Reviewerly/exHarmony huggingface dataset:
Reflecting on siliceous rocks in central Australia: Using advanced remote sensing to map ancient “tool‐stone” resources

Abstract HyMap™ airborne hyperspectral imagery was used to discriminate and map hydrated silica mineralization in the Dalhousie Springs area of central Australia. A spectral feature fitting algorithm was used to match laboratory reference spectra with image pixel spectra, producing a scaled goodness‐of‐fit raster map of silicified “tool‐stone” sources in our study area. Subsequent fieldwork indicated that the algorithm mapped silcrete, a rock composed of hydrated silica, and incidentally, the most frequently utilized raw material for stone artifact manufacture in this area of the Australian arid zone. The soundness of our hydrated silica mineralization map is supported with field observations and spectroscopic analysis of collected silcrete samples. Independent siliceous rock mapping produced by the Commonwealth Scientific and Industry Research Organization offers additional corroboration of our results. Based on the success of our approach, we suggest that archaeologists working in Australia and in similar arid environments elsewhere have much to benefit in using advanced remote sensing products to map lithic resources, including time and cost‐saving advantages for field logistics, enriched assessments of land suitability for archaeological site types, and an improved understanding of resource distributions.
The Development of an Achievement Test for the Principles and Methods of Instruction Course

The aim of this study was to develop an Achievement Test in the Principles and Methods of Instruction Course. 14 objectives were developed in accordance with the aims and goals of the course as determined by the Council of Higher Education. The first form of the achievement test which consisted of 49 items was applied to 486 sophomore students who took the Principles and Methods of Instruction Course at the spring semester of 2016-2017 academic year. Test Analysis Program (TAP, version 14. 7. 4) was used to examine the item discrimination indices, item difficulty indices and reliability coefficient of the achievement test. After conducting the analysis, the difficulty indices of the remaining items ranged between ‘0.15-0.74’ with a mean difficulty index of 0.51. The item discrimination indices were between ‘0.21-0.57’ with a mean difficulty index of 0.37. Finally, the KR-20 value was found to be 0.78.
Extraction of Useful Features from Neural Network for Facial Expression Recognition

Facial expression intensity has been proposed to digitize the degree of facial expressions in order to retrieve impressive scenes from lifelog videos. However, correlation of facial features compared to each facial expression is not determined objectively. Therefore, we recognize facial expressions by using a neural network and calculate the contribution score of input toward output. We verify the score correctly by comparing the accuracy transitions depending on reducing useful and useless features, and process the score statistically. As a result, we extract useful facial features from the neural network.
OLAP Approach in Searching Manufacturing Industries in West Sumatera

Abstract The manufacturing industry is a business that uses machines, tools and workers in the process of converting raw materials into finished goods that can be sold. The manufacturing industry has an important role in the Indonesian economy. The industry contributed a large income to the country. In West Sumatra, there are many manufacturing industries that are growing and developing both on a medium scale and large scale which are spread throughout the cities and districts. So that it makes it difficult for the Department of Industry of West Sumatra Province to collect data on the existence of manufacturing industries. To solve this problem, approach of Online Analitycal Processing (OLAP) is used to search data in a hierarchical manner. OLAP is designed using fact tables and several dimension tables. OLAP will provide the number of industries as a measure . This research can help the people of West Sumatra to find out about the local manufacturing industry and what products the industry produces. In the end, local industrial products will be favored by many local people and increase the income of the province of West Sumatra.
Incorporation of a software engineering evaluation method in an educational software course in Turkey

The research literature identifies the limitations of pre-service teacher training in the evaluation and assessment of educational software for classroom use. This study investigated the enhancement of IT pre-service teacher training in educational software evaluation through the incorporation of software evaluation techniques from the software engineering discipline. Participants in this study were 25 final year pre-service IT teachers at Faculty of Education at a public university in Turkey. The pre-service teachers were introduced to the software engineering evaluation methods and an instructional educational software evaluation method. The results illustrated that the software engineering evaluation methods enhanced the technical evaluation skills of pre-service teachers and increased their confidence. Pre-service teachers reported that they considered themselves more professional after applying these methods. We believe this work highlighted a method to enhance the educational software evaluation skills of IT pre-service teachers through combining technical evaluation skills with traditional educational methods.
A Mobile Recommender System for Location-Aware Telemedical Diagnostics

As recommender systems have proven their effectiveness in providing personalised recommendations based on previous user preferences in e-commerce, this approach is to be transferred for use in medicine. In particular, the aim is to complement the diagnoses made by physicians in rural hospitals of developing countries, in remote areas or in situations of uncertainty by machine recommendations that draw on large bases of expert knowledge to reduce the risk to patients. To this end, a database of patients' medical history and a cluster model is maintained centrally. The model is constructed incrementally by a combination of collaborative and knowledge-based filtering, employing a weighted similarity distance specifically derived for medical knowledge. In the course of this process, the model permanently widens its base of knowledge on a medical area given. To give a recommendation, the model's cluster best matching the diagnostic pattern of a considered patient is sought. Fuzzy sets are employed to cope with possible confusion in decision making, which may occur when large data sets cause clusters to overlap. The degrees of membership to these fuzzy sets are expressed by the Mahalanobis distance, whose weights are derived from risk factors identified by experts. The therapy actually applied after the recommendation and its subsequently observed consequences are fed back for model updating. Readily available mobile digital accessories can be used for remote data entry and recommendation display as well as for communication with the central site. The approach is validated in the area of obstetrics and gynecology.
Detecting Possible Lone Wolf Terrorist’s Locations

Lone wolf terrorists' attacks on innocent civilians in public urban areas of major cities have been so frequent in recent years. They often choose strategic locations to maximize the damage by shooting during public events such as concerts or sports gatherings. Law enforcement agencies need to take preventative actions in advance by detecting such locations where terrorists might attack. However, it is difficult and costly to do so by visiting the target areas and analyze the environments. This paper presents a computational framework which is an alternative way to detect possible locations of lone wolf terrorists using computational algorithms and simulations. This framework is more effective, accurate, and economic than the physical visit and measurement. Law enforcement agencies can utilize the framework for public safety during gatherings of public events.
Navigating the CSR Discourse from a Developing Country’s Perspective: a Shift to Human Capital Development?

Several sources of today’s pressure on managers operating in developing and emerging economies (DEEs) are arguably more associated with social issues than profit-making concerns. Managers are thus faced with understanding and embedding solutions to societal challenges in their core business strategies in order to be sustainable. Consequently, solutions that go beyond the traditional focus of the CSR discourse on philanthropy in DEMs have become much more imperative as companies strive to use CSR to re-engineer their value chain. As lack of adequate human skills remains a major problem to firms and society, the existing challenges of human capital in many DEMs present businesses (both small and big firms) with the opportunity to use CSR to increase the knowledge, skills and abilities of both their workforce and the society in general. A firm that is able to invest in human capital development across the entire spectrum of its several stakeholders is more likely to achieve a higher competitive advantage and sustainable growth. In this chapter, we present case studies of two different approaches to using CSR as a tool for human capital development in Africa and given the success of the companies, it is recommended that firms operating in DEMs should place emphasis on developing and utilizing CSR policies and strategies for human capital development.
An associated probability analysis model based on multi-element fusion

In judicial adjudications, the chain of custody (or chain of evidence) is the core element of conviction. A complete chain of custody can provide a solid basis for judicial trials and sentencing. However, the evidence correlation analysis in the litigation process mainly depends on the judge's manual judgment, which often has the problems of poor interpretability and strong subjectivity. At present, the use of data mining technology to analyze the judicial data is of great significance and practical value in the construction of smart courts. This paper focuses on the problem of multi-factor modeling and reasoning about the trusted relationship between elements, and proposes an association probability analysis model based on multi-element fusion. Also, the process of obtaining the chain of custody of the judicial field is used to further illustrate the specific construction process of the model. Firstly, the factual decision chain is defined based on the knowledge of the judicial domain, and a multi-evidence association network is constructed, in which each evidence entity acts as a node in the network, and calculates the correlation probability between nodes through the association relationship between the evidence elements. Then, according to the event decision chain, the association constraint relationship between the evidences is established through the Bayesian network. Therefore, a multi-evidence association model is established, and all possible chain of custody combinations are obtained through genetic algorithm, so as to optimize the multi-evidence correlation model. Finally, the optimal chain of custody is obtained through the model. The validity of the model is verified by experiments in three types of cases on real data sets.
Deployment of Web Application in LAN based 3 Tier Architecture

In the Client-Server architecture, any of web and desktop application that can be deployed with the help of 3-tier application architecture. It is consist of a presentation layer, an application layer and a data layer. All there layers does play vital role in the 3-tier architecture for performing variety of operations including business logic, storage of data and handling request. In this paper, we presented deployment process of any web application in the local area network where database and application is located on the remote or web server. Other clients only access the application via specific IP address and valid credentials. The entire request transmitted through the client application and send to the web server. Web server does provide resulted data to the requested client via the web application. We identified several loopholes from the 3-tier architecture adoption perspective and we highlighted the web application deployment interoperability issue that deserves substantial further research and development. In this paper, we investigate several tools and techniques including web server, database server and front-end tools for the successful deployment of the web application in the LAN based 3-tier architecture.
Mechanical Condition Monitoring of On-load Tap Changer Based on Textural Features of Recurrence Plots of Vibration Signals

The mechanical condition of an on-load tap changer (OLTC) in suitable conditions is essential for the normal operation of power transformer. This paper describes a method for the mechanical condition monitoring of OLTC by using the improved local binary pattern (LBP) to extract the textural features of recurrence plot resulted from vibration signals in reconstructed phase space, since those signals are closely related to the mechanical switchover process from one tap to another. The dominant gray levels in the gray histogram are selected by ReliefF algorithm to describe the textural property of recurrence plots. The calculated results of vibration signals of some combined OLTC model under normal and typical mechanical faults have shown that the textural features of recurrence plot of vibration signals are changed clearly for the different mechanical condition of OLTC. The dominant gray levels in the gray histogram obtained by ReliefF algorithm is capable of describing the different mechanical conditions of OLTC. The results could provide important reference for the mechanical condition monitoring of OLTC.
Media Literacy Among College Students

The chapter discusses the impact of some of the selected the literacy of media literacy. It supports the students in developing the attitudes, values, and skills to solve the problems, decision making, and building their knowledge. The objective of the present study is to understand the practices on media literacy in college students in Sivagangai District. The chapter shows the respondent frequency of using the social media sites among the college students. Out the 112 respondents, 66 (58.93%) were female and 46 (41.07%) were male. Age wise distribution of respondents the table indicate 51.79% of respondents using social media of 17-20 category, 34.82% of respondents using social media of 21-25, 11.61% of the respondents in 26-30, 1.79% of respondents in above 31. As to the effects of using social media, location-wise distribution of the majority of respondents among 33 respondents, 35% village, 27.12% town, and 23.08% taluk are effects of waste of time. Among 32 respondents, 25% village, 32.20% town, and 23.08% taluk are effects of affecting academic performance.
Privacy Preserving Machine Learning with Limited Information Leakage

Machine learning is now playing important roles in daily lives, however, the privacy leakages are increasingly getting serious in the meantime. Current solutions to the privacy issues in machine learning, like differential privacy or homomorphic encryption either could only be applied to some specific scenarios or bring huge modification to the model construction, not to mention massive efficiency loss. In this paper, we consider addressing the privacy issue in machine learning from another perspective, without modification to models or severe efficiency loss. We proposed a straightforward privacy preserving machine learning scheme, training machine learning models directly over encrypted data. Ideally, this scheme could provide privacy protection to both training data and test data. We gave it a try by applying order preserving encryption (OPE) to the scheme. We discussed the possibility of using OPE to reveal the order information confidentially for model training. Several OPE algorithms were chosen to utilize the proposed method. Finally, comprehensive experiments were deployed on both synthetic and real datasets. The experiments on real datasets show that the learning performance of several well-known classifiers on before and after encryption changes slightly. The experiments on synthetic datasets show the classifier performance could be ranked according to fidelity and reliability.
Intraoperative surgical pathology consultation (frozen section) in resource-limited setting

Background: Intraoperative consultation aims at guiding decision during surgeries. Frozen section (FS) technique is a valuable tool used to rapidly prepare slides from tissues for microscopic interpretation. Over the past 100 years, FS diagnosis of surgically resected tumors and tissue has become a well-established practice in developed countries. On the other hand, developing countries only relatively recently got introduced to this technique. However, it remains unpopular due to a number of factors. This study strives to show that an alternative means in terms of reagents can easily be sought when the challenge of resource limitation is encountered. To the best of our knowledge, such a study has not been conducted in Nigeria. Methods: This was a prospective study over 12 weeks in which a comparison was made from surgical biopsy specimens received for intraoperative consultation. Using commercially available cryocompound, optimal cutting temperature (OCT) and readily available, less expensive, easy to handle alternative to embedding media: water and office glue. Staining was by conventional hematoxylin and eosin. Both groups were then viewed with the light microscope and findings were reported and compared. Results: Fifty-seven cases were studied, of which 24 were positive for tumor. Thirty cases were negative for tumor, and three cases had features consistent with metastatic tumor. Freezing time was 1–2 min for OCT and the glue alternative, while a third group was in frozen water for 2–3 min. The slides' quality was satisfactory for tissues processed in the OCT and glue; however, those processed in water had the worst outcome in terms of artifacts. Freeze and staining artifact were minimal in tissues processed using OCT and glue, whereas tissues processed using water was worst. Conclusion: Office glue is a readily obtainable alternative medium for FS and can provide satisfactorily comparable results to the conventional OCT in a resource-limited setting and is in the opinion of the authors, a good alternative.
Research on existing building space based on the view of sponge City——Taking the bauhinia garden in Tongzhou district of Beijing as an example

As the residential area with the largest proportion in the urban functional division, the matrix distribution range is the largest in the rainwater flow path, and it is also an important part of urban sponge implementation. The article explores the sponge transformation of the existing space of Bauhinia Garden, analyzes the existing problems within the community, gives adaptive advice on relevant issues and summarizes relevant experiences. In order to provide experience for the subsequent renovation of the sponge community, it is necessary to restore the water circulation function of the community.
Becoming Agile with the Scrum Framework

Scrum is an agile framework that helps organizations focus on incrementally delivering the highest business value in the shortest amount of time. This article explains the principles and values, framework, roles, and ceremonies that make up the Scrum ag..
Determining the Best Prediction Accuracy of Software Maintainability Models Using Auto-WEKA

Highly accurate prediction of software maintainability models is a significant requirement to achieve software quality assurance. Development an accurate prediction model may involve on trying several types of machine learning models with different configurations that include tuning parameters and selected features. However, this is a difficult and very time-consuming task to implement. In this paper, we report on the experience of using a new, rapid automated tool to identify the best prediction accuracy of a software maintainability model, namely Auto-WEKA, applied to sets of different models with various configurations. Auto-WEKA is applied to five datasets collected from real-world open-source software systems. The mean magnitude relative error (MMRE) value is used to evaluate the accuracy of predictive models, along with ZeroR model to compare selected model performance with the baseline. The results obtained from this study provide empirical evidence of the ability of Auto-WEKA to identify the best model to predict software maintainability. Auto-WEKA selected the following as the best prediction models: SMOreg in Eclipse JDT Core dataset, RandomSubSpace in Eclipse PDE UI dataset, KStar in Equinox Framework dataset, RandomForet in Lucene and Mylyn datasets. These selected models achieved a low MMRE value and improved performance of the accuracy prediction over the baseline. The proposed tool was found useful in identifying the best model in predicting software maintainability.
Contemplating on Swami Vivekananda’s Philosophy to Restore Consciousness in Retaining Human Dignity

In the prevailing situation, there is an alarmingly increasing rate of crime against humanity. There is an increase in crime against women and children, violence, homicides, terrorism, moral crisis etc. There is hardly a day when we glance through the newspaper where it does not mention about crime being committed by human being.  Children of our era are more vulnerable than the olden days because of the exposure to crime and violence and due to misuse of electronic gadget, social media, internet etc. There are moral deterioration and degradation that are prevailing in every sphere of life. Therefore, there is an urgent need to rebuild our nation starting from the grass root level and by means of educating our children. This paper is an attempt to bring consciousness and awareness of the importance of character education, spiritual and moral renewal in relevant with Swami Vivekananda’s philosophy in the present day situation.
عrbeng:- Android Live Voice and Text Chat Translator

Mobile applications become the basics of human’s daily life. People worldwide face difficulties in communication due to different languages and culture barriers. So it is important to enable people to communicate faster by bringing people together from across the globe. عrbeng is an Arabic/English Android instant messaging translator application to communicate worldwide that makes the world just got a lot smaller. With the feature of live translation capabilities, عrbeng allows exchanging text messages, voice and video chat as well as online and offline file transmission with anyone regardless of language barriers. عrbeng is an Interlingual based machine translation system. With Interlingua عrbeng becomes an unambiguous and international translation application that based on a client/server Socket programming. عrbeng uses an integrated language platforms that offers comprehensive online communication functions. عrbeng performs live translation with high translation performance, less time consuming and with more enhanced quality of translation.