Reviewerly/exHarmony huggingface dataset:
Efektivitas Penurunan Chemichal Oxygen Demand (COD) dan pH Limbah Cair Industri Tahu dengan Tumbuhan Melati Air melalui Sistem Sub-Surface Flow Wetland

Some of tofu industries in Jambi City are household industries, where the wastewater from processing unit was disposed of into the environment without treatment. This study aims to analyze the effect of detention time and the effectiveness of decreasing COD concentration and pH neutralization on wastewater of tofu industry using a sub surface flow - wetlands (SSF-wetland) system combined with a filtration system. The plant selected in this study was water jasmine (Echinodorus palaefolius). Variables of waste water detention time in the reactor are 5, 7, 9, 11, 13 and 15 days. Decreasing of COD concentration and increasing of pH were analyzed by comparing influent and effluent from wastewater samples, also the effect of detention time on the effectiveness of parameter reducing on each system. The water quality standard refers to the regulation of the Minister of Environment and Forestry Number 68 Year 2016. The results showed excellent performance from a combination of the two systems where an initial pH with range of 3 increase to pH 6.5-7. The efficiency of reducing COD concentration reached 47-94% during the 15-day detention time with concentration value 125 mg / l, close to the standard value 100 mg / l. The residence time has more significant effect on the reduction of COD in the SSF-Wetland system than the filtration system. Whereas in pH parameters, the residence time does not have a significant effect on both systems.
Robust Speaker Recognition in Noisy Conditions by Means of Online Training with Noise Profiles

Automated speaker recognition attains impressive reliability when tested under controlled laboratory acoustic conditions. However, the environmental noise that inevitably exits in many real-world speech samples causes considerable degradation of recognition accuracy due to the so-called
Use of Information and Communication Technology by Small and Medium Enterprises in Ogun State, Nigeria

Small and medium enterprises have emerged as promising opportunities to eliminate and reduce unemployment globally. Increasing levels of technological advancement has revolutionized the dynamics of the business terrain. However, SMEs in developing countries are yet to fully explore the benefits of Information and Communications Technology.&#x0D; Survey data was collected from 75 SME ICT users and non-users in Abeokuta and Otta through a structured questionnaire using stratified random sampling technique.&#x0D; Results of regression analysis revealed that demographic variable (Staff Strength) significantly influences use of ICT among SMEs while SME service delivery had no influence on ICT use. Also, analysis of variance on the categories of SMEs was not a determinant factor on the use of ICT.&#x0D; The outcome of this study has implications for owners/ managers of SMEs, stakeholders, government and academic researchers in developing countries as it can provide patterns to help bridge the existing digital divide especially among Nigerian SMEs.
DIGITAL TRANSFORMATION AT HIGH EDUCATION: ARE PROFESSORS OF THE SOUTH EUROPEAN AND SOUTH AMERICAN COUNTRIES PREPARED FOR THAT?

The higher education plays a fundamental role in the society transformation in all of its dimensions, namely teaching, educational management, vision and creation of business and professions.The combination of new challenges in higher education with the increase of mobile technologies (one of the digital transformation pillars) leads to an intensification in teaching opportunities and demands of new teaching methods development.Due to this, several concepts from the e_learning, to u_learning appeared.Therefore, it is critical to understand whether users (students and professors) are receptive and aware to adapt to this new paradigm before deciding to implement teaching-learning methods based on mobile technology.In this context, the aim of the study presented is to investigate if higher education professors, in the technology area, in South Europe and South America countries, are using Mobile Learning with gamification and augmented reality apps and how they can be used to promote student's engagement inside and outside of the classroom, in order to prepare the students for a new reality -the digital transformation.
Publisher Correction: A 204-subject multimodal neuroimaging dataset to study language processing

A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper.
Pengaruh Model Pembelajaran Picture And Picture Berbantuan Media Permainan Roda Keberuntungan Terhadap Aktivitas Dan Hasil Belajar Pada Konsep Daur Hidup Hewan Siswa Kelas IV

ABSTRACTInfluence Of Learning Model Picture And Picture Assisted Media Respective Wheel Games To Activity And Learning Results On The Concept Of Animal Life Cycle Students Of Class IV This research is motivated by low learning activities that affect student learning outcomes and ultimately student learning outcomes do not reach KKM. This study aims to determine how much influence the model of learning picture and picture assisted media game wheel of luck to the activity and student learning outcomes on science subjects class IV SDN Sendangmulyo 02 Semarang. The form of this research is quantitative research with Quasi Experimental Design design with Non-equivalent Control Group Design design. Sampling technique used is Nonprobability. The population of this study is all students of class IV SDN Sendangmulyo 02 Semarang. Data collection techniques in this study using documentation, observation, tests and interviews. Data analysis techniques consist of normality test, homogeneity test, completeness test and t test. Data analysis using t test obtained result 4,452 bigger than t table that is 1,990. The result of the research shows that the use of picture and picture learning model with the media of wheel of lucky game has an effect on the activity and the result of learning of fourth grade students of SDN Sendangmulyo 02 Semarang on the concept of animal life cycle. Keywords: Picture and Picture Model, Lucky Wheel, Activity and Learning Outcomes. ABSTRAKPenelitian ini dilatarbelakangi oleh rendahnya aktivitas belajar yang mempengaruhi hasil belajar siswa dan akhirnya hasil belajar siswa tidak mencapai KKM. Penelitian ini bertujuan untuk mengetahui seberapa besar pengaruh model pembelajaran picture and picture berbantuan media permainan roda keberuntungan terhadap aktivitas dan hasil belajar siswa pada mata pelajaran IPA kelas IV SDN Sendangmulyo 02 Semarang. Bentuk penelitian ini adalah penelitian kuantitatif dengan desain Quasi Experimental Design dengan bentuk desain Non-equivalent Control Group Design. Teknik sampling yang digunakan yaitu Nonprobability. Populasi penelitian ini adalah seluruh siswa kelas IV SDN Sendangmulyo 02 Semarang. Teknik pengumpulan data dalam penelitian ini menggunakan dokumentasi, observasi, tes dan wawancara. Teknik analisis data terdiri dari uji normalitas, uji homogenitas, uji ketuntasan belajar dan uji t. Analisis data menggunakan uji t diperoleh hasil 4,452 lebih besar dari t tabel yaitu 1,990. Hasil penelitian menunjukkan bahwa penggunaan model pembelajaran picture and picture berbantuan media permainan roda keberuntungan berpengaruh terhadap aktivitas dan hasil belajar siswa kelas IV SDN Sendangmulyo 02 Semarang pada konsep daur hidup hewan.Kata kunci: Model Picture and Picture, Roda keberuntungan, Aktivitas dan Hasil Belajar.
Modified AES Cipher Round and Key Schedule

In this paper, Advanced Encryption Standard was modified to address the lowdiffusion rate at the early rounds by adding additional primitive operationssuch as exclusive OR and modulo arithmetic in the cipher round. Furthermore,byte substitution and round constant addition were appended to the keyschedule algorithm. The modified AES was tested against the standard AESby means of avalanche effect and frequency test to measure the diffusion andconfusion characteristics respectively. The results of the avalanche effectevaluation show that there was an average increase in diffusion of 61.98% inround 1, 14.79% in round 2 and 13.87% in round 3. Consequently, the resultsof the frequency test demonstrated an improvement in the randomness of theciphertext since the average difference between the number of ones to zeros isreduced from 11.6 to 6.4 along with better-computed p-values. The resultsclearly show that the modified AES has improved diffusion and confusionproperties and the ciphertext can still be successfully decrypted and recoverback the original plaintext.
Sensor terminal ”Portable” for intelligent navigation of personal mobility robots in informationally structured environment

This study proposes two kinds of systems for building intelligent service robots, namely a sensor terminal named ”Portable” for making various personal mobility robots intelligent and a distributed sensor system for constructing an informationally structured environment consisting of laser range finders and active beacons. The sensor terminal Portable is equipped with a laser range finder and a gyro. Two types of personal mobility robot, namely standing type and wheelchair type, are made intelligent by installing Portable to provide navigation functions such as localization, obstacle detection, and path planning. The sensor system is mainly used to acquire position information about the personal mobility robots, obstacles, and moving objects (e.g., people); this information is used by Portable for navigation. The obtained information is transmitted to the robot, allowing it to operate in a complicated environment. The ability of the proposed system to navigate personal mobility robots is verified in two real environments.
Special Issue on “Side Channel Attacks”

Cryptosystems are widely used in a growing number of embedded applications, such as smart cards, smart phones, Internet of Things (IoT) devices, and so on [...]
3D Motion Reconstruction From 2D Motion Data Using Multimodal Conditional Deep Belief Network

In this paper, we propose a deep generative model named multimodal conditional deep belief network (MCDBN) for cross-modal learning of 3D motion data and their non-injective 2D projections on the image plane. This model has a three-sectional structure, which learns conditional probability distribution of 3D motion data given 2D projections. Two distinct conditional deep belief networks (CDBNs), encode the real-valued spatiotemporal patterns of 2D and 3D motion time series captured from the subjects' movements into compact representations. The third part includes a multimodal restricted Boltzmann machine which in the training process, learns the relationship between the compact representations of data modalities by variation information criteria. As a result, conditioned on a 2D motion data obtained from a video, MCDBN can regenerate 3D motion data in the generation phase. We introduce Pearson correlation coefficient of the ground truth and the regenerated the motion signals as a new evaluation metric in motion reconstruction problems. The model is trained with human motion capture data and the results show that the real and the regenerated signals are highly correlated, which means the model can reproduce the dynamical patterns of the motion accurately.
Performance Evaluation of Completed Local Ternary Pattern (CLTP) for Face Image Recognition

Feature extraction is the most important step that affects the recognition accuracy of face recognition.One of these features are the texture descriptors that are playing an important role as local features descriptor in many of the face recognition systems.Recently, many types of texture descriptors had been proposed and used for face recognition task.The Completed Local Ternary Pattern (CLTP) is one of the texture descriptors that has been proposed for texture image classification and had been tested for different image classification tasks.It proposed to overcome the Local Binary Pattern (LBP) drawbacks where the CLTP is more robust to noise as well as shown a good discriminative property than others.In this paper, a comprehensive study on the performance of the CLTP for face recognition task has been done.The aim of this study is to investigate and evaluate the CLTP performance using eight different face datasets and compared with the previous texture descriptors.In the experimental results, the CLTP had been shown good recognition rates and outperformed the other texture descriptors for this task.
Who is interacting with researchers on Twitter? A survey in the field of Information Science

The social web appears a promising environment to study the societal impact of research, and, although platforms such as Twitter appear to be popular to share scientific content, little is known about the outreach of scientific communication on social media. By surveying a sample of Twitter users who are also followers of communication and Library and Information Science (LIS) researchers, this article aims to understand who is interacting with researchers on Twitter and if the activity of following allows to get closer to science and research. A survey was sent to all followers of 9 active researchers, and 53 responses were collected and analyzed. According to the results, followers are mostly professionals (49%) although the higher education sector (36%) accounts for an important part of the audience. Twitter allows respondents to keep updated, feel as a part of the scientific community and gain more visibility, whereas interactions appear as an important though secondary facet of these users’ activity on Twitter. Finally, participants consider that they do not have influence on the scientific process, maybe because the flow of information on Twitter occurs mostly as retweeting in an unidirectional fashion. More research is needed in order to understand better interactions and engagement on social media before they can be quantified and measured as indicators of societal impact of research.
Sharing is Caring: Dynamic Mechanism for Shared Resource Ownership

Shared ownership of computing resources has long been in the practice; here, multiple agents pool their resources together to achieve high utility and low wastefulness. Sharing incentive, non-wastefulness and strategyproofness are three of the most desirable properties for a feasible system. However, Freeman et al. [2018] showed the fact that these three properties are incompatible in a dynamic setting and thus, a trade off must be maintained. In this work, we propose a dynamic allocation mechanism which fairly allocates the shared resources among the agents, and partially satisfies the above desiderata. Our mechanism outperforms the mechanisms proposed by Freeman et al. [2018] in the single resource case in terms of social welfare both in synthetic and real-life data. We also show that in the single resource case, our mechanism allocates the resources in a way that creates a market equilibrium and thus naturally satisfies several additional properties.
Computing Long Sequences of Consecutive Fibonacci Integers with TensorFlow

Fibonacci numbers appear in numerous engineering and computing applications including population growth models, software engineering, task management, and data structure analysis. This mandates a computationally efficient way for generating a long sequence of successive Fibonacci integers. With the advent of GPU computing and the associated specialized tools, this task is greatly facilitated by harnessing the potential of parallel computing. This work presents two alternative parallel Fibonacci generators implemented in TensorFlow, one based on the well-known recurrence equation generating the Fibonacci sequence and one expressed on inherent linear algebraic properties of Fibonacci numbers. Additionally, the question of using lookup tables in conjunction with spline interpolation or direct computation within a parallel context for the computation of the powers of known quantities is explored. Although both parallel generators outperform the baseline serial implementation in terms of wallclock time and FLOPS, there is no clear winner between them as the results rely on the number of integers generated. Additionally, replacing computations with a lookup table degrades performance, which can be attributed to the frequent access to the shared memory.
CWave: Theory and Practice of a Fast Single-source Any-angle Path Planning Algorithm

Summary Path planning on a two-dimensional grid is a well-studied problem in robotics. It usually involves searching for a shortest path between two vertices on a grid given that some of the grid cells are impassable (occupied by obstacles). Single-source path planning finds shortest paths from a given source vertex to all other vertices of the grid. Singles-source path planning enhances robot autonomy by calculating multiple possible paths for various navigation scenarios when the destination state is unknown. A high-performance algorithm for single-source any-angle path planning on a grid called CWave is proposed here. Any-angle attribute implies that the algorithm calculates paths which can include line segments at any angle, as opposed to standard A* that runs on an 8-connected graph, which permits turns with 45° increments only. The key idea of CWave is to abandon the graph model and operate directly on the grid geometry using discrete geometric primitives (instead of individual vertices) to represent the wave front. In its most basic form ( CWaveInt ), CWave requires only integer arithmetics. CWaveInt , however, can accumulate the distance error at turning points. A modified version of CWave ( CWaveFpuSrc ) with minimal usage of floating-point calculations is also developed to eliminate any accumulative errors, which is proven mathematically and experimentally on several maps. The performance of the algorithm on most of the tested maps is demonstrated to be significantly faster than that of Theta*, Lazy Theta*, Field A*, ANYA, Block A*, and A* adapted for single-source planning (on maps with lower number of isolated obstacles, CWaveFpuSrc is 2−3 times faster than its fastest tested alternative Block A*). An N -threaded implementation ( CWaveN ) of CWave is presented and tested to demonstrate an improved performance (multithreaded implementation is 1.5−3 times faster than single-threaded CWave). The paper discusses foundations and experimental validation of CWave, and presents future work to address the limitations of the current implementations and obtain further performance enhancements.
Improving Population Diversity Through Gene Methylation Simulation

During the runtime of many evolutionary algorithms, the diversity of the population starts out high and then rapidly diminishes as the algorithm converges. The diversity will directly influence the algorithm’s ability to perform effective exploration of the problem space. In most cases if exploration is required in the latter stages of the algorithm, there may be insufficient diversity to allow for this. This paper proposes an algorithm that will better maintain diversity throughout the runtime of the algorithm which will in turn allow for better exploration during the latter portion of the algorithm’s run.
Water Management through Canal Blocking to Improving Rice Productivity in Langsat Permai Village, Bunga Raya District, Siak Regency, Riau Province

The low productivity of paddy in Langsat Permai Village, Bunga Raya District, Siak Regency, one of them is causes the unavailability of sufficient water for crop cultivation, so it is necessary to do water management by making canal blocking to be used on rice plants in the area. This is done to meet the water needs of rice plants during the dry season. Therefore, assistance is provided through water management in Langsat Permai Village, Bunga Raya District, Siak Regency. Mentoring strategies are carried out by discussing directly with farmer groups about the impact of making canal blocking. Through this activity, the availability of water for rice plants during the dry season is fulfilled. Production of 1 Ha of rice before the blocking canal produced 4-5 tons/harvest to 6-7.8 tons/harvest after the canal blocking.
Introduction to Cloudsim

Cloud computing is a subscription-based service where networked storage space and other computer resources can be obtained.Due to its high availability, easy accessibility, scalability and adaptability, cloud computing is highly desirable in the rapidly growing world of computer technology.Because of this high demand, the Cloud Computing and Distributed Systems (CLOUDS) Laboratory built the CloudSim framework, which became very popular open source cloud simulator among the researchers and students.CloudSim is new simulation framework which allows uninterrupted modeling and simulation of cloud computing infrastructure.It helped open up the possibility of evaluating the hypothesis in a controlled environment where experimental results can be reproduced easily.This basic goal of this paper is helping the researchers to understand CloudSim's most important functions and its practical usage, and to take insights on hands-on example of creating a simulated cloud environment.
Policy-based Deployment in a Hybrid and Multicloud Environment

Hybrid and multi-cloud become prominent infrastructure strategy of enterprise. However, the complexity of such infrastructure is a considerable challenge. It is common to see that multi-cloud infrastructure is divided into several smaller units to facilitate the management. The division criteria are geolocation, cost, security, etc. Therefore, how to manage application deployment in such partitioned environment is an intriguing topic of multi-cloud management. We propose a policy-based deployment in multi-cloud infrastructure, which contains policy evaluation and TOSCA standard based orchestration. The system architecture is introduced and a case study with two empirical scenarios is discussed. The results indicate that the proposed policy-based deployment is useful in finding suitable resource and improving deployment efficiency.
Signature Recognition Based on Discrete Wavelet Transform

Personal identification is an actively developing area of research. Human signature is a vital biometric attribute which can be used to authenticate human identity. There are many approaches to recognize signature with a lot of researches. The aim of this research is to introduce an efficient approach for signature recognition. This approach starts with the process the acquired signatures and stores these signatures in the database to be ready for verification. The collection of signature data based on collecting samples of 10 people and 10 signatures for each person through traditional ink stamp method. These signatures are digitized to be ready for processing. Many steps are applied to the acquired images to perform the pre-processing stage. The proposed approach based on discrete wavelet transforms to extract significant features from each signature image. Pre-processing is applied at the beginning of this approach to avoid any unwanted noise. This approach consists of many steps: Data acquisition, pre-processing, signature registration, and feature extraction. High recognition rate results (100%) are obtained through applying this approach.