Reviewerly/exHarmony huggingface dataset:
Model Reduction of Shallow CNN Model for Reliable Deployment of Information Extraction from Medical Reports

Shallow Convolution Neural Network (CNN) is a time-tested tool for the information extraction from cancer pathology reports. Shallow CNN performs competitively on this task to other deep learning models including BERT, which holds the state-of-the-art for many NLP tasks. The main insight behind this eccentric phenomenon is that the information extraction from cancer pathology reports require only a small number of domain-specific text segments to perform the task, thus making the most of the texts and contexts excessive for the task. Shallow CNN model is well-suited to identify these key short text segments from the labeled training set; however, the identified text segments remain obscure to humans. In this study, we fill this gap by developing a model reduction tool to make a reliable connection between CNN filters and relevant text segments by discarding the spurious connections. We reduce the complexity of shallow CNN representation by approximating it with a linear transformation of n-gram presence representation with a non-negativity and sparsity prior on the transformation weights to obtain an interpretable model. Our approach bridge the gap between the conventionally perceived trade-off boundary between accuracy on the one side and explainability on the other by model reduction.
A Priori in the Philosophy of Science

The article is devoted to the analysis of research approaches and attitudes to the study of the a priori in the philosophy of science. In the first part, I outline the basic premises of this study: (a) scientific knowledge as the highest manifestation of rationality; (b) the normative nature of scientific knowledge. In the second part, I turn to the difference in the subject of philosophical research on the history of science – the history of science as a “history of facts” vs the history of science as a history of scientific thought. The third part discusses the main theoretical and technical difficulty associated with changing the subject of research – the possibility of a transition from historical fact to “scientific thought at the time of its birth” (in Helene Metzger terminology). The forth part is devoted to the analysis of the “model approach” (Arianna Betti, Hein van den Berg) in philosophy as a possible way to overcome this difficulty and includes both theoretical and technical aspects of the future direction of research. In conclusion, consequences are drawn about the possibility of using the “model approach” for reconstruction a priori in the history of science as “constitutive elements of scientific knowledge” (David Stump).
Evolution of the WebDSL runtime: reliability engineering of the WebDSL web programming language

Web applications are ideal for implementing information systems; they can organize and persist the data in a database, do not require installation on client machines, and can be instantly updated everywhere. However, web programming is complex due to its heterogeneous nature, causing web frameworks to suffer from insufficient or leaky abstraction, weak static consistency checking, and security features that are not enforced. We developed the WebDSL web programming language, which supports direct expression of intent, strong static consistency checking, linguistic abstractions for web programming concerns, and automatically enforces security features for web applications. We have used WebDSL for over 10 years to create information systems for academic workflows with thousands of users. Based on our experiences with these applications, we improved the WebDSL compiler and runtime to increase robustness, performance, and security of applications. In this experience report, we reflect on the lessons learned and improvements made to the language runtime.
Improvement and Practice of Comprehension Adaptive Robot Programming Workshop for Elementary and Junior High School Students

We have been holding robot programming workshops for children using NXT since 2008 to foster creative thinking and raise interest in engineering. Successful experiences at these workshops can be a motivator for learning programming continuously. Although devising and trying ideas in a workshop are essential, it is hard for participants to secure enough time to conceive and examine their ideas because of time limitations. Especially in our workshop, assembling NXT robots needed a fair amount of time. For this reason, we are developing ways to shorten the robot assembly time as much as possible. We are also improving the contents of the workshop so that children will enjoy programming. This paper describes the contents of our current NXT workshop, along with analyses of survey results.
THE IMPLEMENTATION OF IMAGINATIVE TECHNIQUE IN IMPROVING STUDENTS’ WRITING ABILITY ON DESCRIPTIVE TEXT AT THE SECOND GRADE OF MTs. MUHAMMADIYAH SIDOMULYO

The aim of these research was to get the data how Imaginative Technique Method can improve students’ writing ability on descriptive text at second grade MTs. Muhammadiyah Sidomulyo with target achieved 75% from number of students at second grade average 70. The research is class room research (CAR). Subject of this research is students’ second grade. The instruments of this research are test and observation sheet. The technique of analysis got by formula total students’ completeness divided total students’ multiplied one hundred percent. The result of this research point out Imaginative Technique method can improve students’ writing ability on descriptive text at second grade. This research carried out in two cycles where each cycle consists from two meeting. Cycle I grade average of students get 69.2 and cycle II grade average of student get 75.4. Keywords: Writing Ability, Descriptive Text, Imaginative Technique.
Modeling Data Reuse in Deep Neural Networks by Taking Data-Types into Cognizance

In recent years, researchers have focused on reducing the model size and number of computations (measured as multiply-accumulate or MAC operations) of DNNs. The energy consumption of a DNN depends on both the number of MAC operations and the energy efficiency of each MAC operation. The former can be estimated at design time; however, the latter depends on the intricate reuse patterns and underlying hardware architecture. Hence, estimating it at design time is challenging. This work shows that the conventional approach to estimate the reuse, viz. arithmetic intensity, does not always correctly estimate the degree of reuse in DNNs since it gives equal importance to all the types. We propose a novel model, termed data type aware weighted arithmetic intensity ($DI$), which accounts for the unequal importance of different types in DNNs. We evaluate our model on 25 state-of-the-art DNNs on two GPUs. We show that our model accurately models data-reuse for all possible reuse patterns for different types of convolution and different types of layers. We show that our model is a better indicator of the energy efficiency of DNNs. We also show its generality using the central limit theorem.
Study and Evaluation of Novel Chaotic System Applied to Image Encryption with Security and Statistical Analyses

There is no doubt that chaotic sequences attracted much attention in recent decades due to its distinctive properties. These distinct properties give the availability for the chaotic sequences to be applied in different fields. One of the fields that exploit the chaos features is the encryption field, in which chaotic sequences can be used to encrypt texts or images. The randomization attitude of the chaotic sequences can be affected by the initial condition, or by the code length. As these parameters optimized, the performance of the chaotic sequences enhanced and improved from many points of view. This paper presents study, analysis and evaluation for different chaotic sequences from the security viewpoint. The study and analysis include the standard NIST statistical test suite for random and pseudo random number generators for cryptography applications. The presented sequences are the traditional and enhanced version of chaotic sequences based on the logistic map. The new contribution of the paper is to perform the statistical tests over a range of the code lengths, and initial conditions in order to study the effect of each parameter, then optimize its values. Moreover, the proposed sequences are evaluated and applied to image encryption to verify its robustness.
La pronuncia italiana per i giovani apprendenti sloveni: che cosa ne dicono i dizionari?

The article deals with the representation of Italian pronunciation in five contemporary dictionaries for young Slovenian learners. As the use of a dictionary not only stimulates the development of lexical competence, but can also serve as a useful means for pronunciation learning, the article investigates five categories representing phonetic-phonological features in a dictionary: introduction to phonetics/phonology (e.g. a pronunciation guide), phonetic transcription, phonemes, consonant length and accent. The representation of these features in a dictionary for young learners should be clear and coherent, and in some cases a dictionary (especially a dictionary intended for the youngest users) should also featureaudio pronunciations. The five dictionaries analysed are fragmentary with regard to the pronunciation: only one dictionary includes audio recordings (although the relation between the spelling and the pronunciation remains unclear, as it does not include a pronunciation guide); two dictionaries include deficient phonological transcriptions and incomplete pronunciation guides; one dictionary contains only the Italian alphabet with corresponding phonemes, while another dictionary is without any elements that could familiarize a Slovenian learner with Italian pronunciation.
Availability of education as a determinant for public assessment of the state of national system of education

This article analyzes the data of international sociological project &amp;ndash; &amp;ldquo;European Social Research&amp;rdquo;. Availability of education is viewed as a determinant for public assessment of the state of national system of education. One of the potential indicators of availability of education is a subjective assessment of the presence of equal chances for receiving the desired level of education among residents of the country. Special attention is paid to comparison of assessments given by the Russian and residents of other European countries. The author underlines the importance of carrying out surveys on this topic, as a feedback channel, which allows determining public assessment of the effectiveness of reforms conducted in educational sphere. It is noted that European countries greatly differ depending on the public assessment of the national system of education. The Russians rate the state of national system of education lower than other countries participating in the project. It is concluded that the Russian system of education does not fully meet the demands and requests of the population. The author determines that comparing to the majority of European countries, availability of education in the Russian Federation receives relatively low ratings of the Russians. Since in in participating countries, availability of education is a determinant of public assessment of the state of national system of education, it is claimed that the higher is the subjective assessment, the more positive is the assessment of the state of national system of education overall. In Russia, the established correlation on the European scale is relatively strong, which testifies to the fact that availability of education comes to the forefront among the problems of national system of education.
Optimizing Program Size Using Multi-result Supercompilation

Supercompilation is a powerful program transformation technique with numerous interesting applications. Existing methods of supercompilation, however, are often very unpredictable with respect to the size of the resulting programs. We consider an approach for controlling result size, based on a combination of multi-result supercompilation and a specific generalization strategy, which avoids code duplication. The current early experiments with this method show promising results - we can keep the size of the result small, while still performing powerful optimizations.
TGK-Planner: An Efficient Topology Guided Kinodynamic Planner for Autonomous Quadrotors

In this paper, we propose a lightweight yet effective Topology Guided Kinodynamic planner (TGK-Planner) for quadrotor aggressive flights with limited onboard computing resources. The proposed system follows the traditional hierarchical planning workflow, with novel designs to improve the robustness and efficiency in both the pathfinding and trajectory optimization sub-modules. Firstly, we propose the topology guided graph, which roughly captures the topological structure of the environment and guides the state sampling of a sampling-based kinodynamic planner. In this way, we significantly improve the efficiency of finding a safe and dynamically feasible trajectory. Then, we refine the smoothness and continuity of the trajectory in an optimization framework, which incorporates the homotopy constraint to guarantee the safety of the trajectory. The optimization program is formulated as a sequence of quadratic programmings (QPs) and can be iteratively solved in a few milliseconds. Finally, the proposed system is integrated into a fully autonomous quadrotor and validated in various simulated and real-world scenarios. Benchmark comparisons show that our method outperforms state-of-the-art methods with regard to efficiency and trajectory quality. Moreover, we will release our code as an open-source package.
A Vision-based Infrared Decoy Tracking Algorithm for Air Conditioner Spot Cooling

Air conditioner has become one of the most common electrical appliances in every household. With the increase in their demand, the challenge to reduce the energy usage of air conditioner has become a subject of intense study in recent years. Spot cooling is one of the methods that can reduce the energy wastage. In this method, a control algorithm is implemented to actively track the location of users and direct the air conditioner's air flow to these targeted areas. This can make the cooling more efficient since the air conditioner does not need to cool down the entire room. By selectively directing the air flow, the users can still achieve the same cooling comfort. This paper proposed a technique of spot cooling for air conditioner using infrared (IR) camera and a decoy. The decoy is based on IR light emitting diodes arranged in a specific pattern. The IR camera captures the video of the room to locate the position of the decoy. Image processing techniques include thresholding and template matching are used for the decoy detection. Once the decoy is detected, the movement of the decoy is tracked by using a Kalman filter. To test the performance of the proposed method, a prototype system was implemented on a Raspberry Pi board and the accuracy of detection was evaluated. Experimental results showed that the system is able to detect the position of decoy with 98% accuracy in both day and night-time conditions.
Usage of Mobile Application in Assisting Chemical Experiments

ChemEx is a mobile application that is created to assist students in performing chemical experiments. Students who study Bachelor of Electronic Engineering majoring in Nanotechnology use chemical experiment to synthesise nanoparticles. Through observation, they lack of confidence during the nanoparticles synthesis because they were not involved in any chemistry activities after foundation. To overcome this issue, a mobile application called ChemEx is created using Android Studio. In ChemEx, the usage of apparatuses and instruments, lab safety, the concept molarity and dilution, as well as the data of chemicals are introduced. Pre and post-test are used to evaluate the effectiveness of ChemEx in helping the students. Besides this, feedback form is used to evaluate the satisfaction of students after using ChemEx. The pre and post-test results show that the students have improved their understanding in apparatuses, safety, molarity and dilution. In the meantime, feedbacks show students are satisfied using ChemEx.
Graphic organizer instruction in teaching reading comprehension to low-proficient English as a Second Language (ESL) Students / Umaiyal A/P Krishnan and Hui Min Low

This study aimed to investigate the effects of graphic organizer (GO) instruction to teach readingcomprehension to low-proficient ESL Form 2 students in Malaysia. The study utilized a quasiexperimental design to examine reading comprehension performance of two groups of students,with and without the provision of GO instruction. There were 15 students in each group whowere administered with a pre-test and a post-test. The results from this study supported thepositive effects of GO instruction in improving reading comprehension performance. Studentswho had received GO instruction were found to be more able to identify the keywords in thepassages and answer the questions using own words. Besides that, they also performed better inanswering average- to high-level reading comprehension questions. The findings offer newempirical evidence to support the schema theory in explaining the processes in readingcomprehension. Given the visual representations in the GO instruction, the textual informationfrom the reading passages can be more readily mapped with the students’ existing mentalschemas. This process was found to be useful to aid low-proficient ESL students in performingreading comprehension tasks.
Deep Learning-based Human Detection for UAVs with Optical and Infrared Cameras: System and Experiments

In this paper, we present our deep learning-based human detection system that uses optical (RGB) and long-wave infrared (LWIR) cameras to detect, track, localize, and re-identify humans from UAVs flying at high altitude. In each spectrum, a customized RetinaNet network with ResNet backbone provides human detections which are subsequently fused to minimize the overall false detection rate. We show that by optimizing the bounding box anchors and augmenting the image resolution the number of missed detections from high altitudes can be decreased by over 20 percent. Our proposed network is compared to different RetinaNet and YOLO variants, and to a classical optical-infrared human detection framework that uses hand-crafted features. Furthermore, along with the publication of this paper, we release a collection of annotated optical-infrared datasets recorded with different UAVs during search-and-rescue field tests and the source code of the implemented annotation tool.
Debunking the Fabricated Myths Around 5G

Recently there is a growing concern regarding potential health hazards linked with 5G deployment and radio frequency emitted by these stations. It becomes fundamentally important to scientifically address these concerns. In this paper, the health risks incorporated with 5G are discussed critically in the light of scientific work and debunk these tittle-tattles where required. We confute scientifically the &amp;ldquo;5G appeal&amp;rdquo;, discuss effects of 5G on health, its implications on privacy, pandemics, ecosystem and role of world health organization in fighting these narratives. Finally, we provide future direction to negate these false claims linked with 5G.
SELEKSI FITUR YANG BERPENGARUH MENGGUNAKAN NILAI MEAN PADA KLASIFIKASI FRAGMEN METAGENOME

Pekuwali (2018) has conducted research into the classification of metagenome fragments using spaced k-mers. Optimize the arrangement of features using Genetic Algorithms. Pekuwali (2018) concluded that the best arrangement of features or called chromosomes is 111111110001 with a fitness value of 85.42. Chromosome 111111110001 produces 336 features of extracting DNA fragments. This research aims to find out which features influence classi ﬁ cation and the resulting accuracy. The method used is the Mean value. The mean value method was chosen because the data distribution is normal or close to normal. This study concludes that the influential features in the classification are features 22 to 27 with an accuracy of 78.83% and features 38 to 43 with an accuracy of 79.67%.&#x0D; &#x0D;
Features of the development of the time perspective of graduates of pedagogical university

The article analyzes the phenomenon of time perspective of personality development.The article considers the specifics of the time perspective of students of graduate courses of pedagogical and technical universities, substantiates the idea of the need to form a balanced time perspective of a future specialist as a condition for his professional development.
Nostalgia, Co-creation, and Practice of Design

The study proposes that the research design integrating co-creation, interviews, and visual analysis can effectively operationalize a difficult concept of gastronomic nostalgia surrounding ethnic food artifacts. I employed an example of Mumbai’s street foods to examine consumption, production, and distribution practices and compared the cities of Mumbai, India, and Phoenix, United States. Rigorous qualitative analysis of the data gathered from fourteen Indian immigrants in Phoenix suggested that consumption declined when street foods’ core identity shifted in Phoenix. I discovered that the differences in having street foods in sit-down settings or the lack of a public street food culture might never be bridged in Phoenix. However, specific production and distribution strategies rooted in nostalgic memories from Mumbai may boost consumption.
Implementasi Pengujian Black Box menggunakan Teknik Equivalents Partitions pada Aplikasi Pendaftaran Commuter Line Berbasis Web

Computer Program that contains defectives (mistakes) can cause a disadvantage that can affect to stakeholders. The disadvantaged can take the shape of money related, time, and others. So sometime recently the program is executed it has to be testing. Testing on an application proposed to check the program is running legitimately or not. In testing, this computer program will utilize Black Box Testing. Black Box Testing Strategy had a few strategies, Equivalence Partitions, Boundary Value Analysis, Sample Testing, etc. From many testing methods, we will use the Equivalence Partitions. Equivalence Partitions method is a test based on data input for each form where the application system of performance data information each menu input would be tested and grouped accord to the function whether valid or invalid. Testing is doing on the Application form that will be in the content from the data that suitable with personal data. The final results show there is still much lack when valid data will be inputted causes data stored in the database to be incompatible with the expected data. The results of this test would be used to improve the application at performance data for the future. In the end, the application could handle normal and abnormal data with a percentage of success 91,67%.