Search results for: research industry and business collaboration

Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Antonia Stanojević, Agnes Akkerman

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In contemporary society, economically active people typically spend most of their waking hours doing their job. Having that in mind, this research examines how socialization at the workplace shapes political preferences. Innovatively, it examines, in particular, the possible relationship between employees’ voice suppression by the employer and the formation of their political preferences. Since the employer is perceived as an authority figure, their behavior might induce spillovers to attitudes about political authorities and authoritarian governance. Therefore, a positive effect of suppression of voice by employers on employees' preference for authoritarian governance is expected. Furthermore, this relation is expected to be mediated by two mechanisms: system justification and power distance. Namely, it is expected that suppression of voice would create a power distance organizational climate and increase employees’ acceptance of unequal distribution of power, as well as evoke attempts of oppression rationalization through system justification. The hypotheses will be tested on the data gathered within the first wave of Work and Politics Dataset 2017 (N=6000), which allows for a wide range of demographic and psychological control variables. Although a cross-sectional analysis to be used at this point does not allow for causal inferences, the confirmation of expected relationships would encourage and justify further longitudinal research on the same panel dataset, in order to get a clearer image of the causal relationship between employers' suppression of voice and workers' political preferences.

Keywords: authoritarian values, political preferences, power distance, system justification, voice suppression

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Authors: Xian Chen

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In recent years, the tendency that the decline of material and social vitality of old city in China becomes more and more serious. Nowadays, transformation and renewal of the old city have become a hot topic in urban research. The traditional mode of large-scale promotion has been criticized. Thus, exploration of new ways to update the city turns to be a necessity on the way of sustainable urban development. Pocket Park is a small city open space, its location choose is based on abandoned or idle lands on urban structure, is scattered or hidden in corner of the urban. It has a great significance on improving the old city environment. Based on the theory of ‘pocket park’, this paper summarizes the successful experience of domestic and foreign practice, and discusses the update strategies which are suitable for China's national conditions according to the characteristics and predicament of the old city in China. The main methods and results are as follows: 1)Based on the conception of ‘pocket park’, though describing the research status in domestic and foreign, summarizing the experience which is worth learning and existing problems. 2) From the analysis of ‘pocket park’ function, general design principles and types of the deep-seated difficulties in renewal the old city and the possibility of the application of ‘pocket park’,the varied implementation of ‘pocket park’ form are established, and application value in the old city renewal are summed up. 3) It can’t be denied that pocket park plays an irreplaceable role in solving the recession and renewing the vitality of the old city. Anymore, It is recommended to develop corresponding supportive development policies.

Keywords: sustainable development, strategy, old city renewal, pocket park

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Authors: Mei-Hui Liu

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This study examines the effectiveness of a blended professional development program on preservice EFL (English as a foreign language) teachers’ learning to teach speech acts with the advent of Information and Communication Technology, researchers and scholars underscore the significance of integrating online and face-to-face learning opportunities in the teacher education field. Yet, a paucity of evidence has been documented to investigate the extent to which such a blended professional learning model may impact real classroom practice and student learning outcome. This yearlong project involves various stakeholders, including 25 preservice teachers, 5 English professionals, and 45 secondary school students. Multiple data sources collected are surveys, interviews, reflection journals, online discussion messages, artifacts, and discourse completion tests. Relying on the theoretical lenses of Community of Inquiry, data analysis depicts the nature and process of preservice teachers’ professional development in this blended learning community, which triggers and fosters both face-to-face and synchronous/asynchronous online interactions among preservice teachers and English professionals (i.e., university faculty and in-service teachers). Also included is the student learning outcome after preservice teachers put what they learn from the support community into instructional practice. Pedagogical implications and research suggestions are further provided based on the research findings and limitations.

Keywords: blended professional development, preservice EFL teachers, speech act instruction, student learning outcome

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Authors: May Fadheel Estephan, Richard Perks

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Context: Cancer is a serious health concern that affects millions of people worldwide. Early detection and treatment are essential for improving patient outcomes. However, current methods for cancer detection have limitations, such as low sensitivity and specificity. Research Aim: The aim of this study was to develop an optical sensor for cancer detection using elastic light scattering spectroscopy (ELSS). ELSS is a noninvasive optical technique that can be used to characterize the size and concentration of particles in a solution. Methodology: An optical probe was fabricated with a 100-μm-diameter core and a 132-μm centre-to-centre separation. The probe was used to measure the ELSS spectra of polystyrene spheres with diameters of 2, 0.8, and 0.413 μm. The spectra were then analysed to determine the size and concentration of the spheres. Findings: The results showed that the optical probe was able to differentiate between the three different sizes of polystyrene spheres. The probe was also able to detect the presence of polystyrene spheres in suspension concentrations as low as 0.01%. Theoretical Importance: The results of this study demonstrate the potential of ELSS for cancer detection. ELSS is a noninvasive technique that can be used to characterize the size and concentration of cells in a tissue sample. This information can be used to identify cancer cells and assess the stage of the disease. Data Collection: The data for this study were collected by measuring the ELSS spectra of polystyrene spheres with different diameters. The spectra were collected using a spectrometer and a computer. Analysis Procedures: The ELSS spectra were analysed using a software program to determine the size and concentration of the spheres. The software program used a mathematical algorithm to fit the spectra to a theoretical model. Question Addressed: The question addressed by this study was whether ELSS could be used to detect cancer cells. The results of the study showed that ELSS could be used to differentiate between different sizes of cells, suggesting that it could be used to detect cancer cells. Conclusion: The findings of this research show the utility of ELSS in the early identification of cancer. ELSS is a noninvasive method for characterizing the number and size of cells in a tissue sample. To determine cancer cells and determine the disease's stage, this information can be employed. Further research is needed to evaluate the clinical performance of ELSS for cancer detection.

Keywords: elastic light scattering spectroscopy, polystyrene spheres in suspension, optical probe, fibre optics

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Authors: Guneet Saini, Uthej Vattipalli

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In a world with increased demand for sustainable construction, waste product of one industry could be a boon to the other in reducing the carbon footprint. Usage of industrial waste such as fly ash and ground granulated blast furnace slag have become the epicenter of curbing the use of cement, one of the major contributors of greenhouse gases. In this paper, empirical studies have been done to develop alkali activated self-compacting geopolymer concrete (GPC) using ground granulated blast furnace slag (GGBS), incorporated with 2% nano-silica by weight, through evaluation of its fresh and hardening properties. Experimental investigation on 6 mix designs of varying molarity of 10M, 12M and 16M of the alkaline solution and a binder content of 450 kg/m³ and 500 kg/m³ has been done and juxtaposed with GPC mix design composed of 16M alkaline solution concentration and 500 kg/m³ binder content without nano-silica. The sodium silicate to sodium hydroxide ratio (SS/SH), alkaline activator liquid to binder ratio (AAL/B) and water to binder ratio (W/B), which significantly affect the performance and mechanical properties of GPC, were fixed at 2.5, 0.45 and 0.4 respectively. To catalyze the early stage geopolymerisation, oven curing is done maintaining the temperature at 60˚C. This paper also elucidates the test results for fresh self-compacting concrete (SCC) done as per EFNARC guidelines. The mechanical properties tests conducted were: compressive strength test after 7 days, 28 days, 56 days and 90 days; flexure test; split tensile strength test after 28 days, 56 days and 90 days; X-ray diffraction test to analyze the mechanical performance and sorptivity test for testing of permeability. The study revealed that the sample of 16M concentration of alkaline solution with 500 Kg/m³ binder content containing 2% nano silica produced the highest compressive, flexural and split tensile strength of 81.33 MPa, 7.875 MPa, and 6.398 MPa respectively, at the end of 90 days.

Keywords: alkaline activator liquid, geopolymer concrete, ground granulated blast furnace slag, nano silica, self compacting

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Authors: Jiraphorn Satechan, Thanaphon Khamthieng, Warunee Phanwong

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This action research aimed at designing and developing the cleaning equipment to preventing dust diffusion of bus air filter. Quantitative and qualitative data collection methods were used to conduct data from October 1st, 2018 to September 30th, 2019. All of participants were male (100.0%) with aged 40- 49 years and 57.15%, of them finish bachelor degree. 71.43% of them was a driver and 57.15% of them had the working experience between 10 and 15 years. Research revealed that the participants assessed the quality of the bus air filter cleaning equipment for preventing dust diffusion at a moderate level (σ= 0.29), and 71.43 of them also suggested the development methods in order to improve the quality of bus air filters cleaning equipment as follows: 1) to install the circuit breaker for cutting the electricity and controlling the on-off of the equipment and to change the motor to the DC system, 2) should install the display monitor for wind pressure and electricity system as well as to install the air pressure gauge, 3) should install the tank lid lock for preventing air leakage and dust diffusion by increasing the blowing force and sucking power, 4) to stabilize the holding points for preventing the filter shaking while rotating and blowing for cleaning and to reduce the rotation speed in order to allow the filters to move slowly for the air system to blow for cleaning more thoroughly, 5) the amount of dust should be measured before and after cleaning and should be designed the cleaning equipment to be able to clean with a variety of filters, and sizes. Moreover, the light-weight materials should be used to build the cleaning equipment and the wheels should be installed at the base of the equipment in order to make it easier to move.

Keywords: Cleaning Equipment, Bus Air Filters, Preventing Dust Diffusion, Innovation

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Authors: Kyung Bae Park, Sung Ho Ha

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Online user-generated contents (UGC) significantly change the way customers behave (e.g., shop, travel), and a pressing need to handle the overwhelmingly plethora amount of various UGC is one of the paramount issues for management. However, a current approach (e.g., sentiment analysis) is often ineffective for leveraging textual information to detect the problems or issues that a certain management suffers from. In this paper, we employ text mining of Latent Dirichlet Allocation (LDA) on a popular online review site dedicated to complaint from users. We find that the employed LDA efficiently detects customer complaints, and a further inspection with the visualization technique is effective to categorize the problems or issues. As such, management can identify the issues at stake and prioritize them accordingly in a timely manner given the limited amount of resources. The findings provide managerial insights into how analytics on social media can help maintain and improve their reputation management. Our interdisciplinary approach also highlights several insights by applying machine learning techniques in marketing research domain. On a broader technical note, this paper illustrates the details of how to implement LDA in R program from a beginning (data collection in R) to an end (LDA analysis in R) since the instruction is still largely undocumented. In this regard, it will help lower the boundary for interdisciplinary researcher to conduct related research.

Keywords: latent dirichlet allocation, R program, text mining, topic model, user generated contents, visualization

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Authors: Aldilla Damayanti Purnama Ratri, Hendri Subakti, Buldan Muslim

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Ionosphere’s anomalies as an effect of earthquake activity is a phenomenon that is now being studied in seismo-ionospheric coupling. Generally, variation in the ionosphere caused by earthquake activity is weaker than the interference generated by different source, such as geomagnetic storms. However, disturbances of geomagnetic storms show a more global behavior, while the seismo-ionospheric anomalies occur only locally in the area which is largely determined by magnitude of the earthquake. It show that the earthquake activity is unique and because of its uniqueness it has been much research done thus expected to give clues as early warning before earthquake. One of the research that has been developed at this time is the approach of seismo-ionospheric-coupling. This study related the state in the lithosphere-atmosphere and ionosphere before and when earthquake occur. This paper choose the total electron content in a vertical (VTEC) in the ionosphere as a parameter. Total Electron Content (TEC) is defined as the amount of electron in vertical column (cylinder) with cross-section of 1m2 along GPS signal trajectory in ionosphere at around 350 km of height. Based on the analysis of data obtained from the LAPAN agency to identify abnormal signals by statistical methods, obtained that there are an anomaly in the ionosphere is characterized by decreasing of electron content of the ionosphere at 1 TECU before the earthquake occurred. Decreasing of VTEC is not associated with magnetic storm that is indicated as an earthquake precursor. This is supported by the Dst index showed no magnetic interference.

Keywords: earthquake, DST Index, ionosphere, seismoionospheric coupling, VTEC

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Authors: María García-García, Esther Simancas-González, Said Balhadj, Carmen Silva-Robles, Driss Ferhane

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Cooperation between the territories on both sides of the Strait of Gibraltar is an urgent reality. the south of Spain and northern Morocco share a common historical past and belong to a very similar geographical and ecological area. Economic, social and cultural relations make cooperation between the two countries’ (Spain and Morocco) a priority for the EU and both countries governments. Likewise, deepened changes happened in production systems and consumption patterns had seriously damaged and weakened the craftwork sector. The promotion of local crafts, and its economic value, and the cooperation with the north of Morocco has been an important issue for the Andalusian government in recent years. The main aim of this work is to understand the strengths and weaknesses of the Tangier - Tetuan region craftworks sector in order to develop accurate communication and promotion plans. From the knowledge of the real identity, the sector could be repositioned. Promotion and communication could be a spur to traditional sectors, such as crafts. Competitiveness requires "the culture of communication, the cooperation between different companies to build powerful territory brands and maintain the establishment confidence and effectiveness relationships among agencies and organizations". The lack of previous literature addressing how Tangier craftwork promote and communicate its value to their stakeholders, has conducted the study to an exploratory approach with a double dimension: internal, Tangier craftwork sector image, and external, Andalusia image of the sector in Tangier. Different interviews were conducted with Andalusian partners involved in the artisanal sector (9 master craftsmen and 3 institutions) and focus groups with 9 Tangiers craftsmen were developed. The result of these interviews and expert groups are reflected in a SWOT analysis which reveals a handcraft industry with a worrying wide-spread and undifferentiated identity and reluctance to innovation and new technologies.

Keywords: communication management, image, Moroccan crafts, Spain-Morocco cooperation

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Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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In this paper, we focus on the importance of scalable architecture for data centers and buildings in general to help an enterprise achieve environmental sustainability. The scalable architecture helps in many ways, such as adaptability to the business and user requirements, promotes high availability and disaster recovery solutions that are cost effective and low maintenance. The scalable architecture also plays a vital role in three core areas of sustainability: economy, environment, and social, which are also known as the 3 pillars of a sustainability model. If the architecture is scalable, it has many advantages. A few examples are that scalable architecture helps businesses and industries to adapt to changing technology, drive innovation, promote platform independence, and build resilience against natural disasters. Most importantly, having a scalable architecture helps industries bring in cost-effective measures for energy consumption, reduce wastage, increase productivity, and enable a robust environment. It also helps in the reduction of carbon emissions with advanced monitoring and metering capabilities. Scalable architectures help in reducing waste by optimizing the designs to utilize materials efficiently, minimize resources, decrease carbon footprints by using low-impact materials that are environmentally friendly. In this paper we also emphasize the importance of cultural shift towards the reuse and recycling of natural resources for a balanced ecosystem and maintain a circular economy. Also, since all of us are involved in the use of computers, much of the scalable architecture we have studied is related to data centers.

Keywords: scalable architectures, sustainability, application design, disruptive technology, machine learning and natural language processing, AI, social media platform, cloud computing, advanced networking and storage devices, advanced monitoring and metering infrastructure, climate change

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Leslie M. Mullins

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In the face of dramatically shifting demographic trends and macroeconomic pressures on affordable housing in high-cost cities, municipalities and developers have been forced to develop new models of sustainable development that integrates elements of substantial rehabilitation and new construction while controlling for relocation and mass displacement. Community development partners in the San Francisco Bay Area of Northern California are starting to prioritize anti-displacement strategies when rehabilitating severely neglected public housing developments. This study explored the community-driven efforts to transform four dilapidated public housing sites (N=2,600 households) into thriving mixed-income housing communities. Eight interviews were conducted with frontline workers (property managers and service providers), who directly worked with residents throughout critical stages of the relocation and leasing process. Interviews were audio-recorded, transcribed, and analyzed by a systematic procedure for qualitative analysis to identify key themes on the topics of interest. Also, an extensive literature analysis was conducted to determine promising practices throughout the industry. This study highlighted that resident’s emotional attachment to their homes (regardless of the deteriorating conditions of their unit) could both a) impede the relocation process and substantially impact the budget and timeline, while b) simultaneously providing a basis for an enhanced sense of belonging and community cohesion. This phenomenon often includes the welcoming of new residents and cultures. Resident centered workshops, healing centered rituals, and extensive 'hands-on' guidance was highlighted as promising practices that resulted in residential retention rates that were two to three times the national average and positively impacted the overall project’s budget and timeline.

Keywords: anti-displacement strategies, community based practices, community cohesion, cultural preservation, healing-centered, public housing, relocation, trauma-informed

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Authors: G. Tamilpavai, C. Vishnuppriya

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Bioinformatics is an active research area which combines biological matter as well as computer science research. The longest common subsequence (LCSS) is one of the major challenges in various bioinformatics applications. The computation of the LCSS plays a vital role in biomedicine and also it is an essential task in DNA sequence analysis in genetics. It includes wide range of disease diagnosing steps. The objective of this proposed system is to find the longest common subsequence which presents in a normal and various disease affected human DNA sequence using Self Organizing Map (SOM) and LCSS. The human DNA sequence is collected from National Center for Biotechnology Information (NCBI) database. Initially, the human DNA sequence is separated as k-mer using k-mer separation rule. Mean and median values are calculated from each separated k-mer. These calculated values are fed as input to the Self Organizing Map for the purpose of clustering. Then obtained clusters are given to the Longest Common Sub Sequence (LCSS) algorithm for finding common subsequence which presents in every clusters. It returns nx(n-1)/2 subsequence for each cluster where n is number of k-mer in a specific cluster. Experimental outcomes of this proposed system produce the possible number of longest common subsequence of normal and disease affected DNA data. Thus the proposed system will be a good initiative aid for finding disease causing sequence. Finally, performance analysis is carried out for different DNA sequences. The obtained values show that the retrieval of LCSS is done in a shorter time than the existing system.

Keywords: clustering, k-mers, longest common subsequence, SOM

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Authors: Dr. Dionysis Panos Dpt. Communication, Internet Studies Cyprus University of Technology

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The widespread use of New Media and particularly Social Media, through fixed or mobile devices, has changed in a staggering way our perception about what is “intimate" and "safe" and what is not, in interpersonal communication and social relationships. The distribution of self and identity-related information in communication now evolves under new and different conditions and contexts. Consequently, this new framework forces us to rethink processes and mechanisms, such as what "exposure" means in interpersonal communication contexts, how the distinction between the "private" and the "public" nature of information is being negotiated online, how the "audiences" we interact with are understood and constructed. Drawing from an interdisciplinary perspective that combines sociology, communication psychology, media theory, new media and social networks research, as well as from the empirical findings of a longitudinal comparative research, this work proposes an integrative model for comprehending mechanisms of personal information management in interpersonal communication, which can be applied to both types of online (Computer-Mediated) and offline (Face-To-Face) communication. The presentation is based on conclusions drawn from a longitudinal qualitative research study with 458 new media users from 24 countries for almost over a decade. Some of these main conclusions include: (1) There is a clear and evidenced shift in users’ perception about the degree of "security" and "familiarity" of the Web, between the pre- and the post- Web 2.0 era. The role of Social Media in this shift was catalytic. (2) Basic Web 2.0 applications changed dramatically the nature of the Internet itself, transforming it from a place reserved for “elite users / technical knowledge keepers" into a place of "open sociability” for anyone. (3) Web 2.0 and Social Media brought about a significant change in the concept of “audience” we address in interpersonal communication. The previous "general and unknown audience" of personal home pages, converted into an "individual & personal" audience chosen by the user under various criteria. (4) The way we negotiate the nature of 'private' and 'public' of the Personal Information, has changed in a fundamental way. (5) The different features of the mediated environment of online communication and the critical changes occurred since the Web 2.0 advance, lead to the need of reconsideration and updating the theoretical models and analysis tools we use in our effort to comprehend the mechanisms of interpersonal communication and personal information management. Therefore, is proposed here a new model for understanding the way interpersonal communication evolves, based on a revision of social penetration theory.

Keywords: new media, interpersonal communication, social penetration theory, communication exposure, private information, public information

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: S. Gokul Prassad, S. Aakash, K. Malar Mohan

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In the process to cope with the challenges faced by the automobile industry in providing ride comfort, the electronics and control systems play a vital role. The control systems in an automobile monitor various parameters, controls the performances of the systems, thereby providing better handling characteristics. The automobile suspension system is one of the main systems that ensure the safety, stability and comfort of the passengers. The system is solely responsible for the isolation of the entire automobile from harmful road vibrations. Thus, integration of the control systems in the automobile suspension system would enhance its performance. The diverse road conditions of India demand the need of an efficient suspension system which can provide optimum ride comfort in all road conditions. For any passenger vehicle, the design of the suspension system plays a very important role in assuring the ride comfort and handling characteristics. In recent years, the air suspension system is preferred over the conventional suspension systems to ensure ride comfort. In this article, the ride comfort of the adaptive suspension system is compared with that of the passive suspension system. The schema is created in MATLAB/Simulink environment. The system is controlled by a proportional integral differential controller. Tuning of the controller was done with the Particle Swarm Optimization (PSO) algorithm, since it suited the problem best. Ziegler-Nichols and Modified Ziegler-Nichols tuning methods were also tried and compared. Both the static responses and dynamic responses of the systems were calculated. Various random road profiles as per ISO 8608 standard are modelled in the MATLAB environment and their responses plotted. Open-loop and closed loop responses of the random roads, various bumps and pot holes are also plotted. The simulation results of the proposed design are compared with the available passive suspension system. The obtained results show that the proposed adaptive suspension system is efficient in controlling the maximum over shoot and the settling time of the system is reduced enormously.

Keywords: automobile suspension, MATLAB, control system, PID, PSO

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Authors: Kimberley K. Whyte-Jones

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Public participation may improve the quality of environmental management decisions. However, the quality of such a decision is strongly dependent on the quality of the process that leads to it. In order to ensure an effective and efficient process, key features of best practice in participation should be carefully observed; this would also combat disillusionment of citizens, decision-makers and practitioners. The overarching aim of this study is to determine what constitutes an effective public participation process relevant to the Newfoundland and Labrador, Canada context, and to discover whether the public participation process that led to the 2014-2024 Provincial Sustainable Forest Management Strategy (PSFMS) met best practices criteria. The research design uses an exploratory case study strategy to consider a specific participatory process in environmental decision-making in Newfoundland and Labrador. Data collection methods include formal semi-structured interviews and the review of secondary data sources. The results of this study will determine the validity of a specific public participation best practice framework. The findings will be useful for informing citizen participation processes in general and will deduce best practices in public participation in environmental management in the province. The study is, therefore, meaningful for guiding future policies and practices in the management of forest resources in the province of Newfoundland and Labrador, and will help in filling a noticeable gap in research compiling best practices for environmentally related public participation processes.

Keywords: best practices, environmental decision-making, forest management, public participation

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Authors: Adel A. Ghobbar, Ahmad Bakkar

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Although special care is given to maintenance, aircraft systems fail, and these failures cause delays and cancellations. The occurrence of Delays and Cancellations affects operators and manufacturers negatively. To reduce technical delays and cancellations, one should be able to determine the important systems causing them. The goal of this research is to find a method to define the most expensive delays and cancellations systems for Airline operators. A predictive model was introduced to forecast the failure and their impact after carrying out research that identifies relevant information to tackle the problems faced while answering the questions of this paper. Data were obtained from the manufacturers’ services reliability team database. Subsequently, delays and cancellations evaluation methods were identified. No cost estimation methods were used due to their complexity. The model was developed, and it takes into account the frequency of delays and cancellations and uses weighting factors to give an indication of the severity of their duration. The weighting factors are based on customer experience. The data Analysis approach has shown that delays and cancellations events are not seasonal and do not follow any specific trends. The use of weighting factor does have an influence on the shortlist over short periods (Monthly) but not the analyzed period of three years. Landing gear and the navigation system are among the top 3 factors causing delays and cancellations for all three aircraft types. The results did confirm that the cooperation between certain operators and manufacture reduce the impact of delays and cancellations.

Keywords: reliability, availability, delays & cancellations, aircraft maintenance

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Authors: Jay Gohel, Anant Parghi

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A tuned liquid column damper (TLCD) is a modified passive system of tuned mass damper, where a liquid is used in place of mass in the structure. A TLCD consists of U-shaped tube with an orifice that produces damping against the liquid motion in the tube. This paper provides a state-of-the-art review on the vibration control of wind and earthquake excited structures using liquid dampers. Further, the paper will also discuss the theoretical background of TCLD, history of liquid dampers and existing literature on experimental, numerical, and analytical study. The review will also include different configuration of TLCD viz single TLCD, multi tuned liquid column damper (MTLCD), TLCD-Interior (TLCDI), tuned liquid column ball damper (TLCBD), tuned liquid column ball gas damper (TLCBGD), and pendulum liquid column damper (PLCD). The dynamic characteristics of the different configurate TLCD system and their effectiveness in reducing the vibration of structure will be discussed. The effectiveness of semi-active TLCD will be also discussed with reference to experimental and analytical results. In addition, the review will also provide the numerous examples of implemented TLCD to control the vibration in real structures. Based on the comprehensive review of literature, some important conclusions will be made and the need for future research will be identified for vibration control of structures using TLCD.

Keywords: earthquake, wind, tuned liquid column damper, passive response control, structures

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Authors: Rudzani Manafe, Ezekiel Green

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Brucella, has many different virulence factors that act as a causative agent of brucellosis, depending on the environment and other factors, some factors may play a role more than others during infection and as a result, play a role in becoming a causative agent for pathogenesis. Brucella melitensis and Brucella abortus are considered to be pathogenic to humans. The genetic regularity of nine potential causes of virulence of two Brucella species in Eastern Cape livestock have been examined. A hundred and twenty isolates obtained from Molecular Pathogenesis and Molecular Epidemiology Research Group (MPMERG) were used for this study. All isolates were grown on Brucella agar medium. Nine primer pairs were used for the detection of virB2, virB5, vceC, btpA, btpB, prpA, betB, bpe275, and bspB virulence factors using Polymerase chain reaction (PCR). Approximately 100% was observed for genes BecC and BetB from B. arbotus. While the lowest gene observed was PrpA at 4.6% from B. arbotus. BetB was detected in 34.7%, while virB2 and prpA (0%) were not detected in B. melitensis. The results from this research suggest that most isolates of Brucella have virulence-related genes associated with disease pathogenesis. Finally, our findings showed that Brucella strains in the Eastern Cape Province are extremely virulent as virulence characteristics exist in most strains investigated.

Keywords: putative virulence genes, brucella, polymerase chain reaction, milk

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Authors: Álvaro Turriago-Hoyos

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Most research tends to see innovation as an explanatory factor in achieving high levels of competitiveness and productivity. More recent studies have begun to analyze the determinants of innovation in the services sector as opposed to the much-discussed industrial sector of a country’s economy. This research paper focuses on the services sector in Colombia, one of Latin America’s fastest growing and biggest economies. Over the past decade, much of Colombia’s economic expansion has relied on commodity exports (mainly oil and coffee) whilst the industrial sector has performed relatively poorly. Such developments highlight the potential of the innovative role played by the services sector of the Colombian economy and its future growth prospects. This research paper analyzes the relationship between inputs, which at the same time are internal sources of innovation (such as R&D activities), and external sources that are improved by technology acquisition. The outputs are basically the four kinds of innovation that the OECD Oslo Manual recognizes: product, process, marketing and organizational innovations. The instrument used to measure this input-output relationship is based on Knowledge Production Function approaches. We run Probit models in order to identify the existing relationships between the above inputs and outputs, but also to identify spill-overs derived from interactions of the components of the value chain of the services firms analyzed: customers, suppliers, competitors, and complementary firms. Data are obtained from the Colombian National Administrative Department of Statistics for the period 2008 to 2013 published in the II and III Colombian National Innovation Survey. A short summary of the results obtained lead to conclude that firm size and a firm’s level of technological development turn out to be important discriminating factors for the description of the innovative process at the firm level. The model’s outcomes show a positive impact on the probability of introducing any kind of innovation both on R&D and Technology Acquisition investment. Also, cooperation agreements with customers, research institutes, competitors, and the suppliers are significant. Belonging to a particular industrial group is an important determinant but only to product and organizational innovation. It is possible to establish that Health Services, Education, Computer, Wholesale trade, and Financial Intermediation are the ISIC sectors, which report the highest number of frequencies of the considered set of firms. Those five sectors of the sixteen considered, in all cases, explained more than half of the total of all kinds of innovations. Product Innovation, which is followed by Marketing Innovation, gets the highest results. Displaying the same set of firms distinguishing by size, and belonging to high and low tech services sector shows that the larger the firms the larger a number of innovations, but also that always high-tech firms show a better innovation performance.

Keywords: Colombia, determinants of innovation, innovation, services sector

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Authors: Marek Gancarz, Agnieszka Nawrocka, Robert Rusinek, Marcin Tadla

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Volatile organic compounds (VOCs) are the fungi metabolites in the gaseous form produced during improper storage of agricultural commodities (e.g. grain, food). The spoilt commodities produce a wide range of VOCs including alcohols, esters, aldehydes, ketones, alkanes, alkenes, furans, phenols etc. The characteristic VOCs and odours can be determined by using electronic nose (e-Nose) which contains a matrix of different kinds of sensors e.g. resistive sensors. The aim of the present studies was to determine relationship between response of the resistive sensors on the chosen volatiles and their concentration. According to the literature, it was chosen volatiles characteristic for the cereals: ethanol, 3-methyl-1-butanol and hexanal. Analysis of the sensor signals shows that a signal shape is different for the different substances. Moreover, each VOC signal gives information about a maximum of the normalized sensor response (R/Rmax), an impregnation time (tIM) and a cleaning time at half maximum of R/Rmax (tCL). These three parameters can be regarded as a ‘VOC fingerprint’. Seven resistive sensors (TGS2600-B00, TGS2602-B00, TGS2610-C00, TGS2611-C00, TGS2611-E00, TGS2612-D00, TGS2620-C00) produced by Figaro USA Inc., and one (AS-MLV-P2) produced by AMS AG, Austria were used. Two out of seven sensors (TGS2611-E00, TGS2612-D00) did not react to the chosen VOCs. The most responsive sensor was AS-MLV-P2. The research was supported by the National Centre for Research and Development (NCBR), Grant No. PBS2/A8/22/2013.

Keywords: agricultural commodities, organic compounds, resistive sensors, volatile

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Authors: Joyly Jill Apud

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Corruption is an all-encompassing issue worldwide. Many attempts have been done to address such cases especially by the government through increasing transparency. The Philippine government increased the mechanism of transparency by opening to public its financial transactions through Full Disclosure Policy – mandating all local governments to post in their websites all financial transactions (Philippine Public Transparency Reporting Project, 2011). For transparency to be fully realized, the challenge lies in creating a mechanism where the constituents are encouraged to engage as social auditors. In line of the said challenge, the study focused in Davao City, Philippines measuring the respondent’s awareness, access and utilization of Full Disclosure Policy (FDP). Particularly, this study determined the significant difference on the awareness, access and utilization of respondents when grouped according to sector and the significant relationship between respondents’ awareness and in the access and utilization of FDP reports. The study used descriptive-correlation, Mean, Anova and Pearson R as statistical treatment. The 120 respondents are from the different sectors of Davao City. These are the Academe, Youth, LGUs, NGOs, Business, and Church groups. The awareness of the respondents was measured in three main categories: Existence of the Policy, Content of the Policy and the Manner of Publication. Access and Utilization of the FDP reports is divided into three: Budget Reports, Procurement Reports and Special Purpose Fund Reports. Results showed that the respondents are moderately aware of the Policy. Though it manifested that the respondents are aware of the disclosure, they are unaware of the Full Disclosure Policy and Full Disclosure Policy Portal. Moreover, the respondents seldom access and utilize all the FDP reports. Further results revealed that there is a significant difference in the awareness and the access and utilization of FDP when grouped according to sector. Moreover, significant relationship in the awareness and the access and utilization of the FDP is evident. It showed that the higher the awareness on FDP, the higher the level of access and utilization on the FDP reports.

Keywords: corruption, e-governance, budget transparency, participation

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Authors: Niamh Herlihy, Helen Fischer, Rainer Sauerborn, Anneliese Depoux, Avner Bar-Hen, Antoine Flauhault, Stefanie Schütte

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In the recent decades, there has been an increase in the number of publications both in the scientific and grey literature on the potential health risks associated with climate change. Though interest in climate change and health is growing, there are still many gaps to adequately assess our future health needs in a warmer world. Generating a greater understanding of the health impacts of climate change could be a key step in inciting the changes necessary to decelerate global warming and to target new strategies to mitigate the consequences on health systems. A long term and broad overview of existing scientific literature in the field of climate change and health is currently missing in order to ensure that all priority areas are being adequately addressed. We conducted a scoping review of published peer-reviewed literature on climate change and health from two large databases, PubMed and Web of Science, between 1990 and 2015. A scoping review allowed for a broad analysis of this complex topic on a meta-level as opposed to a thematically refined literature review. A detailed search strategy including specific climate and health terminology was used to search the two databases. Inclusion and exclusion criteria were applied in order to capture the most relevant literature on the human health impact of climate change within the chosen timeframe. Two reviewers screened the papers independently and any differences arising were resolved by a third party. Data was extracted, categorized and coded both manually and using R software. Analytics and infographics were developed from results. There were 7269 articles identified between the two databases following the removal of duplicates. After screening of the articles by both reviewers 3751 were included. As expected, preliminary results indicate that the number of publications on the topic has increased over time. Geographically, the majority of publications address the impact of climate change and health in Europe and North America, This is particularly alarming given that countries in the Global South will bear the greatest health burden. Concerning health outcomes, infectious diseases, particularly dengue fever and other mosquito transmitted infections are the most frequently cited. We highlight research gaps in certain areas e.g climate migration and mental health issues. We are developing a database of the identified climate change and health publications and are compiling a report for publication and dissemination of the findings. As health is a major co-beneficiary to climate change mitigation strategies, our results may serve as a useful source of information for research funders and investors when considering future research needs as well as the cost-effectiveness of climate change strategies. This study is part of an interdisciplinary project called 4CHealth that confronts results of the research done on scientific, political and press literature to better understand how the knowledge on climate change and health circulates within those different fields and whether and how it is translated to real world change.

Keywords: climate change, health, review, mapping

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Authors: Ran Etgar, Yuval Cohen, Erel Avineri

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One of the major challenges of transportation in medium sized inner-cities (such as Tel-Aviv) is the last-mile solution. Personal rapid transit (PRT) seems like an applicable candidate for this, as it combines the benefits of personal (car) travel with the operational benefits of transit. However, the investment required for large area PRT grid is significant and there is a need to economically justify such investment by correctly evaluating the grid capacity. PRT main elements are small automated vehicles (sometimes referred to as podcars) operating on a network of specially built guideways. The research is looking at a specific concept of elevated PRT system. Literature review has revealed the drawbacks PRT modelling and simulation approaches, mainly due to the lack of consideration of technical and operational features of the system (such as headways, acceleration, safety issues); the detailed design of infrastructure (guideways, stations, and docks); the stochastic and sessional characteristics of demand; and safety regulations – all of them have a strong effect on the system performance. A highly detailed model of the system, developed in this research, is applying a discrete event simulation combined with an agent-based approach, to represent the system elements and the podecars movement logic. Applying a case study approach, the simulation model is used to study the capacity of the system, the expected throughput of the system, the utilization, and the level of service (journey time, waiting time, etc.).

Keywords: capacity, productivity measurement, PRT, simulation, transportation

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Authors: Liuhui Zhu, Peng Zeng

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With the rapid development in China, the urbanization has entered the transformation and promotion stage, and its direction of development has shifted to overall regional synergy. China has a large number of towns and villages, with comparative small scale and scattered distribution, which always support and provide resources to cities leading to urban-rural opposition, so it is difficult to achieve common development in a single town or village. In this context, the regional development should focus more on towns and villages to form a synergetic system, joining the regional association with cities. Thus, the paper raises the question about how to effectively organize towns and villages system to regulate the resource allocation and improve the comprehensive value of the regional area. To answer the question, it is necessary to find a suitable research unit and analysis of its present situation of towns and villages system for optimal development. By combing relevant researches and theoretical models, the county is the most basic administrative unit in China, which can directly guide and regulate the development of towns and villages, so the paper takes county as the research unit. Following the theoretical concept of ‘three structures and one network’, the paper concludes the research framework to analyse the present situation of towns and villages system, including scale structure, functional structure, spatial structure, and organization network. The analytical methods refer to the fractal theory and gravity model, using statistics and spatial data. The scale structure analyzes rank-size dimensions and uses the principal component method to calculate the comprehensive scale of towns and villages. The functional structure analyzes the functional types and industrial development of towns and villages. The spatial structure analyzes the aggregation dimension, network dimension, and correlation dimension of spatial elements to represent the overall spatial relationships. In terms of organization network, from the perspective of entity and ono-entity, the paper analyzes the transportation network and gravitational network. Based on the present situation analysis, the optimization strategies are proposed in order to achieve a synergetic relationship between towns and villages in the county area. The paper uses Suning county in the Beijing-Tianjin-Hebei region as a case study to apply the research framework and methods and then proposes the optimization orientations. The analysis results indicate that: (1) The Suning county is lack of medium-scale towns to transfer effect from towns to villages. (2) The distribution of gravitational centers is uneven, and the effect of gravity is limited only for nearby towns and villages. The gravitational network is not complete, leading to economic activities scattered and isolated. (3) The overall development of towns and villages system is immature, staying at ‘single heart and multi-core’ stage, and some specific optimization strategies are proposed. This study provides a regional view for the development of towns and villages and concludes the research framework and methods of towns and villages system for forming an effective synergetic relationship between them, contributing to organize resources and stimulate endogenous motivation, and form counter magnets to join the urban-rural integration.

Keywords: towns and villages system, organization structure, county area, fractal theory, gravity model

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Authors: Hasan Sungur, Evrim Baran, Benjamin Ahn, Aliye Karabulut Ilgu, Chris Rehmann, Cassandra Rutherford

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Engineering identity contributes to the professional and educational persistence of women engineers. A crucial factor contributing to the development of the engineering identity is recognition. Those without adequate recognition often do not succeed in positively building their identities. This research draws on Honneth’s recognition theory to identify factors impacting women civil engineers’ feelings of recognition as civil engineers. A survey was composed and distributed to 330 female alumni who graduated from the Department of Civil, Construction, and Environmental Engineering at Iowa State University in the last ten years. The survey items include demographics, perceptions of the identity of civil engineering, and factors that influence the recognition of civil engineering identities, such as views of society and family. Descriptive analysis of the survey responses revealed that the perceptions of civil engineering varied widely. Participants’ definitions of civil engineering included the terms: construction, design, and infrastructure. Almost half of the participants reported that the major reason to study civil engineering was their interest in the subject matter, and most reported that they were proud to be civil engineers. Many study participants reported that their parents see them as civil engineers. Treatment of institutions and the workplace were also considered as having a significant impact on the recognition of women civil engineers. Almost half of the participants reported that they felt isolated or ignored at work because of their gender. This research emphasizes the importance of recognition for the development of the civil engineering identity of women

Keywords: civil engineering, gender, identity, recognition

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Authors: Rizki Nor Amelia, Farida A. Setiawati

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This study aimed to: (1) describe the characteristics of teacher-made test instrument used to measure the ability of students’chemistry, and (2) identify the presence of the compability difficulty level set by teachers to difficulty level by empirical results. Based on these objectives, this study was a descriptive research. The analysis in this study used the Rasch model and Chi-square statistics. Analysis using Rasch Model was based on the response patterns of high school students to the teacher-made test instrument on chemistry subject Academic Year 2015/2016 in the Yogyakarta. The sample of this research were 358 students taken by cluster random sampling technique. The analysis showed that: (1) a teacher-made tests instrument has a medium on the mean difficulty level. This instrument is capable to measure the ability on the interval of -0,259 ≤ θ ≤ 0,659 logit. Maximum Test Information Function obtained at 18.187 on the ability +0,2 logit; (2) 100% items categorized either as easy or difficult by rasch model is match with the teachers’ judgment; while 37 items are categorized according to rasch model which 8.10% and 10.81% categorized as easy and difficult items respectively according to the teachers, the others are medium categorized. Overall, the distribution of the level of difficulty formulated by the teachers has the distinction (not match) to the level of difficulty based on the empirical results.

Keywords: chemistry, items parameter fitness, Rasch model, teacher-made test

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Authors: Robert Lindner

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In recent years a multitude of international efforts, including the United Nations’ aspirational 2030 Agenda for Sustainable Development, provided a new momentum to facilitate energy access and rural electrification projects to combat energy poverty in developing states in Asia. Rural electrification projects promise to facilitate other sustainable development aims, such as the empowerment of local communities through the creation of economic opportunities or increased disaster resilience. This study applies a multi-governance research framework to study the cases of the ongoing energy system transition in Myanmar and Cambodia. It explores what impact the international aid community, especially multilateral development banks and international development agencies, has on the governance of the transitions and how diverging aid donor interest shape policy making and project planning. The study is based on policy analysis and expert interviews, as well as extensive field research. It critically examines the current development trajectories and the strategies of the stakeholders involved. It concludes that institutional and technological competition between donors, as well as a lack of transparency and inclusion in the project planning and implementation phases, contributes to insufficient coordination in national energy policy making and project implementation at the local level. The study further discusses possible alternative approaches that might help to promote the spread of sustainable energy technologies.

Keywords: energy governance, developing countries, multi-level governance, energy transitions

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