Search results for: technological pedagogical model

Authors: Harpreet Kaur, Er. Arjun, Kirandeep Kaur, P. K. Mittal

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Simulation of a human body from a 20% gelatin & 80% water mixture is examined from a wound ballistics point of view. Parameters such as incapacitation energy & temporary to permanent cavity size & tools of hydrodynamics have been employed to arrive at a model of the human body similar to the one adopted by NATO. Calculations using equations of motion yield a value of 339 µs in which a temporary cavity with maximum size settles down to a permanent cavity. This occurs for 10mm size bullets & settles down to a permanent cavity in the case of 4 different bullets, i.e., 5.45, 5.56, 7.62,10 mm sizes. The obtained results are in excellent agreement with the body as a right circular cylinder of 15 cm height & 10 cm diameter. An effort is made here in this work to present a sound theoretical base to parameters commonly used in wound ballistics from field experience discussed by Col Coats & Major Beyer.

Keywords: gelatine, gunshot, hydrodynamic model, oscillation time, temporary and permanent cavity, wound ballistics

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Authors: Thomas Paris, Vincent Bruyere, Patrick Namy

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A numerical model is developed to simulate gas blowdowns through a thin tube and a filter (porous media), separating a high pressure gas filled reservoir to low pressure ones. Based on a previous work, a one-dimensional approach is developed by using the finite element method to solve the transient compressible flow and to predict the pressure and temperature evolution in space and time. Mass, momentum, and energy conservation equations are solved in a fully coupled way in the reservoirs, the pipes and the porous media. Numerical results, such as pressure and temperature evolutions, are firstly compared with experimental data to validate the model for different configurations. Couplings between porous media and pipe flow are then validated by checking mass balance. The influence of the porous media and the nature of the gas is then studied for different initial high pressure values.

Keywords: compressible flow, fluid mechanics, heat transfer, porous media

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Authors: Alireza Ghadiri, Soheila Memarzadeh, Arash Ghadiri

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Heat pipes are efficient heat transfer devices for solar hot water heating systems. However, the effective downward transfer of solar energy in an integrated heat pipe system provides increased design and implementation options. There is a lack of literature about flat plate wicked assisted heat pipe solar collector, especially with the presence of finned water-cooled condenser wicked heat pipes for solar energy applications. In this paper, the consequence of incorporating fins arrays into the condenser region of screen mesh heat pipe solar collector is investigated. An experimental model and a transient theoretical model are conducted to compare the performances of the solar heating system at a different period of the year. A good agreement is shown between the model and the experiment. Two working fluids are investigated (water and methanol) and results reveal that water slightly outperforms methanol with a collector instantaneous efficiency of nearly 60%. That modest improvement is achieved by adding fins to the condenser region of the heat pipes. Results show that the collector efficiency increase as the number of fins increases (upon certain number) and reveal that the mesh number is an important factor which affect the overall collector efficiency. An optimal heat pipe mesh number of 100 meshes/in. With two layers appears to be favorable in such collectors for their design and operating conditions.

Keywords: heat pipe, solar collector, capillary limit, mesh number

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Authors: Jamie Sundvall, Lisa Jennings

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Site based field internship learning (SBL) is an educational approach within a Master’s of Social Work (MSW) university field placement department that promotes a more streamlined approach to the integration of theory and evidence based practices for social work students. The SBL model is founded on research in the field, consideration of current work force needs, United States national trends of MSW graduate skill and knowledge deficits, educational trends in students pursing a master’s degree in social work, and current social problems that require unique problem solving skills. This study explores the use of site-based learning in a hybrid social work program. In this setting, site based learning pairs online education courses and social work field education to create training opportunities for social work students within their own community and cultural context. Students engage in coursework in an online setting with both synchronous and asynchronous features that facilitate development of core competencies for MSW students. Through the SBL model, students are then partnered with faculty in a virtual course room and a university vetted site within their community. The study explores how this model of learning creates community partnerships, through which students engage in a learning loop to develop social work skills, while preparing students to address current community, social, and global issues with the engagement of technology. The goal of SBL is to more effectively equip social work students for practice according to current workforce demands, provide access to education and care to populations who have limited access, and create self-sustainable partnerships. Further, the model helps students learn integration of evidence based practices and helps instructors more effectively teach integration of ethics into practice. The study found that the SBL model increases the influence and professional relevance of the social work profession, and ultimately facilitates stronger approaches to integrating theory into practice. Current implementation of the practice in the United States will be presented in the study. dditionally, future research conceptualization of SBL models will be presented, in order to collaborate on advancing best approaches of translating theory into practice, according to the current needs of the profession and needs of social work students.

Keywords: collaboration, fieldwork, research, site-based learning, technology

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Authors: Yagya Murti Aryal, Bipin Adhikari, Pradeep Gyawali

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The Lesser Himalaya zone of Nepal consists of thrusting and folding belts, which play an important role in the sustainable management of groundwater in the Himalayan regions. The study area is located in the Dolakha and Ramechhap Districts of Bagmati Province, Nepal. Geologically, these districts are situated in the Lesser Himalayas and partly encompass the Higher Himalayan rock sequence, which includes low-grade to high-grade metamorphic rocks. Following the Gorkha Earthquake in 2015, numerous springs dried up, and many others are currently experiencing depletion due to the distortion of the natural groundwater flow. The primary objective of this study is to identify potential groundwater areas and determine suitable sites for artificial groundwater recharge. Two distinct statistical approaches were used to develop models: The Frequency Ratio (FR) and Shannon Entropy (SE) methods. The study utilized both primary and secondary datasets and incorporated significant role and controlling factors derived from field works and literature reviews. Field data collection involved spring inventory, soil analysis, lithology assessment, and hydro-geomorphology study. Additionally, slope, aspect, drainage density, and lineament density were extracted from a Digital Elevation Model (DEM) using GIS and transformed into thematic layers. For training and validation, 114 springs were divided into a 70/30 ratio, with an equal number of non-spring pixels. After assigning weights to each class based on the two proposed models, a groundwater potential map was generated using GIS, classifying the area into five levels: very low, low, moderate, high, and very high. The model's outcome reveals that over 41% of the area falls into the low and very low potential categories, while only 30% of the area demonstrates a high probability of groundwater potential. To evaluate model performance, accuracy was assessed using the Area under the Curve (AUC). The success rate AUC values for the FR and SE methods were determined to be 78.73% and 77.09%, respectively. Additionally, the prediction rate AUC values for the FR and SE methods were calculated as 76.31% and 74.08%. The results indicate that the FR model exhibits greater prediction capability compared to the SE model in this case study.

Keywords: groundwater potential mapping, frequency ratio, Shannon’s Entropy, Lesser Himalaya Zone, sustainable groundwater management

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Authors: Yogesh C. Sharma, A. Seetharaman

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The decision-making process in humans is a complicated system influenced by a variety of intrinsic and extrinsic factors. Human decisions have a ripple effect on subsequent decisions. In this study, the scope of human decision making is limited to employees. In an organisation, a person makes a variety of decisions from the time they are hired to the time they retire. The goal of this research is to identify various elements that influence decision-making. In addition, the environment in which a decision is made is a significant aspect of the decision-making process. Employees in today's workplace use artificial intelligence (AI) systems for automation and decision augmentation. The impact of AI systems on the decision-making process is examined in this study. This research is designed based on a systematic literature review. Based on gaps in the literature, limitations and the scope of future research have been identified. Based on these findings, a research framework has been designed to identify various factors affecting employee decision making. Employee decision making is influenced by technological advancement, data-driven culture, human trust, decision automation-augmentation, and workplace motivation. Hybrid human-AI systems require the development of new skill sets and organisational design. Employee psychological safety and supportive leadership influences overall job satisfaction.

Keywords: employee decision making, artificial intelligence (AI) environment, human trust, technology innovation, psychological safety

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Authors: Talib M. Albayati, Omar S. Mahdy, Ghanim M. Alwan

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This work is aimed to prepare magnetic nanoporous material Fe/MCM-41 and study its Physical characterization in order to enhance the magnetic properties for study the operating conditions on separation efficiency of methyl orange (MO) from wastewater by adsorption process. The experimental results are analysed to select the best operating conditions for different studied parameters which were obtained for both adsorbents mesoporous material samples MCM-41 and magnetic Fe/MCM-41 as follow: constant temperature (20 ºC), pH: (2) adsorbent dosage (0.03 gm), contact time (10 minute) and concentrations (30 mg/L). The results are demonstrated that the adsorption processes can be well fitted by the Langmuir isotherm model for pure MCM-41 with a higher correlation coefficient (0.999) and fitted by the freundlich isotherm model for magnetic Fe/MCM-41 with a higher correlation coefficient of (0.994).

Keywords: adsorption, nanoporous materials, mcm-41, magnetic material, wastewater, orange, wastewater

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Authors: Abdi Omar Shuriye

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A social business is a business designed to address socio-economic problems to enhance the welfare of the communities involved. Lately, social business, with its focus on innovative ideas, is capturing the interest of educational institutions, governments, and non-governmental organizations. Social business uses a business model to achieve a social goal, and in the last few decades, the idea of imbuing social business into the education system of higher learning institutions has spurred much excitement. This is due to the belief that it will lead to job creation and increased social resilience. One of the higher learning institutions which have invested immensely in the idea is Albukhari International University; it is a private education institution, on a state-of-the-art campus, providing an advantageous learning ecosystem. The niche area of this institution is social business, and it graduates job creators, not job seekers; this Malaysian institution is unique and one of its kind. The objective of this paper is to develop a work plan, direction, and milestone as well as the focus area for the infusion of social business into higher learning institutions with special reference to Al-Bukhari International University. The purpose is to develop a prototype and model full-scale to enable higher learning education institutions to construct the desired curriculum fermented with social business. With this model, major predicaments faced by these institutions could be overcome. The paper sets forth an educational plan and will spell out the basic tenets of social business, focusing on the nature and implementational aspects of the curriculum. It will also evaluate the mechanisms applied by these educational institutions. Currently, since research in this area remains scarce, institutions adopt the process of experimenting with various methods to find the best way to reach the desired result on the matter. The author is of the opinion that social business in education is the main tool to educate holistic future leaders; hence educational institutions should inspire students in the classroom to start up their own businesses by adopting creative and proactive teaching methods. This proposed model is a contribution in that direction.

Keywords: social business, curriculum, skills, university

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Authors: Chris Schoborg, Morgan C. Wang

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In the realm of the National Football League (NFL), substantial dedication of time and effort is invested by both players and coaches in meticulously analyzing the game footage of their opponents. The primary aim is to anticipate the actions of the opposing team. Defensive players and coaches are especially focused on deciphering their adversaries' intentions to effectively counter their strategies. Acquiring insights into the specific play type and its intended direction on the field would confer a significant competitive advantage. This study establishes pre-snap information as the cornerstone for predicting both the play type (e.g., deep pass, short pass, or run) and its spatial trajectory (right, left, or center). The dataset for this research spans the regular NFL season data for all 32 teams from 2013 to 2022. This dataset is acquired using the nflreadr package, which conveniently extracts play-by-play data from NFL games and imports it into the R environment as structured datasets. In this study, we employ a recently developed machine learning algorithm, XGBoost. The final predictive model achieves an impressive lift of 2.61. This signifies that the presented model is 2.61 times more effective than random guessing—a significant improvement. Such a model has the potential to markedly enhance defensive coaches' ability to formulate game plans and adequately prepare their players, thus mitigating the opposing offense's yardage and point gains.

Keywords: lift, NFL, sports analytics, XGBoost

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Authors: Sujit Kumar Pradhan, Anil Kumar, Vijay Kumar

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The testing process of the software during the software development time is a crucial step as it makes the software more efficient and dependable. To estimate software’s reliability through the mean value function, many software reliability growth models (SRGMs) were developed under the assumption that operating and testing environments are the same. Practically, it is not true because when the software works in a natural field environment, the reliability of the software differs. This article discussed an SRGM comprising change-point and imperfect debugging in a simulated testing environment. Later on, we extended it in a multi-release direction. Initially, the software was released to the market with few features. According to the market’s demand, the software company upgraded the current version by adding new features as time passed. Therefore, we have proposed a generalized multi-release SRGM where change-point and imperfect debugging concepts have been addressed in a simulated testing environment. The failure-increasing rate concept has been adopted to determine the change point for each software release. Based on nine goodness-of-fit criteria, the proposed model is validated on two real datasets. The results demonstrate that the proposed model fits the datasets better. We have also discussed the optimal release time of the software through a cost model by assuming that the testing and debugging costs are time-dependent.

Keywords: software reliability growth models, non-homogeneous Poisson process, multi-release software, mean value function, change-point, environmental factors

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Authors: Tatsuya Yamazaki, Kazuya Miyakawa, Tomohiko Sugiyama, Toshitaka Iwatani

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The introduction of sensor technologies into agriculture is a necessary step to realize Precision Agriculture. Although sensing methodologies themselves have been prevailing owing to miniaturization and reduction in costs of sensors, there are some difficulties to analyze and understand the sensing data. Targeting at pears ’Le Lectier’, which is particular to Niigata in Japan, cultivation environmental data have been collected at pear fields by eight sorts of sensors: field temperature, field humidity, rain gauge, soil water potential, soil temperature, soil moisture, inner-bag temperature, and inner-bag humidity sensors. With regard to the inner-bag temperature and humidity sensors, they are used to measure the environment inside the fruit bag used for pre-harvest bagging of pears. In this experiment, three kinds of fruit bags were used for the pre-harvest bagging. After over 100 days continuous measurement, volumes of sensing data have been collected. Firstly, correlation analysis among sensing data measured by respective sensors reveals that one sensor can replace another sensor so that more efficient and cost-saving sensing systems can be proposed to pear farmers. Secondly, differences in characteristic and performance of the three kinds of fruit bags are clarified by the measurement results by the inner-bag environmental sensing. It is found that characteristic and performance of the inner-bags significantly differ from each other by statistical analysis. Lastly, a relational model between the sensing data and the pear outlook quality is established by use of Structural Equation Model (SEM). Here, the pear outlook quality is related with existence of stain, blob, scratch, and so on caused by physiological impair or diseases. Conceptually SEM is a combination of exploratory factor analysis and multiple regression. By using SEM, a model is constructed to connect independent and dependent variables. The proposed SEM model relates the measured sensing data and the pear outlook quality determined on the basis of farmer judgement. In particularly, it is found that the inner-bag humidity variable relatively affects the pear outlook quality. Therefore, inner-bag humidity sensing might help the farmers to control the pear outlook quality. These results are supported by a large quantity of inner-bag humidity data measured over the years 2014, 2015, and 2016. The experimental and analytical results in this research contribute to spreading Precision Agriculture technologies among the farmers growing ’Le Lectier’.

Keywords: precision agriculture, pre-harvest bagging, sensor fusion, structural equation model

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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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Authors: Trieu Anh Ngoc, Nguyen Quang Kim

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Located at the downstream of the Mekong Delta, the Vietnamese Mekong Delta is well-known as 'rice bowl' of Vietnam. The Vietnamese Mekong Delta experiences widespread flooding annually where is habitat for about 17 million people. The economy of this region mainly depends on the agricultural productivities. The suspended sediment load in the Mekong River plays an important role in carrying contaminants and nutrients to the delta and changing the geomorphology of the delta river system. In many past decades, flooding and suspended sediment were considered as indispensable factors in agricultural cultivations. Although flooding in the wet season caused serious inundation in paddy field and affected livelihoods, it is an effective facility for flushing acid and saline to this area - alluvial soil heavily contaminated with acid and salt intrusion. In addition, sediment delivery to this delta contained rich-nutrients distributed and deposited on the fields through flooding process. In recent decades, the changing of flow and sediment transport have been strongly and clearly occurring due to upstream dam development and climate change. However, effects of sediment delivery on agricultural cultivations were less attention. This study investigated the impacts of upstream flow on sediment distribution in the Vietnamese Mekong Delta. Flow fluctuation and sediment distribution were simulated by the Mike 11 model, including hydrodynamics model and advection-dispersion model. Various scenarios were simulated based on anticipated upstream discharges. Our findings indicated that sediment delivery into the Vietnamese Mekong Delta come from not only Tien River but also border of Cambodia floodplains. Sediment distribution in the Vietnamese Mekong Delta is dramatically changed by the distance from the main rivers and the secondary channels. The dam development in the upstream is one of the major factors leading a decrease in sediment discharge as well as sediment deposition. Moreover, sea level rise partially contributed to decrease in sediment transport and change of sediment distribution between upstream and downstream of the Vietnamese Mekong Delta.

Keywords: sediment transport, sea level rise, climate change, Mike Model

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Authors: Azhar Naila, Steuer Benjamin

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Over-exploitation of resources and the burden on natural systems have provoked worldwide concerns about the potential resource as well as supply risks in the future. It has been estimated that the consumption of materials and resources will double by 2060, substantially mounting the amount of waste and emissions produced by individuals, organizations, and businesses, which necessitates sustainable technological innovations to address the problem. Therefore, there is a need to design products and services purposefully for material resource efficiency. This directs us toward the conceptualization and implementation of the ‘Circular Economy (CE),’ which has gained considerable attention among policymakers, researchers, and businesses in the past decade. A large amount of literature focuses on the concept of CE. However, contextual empirical research on the need to embrace CE in an emerging economy like Pakistan is still scarce, where the traditional economic model of take-make-dispose is quite common. Textile exports account for approximately 61% of Pakistan's total exports, and the industry provides employment for about 40% of the country's total industrial workforce. The industry provides job opportunities to above 10 million farmers, with cotton as the main crop of Pakistan. Consumers, companies, as well as the government have explored very limited CE potential in the country. This gap has motivated us to carry out the present study. The study is based on a mixed method approach, for which key informant interviews have been conducted to get insight into the present situation of the ecosystem readiness for the adoption of CE in 20 textile manufacturing industries. The subject study has been conducted on the following areas i) the level of understanding of the CE concept among key stakeholders in the textile manufacturing industry ii) Companies are pushing boundaries to invest in circularity-based initiatives, exploring the depths of risk-taking iii) the current national policy framework support the adoption of CE. Qualitative assessment has been undertaken using MAXQDA to analyze the data received after the key informant interviews. The data has been transcribed and coded for further analysis. The results show that most of the key stakeholders have a clear understanding of the concept, whereas few consider it to be only relevant to the end-of-life treatment of waste generated from the industry. Non-governmental organizations have been observed to be key players in creating awareness among the manufacturing industries. Maximum companies have shown their consent to invest in initiatives related to the adoption of CE. Whereas a few consider themselves far behind the race due to a lack of financial resources and support from responsible institutions. Mostly, the industries have an ambitious vision for integrating CE into the company’s policy but seem not to be ready to take any significant steps to nurture a culture for experimentation. However, the government is not playing any vital role in the transition towards CE; rather, they have been busy with the state’s uncertain political situation. Presently, Pakistan does not have any policy framework that supports the transition towards CE. Acknowledging the present landscape a well-informed CE transition is immediately required.

Keywords: circular economy, textile supply chain, textile manufacturing industries, resource efficiency, ecosystem readiness, multi-case study analysis

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Authors: M. G. Shilina

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The prospects for political and economic development of the Eurasian space are currently discussed at both governmental and expert levels. New concepts actively proposed by the Eurasian governments require the analysis and search for effective implementation options. In the paper, an attempt to identify effective solutions to the problems surrounding the current economic integration of the Eurasian states is given on the basis of an interdisciplinary, comprehensive, structured analysis. The phenomenon is considered through the prism of the international law, world economy and politics, combined with the study of existing intergovernmental practice. The modeling method was taken as the basis for the research and is supplemented by legal and empirical methods. The detailed multi-level model of practical construction the 'Great Eurasia' (the GE) concept is proposed, the option for building a phased interaction in Eurasia is given through the prism of construction by the Eurasian Economic Union (the EAEU) as the main tool. The Shanghai Cooperation Organization (the SCO) is seen as the most promising element of the model. The SCO is capable of streamlining the formation of the GE and determine the transformation of Eurasia into a common economic space. Effective development of the economic integration between Eurasian states on the framework of the SCO is optimal. The SCO+ could be used as a platform for integration-integration processes formation. The creation of stable financial ties could become the basis for the possible formation of an expanded transregional integration platform. The paper concludes that the implementation of the proposed model could entail a gradual economic rapprochement of Eurasia and beyond.

Keywords: economic integration, The Eurasian Economic Union, The European Union, The Shanghai Cooperation Organization, the silk road economic belt

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Authors: Bundit Pungnirund

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The purposes of this research were to develop and to monitor the antecedent factors which directly affected the success rate of new product development. This was a case study of the leather industry in Bangkok, Thailand. A total of 350 leather factories were used as a sample group. The findings revealed that the new product development model was harmonized with the empirical data at the acceptable level, the statistic values are: x^2=6.45, df= 7, p-value = .48856; RMSEA = .000; RMR = .0029; AGFI = .98; GFI = 1.00. The independent variable that directly influenced the dependent variable at the highest level was marketing outcome which had a influence coefficient at 0.32 and the independent variables that indirectly influenced the dependent variables at the highest level was a clear organization policy which had a influence coefficient at 0.17, whereas, all independent variables can predict the model at 48 percent.

Keywords: antecedent, new product development, leather industry, Thailand

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Authors: Fahad Suleiman

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Queuing, in medical system is the process of moving patients in a specific sequence to a specific service according to the patients’ nature of illness. The term scheduling stands for the process of computing a schedule. This may be done by a queuing based scheduler. This paper focuses on the medical consultancy system, the different queuing algorithms that are used in healthcare system to serve the patients, and the average waiting time. The aim of this paper is to build automatic queuing system for organizing the medical queuing system that can analyses the queue status and take decision which patient to serve. The new queuing architecture model can switch between different scheduling algorithms according to the testing results and the factor of the average waiting time. The main innovation of this work concerns the modeling of the average waiting time is taken into processing, in addition with the process of switching to the scheduling algorithm that gives the best average waiting time.

Keywords: queuing systems, queuing system models, scheduling algorithms, patients

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Authors: Widi Astuti, Rizki Agus Hermawan, Hariono Mukti, Nurul Retno Sugiyono

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The removal of lead ion (Pb²⁺) from aqueous solution by activated carbon with phosphoric acid activation employing mangrove propagule as precursor was investigated in a batch adsorption system. Batch studies were carried out to address various experimental parameters including pH and contact time. The Langmuir and Freundlich models were able to describe the adsorption equilibrium, while the pseudo first order and pseudo second order models were used to describe kinetic process of Pb²⁺ adsorption. The results show that the adsorption data are seen in accordance with Langmuir isotherm model and pseudo-second order kinetic model.

Keywords: activated carbon, adsorption, equilibrium, kinetic, lead, mangrove propagule

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Authors: Umer Mukhtar

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Supply Chain Competitiveness is the capability of a supply chain to deliver value to the customer for the sake of competitive advantage. Service Performance and Quality intervene between supply chain actors including functions inside the firm in a significant way for the supply chain to achieve a competitive position in the market to gain competitive advantage. Supply Chain competitiveness is the current issue of interest because of supply chains’ competition for competitive advantage rather than firms’. A proposed theoretical model is developed by extracting and integrating different theories to pursue further inquiry based on case studies and survey design. It is also intended to develop a scale of service performance for functions of the focal firm that is a revolving center for a whole supply chain.

Keywords: supply chain competitiveness, service performance in supply chain, service quality in supply chain, competitive advantage by supply chain, networks and supply chain, customer value, value supply chain, value chain

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Authors: Hartani Kada, Merah Abdelkader

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Aiming at the high nonlinearities and unmatched uncertainties of the intelligent electric vehicles’ dynamic system, this paper presents a lateral motion control algorithm for intelligent electric vehicles with four in-wheel motors. A fuzzy logic procedure is presented and formulated to realize lateral control in lane change. The vehicle dynamics model and a desired target tracking model were established in this paper. A fuzzy logic controller was designed for integrated active front steering (AFS) and direct yaw moment control (DYC) in order to improve vehicle handling performance and stability, and a fuzzy controller for the automatic steering problem. The simulation results demonstrate the strong robustness and excellent tracking performance of the control algorithm that is proposed.

Keywords: fuzzy logic, lateral control, AFS, DYC, electric car technology, longitudinal control, lateral motion

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Authors: Sa’ed Abed, Mohammad H. Al Shayeji, Ovais Ahmed, Sahel Alouneh

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Session Initiation Protocol (SIP) is a signaling layer protocol for building, adjusting and ending sessions among participants including Internet conferences, telephone calls and multimedia distribution. SIP facilitates user movement by proxying and forwarding requests to the present location of the user. In this paper, we provide a formal Specification and Description Language (SDL) and Message Sequence Chart (MSC) to model and define the Internet Engineering Task Force (IETF) SIP protocol and its sample services resulted from informal SIP specification. We create an “Abstract User Interface” using case analysis so that can be applied to identify SIP services more explicitly. The issued sample SIP features are then used as case scenarios; they are revised in MSCs format and validated to their corresponding SDL models.

Keywords: modeling, MSC, SDL, SIP, validating

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Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Taif Rocky, Uttam Saha, Mahobul Islam

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With a rapid urbanisation in Bangladesh, waste management remains one of the core challenges. Turning municipal waste into biogas for mass usage is a solution that Bangladesh needs to adopt urgently. Practical Action with its commitment to challenging poverty with technological justice has piloted such idea in Gaibandha. The initiative received immense success and drew the attention of policy makers and practitioners. We believe, biogas from waste can highly contribute to meet the growing demand for energy in the country at present and in the future. Practical Action has field based experience in promoting small scale and innovative technologies. We have proven track record in integrated solid waste management. We further utilized this experience to promote waste to biogas at end users’ level. In 2011, we have piloted a project on waste to biogas in Gaibandha, a northern secondary town of Bangladesh. With resource and support from UNICEF and with our own innovative funds we have established a complete chain of utilizing waste to the renewable energy source and organic fertilizer. Biogas is produced from municipal solid waste, which is properly collected, transported and segregated by private entrepreneurs. The project has two major focuses, diversification of biogas end use and establishing a public-private partnership business model. The project benefits include Recycling of Wastes, Improved institutional (municipal) capacity, Livelihood from improved services and Direct Income from the project. Project risks include Change of municipal leadership, Traditional mindset, Access to decision making, Land availability. We have observed several outcomes from the initiative. Up scaling such an initiative will certainly contribute for sustainable cleaner and healthier urban environment and urban poverty reduction. - It reduces the unsafe disposal of wastes which improve the cleanliness and environment of the town. -Make drainage system effective reducing the adverse impact of water logging or flooding. -Improve public health from better management of wastes. -Promotes usage of biogas replacing the use of firewood/coal which creates smoke and indoor air pollution in kitchens which have long term impact on health of women and children. -Reduce the greenhouse gas emission from the anaerobic recycling of wastes and contributes to sustainable urban environment. -Promote the concept of agroecology from the uses of bio slurry/compost which contributes to food security. -Creates green jobs from waste value chain which impacts on poverty alleviation of urban extreme poor. -Improve municipal governance from inclusive waste services and functional partnership with private sectors. -Contribute to the implementation of 3R (Reduce, Reuse, Recycle) Strategy and Employment Creation of extreme poor to achieve the target set in Vision 2021 by Government of Bangladesh.

Keywords: kitchen waste, secondary town, biogas, segregation

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Authors: Atheer Al-Nuaimi, Harry Evdorides

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Every day many people die or get disabled or injured on roads around the world, which necessitates more specific treatments for transportation safety issues. International road assessment program (iRAP) model is one of the comprehensive road safety models which accounting for many factors that affect road safety in a cost-effective way in low and middle income countries. In iRAP model road safety has been divided into five star ratings from 1 star (the lowest level) to 5 star (the highest level). These star ratings are based on star rating score which is calculated by iRAP methodology depending on road attributes, traffic volumes and operating speeds. The outcome of iRAP methodology are the treatments that can be used to improve road safety and reduce fatalities and serious injuries (FSI) numbers. These countermeasures can be used separately as a single countermeasure or mix as multiple countermeasures for a location. There is general agreement that the adequacy of a countermeasure is liable to consistent losses when it is utilized as a part of mix with different countermeasures. That is, accident diminishment appraisals of individual countermeasures cannot be easily added together. The iRAP model philosophy makes utilization of a multiple countermeasure adjustment factors to predict diminishments in the effectiveness of road safety countermeasures when more than one countermeasure is chosen. A multiple countermeasure correction factors are figured for every 100-meter segment and for every accident type. However, restrictions of this methodology incorporate a presumable over-estimation in the predicted crash reduction. This study aims to adjust this correction factor by developing new models to calculate the effect of using multiple countermeasures on the number of fatalities for a location or an entire road. Regression models have been used to establish relationships between crash frequencies and the factors that affect their rates. Multiple linear regression, negative binomial regression, and Poisson regression techniques were used to develop models that can address the effectiveness of using multiple countermeasures. Analyses are conducted using The R Project for Statistical Computing showed that a model developed by negative binomial regression technique could give more reliable results of the predicted number of fatalities after the implementation of road safety multiple countermeasures than the results from iRAP model. The results also showed that the negative binomial regression approach gives more precise results in comparison with multiple linear and Poisson regression techniques because of the overdispersion and standard error issues.

Keywords: international road assessment program, negative binomial, road multiple countermeasures, road safety

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Authors: Hector Liu, Chih-Ming Tsai

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Consumer behaviors in the subscription of over-the-top (OTT) media services have substantially changed because of the COVID-19 pandemic; hence, this study aims to determine the factors affecting subscription intentions. The increased usage of OTT media, particularly in the lockdowns during the COVID-19 pandemic, has intensified the competition between both global and local streaming providers. While studies have discussed antecedents accounting for this change, they have paid limited attention to the psychological factors that shape consumer behavior in using OTT services. Given the changes in consumers’ psychological states during the pandemic, this study seeks to fill the research gap by integrating the expectancy-value model to provide insights into the key gratifications that consumers seek and obtain and that have affected their subscription to OTT services. This study proposes a theoretical model and assesses this framework on data collected from 1,068 OTT service users in Taiwan. The results strengthen the literature by indicating a clear growth in the popularity and subscription of OTT services because of the COVID-19 lockdowns as well as factors such as perceived quality and satisfaction, which influence behavioral intentions for OTT services. Most crucially, however, OTT viewers who acquired a sense of belonging, a sense of being accompanied, and a sense of reduction in anxiety due to being quarantined and in lockdown show a higher tendency to continue their subscriptions to their OTT services of choice during the pandemic. With consumer behavior trends forever changed by the COVID-19 pandemic, the implications from this study provide OTT service platforms with an opportunity to capitalize on their current and potential customers’ changing desires, demands, and factors for a continued subscription.

Keywords: consumer behavior, COVID-19, expectancy-value model, OTT media services

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Authors: Sazzad Hossain Talukder

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Survival in the competitive international market with unforeseen environmental contingencies has always been a concern of the firms that led to adopting different strategies to deal with different situations. Language strategy is considered to enhance the international performance of a firm by organizing language diversity and fostering communications within and outside the firm. Yet there is a lack of theoretical attention or model development on the role of language strategy on firm international survival. From resource dependence perspective, the adoption of language strategy and its relationship with firm survival are determined by the firm´s capability to prevent dependency concentration and/or increase relative power on the external environment. However, the impact of language strategy on firm survival is complex and multifaceted as the strategy influence firm performance indirectly through communication, coordination, learning and value creation. The evidence of various types of language strategies and different forms of firm survival also bring in complexities to understand the effects of a language strategy on the international survival of a firm. Based on language literatures and resource dependence logic, certain propositions are developed to conceptualize the relationship between language strategy and firm international survival in this conceptual paper. For the purpose of this paper, a conceptual model is proposed to examine how different kinds of language strategy foster reduction of resource dependency that lead to firm international survival in respond to local responsiveness and global integration. In this proposed model, it is theorized that language strategy has a positive relationship with the international survival of the firm, as the strategy is likely to reduce external resource dependency and increase the ability to continue independent operations both in short and long term.

Keywords: language strategy, language diversity, firm international survival, resource dependence logic

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Authors: Mohamed Lotfy, Ghada Soliman

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Recognizing Arabic dot-matrix digits is a challenging problem due to the unique characteristics of dot-matrix fonts, such as irregular dot spacing and varying dot sizes. This paper presents an approach for recognizing Arabic digits printed in dot matrix format. The proposed model is based on Convolutional Neural Networks (CNN) that take the dot matrix as input and generate embeddings that are rounded to generate binary representations of the digits. The binary embeddings are then used to perform Optical Character Recognition (OCR) on the digit images. To overcome the challenge of the limited availability of dotted Arabic expiration date images, we developed a True Type Font (TTF) for generating synthetic images of Arabic dot-matrix characters. The model was trained on a synthetic dataset of 3287 images and 658 synthetic images for testing, representing realistic expiration dates from 2019 to 2027 in the format of yyyy/mm/dd. Our model achieved an accuracy of 98.94% on the expiry date recognition with Arabic dot matrix format using fewer parameters and less computational resources than traditional CNN-based models. By investigating and presenting our findings comprehensively, we aim to contribute substantially to the field of OCR and pave the way for advancements in Arabic dot-matrix character recognition. Our proposed approach is not limited to Arabic dot matrix digit recognition but can also be extended to text recognition tasks, such as text classification and sentiment analysis.

Keywords: computer vision, pattern recognition, optical character recognition, deep learning

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Authors: Lamin B Ceesay, Cecilia Rossignoli

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Inter-organizational collaboration is a growing phenomenon in both research and practice. The partnership between organizations enables firms to leverage external resources, experiences, and technology that lie with other firms. This collaborative practice is a source of improved business model performance, technological advancement, and increased competitive advantage for firms. However, the competitive intents, and even diverse institutional logics of firms, make inter-firm innovation-based partnership even more complex, and its governance more challenging. The purpose of this paper is to present a systematic review of research linking the inter-organizational relationship of firms with their innovation practice and specify the different project management issues and gaps addressed in previous research. To do this, we employed a systematic review of the literature on inter-organizational innovation using two complementary scholarly databases - ScienceDirect and Web of Science (WoS). Article scoping relies on the combination of keywords based on similar terms used in the literature:(1) inter-organizational relationship, (2) business network, (3) inter-firm project, and (4) innovation network. These searches were conducted in the title, abstract, and keywords of conceptual and empirical research papers done in English. Our search covers between 2010 to 2019. We applied several exclusion criteria including Papers published outside the years under the review, papers in a language other than English, papers neither listed in WoS nor ScienceDirect and papers that are not sharply related to the inter-organizational innovation-based partnership were removed. After all relevant search criteria were applied, a final list of 84 papers constitutes the data for this review. Our review revealed an increasing evolution of inter-organizational relationship research during the period under the review. The descriptive analysis of papers according to Journal outlets finds that International Journal of Project Management (IJPM), Journal of Industrial Marketing, Journal of Business Research (JBR), etc. are the leading journal outlets for research in the inter-organizational innovation project. The review also finds that Qualitative methods and quantitative approaches respectively are the leading research methods adopted by scholars in the field. However, literature review and conceptual papers constitute the least in the field. During the content analysis of the selected papers, we read the content of each paper and found that the selected papers try to address one of the three phenomena in inter-organizational innovation research: (1) project antecedents; (2) project management and (3) project performance outcomes. We found that these categories are not mutually exclusive, but rather interdependent. This categorization also helped us to organize the fragmented literature in the field. While a significant percentage of the literature discussed project management issues, we found fewer extant literature on project antecedents and performance. As a result of this, we organized the future research agenda addressed in several papers by linking them with the under-researched themes in the field, thus providing great potential to advance future research agenda especially, in the under-researched themes in the field. Finally, our paper reveals that research on inter-organizational innovation project is generally fragmented which hinders a better understanding of the field. Thus, this paper contributes to the understanding of the field by organizing and discussing the extant literature to advance the theory and application of inter-organizational relationship.

Keywords: inter-organizational relationship, inter-firm collaboration, innovation projects, project management, systematic review

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Authors: Hamsini Pulugurtha, V.S. Lakshmi Jagadmaba Paluri

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Distributed denial of service attack (DDoS) is one altogether the top-rated cyber threats presently. It runs down the victim server resources like a system of measurement and buffer size by obstructing the server to supply resources to legitimate shoppers. Throughout this text, we tend to tend to propose a mathematical model of DDoS attack; we discuss its relevancy to the choices like inter-arrival time or rate of arrival of the assault customers accessing the server. We tend to tend to further analyze the attack model in context to the exhausting system of measurement and buffer size of the victim server. The projected technique uses an associate in nursing unattended learning technique, self-organizing map, to make the clusters of identical choices. Lastly, the abstract applies mathematical correlation and so the standard likelihood distribution on the clusters and analyses their behaviors to look at a DDoS attack. These systems not exclusively interconnect very little devices exchanging personal data, but to boot essential infrastructures news standing of nuclear facilities. Although this interconnection brings many edges and blessings, it to boot creates new vulnerabilities and threats which might be conversant in mount attacks. In such sophisticated interconnected systems, the power to look at attacks as early as accomplishable is of paramount importance.

Keywords: application attack, bandwidth, buffer correlation, DDoS distribution flooding intrusion layer, normal prevention probability size

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Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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