Reviewerly/exHarmony huggingface dataset:
Identify Attitude and Perception of Farmers on Mobile Based Agriculture: Reuters’ Market Light (RML)

Farmers need dynamic information relating to agriculture and rural development. Therefore, to satisfy the need of information and knowledge, Reuters Market Light (RML) offers highly customized and localized agricultural related information service. RML provides information services via mobile phone-based Short Message Service (SMS) primarily aimed at farmers. The study was carried out in the Erode district of Tamil Nadu state. The results revealed that majority of the respondents had a strong positive attitude towards market and the respondents had a high level positive perception towards mobile phone with regard to farm information and technology transfer.
Aplikasi Pelayanan Pengaduan Masyarakat Berbasis Web pada Rumah Sakit Umum Daerah Langsa

Information technology is one of the things that has an important role in the era of globalization. Technological developments rapidly growth from year to year then its own facilities so as to provide convenience for its users. Information technology directly affects the lives of individuals and social especially at government agencies. Langsa General Hospital is one of the government agencies that has grown in the field of public health services, which is one of the public facilities are very important in the life of the community. It must be in balance with good services and facilities provided by the hospital. One of the facilities needed Area of Langsa General Hospital which is a container for the community can channel feedback in the form of a complaint with the objective as a means of communication between the hospital and the community which acts as a users of the service, with the existence of the container, the hospital can increase quality or improve any service provided to the community hospital.
Hate Speech in Nigeria and Its Implication for National Cohesion

This paper investigates the use of hate speech in Nigeria.Data for the study were collected through questionnaire distribution.The population for the study was randomly drawn from academic staff, non-academic staff and students of Abia State Polytechnic, Aba, Nigeria.Results from data analysis reveal that majority of the respondents were aware of the use of hate speech in Nigeria and its negative consequences.Over 70% of the respondents indicated that economic hardship, maginalisation and the desire to demean and outwit others are among the reasons people use hate speech.Below 60% of the respondents indicated that hate speech has no effect on national unity/cohesion while over 60% of them said it could result in violence and under-development.Based on the above, the paper concludes that hate speech is a threat to national cohesion and development and therefore should be managed effectively. Objectives of the studyThe objectives of the study include to i. ascertain perception of hate speech and level of awareness on what constitutes hate speech in Nigeria by Abia State Polytechnic, Aba staff and students; ii.determine why people use hate speech in Nigeria and the people"s perception of hate speech laws; and iii. to determine the effect of hate speech on national cohesion
Application of Multivariate Analysis in the Evaluation of Metals Distribution in Soil from Awwal Mining Site Kebbi, Nigeria

Multivariate statistical techniques such as principal component analysis (PCA), factor analysis (FA), and hierarchical cluster analysis (HCA) were utilized for the evaluation of metal distribution and variations in the soil at Awwal mining site. PCA was used to determine a reduced number of three principal components (PC) indicating about 82% of the total variation in the soil samples. The result of FA justifies the results of the PCA obtained. HCA classified the soil samples at the sites into two clusters, with cluster one having the higher metal levels, while cluster two had low metal levels but characterized with dominant toxic heavy metals (As and Pb). The results of the multivariate analysis showed that natural percentage abundance in soil and mineral composition of the mining ores were the main sources of the metals under study. Due to high metal levels in the soils, disposal and management of the mining waste/tailings and rehabilitation of the mining site after closure of mining should be done with care and caution to avoid leaching of the toxic metals to surface and underground water for the protection of health and safety of the neighboring community.&#x0D; Keywords: Soil, Metals, Mining, Multivariate analysis, Awwal.
EFEKTIVITAS PENGGUNAAN MEDIA POWER POINT DALAM UPAYA MENINGKATKAN PRESTASI BELAJAR MATEMATIKA SISWA KELAS III-A SD NEGERI 11 CAKRANEGARA

This research is a classroom action research consisting of two cycles where each cycle consists of four stages, namely the stages of planning, implementation, observation, and reflection. Each cycle consists of 3 meetings. This study aims to determine whether using power point media in PBM can improve Mathematics learning achievement in Class III-A Students at SD Negeri 11 Cakranegara Semester I Academic Year 2017/2018. The place of research in SD Negeri 11 Cakranegara, for 6 (six) months from July to December 2017 with research subjects of class III-A students totaling 27 people. Data collection techniques used by observation, evaluation, and documentation. While the data analysis technique is qualitative descriptive. In the study, the final success indicator for student learning achievement was set at 85% of students reaching 70. The indicator was reached in the second cycle, so the action research was carried out in 2 cycles where each cycle consisted of 3 (three) meetings. The results of the study showed that after the use of power point media in PBM, the student learning achievement increased by 8.7% with an average value in the first cycle of 68.15 and in the second cycle it increased to 76.85. While for learning completeness there was an increase of 29.63% from the first cycle of 62.96% and in the second cycle it increased to 92.59%. Thus, the use of Power point media in PBM can effectively improve student achievement, especially students of class III-A on Mathematics subjects at SD Negeri 11 Cakranegara.
Dynamically Identifying Deep Multimodal Features for Image Privacy Prediction

With millions of images shared online, privacy concerns are on the rise. In this paper, we propose an approach to image privacy prediction by dynamically identifying powerful features corresponding to objects, scene context, and image tags derived from Convolutional Neural Networks for each test image. Specifically, our approach identifies the set of most “competent” features on the fly, according to each test image whose privacy has to be predicted. Experimental results on thousands of Flickr images show that our approach predicts the sensitive (or private) content more accurately than the models trained on each individual feature set (object, scene, and tags alone) or their combination.
Simulasi Analisis Bukti Digital Pada Layanan Cloud Computing Menggunakan Metode NIST 800-86

Ease and support for cloud-based data storage It has supported an increase in the number of cloud services. The increasing number of uses for cloud services also increases the number of digital-based criminal actions related to the addition of facilities to cloud services. The cloud service feature designed to store data to support the smooth running of business processes can be misused by criminal assistance to store crime data. Accurate digital evidence is one way to prove a digital crime, which can then be used as supporting evidence in the trial. This study discusses the analysis of digital evidence from a cloud service. The analysis process using the NIST 800-86 method is carried out on digital evidence from 5 previously prepared scenarios related to the use of cloud service features that use being misused. Data acquisition techniques use the method of direct acquisition and physical imaging to obtain digital evidence. The experimental results showed that after scenario 1 and scenario 3, information on the file name and directory of the paths downloaded by client 1 and client 2 were obtained with information on the IP address, mac address, user name, password and time stamp. After scenario 2, digital evidence has been obtained that contains information on the name and location of the folder on the cloud server. After scenario 4, information on the name of the file and the shared folder is successfully obtained, equipped with client information that has the right to access the files and folders. After scenario 5, information about the file name and directory of the file path is successfully obtained.
Cautious Rule-Based Collective Inference

Collective inference is a popular approach for solving tasks as knowledge graph completion within the statistical relational learning field. There are many existing solutions for this task, however, each of them is subjected to some limitation, either by restriction to only some learning settings, lacking interpretability of the model or theoretical test error bounds. We propose an approach based on cautious inference process which uses first-order rules and provides PAC-style bounds.
RANCANG BANGUN PROTOTYPE INTELLIGENT BOOTH KAKI LIMA (OTOMATISASI BUKA/TUTUP)

A food and beverage booth owner who sells alongside the road, has difficulty when opening and closing the booth also when the rain comes suddenly - suddenly the owner has difficulty protecting electronic equipment from rainwater which can cause a short circuit, because the process is still done manually. To overcome this problem, a system with a microcontroller circuit using Arduino Uno and a DC motor can be made that can open and close the booth with a push button command that can facilitate the process which is still done manually and with a rain sensor circuit that can detect rain as an order to close the front of the booth to protect electronic equipment from rainwater. This system is implemented in an intelligent booth prototype to test whether the algorithm made can overcome the problems experienced by the booth owner.
PENGEMBANGAN MEDIA PEMBELAJARAN IPS MENGGUNAKAN SPARKOL VIDEOSCRIBE TEMA KEGIATAN EKONOMI SISWA KELAS VII DI MTS MA’ARIF NU 14 SIDOREJO

The purpose of this research is to produce IPS learning media using sparkol videoscribe which is valid, practical and effective to meet students' need. IPS learning media will then be tested feasibility by experts. This research uses the research procedure and development model of ADDIE. This development model consists of 5 development stages namely Analisys, Design, Development, Implementation, and Evaluation. The results showed that IPS learning media using sparkol videoscribe is feasible to use in learning. This is demonstrated by the results of the expert test on the display design of sparkol videoscribe learning media included into the criteria "Very Eligible" with a percentage of 86%, expert test results on the presentation of sparkol videoscribe learning media materials included into the criteria "Very Eligible" with a percentage of 83% and test result with small group that is 10 student to know student response to learning media of IPS using sparkol videoscribe included in criterion "Very Eligible" with percentage equal to 96%. IPS learning media using sparkol videoscribe can be used as a reference material in the subjects of social studies especially on the subject of economic activity.Keywords: IPS Learning Media, Sparkol Videoscribe
Support Vector Data Description with Fractional Order Kernel

Support Vector Data Description (SVDD) as a kernel-based method constructs a minimum hypersphere so as to enclose all the data of the target class in the kernel mapping space. In this paper, it is found that the kernel matrix G of SVDD can always have the Singular Value Decomposition (SVD) and the corresponding kernel mapping space can be made up of a set of base vectors generated by SVD. In order to make the kernel mapping more flexible, we induce a parameter λ into the set of base vectors and thus propose a novel SVDD with fractional order kernel (named λ-SVDD). In doing so, we can expand the solution space for the optimized dual problem of the SVDD. The experimental results on both synthetic data set and some real data sets show that the proposed method can bring more accurate description for all the tested target cases than the conventional SVDD.
Evaluating Passwords User Behavior and the Psychology of Password Management

Regardless of how complex an association's security framework is, it stays helpless because of the human factor. Content based passwords are usually utilized for verification in figuring condition. Despite the fact that passwords are considered as the underlying line of assurance for users, they stay simple to compromise. To improve the security of frameworks, different password synthesis policies are embraced. These strategies guarantee that users are made to pick solid passwords that assistance anticipate online ruptures and information spills. Be that as it may, it likewise make passwords hard to retain and review, diminishing the general ease of use. In this examination we researched the ease of use of password strategies and users' view of password security. We additionally reviewed and examined the patterns practiced by users while producing passwords (Crantor, Hong and Reiter, 2016).&#x0D; Users are not as mindful of security prerequisites and practices as they think. By far most of users' passwords are breakable within days or shorter. Strikingly, we found that the utilization of numbers and uppercase letters is common among clients. Numbers are generally utilized toward the end of the passwords and uppercase letters are for the most part utilized toward the start of passwords. The presence of such patterns makes it simpler for attackers to create progressively compelling dictionaries. In light of the examination in this investigation, we make suggestions to the IT office to improve the password policy (Shen, 2016).
Conceptual model for pair design and pair testing based on the characteristics of pair programming

Pair programming is a method that is widespread in the field of agile software development (ASD) and is acknowledged as state of the art of programming. This article initially addresses the question of what constitutes the key attributes of pair programming. Therefore, we analysed the extent to which these attributes can be applied to the development-related areas of human-centred design (HCD) and the quality assurance (QA) of software. The results of this analyses lead to the presentation and consideration of a new conceptual model for the application of the attributes of pair programming in the context of pair design (HCD) and/or pair testing (QA). The discussion shows that a transferability and application is appropriate and that both HCD and QA benefit, particularly in terms of the product quality and product throughput time.
A Factored Approach to Deterministic Contingent Multi-Agent Planning

Collaborative Multi-Agent Planning (MAP) under uncertainty with partial observability is a notoriously difficult problem. Such MAP problems are often modeled as DecPOMDPs, or its qualitative variant, QDec-POMDP, which is essentially a MAP version of contingent planning. The QDecPOMDP model was introduced with the hope that its simpler, non-probabilistic structure will allow for better scalability. Indeed, at least with deterministic actions, the recent IMAP algorithm scales much better than comparable DecPOMDP algorithms (Bazinin and Shani 2018). In this work we suggest a new approach to solving Deterministic QDecPOMDPs based on problem factoring. First, we find a solution to a MAP problem where the results of any observation is available to all agents. This is essentially a single-agent planning problem for the entire team. Then, we project the solution tree into sub-trees, one per agent, and let each agent transform its projected tree into a legal local tree. If all agents succeed, we combine the trees into a valid joint-plan. Otherwise, we continue to explore the space of team solutions. This approach is sound, complete, and as our empirical evaluation demonstrates, scales much better than the IMAP algorithm.
Efficiently Compressible Density Operators via Entropy Maximization

We address the problem of efficiently and effectively compress density operators (DOs), by providing an efficient procedure for learning the most likely DO, given a chosen set of partial information. We explore, in the context of quantum information theory, the generalisation of the maximum entropy estimator for DOs, when the direct dependencies between the subsystems are provided. As a preliminary analysis, we restrict the problem to tripartite systems when two marginals are known. When the marginals are compatible with the existence of a quantum Markov chain (QMC) we show that there exists a recovery procedure for the maximum entropy estimator, and moreover, that for these states many well-known classical results follow. Furthermore, we notice that, contrary to the classical case, two marginals, compatible with some tripartite state, might not be compatible with a QMC. Finally, we provide a new characterisation of quantum conditional independence in light of maximum entropy updating. At this level, all the Hilbert spaces are considered finite dimensional.
Robust Facial Landmark Localization Based on Two-Stage Cascaded Pose Regression

In this paper, we propose a two-stage cascaded pose regression for facial landmark localization under occlusion. In the first stage, a global cascaded pose regression with robust initialization is performed to get localization results for the original face and its mirror image. The localization difference between the original image and the mirror image is used to determine whether the localization of each landmark is reliable, while unreliable localization with a large difference can be adjusted. In the second stage, the global results are divided into four parts, which are further refined by local regressions. Finally, the four refined local results are integrated and adjusted to get the final output.
Conditions on Features for Temporal Difference-Like Methods to Converge

The convergence of many reinforcement learning (RL) algorithms with linear function approximation has been investigated extensively but most proofs assume that these methods converge to a unique solution. In this paper, we provide a complete characterization of non-uniqueness issues for a large class of reinforcement learning algorithms, simultaneously unifying many counter-examples to convergence in a theoretical framework. We achieve this by proving a new condition on features that can determine whether the convergence assumptions are valid or non-uniqueness holds. We consider a general class of RL methods, which we call natural algorithms, whose solutions are characterized as the fixed point of a projected Bellman equation. Our main result proves that natural algorithms converge to the correct solution if and only if all the value functions in the approximation space satisfy a certain shape. This implies that natural algorithms are, in general, inherently prone to converge to the wrong solution for most feature choices even if the value function can be represented exactly. Given our results, we show that state aggregation-based features are a safe choice for natural algorithms and also provide a condition for finding convergent algorithms under other feature constructions.
Workshop Sistem Informasi Geografis (SIG): Peningkatan Kapasitas Petugas Surveilans Puskesmas di Wilayah Kabupaten Gunung Kidul dalam Pembuatan Peta Sebaran Penyakit

One of surveillance quality is the data should be usefull for prevention and disease control as wellas detecting pattern or trend. This only can be done if the data have analyzed. Map is one of dataanalyzing which is important to draw disease distribution. In this training, Primarly health caresurveillance officer are expected to know and able to make simple map with GeospatialInformation System (GIS) software. This activity is software using training using free software epiinfo version 7.2 by CDC where previously the participants have given brief material about GIS inthe field of health. Observation was conduct to see if there are increasing of skill for makingdigital map. The participants also given a modul to help them re-learning after completion of theactivity. Based on the observation during training, participant looked enthusiastic and active inasking questions. For observation results, it showed increasing 100% of skill for creating mapswhereareas berfore workshop there are no participant who experienced for making digital maps.Over all, this training is effective to provide refreshing and knowledge in the field of informationtechnology that supports health data processing and analyzing in Puskesmas.
Special Session: 2018 Low-Power Image Recognition Challenge and Beyond

The IEEE Low-Power Image Recognition Challenge (LPIRC) is an annual competition started in 2015. The competition identifies the best technologies that can detect objects in images efficiently (short execution time and low energy consumption). This paper summarizes LPIRC in year 2018 by describing the winners' solutions. The paper also discusses the future of low-power computer vision.
A Mobile 3D Serious Game that Operates like a Pure-Tone Air Conduction Hearing Test

In this paper, we present a Mobile 3D serious game that operates like a Pure-Tone Air Conduction Hearing Test and uses the principles of Conditioned Play Audiometry (CPA) [1].The end users are preschool children and this fact leads us to choose the touch screen, as an input device, considering that this response mode should be more appropriate for such ages [2].The application is designed to be used outside a sound booth.At the design phase, we adopted techniques that audiologists use during the hearing test with children that are older than 2,5 years old, to overcome difficulties like boredom, denial to participate, and cases where the child is unable to wear headphones (CPA) [2].The aim of the application is to offer the audiologists or speech-language pathologists a preparatory tool for training children in responding to a pure tone audiometry test.The training helps them to overcome difficulties related to attention or response mode and converts the medical test into a cheerful 3D game for children [3].The user's performance during the test is recorded, giving the ability to assess readiness for the actual audiometric evaluation that takes place in the clinic.The application also allows the order of the produced tones to be chosen by the audiologist or speech-language pathologist, providing the possibility of adjusting the test to any individual.
Health and Nutrition Issues Affecting Academic Involvement of Adult Learners in Literacy Programmes of Kogi State, Nigeria

OBJECTIVE: This study investigated health and nutrition issues affecting academic involvement of Adult learners in literacy programme in Kogi State, Nigeria. The specific purpose of the study was: to ascertain the extent health and nutrition affect academic involvement of adult learners in literacy programmes in Kogi State Nigeria.&#x0D; &#x0D; MATERIALS &amp;amp; METHOD: The design for the study was a descriptive survey design. A structured questionnaire was used to collect data which wereanalysed using mean scores and standard deviation while t-test statistic was used to test the hypothesis that guided the study.&#x0D; &#x0D; RESULTS: Results of the analysis showed among others health and nutrition issues such as chronic illness, poor nutrition and hunger affect academic involvement of adult learners. The results also showed that unhealthy adult learners do not feel happy in class during lessons or learning activities. &#x0D; &#x0D; CONCLUSION: Based on the finding, it was concluded that health and nutrition have some level of relationship with adult learners&amp;rsquo; academic involvement to a high extent.