bluuebunny/crossref_metadata_2025 huggingface dataset:
Teaching Through the Uncanny: Red Candle Games’ Devotion
Authors:   University of Manchester, Scott Gregory Adam , Alexander Katherine
Published: August 2022

On 19th February 2019, horror game Devotion (Huan yuan 還願) by Red Candle Games (赤燭遊戲) was launched on the popular PC platform Steam. One week later it was pulled from digital distribution after a satirical message was discovered in one of its graphical assets. In this essay we analyse how the immersive narrative deploys traditional Chinese religious imagery, supernatural literary themes, and sometimes gruesome experiences to explore issues of family, guilt, and redemption. We seek to initiate a conversation about Devotion as a significant cultural text that gives players a unique experience of the rich symbolism of Chinese religious culture. Additionally, we highlight how digital game media such as this can productively be used in teaching.
The Revolution will not be Gamified: Video Game Activism and Playful Resistance across the Sinosphere
Authors:   RMIT University, Davies Hugh
Published: August 2022

Videogames are political spaces. For more than twenty years, videogames have been co-opted by activists globally to organise protests in amorphous, organic, and rhizomatic assemblages. Presenting instances of videogame-based activism in global Chinese language contexts, this paper connects cases of videogame activism in Hong Kong’s anti-extradition movement of 2019, to earlier videogame protest repertoires and playful resistance in Mainland China and Taiwan. Through an extensive literature review approach, this paper surveys cross-disciplinary discussions on Sinophonic game-based activism in three ways: by contextualising the antagonisms that drove the protesters to action; by exploring the strategies and tactics employed in each; and by drawing them into a lineage of Sinophone activism that has spread predominantly through Massively Multiplayer Online Games. With much of the discourse surrounding videogame activism occurring in US and European contexts, this paper recalibrates existing discourses of videogame activism to consider their most prominent instances: those that occur in Sinophone contexts.
Towards Sinophone Game Studies
Authors:   University of Cambridge, Inwood Heather
Published: August 2022

The editor’s introduction discusses progress so far and possible future directions in the emerging field of Sinophone game studies, taken to mean the study of games – in this case, specifically video, computer, digital, or electronic games – in a Sinophone context, including mainland China and the broader Chinese-speaking world. Recent industry figures and news stories related to video gaming in the People’s Republic of China (PRC) paint a picture of continued expansion and growing global ambitions, albeit tempered by the regular introduction of fresh government regulations surrounding game content, gaming permissions for under-18s, game streaming, and game license approval. The eleven contributions to this issue, however, reflect the diversity of possible approaches to the study of Sinophone gaming, focusing not just on the often-conflicting politics and economics of the PRC games industry, but also exploring Taiwan’s flourishing indie game scene, political uses of games in Hong Kong, game-based representations of online and offline realities, issues in the transnational adaptation and localisation of games, and more besides. Sinophone game studies is a highly fruitful area of academic research that is intrinsically inter- and cross-disciplinary in nature and well placed to respond to some of the most pressing issues of our time, whether they be international conflict, ecological crisis, identity politics, minority rights, or even the development of disparate virtual worlds into a cross-platform ‘metaverse’ in which many of us may one day live our lives.
DEVELOPMENT OF A GRAPHICAL USER INTERFACE TO SUPPORT THE SEMI-AUTOMATIC SEMANTIC SEGMENTATION OF UAS-IMAGES
Authors: Masiero A. , Cortesi I. , Tucci G.
Published: August 2022

Abstract. The development of remote sensing techniques dramatically improved the human knowledge of natural phenomena and the real time monitoring and interpretation of the events happening in the environment. The recently developed terrestrial, aerial and satellite remote sensors caused the availability of huge amount of data. The large size of such data is leading the research community to the search for efficient methods for real time information extraction, and, more in general, understanding the collected data. Nowadays, this is typically done by means of artificial intelligence-based methods, and, more specifically, usually by means of machine learning tools. Focusing on semantic segmentation, which is clearly related to a proper interpretation of the acquired remote sensing data, supervised machine learning is often used: it is based on the availability of a set of ground truth labeled data, which are used in order to properly train a machine learning classifier. Despite the latter, after a proper training phase, usually allows to obtain quite effective segmentation results, the ground truth labeled data production is usually a very laborious and time consuming task, performed by a human operator. Motivated by the latter consideration, this work aims at introducing a graphical interface developed in order to support semi-automatic semantic segmentation of images acquired by a UAS. Certain of the potentialities of the proposed graphical are shown in the specific case of plastic litter detection in multi-spectral images.
SPECTRAL: AWESOME SPECTRAL INDICES DEPLOYED VIA THE GOOGLE EARTH ENGINE JAVASCRIPT API
Authors: Montero D. , Aybar C. , Mahecha M. D. , Wieneke S.
Published: August 2022

Abstract. Spectral Indices derived from Remote Sensing (RS) data are widely used for characterizing Earth System dynamics. The increasing amount of spectral indices led to the creation of spectral indices catalogues, such as the Awesome Spectral Indices (ASI) ecosystem. Google Earth Engine (GEE) is a cloud-based geospatial processing service with an Application Programming Interface (API) that is accessible through JavaScript (Code Editor) and Python. Tools for computing indices, including raster operations, normalized differences, and expression evaluation methods have been developed in the API. However, users still have to hard-code spectral indices for the JavaScript library since there are no implementations that link catalogues of spectral indices to the Code Editor. Here we present spectral, a module that links the Awesome Spectral Indices (ASI) catalogue to GEE for querying and computing spectral indices inside the Code Editor. The module allows accessing and computing spectral indices from the catalogue for multiple remote sensing products in GEE. All indices can be queried by using a key-value model and computed by using a single method. The module demonstrates that spectral indices can be easily computed inside the Code Editor. Image and Image Collection objects can be used for the calculation of all spectral indices in the catalogue if the specific dataset counts with the required bands. We anticipate that spectral will be used by most GEE users for Earth System research. Analyses conducted by the community will be sped up by avoiding hard-coding and RS investigations will be boosted.
GEOSPATIAL DATA EXCHANGE USING BINARY DATA SERIALIZATION APPROACHES
Authors: Mooney P. , Minghini M.
Published: August 2022

Abstract. In this paper we investigate the benefits of binary data serialization as a means of storing and sharing large amounts of geospatial data in an interoperable way. De-facto text-based exchange encodings typically exposed by modern Application Programming Interfaces (APIs), including eXtensible Markup Language (XML) and JavaScript Object Notation (JSON), are generally inefficient for an increasingly higher number of applications due to their inflated volumes of data, low speed and the high computational cost for parsing and processing. In this work we consider comparisons of JSON/Geospatial JSON (GeoJSON) and two popular binary data encodings (Protocol Buffers and Apache Avro) for storing and sharing geospatial data. Using a number of experiments, we illustrate the advantages and disadvantages of both approaches for common workflows that make use of geospatial data encodings such as GeoPackage and GeoJSON. The paper contributes a number of practical recommendations around the potential for binary data serialization for interoperable (geospatial) data storage and sharing in the future.
EARTH OBSERVATION DATACUBES MULTI-VISUALIZATION TOOLBOX
Authors: Muller C. , Lestrade A. , Marty M. , Sadiku A. , Neijt J. , Voumard Y. , Gobron S.
Published: August 2022

Abstract. Too much information often kills information. With the increasing number of satellites and their ever-increasing performance, new tools must be made available to deal with this data onslaught. We noticed that a number of computer graphics tools were largely under-exploited to help scientists better interpret and find relevant information in large datasets. A modern approach to run large processes efficiently is the use of GPUs, but nowadays the emphasis is often put on the parallel processing of geospatial datasets rather than focusing on their visualization. Considering geospatial data using GPU resources for intermediate computation and visualization is this paper main contribution. Given the increasing interest in interacting directly with this data using Web pages or Notebooks, this article presents tools allowing a program to run on the GPU and display, using the WebGL API, these matrices of data, also called datacubes. This paper shows a range of models applicable to datacubes deployed in the context of terrestrial observation. The end goal is to display on a PC very large (i.e. 10243) datacubes rendered on the fly and in real time. Furthermore, results show our models can process large amounts of data and render them in real time. All these innovative rendering models are assembled in a toolbox dedicated to datacube visualization. Finally, we give several examples of how to use this toolbox which enables the retrieval of raw data from an external server to real-time rendering on a local Web page.
MULTI-SENSOR FEEDER: AUTOMATED AND EASY-TO-USE BIRDS MONITORING TOOL FOR CITIZENS
Authors: Niers T. , Stenkamp J. , Jakuschona N. , Bartoschek T.
Published: August 2022

Abstract. Nowadays, more species are threatened with extinction than ever before in the human era. Especially breeding birds are considered endangered. At the same time, it is difficult to obtain sufficient data not only to raise awareness for this situation, but also to gain a better understanding and to develop potential countermeasures. We show how a citizen science based biodiversity monitoring for birds, using an automated and easy-to-use multi-sensor feeder, can look like. In doing so, we compare different configuration options concerning technical components, casing, as well as software to be used and present our suggested prototype: A smart bird feeder including an environmental sensor, a microphone, as well as a balance and a camera in a wooden case. It identifies the type of visiting birds using AI and publishes the recognized species, including all further collected data, on an open access website. The station can be reproduced by anyone at an affordable price in a Do-It-Yourself format, making citizens a key contributor to biodiversity monitoring.
USING SENTINEL 2 IMAGES TO QUANTIFY AGRICULTURAL ENCROACHMENT IN BURKINA FASO’S PROTECTED LIVESTOCK RESERVES
Authors: Orenstein A. , Diop P. S.
Published: August 2022

Abstract. Tensions around land use between agricultural and livestock-herding communities remain contentious in Burkina Faso. As such, land use patterns and interactions between grazing land and cropland are important to the dynamics of these tensions and conflicts. This study uses Sentinel 2 satellite imagery to evaluate the expansion and encroachment of cropland in two protected livestock reserves in Southern Burkina Faso: the Niassa and Sondré-Est Pastoral Zones. This study specifically looks at cropland expansion within the borders of the protected reserves. The method used, the 3 Period Timescan, creates a temporal NDVI profile across three key periods of the growing season (the start/planting period, middle and end/harvest). Cropland is easily identified against other land use types due to its unique NDVI profile, which shows a significant increase between the planting and pre-harvest period and stands out significantly against the smoother profile of natural vegetation. The NDVI profile is then made into a Red-Green-Blue composite image which allows for easy identification between cultivated and non-cultivated areas. This study found a significant expansion of cropland in both protected zones between the period of 2016 and 2021.
CROWDSOURCED ACOUSTIC OPEN DATA ANALYSIS WITH FOSS4G TOOLS
Authors: Roelandt N. , Aumond P. , Moisan L.
Published: August 2022

Abstract. NoiseCapture is an Android application developed by the Gustave Eiffel University and the French National Centre for Scientific Research as central element of a participatory approach to environmental noise mapping. The application is open-source, and all its data are available freely. This study presents the results of the first exploratory analysis of 3 years of data collection through the lens of sound sources. This analysis is only based on the tags given by the users and not on the sound spectrum of the measurement, which will be studied at a later stage. The first results are encouraging, we were able to observe well known temporal sound source dynamics like road sounds temporal dynamic related to commuting or bird songs in the dataset. We also found correlations between wind and rain tags and their measurements by the the national meteorological service. The context of the study, the Free and Open Source Software tools and techniques used and literate programming benefits are presented.
DIGITAL TWIN 3D PLATFORM FOR COLLABORATIVE REPRESENTATION AND EDITING OF IFC DOCUMENTS APPLIED TO THE BIM METHODOLOGY
Authors: Silva J. P. , Pereira J. P. , Santos J.
Published: August 2022

Abstract. Currently , the Architecture, Engineering, Construction (AEC) sector lacks tools for digitization, being forced to resort to proprietary software and closed file formats with complex and highly expensive licensing models. Thus, new opportunities arise for the creation of tools, resources and knowledge that promote the renewal and impetus of the entire sector. Most of the sector’s R&D activities are not only directed to the development of digital tools, but also to develop and provide the methodological bases of standardization, organization, and management of information necessary for the implementation of the BIM and Digital Twin methodology in Portugal, applied to the construction and asset management of buildings and infrastructures. In the present work, the described solution is a cross-platform web application that has all base requirements of a standard BIM platform, plus georeferencing of IFC documents using orthophoto maps and free access to base cartography available globally. All components of the solution were developed using open source technologies and universal free access. The contributions of this work will also serve to improve the set of tools and solutions available to the community. The developed platform will be available openly to all companies that want to engage in the BIM community and ought to actively participate in and foster the development, improvement, and promotion of this platform within the AEC sector.
SCALING-UP DEEP LEARNING PREDICTIONS OF HYDROGRAPHY FROM IFSAR DATA IN ALASKA
Authors: Stanislawski L. V. , Shavers E. J. , Duffy A. J. , Thiem P. , Jaroenchai N. , Wang S. , Jiang Z. , Kronenfeld B. J. , Buttenfield B. P.
Published: August 2022

Abstract. The United States National Hydrography Dataset (NHD) is a database of vector features representing the surface water features for the country. The NHD was originally compiled from hydrographic content on U.S. Geological Survey topographic maps but is being updated with higher quality feature representations through flow-routing techniques that derive hydrography from high-resolution elevation data. However, deriving hydrography through flow-routing methods is a complex process that needs to be tailored to different geographic conditions, which can lead to varying solutions. To address this problem, this paper evaluates automated deep learning and its transferability to extract hydrography from interferometric synthetic aperture radar (IfSAR) elevation data spanning a range of geographic conditions in Alaska.
AUTOMATIC ASSESSMENT OF LAKE STATUS USING AN OPEN SOURCE APPROACH: LAKE LUGANO’S CASE STUDY
Authors: Strigaro D. , Cannata M. , Capelli C. , Lepori F.
Published: August 2022

Abstract. Climate change and human activities are increasingly threatening water resources. In particular sub-alpine lakes are fundamental not only for tourism or other economical activities, but also as a source of water. In this context, there is a strong need to monitor such resources to understand, study and react to known and unknown impacts, so that appropriate mitigation actions can be taken. Unfortunately, although monitoring data already exist for many of these lakes, the information is archived in different formats and servers undermining the full exploitation of data and preventing a more efficient data management. The aim of this work is to improve this situation by implementing a system that integrates and standardizes data coming from different sources. In addition, the system integrates web based tools that estimate lake state indicators using open source software and standard. Thanks to this system, it will be possible to exploit the data potential more fully. This paper focuses on the achievements reached by the research carried out on Lake Lugano in the context of the project SIMILE after two years of work.
ANALYSIS OF LOCAL AND REMOTE MAPPERS’ OPEN GEOGRAPHIC DATA CONTRIBUTION TO OIL SPILL DISASTER RESPONSE IN NIGER DELTA REGION, NIGERIA
Authors: Sunday V. N. , Ndukwu R. I. , Brovelli M. A.
Published: August 2022

Abstract. This paper provides a comparative analysis of the contributions of Local Volunteer Mappers (LVM, resident in Nigeria) and Remote Volunteer Mappers (RVM, not resident in Nigeria) in an organized crowd-sourced disaster response mapping using OpenStreetMap. The study sampled two Local Government Areas in Ogoni land - a major oil spill disaster vulnerable area of the Niger Delta Region. The study engaged mappers using the Humanitarian OpenStreetMap (HOT) tasking manager for Tai (Project task 6358, with 596 grids –RVM) and Gokana LGA (Project task 6359, with 706 grids –LVM), respectively in a Mapathon battle challenge. The result shows that project task 6358 was completely mapped and validated in six months, while project task 6359 took 28 months. Each of the 56 RVM spent an average of 20.77 minutes/grid, generating a total of 16,416 edits of 13,552 building footprints and 858km of roads. The 173 LVM spent an average of 41.1 minutes/grid to generate 18,367 edits of 14,983 building foot prints and 521km of roads. The study also showed that a total of 103 RVM joined but only 56 completely mapped the task within six months whereas 173 LVM joined and completely mapped the task within 28 months. Demographic characteristics of both categories of mappers showed that 52% of the RVM were advanced mappers whereas 72% of the LVM were beginner mappers on the HOT Tasking Manager. Conclusively, the lacuna or differential response of RVM and LVM requires investigation in terms of geographic context, digital citizenry, economic disposition and demographic characteristics of online volunteer mappers.
SPEED-RELATED TRAFFIC ACCIDENT ANALYSIS USING GIS-BASED DBSCAN AND NNH CLUSTERING
Authors: Topcuoglu B. , Memisoglu Baykal T. , Tuydes Yaman H.
Published: August 2022

Abstract. To ensure road safety and reduce traffic accidents, it is essential to determine geographical locations where traffic accidents occur the most. Spatial clustering methods of hot spots are used very effectively to detect such risky areas and take precautions to minimize or even avoid fatal or injury accidents. This study aims to determine speed-related hot spots in the pilot Mersin Region, which includes seven cities in the central-southern part of Turkey. Two different hot spot clustering methods, the Nearest Neighbourhood Hierarchical Clustering Method (NNH) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Method, were employed to analyse traffic accident data between 2014-2021, obtained from the General Directorate of Highways. CrimeStat III program, which is free software, was used to detect NNH clusters, while the DBSCAN clusters were obtained using the open-source GIS program QGIS, which was also used to visualize and evaluate the results comparatively. As a result of the analysis, it was determined which method gave more effective results in determining the traffic accident risk clusters. These clusters were analysed based on road geometries (intersection or corridors). In addition, by considering the areas where repeated accidents have occurred over the years, future predictions of traffic accidents have been estimated.
SEMANTIC QUERYING IN EARTH OBSERVATION DATA CUBES
Authors: van der Meer L. , Sudmanns M. , Augustin H. , Baraldi A. , Tiede D.
Published: August 2022

Abstract. Earth observation (EO) data cubes have revolutionized the way large volumes of EO data can be stored, accessed, and processed. However, users coming from application domains outside of traditional EO research still face some significant technical barriers when querying an EO data cube with the aim to infer knew knowledge about real world entities and events. They have to interpret EO data in order to give them meaning, which is an ill-posed problem that requires advanced expertise in the field of EO analytics. We propose a semantic querying framework in which users query the EO data cube through an ontology, rather than accessing the data values themselves. The ontology formalizes symbolic representations of real-world entities and events, which are mapped to data values in the EO data cube through a mapping component formulated by an EO expert. This takes away the need for users to be aware of the EO data and how to interpret them, and therefore lowers the technical barriers to extract valuable information from EO data. We implemented a proof-of-concept of our approach as an open-source Python package.
construction of a sociotechnical surveillance network in Brazil
Authors: Henrique da Costa Braga Pedro , Leal Sobral André Vinicius , Gonçalves Severo Fernando , Jullian da Silva Graça Ricardo , Cukierman Henrique Luiz
Published: August 2022

Young activists in Brazil became targets of state persecution for taking part in the mass protests that took to the streets and the Web during the lead-up to the 2014 World Cup and, subsequently, during the 2016 Olympic Games. The present article is a case study tackling the growth and development of the state’s Internet surveillance apparatus and how it was used to suppress young political activists. We begin this paper with a theoretical discussion on the concept of surveillance and how it is inseparable from modern capitalist society. To that end, we used science, technology and society studies as the theoretical foundation for our analysis. Further along, we describe the Brazilian political atmosphere during the mass demonstrations. Lastly, we conclude with an analysis of the personal accounts collected via interviews with the activists that were persecuted and monitored by the state.
REY in pore waters of sediments hosting Fe-Mn nodules of the Interoceanmetal exploration area in the Clarion-Clipperton Fracture Zone, NE Pacific
Authors: Milakovska Zlatka , Hikov Atanas , Stoyanova Valcana , Peytcheva Irena , Lyubomirova Valentina , Abramowski Tomasz
Published: August 2022

Our study is focused on REE and yttrium (REY) geochemistry of pore waters from core-box sediments. The samples were collected from the 0–5 cm, 10–15 cm, 25–30 cm, and 35–40 cm depth intervals of four stations of the eastern part of block H_22 of IOM license area of the Clarion-Clipperton Fracture Zone, NE Pacific. The REE studies in marine pore fluids were limited by analytical challenges. The pore water analysis we applied is based on a modern, improved analytical technique (ICP-MS, Perkin-Elmer SCIEX Elan DRC-e) with a cross-flow nebulizer and a spectrometer optimized (RF, gas flow, lens voltage) using a quadrupole cell in a DRC (Dynamic Reaction Cell) mode that allowed us to define the whole suite of REE. The ƩREY values of the samples vary from 4.05 μg/l to 106.34 μg/l. The REE content is at least one order of magnitude higher than the oceanic water. We followed the natural variations of La, Lu, Ce, and Y in absolute concentrations for station 3607. Cerium and Y are slightly enriched around the water-sediment interface, while La and Lu are enriched in the deeper layers. PAAS normalized REY patterns show a pronounced negative Ce/Ce* ratio together with a little MREE and HREY enrichment. The relatively “flat” REE patterns are typical for the shallow open ocean and characterize REE released from the organic matter degradation. We assume that the decomposition of and adsorption on organic matter and oxidation conditions are the main factors for REE fractionation in the pore water. The reason for some scatter in our REY data might be linked to bioturbation that has affected the sediment profiles.
Group-Based Data Offloading Techniques Assisted by D2D Communication in 5G Mobile Network
Authors: Ally Juma
Published: August 2022

Machine type communication devices proposed as one of the substantial data collections in the 5G of wireless networks. However, the existing mobile communication network is not designed to handle massive access from the MTC devices instead of human type communication. In this context, we propose the device-to-device communication assisted a mobile terminal (smartphone) on data computing, focusing on data generated from a correlated source of machine type communication devices. We consider the scenario that the MTC devices after collecting the data will transmit to a smartphone for computing. With the limitation of computing resources at the smartphone, some data are offloaded to the nearby mobile edge-computing server. By adopting the sensing capability on MTC devices, we use a power exponential function to compute a correlation coefficient existing between the devices. Then we propose two grouping techniques K-Means and hierarchical clustering to combine only the MTC devices, which are spatially correlated. Based on this framework, we compare the energy consumption when all data processed locally at a smartphone or remotely at mobile edge computing server with optimal solution obtained by exhaustive search method. The results illustrated that; the proposed grouping technique reduce the energy consumption at a smartphone while satisfying a required completion time.
Effect of Temperature, Catalyst Concentration and Time, on Polylactic Acid Production from Sisal Boles Juice by Ring Open Polymerization
Authors: Msuya Neema , Temu Abraham , Minja Rwaichi
Published: August 2022

Polylactic acid (PLA) is a biodegradable and renewable alternative to non-biodegradable petrochemical-based polymers that is environmentally friendly and green. PLA can be made from a variety of agricultural wastes that contain sugars, such as sisal boles. This study aimed at analysing the possibility of producing PLA from lactic acid (LA) produced from sisal bole. A 2n factorial design was used to analyse the effects of temperature (160-180ºC), time (1-2 hrs) and tin octoate catalyst concentration (0.025-0.05%) on the PLA yield during polymerization. Minitab Version 20.2.0 was used to design the experiment and analyse the effects on the responses through ANOVA. It was possible to produce 0.73±0.05 g of lactide per g of sisal bole LA used. More than 99% conversion of lactide into PLA was done for 2 hrs when the system temperature was 180ºC regardless of the catalyst ratio used. Temperature and time significantly affected the yield with p-values of less than 0.05 at 95% confidence level. The current findings support sisal bole juice as an alternative feedstock for LA production, a precursor for PLA. The use of sisal bole (SB) waste will protect environment by using waste biomass as an opportunity to participate in a global move to produce biobased plastics and promote the ban on the use of petrochemical-based plastics in packaging.
Renewable Energy Microgrids to Improve Electrification Rate in Democratic Republic of Congo: Case of Hydro, Municipal Waste and Solar
Authors: Josue Ngondo , Mushi Aviti
Published: August 2022

Worldwide, it is imperative for citizens to have access to electrici-ty. This applies to Congolese--rural and urban dwellers, and if possible, it should be guaranteed by government’s laws and poli-cies. However, the rural and urban areas of Democratic Republic of Congo (DRC) suffer majorly from lack of access to electricity. The major reasons are the high costs associated with connection to the national central grid and production insufficiency. There-fore, one feasible approach to electrify these areas is to use mi-crogrids. This technology is decent and viable option for energy revolution since it incorporates energy storage systems, distribut-ed generators, and localized loads. This paper has taken to im-plement this solution by firstly analysing some cities located at the borders of large rivers or watercourses (with known depth and width), such as the Congo River considered for hydrokinetic pow-er (HKP). However, where the Congo River does not pass through, the paper will consider largest rivers passing in the area. For the case of photovoltaic electricity production, large cities are considered those with good sunshine and large population who have purchasing power for the photovoltaic electricity. The waste to energy power plans will consider the top ten densely populated cities in DRC. The proposed microgrids will operate in isolation (islanded) mode. This paper proposed 44 projects to generate 795 690 kW total energy from the microgrids. These energies are divided as 661 000 kW from solar photovoltaic, 83 790 kW from waste to energy, and 50 900 kW from hydrokinetic generation. The urban share will be 94.9% and rural area share will be 5.1% of this generation. Further work needs to include biomass as a possible renewable energy to add in the mix.
Estimation of Storage Tank Capacities for Different Roof Catchment Areas for Rainwater Harvesting in Dodoma Urban, Tanzania
Authors: Mdee Ombeni , Tembo Malugu , Mwegoha William
Published: August 2022

This study uses a mass balance model and economic analysis technique to present an estimation of roofing areas and storage tank capacity for Rainwater Harvesting (RWH) system. The water-saved benefits were estimated using the monthly rainfall of over 39 years from 1981 to 2020 and five roofing areas. The proposed roof-storage-ratio method presents the minimum requirement of roof area and storage tank size when the ratio value is closer to 1. The benefit-cost ratio and percentage of reliability indicated the optimal roofing areas ranging between 200 and 300 m2 for storage tank capacity between 20 and 25 m3, with a minimum discount rate of 5%. The increased capacity of storage tank and roofing area would also be a potential factor to increase the investment cost for installing the RWH system.
Efficient and Simple Heuristic Algorithm for Portfolio Optimization
Authors: John Collether
Published: August 2022

Markowitz model considers what is termed as standard portfolio optimization. The portfolio optimization problem is a problem which based on asset allocation and diversification for maximum return with minimum risk. Thus, the standard portfolio optimization problem happens when the constraints considered are budget and no-short selling. In reality however, portfolio optimization has realistic constraints to be incorporated such as holding sizes, cardinality and transaction cost. When realistic constraints are added into portfolio optimization problem, it becomes too complex to be solved by standard optimization methods which in this case turns to be an extended portfolio optimization problem. Markowitz solution and the standard methods like quadratic programming become inapplicable. With such limitation, heuristic methods are usually used to deal with this extended portfolio optimization problem. Therefore, this paper proposes a heuristic algorithm for the extended portfolio optimization problem. It is a hill climbing algorithm named Hill Climbing Simple (HC-S) which is then validated by solving the standard Markowitz model. In fact, the proposed algorithm is benchmarked with the quadratic programming (QP), which is a standard method. By benchmarking HC-S with QP, it showed that HC-S can attains similar accurate solutions. Also, HC-S demonstrated to be more effective and efficient than threshold accepting (TA), an established algorithm for portfolio optimization since HC-S find solutions with significant higher objective value and require less computing time as compared to standard methods.
Production of Paper Pulp Using Sisal Fiber Waste from Sisal Spinning Processes
Authors: Bosco Mtweve , Mbise Ekael , Minja Rwaichi
Published: August 2022

Disposal of large volumes of textile waste is an escalating problem for textile industries. Sisal spinning industry is the one of the textile industries releasing large volumes of textile waste in the landfills. The rising costs, and reduction of available space together with increasing stringent environmental measures are making burying and land filling of textile waste, a declining option. This study therefore explores recycling options where the potential of using sisal fiber waste produced during sisal spinning processes as raw materials for the production of paper pulp was investigated. Sampling was done at 21stCentury Holdings Limited allocated at Chang’ombe industrial street Dar es Salaam mainly dealer of sisal yarns production. Materials were prepared and cut into small pieces of about ½ inches to reduce the fiber into unit lengths so as to achieve pulping required performance. Pulping process was achieved through Soda pulping techniques with two different effective alkali charges (EA-20% and EA-24%) for 240 minutes under maximum temperature 140 C, and liquor to fiber ratio 4:1by using Mathis Labomat dyeing Machine. The kappa number obtained was (25.5, 34.5) for material treated under EA 24% and EA 20% respectively, Percentage pulp yield were (47.1, 54.4) for EA 24% and EA20% pulp respectively. Freeness (630CFS, 555CSF) after refining at 4500rpm. Finally, the resulting pulp was used for hand sheet making and the sheets were tested for their mechanical properties; Grammage (61.1, 61.1) g/m2, Tensile index (9.9, 22.3) Nm/g, Tear index (13.3, 17.4) Nm2/g, burst index (1.7, 3.7 and 1.6) k.pa.m2/g and Elongation at break (2.02, 2.22) % for EA24% pulp, EA20% pulp respectively. The findings shows that sisal fiber wastes have a promising potential for paper pulp production compared to other non-wood raw material.
Viability Analysis of Ubungo II Gas Power Plant Efficiency Improvement Using Co-generation System
Authors: Nyanda Elias , Mushi Aviti , Justo Jackson
Published: August 2022

The power utility, Tanzania Electric Supply Company Limited (TANESCO) is faced with challenges of supplying adequate power to the ever-increasing demand. To this end, this paper explores the installed Ubungo Gas Power Plant (UGP II) located in Dar es Salaam to find means of utilizing it in co-generation method. The study embarked on detailed modelling of the system and run simulations which indicated that the co-generation can result to power generation efficiency increase between 10.42 to 50.92%. It is recommended to change the UGP II to exploit this co-generation method. Further, the study could be improved by including more parameters of the gas and steam plant and verify them experimentally.
Assessment of Energy Efficiency in Beverage Industry
Authors: Mtebwa Mahamudu , Ichwekeleza Wiston
Published: August 2022

The brewery industry has a significant contribution to the national income. However, it is also associated with energy-intensive processes and pollution. In this work, the energy efficiency assessment of the largest brewery in Tanzania i.e., Tanzania Breweries Limited has been conducted. Energy consumption analysis was conducted according to IEEE SA 739-1995. Important parameters used to assess brewery energy efficiency were boiler efficiency and losses, equipment energy productivity as well as load factor. It was found that the main energy consumers are packaging (54.63%), brewing (29.30%) and utilities (15.17%). More importantly, it was found that about 68% of the brewery energy demand is thermal energy which is supplied by the boiler whose efficiency (62%) is significantly lower than the expected value of 94-95%. Load factor analysis showed that the equipment of both brewing and packaging line 4 are significantly oversized. Furthermore, energy productivity of 45.5 kWh/L of beer is significantly higher than the industry minimum of 23.6 kWh/L.
Affective States and Heart Rate Response: Measuring Foreign Language Speaking Performance Reactions in a Japanese University Classroom
Authors: Shachter Jonathan , Kangas Maria , Sweller Naomi , Stewart Jeffrey
Published: August 2022

While psychologists often use a combination of physiological and self-reported data to examine the dynamic effects of stress on performance, the impact of affective states on Foreign Language (FL) speaking performance has almost exclusively been assessed using self-report methodology (e.g., questionnaires, interviews). In fact, studies that correlate physiological data with self-report measures in a classroom context are extremely rare due to both cost and logistical restraints. This study set out to address this gap in language learning research by employing Fitbit smart watches as a tool to unobtrusively collect heart rate (HR) response data. Participants in this study were undergraduate Japanese language students (5 males and 5 females, mean age = 19.7 years, SD = .95) at a private university in Japan. Over three sessions, students wore Fitbit smart watches and performed three different class-observed dialogs (with randomized partners and performance order) while seated at their desks. Students were also asked to report their affective state (to index their feelings in the moment) across three intervals within each class session: class start, pre-performance, and post-performance. Using multi-level modeling statistical analysis, elevated self-reported state feelings of distress and embarrassment were found to be significantly positively related with elevated HR response. To further understanding of how affective states unfold in classroom environments, researchers should consider both physiological and self-report measures. With advances in wearable technology, similar research designs to this study may become more commonplace.
Beyond the Boundaries of the Self: Applying Relational Theory Towards an Understanding of the Teacher-Student Relationship as a Driver of Motivation in Foreign Language Learning
Authors: Moskowitz Sharona , Dewaele Jean-Marc , Resnik Pia
Published: August 2022

Previous research on the foreign language (FL) learner has yielded a rich body of knowledge on personality, individual differences, and conceptions of the self as a measure of motivation. While these contributions have greatly enriched our understanding of learner psychology, the current paper proposes an analytical framing of language learning based on relational theory, which positions human relationships with others as the main driver of the psyche and behavior. As human beings are relationally dependent from birth, according to this theory, the self can only be conceptualized in relation to others. Applied to language learning, this perspective shifts the focus from the attainment of knowledge as an individual, private endeavor, to a relational process in which students and teacher are interwoven perforce. As part of a larger study on student perceptions of teacher emotion, qualitative data were collected as case studies from eight adult learners and analyzed using qualitative content analysis. Results support the power of the teacher-student relationship to influence and motivate students both positively and negatively, affirming the notion of FL learning as a relational process in accordance with Gergen’s (2009) notion that relationships are not merely the self interacting with the other but a true confluence.
Dear Diary: An Exploration of L2 Teachers’ Emotional Experiences
Authors: Dumančić Dino , Martinović Anna , Burić Irena
Published: August 2022

Studies focusing on affective factors/emotions in learning are a mainstay in second language (L2) research. L2 teacher-focused research has also made advances in this domain and established the importance of affective factors for both learners and teachers. Despite the field’s understanding of the emotional complexity of L2 teaching, much remains undiscovered. The aim of this qualitative research was to investigate L2 teachers’ (N = 21) emotional experiences in the classroom. Specifically, by using a teacher diary we set out to document: (1) the emotions teachers reported in their place of work and during their interactions with learners, (2) the classroom activities teachers were engaged in when they experienced specific emotions, and (3) the regulatory practices they engaged in when dealing with both pleasant and unpleasant emotions. Our findings show that L2 teachers most frequently experienced pleasant emotions such as satisfaction, joy, and pride. In regard to unpleasant emotions, they primarily revealed frustration, irritability, and disappointment. Both types of emotions were mostly instigated by their learners and were related to L2 classroom activities in the areas of grammar, speaking, and reading. The teachers admitted to regulating both pleasant and unpleasant emotions. Finally, teachers revealed that they used down-regulation, reappraisal, deep breathing, and suppression as the most frequent emotion regulation strategies.
The Effects of Effort Feedback and L2 Task Attributions on Task Engagement and Performance
Authors: Yamazaki Joseph
Published: August 2022

Despite their well-established connections to student motivation and to learning outcomes, attributions, particularly at the task-level, have not garnered much attention in L2 learning research. However, research evidence in educational psychology (e.g., Stajkovic & Sommer, 2000) suggests that L2 task attributions may affect subsequent task engagement and performance. L2 task engagement is a construct studied extensively in recent L2 learning research because of its association with high-quality task performance and learning outcomes. The primary objective of this work-in-progress study is to clarify this potential link between L2 task attributions, engagement, and performance. In addition, the effect of effort feedback on these three constructs is also investigated. Previous research (e.g., Amemiya & Wang, 2018) has documented that effort feedback typically used with good intentions by L2 teachers may, in fact, backfire and exert negative influences on how individuals shape task attributions, which in turn lead to poor-quality task engagement and performance. A within-group quasi-experimental research design will be adopted for these purposes, and 120 Japanese high school students will be recruited. Participants will be divided into two groups to counterbalance the order of effort feedback provision. Three reading tasks from the EIKEN Test in Practical English Proficiency, Grade Pre-2, will be used, and time on task will be recorded as an indicator of task engagement. After performing the tasks, the participants will receive effort feedback and report their task attributions. The relationship between effort feedback, task attributions, engagement, and performance will be analyzed through hierarchical multiple regression analyses.
EDUCATION TRANSFORMATION IN THE DIGITALIZATION AGE AS THE FUTURE OF THE NATION
Authors: Sitepu Edward , Sembiring Milisi , Kia A Dan , Sostenis Nggebu
Published: August 2022

Technology-based education is expected to be able to improve the quality of education and also in the long term improve the welfare of a nation. The case study approach in several countries and using the results of existing studies in those countries shows a significant influence on digital technology-based learning and teaching. This was emphasized by UNDP regarding the importance of using technology in learning. Studies in England, Turkey and in Asean countries and specifically in Indonesia show that improving the welfare of the nation is possible because more advanced education and the use of learning technology are able to shape students' thinking, learning attitudes and of course their independence in the future. This is certainly encouraging in the midst of the Government's spirit to promote education with an independent learning corps as a complementary to education for all.
Keywords: education, technology, welfare, nation, learning and teaching.
Teaching English Language in Early Childhood
Authors: Jenny Jingga
Published: August 2022

Learning English is a crucial skill that will enable youngsters to reach their full potential in the future. They can learn English quickly and successfully if they use the appropriate strategies since early childhood. As a result, it is critical that kids learn English that is both practical and beneficial. For youngsters, learning should not be a stressful experience. It should be entertaining as well as stimulating. Reading, listening, and speaking English should become second nature to them as a result of their study. They will learn more and use English language at a higher level as their confidence grows. This paper outlines various resources for EFL teachers to help youngsters learn a foreign language more effectively since they are in their early childhood. These are designed to help them teaching effectively while also providing the excitement and variety that children require. This paper's final section discusses how to ensure that youngsters learn English using easy approaches that will undoubtedly make teachers' jobs more enjoyable and rewarding. Furthermore, it is expected that the teachers would have enough new ideas to be the most inspiring teachers possible.
Keywords : Teaching Language, Early Childhood
Theory Of Cognitive Development By Jean Piaget
Authors: Pakpahan Farida Hanum , Saragih Marice
Published: August 2022

Although many core themes and concepts unite the field of cognitive development, it is a wide and varied field, particularly when it comes to cognitive development in early. Piaget proposed four cognitive developmental stages for children, including sensorimotor, preoperational, concrete operational, and the formal operational stage. Although Piaget’s theories have had a great impact on developmental psychology, his notions have not been fully accepted without critique. Piaget’s theory has some shortcomings, including overestimating the ability of adolescence and underestimating infant’s capacity. Piaget also neglected cultural and social interaction factors in the development of children’s cognition and thinking ability. Cognitive development occurs at several stages during childhood. As a result, cognitive development studies the nature of child development in terms of how they gain conscious control over their intellect and behavior. Piaget contributions, particularly in regards to the process of education among children and transferring cognition into psychology, have had a significant effect on the science of child development.
Keywords: Cognitive Development, Child Development