited the project theme to those set by the company. Furthermore, in order to improve the problem solving level of the students, we aimed to design a product as a result of their problem solving. After the project, about 60% to 90% of the students felt that their competencies had improved in the 12 competencies of the “Fundamental Competencies for Working Persons” defined by the Ministry of Economy, Trade and Industry (METI). This paper describes the project to develop a product using “Original Sticky Notes” by fourth-year students of International College of Technology, Kanazawa and its educational effects.
Design of Museum Historical Heritage Management System Using Blockchain Digital Certificate and Hyperledger Composer

Computerized technology in the management system of digital museum objects is still limited in its application in centralized storage. This action provides vulnerability to manipulating original data from a collection. In this research, a historical object management system in Dapps was designed using a digital blockchain certificate based on Hyperledger Composer. Within the architecture, the blockchain-based web app or Dapps will manage the collection transparently, secure the access control, and store every transaction into its log. The Source of data used in the form of asset collection was taken from the Prabu Geusan Ulun Museum in Sumedang Regency. We evaluate the system by dividing the test into black boxes and white boxes. The functionality of the system is carried out in the black box using human interaction and measurements of security and performance are carried out in the white box using some testing tools.
[Performance evaluation and validation of automated digital image analysis in peripheral blood cells morphology examination].

Objective: To verify and evaluate the performance of automated digital image(DIA) for peripheral blood cell morphology examination. Methods: Three hundred and seventy-nine routine peripheral blood smears and 18 plasmodium positive peripheral blood smears were collected. Blood smears were made and stained by Wright -Giemsa method.White blood cell (WBC) differentiation of blood smears were pre-classified by DIA (DIA direct classification), re-classified (manually reviewed after DIA classification), and artificially classified under microscope. the inter-assay and intra-assay coefficients of variation (CV) of DIA were respectively calculated for repeatability verification. Taking the artificial microscopy as the gold standard, the sensitivity、specificity and accuracy of DIA were calculated. The DIA ability of peripheral blood blast cell morphological count, platelet (PLT) morphological count and morphological examination of plasmodium were also verified. Results: Except for eosinophils and basophils, the inter-assay and intra-assay CV of WBC classification by DIA in normal samples were < 10%. The CV of WBC classification in abnormal samples increased with the decrease of cell percentage. The sensitivity, specificity and accuracy of DIA pre-classification were 90.5%, 99.2%, 98.2%. Through pre-classification and re-classification by DIA,the results of the blood smears which triggered blast cell alarm had a good correlation with manual classification(r=0.812, 0.983, both P<0.01). The PLT morphological count by DIA had high correlation with hematology analyzer (r=0.946, P<0.01). The deviation absolute value of two methods of PLT count was < 15%, while in PLT aggregation or giant thrombocytosis samples,the deviation absolute value of PLT count by two methods was > 15%. After image acquisition by DIA, 17 plasmodium trophozoites were detected in 18 plasmodium-positive peripheral blood smears, and the images were clear. Conclusions: The DIA system has good repeatability, high sensitivity, specificity and accuracy in peripheral blood WBC classification. Its pre-classification and re-classification results have high correlation with the manual classification results.目的： 评价全自动数字图像分析（DIA）系统用于外周血细胞形态学分类计数的性能。 方法： 选取北京大学第一医院血常规检验外周血涂片379份，疟原虫感染外周血涂片18份，经瑞氏-姬姆萨染色，通过DIA系统完成白细胞（WBC）预分类（DIA直接分类）、再分类（DIA分类后人工审核），以及人工直接显微镜分类。分别计算DIA系统的批内及批间变异系数（CV）进行重复性验证；以人工分类结果为金标准，计算DIA系统检测的灵敏度、特异度、正确率。并对其外周血原始细胞形态学计数、血小板（PLT）形态学计数及疟原虫形态学检查能力进行验证。 结果： 除嗜酸粒细胞、嗜碱粒细胞外，DIA系统对正常样本WBC分类的CV均<10%，异常样本WBC分类的CV随所占百分比减低而增大；DIA系统进行WBC预分类的灵敏度、特异度和正确率分别为90.5%、99.2%和98.2%。触发原始细胞报警的血涂片经DIA系统预分类、再分类后，其结果均与人工分类结果具有相关性（r=0.812、0.983，均P<0.01）。DIA系统血小板形态学计数与血细胞分析仪计数结果具有相关性（r=0.946，P<0.01）；两种方法计数血小板偏差绝对值<15%；血小板聚集及巨大血小板增多样本偏差绝对值均>15%。经DIA系统采集图像的18份疟原虫阳性外周血涂片，其中17份检出疟原虫滋养体，且图像清晰。 结论： DIA系统进行外周血分类计数的重复性较好，灵敏度、特异度和正确率较高；其预分类、再分类结果与人工分类结果具有相关性。.
Flooding

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 58, Issue 12 p. 23686B-23686C Policy and Practice Flooding First published: 03 February 2022 https://doi.org/10.1111/j.1467-6346.2022.10378.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume58, Issue12February 2022Pages 23686B-23686C RelatedInformation