Search results for: topic Analysis

Authors: Begum Koru, Isik Aybay, Demet Celik Ulusoy

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The discipline of law is quite complex and has its own terminology. Apart from written legal rules, there is also living law, which refers to legal practice. Basic legal rules aim at the happiness of individuals in social life and have different characteristics in different branches such as public or private law. On the other hand, law is a national phenomenon. The law of one nation and the legal system applied on the territory of another nation may be completely different. People who are experts in a particular field of law in one country may have insufficient expertise in the law of another country. Today, in addition to the local nature of law, international and even supranational law rules are applied in order to protect basic human values and ensure the protection of human rights around the world. Systems that offer algorithmic solutions to legal problems using artificial intelligence (AI) tools will perhaps serve to produce very meaningful results in terms of human rights. However, algorithms to be used should not be developed by only computer experts, but also need the contribution of people who are familiar with law, values, judicial decisions, and even the social and political culture of the society to which it will provide solutions. Otherwise, even if the algorithm works perfectly, it may not be compatible with the values of the society in which it is applied. The latest developments involving the use of AI techniques in legal systems indicate that artificial law will emerge as a new field in the discipline of law. More AI systems are already being applied in the field of law, with examples such as predicting judicial decisions, text summarization, decision support systems, and classification of documents. Algorithms for legal systems employing AI tools, especially in the field of prediction of judicial decisions and decision support systems, have the capacity to create automatic decisions instead of judges. When the judge is removed from this equation, artificial intelligence-made law created by an intelligent algorithm on its own emerges, whether the domain is national or international law. In this work, the aim is to make a general analysis of this new topic. Such an analysis needs both a literature survey and a perspective from computer experts' and lawyers' point of view. In some societies, the use of prediction or decision support systems may be useful to integrate international human rights safeguards. In this case, artificial law can serve to produce more comprehensive and human rights-protective results than written or living law. In non-democratic countries, it may even be thought that direct decisions and artificial intelligence-made law would be more protective instead of a decision "support" system. Since the values of law are directed towards "human happiness or well-being", it requires that the AI algorithms should always be capable of serving this purpose and based on the rule of law, the principle of justice and equality, and the protection of human rights.

Keywords: AI and law, artificial law, protection of human rights, AI tools for legal systems

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Authors: Carolina B. A. Morais, Antonio Bob Santos

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In order to determine how innovation procurement can strengthen public efficiency and foster the modernization of public services, while at the same time promoting the opening of new private markets, this paper aims to present the two key instruments for the practice of innovation procurement at a European, national, and regional level – Pre-Commercial Procurement (PCP), and Public Procurement of Innovative Solutions (PPI). Thus, it starts with a theoretical framework on the emergence of this topic in the European Innovation Policy (Section 2), then continues with the identification and systematization of the main mechanisms for its effective adoption, both on the demand and supply side of the market (Section 3), as well as to expose and describe methods and tools for positioning innovation at the heart of public entities. The innovative projects best distinguished by the European Commission for their good practices in innovation procurement are identified, and the main methodology for the development and management of innovation procurement – Forward Commitment Procurement (FCP) – is applied to them in a pioneering way (Section 4). The relevance of innovation in public procurement is systematized and reflected upon in Section 5.

Keywords: innovation procurement, innovation policy, innovation, pubic procurement

Procedia PDF Downloads 90

Authors: G. Erkomaishvili, R. Gvelesiani, E. Kharaishvili, M. Chavleishvili

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The topic reviews the situation existing currently in Georgia in the field of tourism in conditions of globalization: Touristic resources, the paces of development of the tourism infrastructure, tourism policy, possibilities of development of the Wellness industry in Georgia that is the newest direction of the medical tourism. The factors impeding the development of the industry of tourism, namely-existence of the conflict zones, high rates of the bank credits, deficiencies associated with the tax laws, a level of infrastructural development, quality of services, deficit in the competitive staff, increase of prices in the peak seasons, insufficient promotion of the touristic opportunities of Georgia on the international markets are studied and analyzed. Besides, the levels of development of tourism in Georgia according to the World Economic Forum, aspects of cooperation with the European Union etc. are reviewed. As a result of these studies, a strategy of development of tourism and one of its directions-Wellness industries in Georgia is introduced with the relevant conclusions, on which basis the recommendations are provided.

Keywords: about tourism, tourism policy, wellness industry, business, innovation, technology

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Authors: Tuba Senel Zor, Oktay Aslan

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With current trends in nanoscience and nanotechnology (NST), scientists have paid much attention to education and nanoliteracy in parallel with the developments on these fields. To understand the advances in NST research requires a population with a high degree of science literacy. All citizens should soon need nanoliteracy in order to navigate some of the important science-based issues faced to their everyday lives. While the fields of NST are advancing rapidly and raising their societal significance, general public’s awareness of these fields has remained at a low level. Moreover, students enrolled different education levels and teachers don’t have awareness at expected level. This problem may be stemmed from inadequate education and training. To remove the inadequacy, teachers have greatest duties and responsibilities. Especially science teachers at all levels need to be made aware of these developments and adequately prepared so that they are able to teach about these advances in a developmentally appropriate manner. If the teachers develop understanding and awareness of NST, they can also discuss the topic with their students. Therefore, the awareness and conceptual understandings of both the teachers who will teach science to students and the students who will be introduced about NST should be increased, and the necessary training should be provided. The aim of this study was to examine the effect of NST education on preservice science teachers’ awareness of NST. The study was designed in one group pre-test post-test quasi-experimental pattern. The study was conducted with 32 preservice science teachers attending the Elementary Science Education Program at a large Turkish university in central Anatolia. NST education was given during five weeks as two hours per week. Nanoscience and Nanotechnology Awareness Questionnaire was used as data collected tool and was implemented for pre-test and post-test. The collected data were analyzed using Statistical package for the Social Science (SPSS). The results of data analysis showed that there was a significant difference (z=6.25, p< .05) on NST awareness of preservice science teachers after implemented NST education. The results of the study indicate that NST education has an important effect for improving awareness of preservice science teachers on NST.

Keywords: awareness level, nanoliteracy, nanoscience and nanotechnology education, preservice science teachers

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Authors: Evgeniya Ivanova

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Nowadays, in the literature, there is still no fixed definition of knowledge management that often remains only as an academic discipline. The current market situation is changing very quickly, the need of new technologies is high, and knowledge management is the area that ensures that the know-how has not been lost during market development and adoption. The study examines how knowledge management is being leveraged and practiced in the management consultancy companies and provides not only the tips and best practices of applied knowledge management approaches but also the validation matrix for its successful or unsuccessful implementation. Different knowledge management approaches are explored on the basis of their practical implementation, including related challenges, knowledge sharing process, and barriers that are typical for consulting firms mostly driven by the agile working culture. The relevance of proposed topic is confirmed by the finding that corporate working culture and the exponentially developing technologies have a direct impact on the success of practical implementation of knowledge management.

Keywords: knowledge management, knowledge management in practice, consulting firm, knowledge management success

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Authors: Riona Dighe

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This research attempts to identify an alternative approach to the measurement of Gross National Happiness (GNH). It uses artificial intelligence (AI), incorporating natural language processing (NLP) and sentiment analysis to measure GNH. We use ‘off the shelf’ NLP models responsible for the sentiment analysis of a sentence as a building block for this research. We constructed an algorithm using NLP models to derive a sentiment analysis score against sentences. This was then tested against a sample of 20 respondents to derive a sentiment analysis score. The scores generated resembled human responses. By utilising the MLP classifier, decision tree, linear model, and K-nearest neighbors, we were able to obtain a test accuracy of 89.97%, 54.63%, 52.13%, and 47.9%, respectively. This gave us the confidence to use the NLP models against sentences in websites to measure the GNH of a country.

Keywords: artificial intelligence, NLP, sentiment analysis, gross national happiness

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Authors: P. Wlodarczak, J. Soar, M. Ally

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The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.

Keywords: social media, text mining, knowledge discovery, predictive analysis, machine learning

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Authors: Majid A. AlSayari

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The study reported here investigated social cognitive theory (SCT) in the context of Vocational Rehab (VR) for people with disabilities. The prime purpose was to increase knowledge of VR phenomena and make recommendations for improving VR services. The sample consisted of 242 persons with Spinal Cord Injuries (SCI) who completed questionnaires. A further 32 participants were Trainers. Analysis of questionnaire data was carried out using factor analysis, multiple regression analysis, and thematic analysis. The analysis suggested that, in motivational terms, and consistent with research carried out in other academic contexts, self-efficacy was the best predictor of VR performance. The author concludes that that VR self-efficacy predicted VR training performance.

Keywords: people with physical disabilities, social cognitive theory, self-efficacy, vocational training

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Authors: K. W. Nam, B. J. Kim, S. J. Lee

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Along with the development of network infrastructures, such as high-speed Internet and mobile environment, the explosion of multimedia data is expanding the range of multimedia services beyond voice and data services. Amid this flow, research is actively being done on the creation, management, and transmission of metadata on digital content to provide different services to users. This paper proposes a system for the insertion, storage, and retrieval of metadata about digital content. The metadata server with Binary XML was implemented for efficient storage space and retrieval speeds, and the transport data size required for metadata retrieval was simplified. With the proposed system, the metadata could be inserted into the moving objects in the video, and the unnecessary overlap could be minimized by improving the storage structure of the metadata. The proposed system can assemble metadata into one relevant topic, even if it is expressed in different media or in different forms. It is expected that the proposed system will handle complex network types of data.

Keywords: video, multimedia, metadata, editing tool, XML

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Authors: Kyunghee Oh, Dooho Choi

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Although there is no theoretical weakness in a cryptographic algorithm, Side Channel Analysis can find out some secret data from the physical implementation of a cryptosystem. The analysis is based on extra information such as timing information, power consumption, electromagnetic leaks or even sound which can be exploited to break the system. Differential Power Analysis is one of the most popular analyses, as computing the statistical correlations of the secret keys and power consumptions. It is usually necessary to calculate huge data and takes a long time. It may take several weeks for some devices with countermeasures. We suggest and evaluate the methods to shorten the time to analyze cryptosystems. Our methods include distributed computing and parallelized processing.

Keywords: DPA, distributed computing, parallelized processing, side channel analysis

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Authors: Mustapha Kamel Mihoubi, Reda Madi

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The problem of natural disasters in general and flooding in particular is a topic which marks a memorable action in the world and specifically in cities and large urban areas. Torrential floods and faster flows pose a major problem in urban area. Indeed, a better management of risks of floods becomes a growing necessity that must mobilize technical and scientific means to curb the adverse consequences of this phenomenon, especially in the Saharan cities in arid climate. The aim of this study is to deploy a basic calculation approach based on a hydrologic and hydraulic quantification for locating the black spots in urban areas generated by the flooding and to locate the areas that are vulnerable to flooding. The principle of flooding method is applied to the city of Ghardaia to identify vulnerable areas to inundation and to establish maps management and prevention against the risks of flooding.

Keywords: Alea, Beni Mzab, cartography, HEC-RAS, inundation, torrential, vulnerability, wadi

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Authors: Dalya M. Hassan

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Marketplaces and commercial streets represent some of the most used and lively urban public spaces. Not only do they provide an outlet for commercial exchange, but they also facilitate social and recreational encounters. Such encounters can be influenced by both formal as well as informal vending activities. This paper explores and documents forms of informal vending practices and how they relate to social patterns that occur along the sidewalks of Commercial Streets in Cairo. A qualitative single case study approach of ‘Midan El Gami’ marketplace in Heliopolis, Cairo is adopted. The methodology applied includes direct and walk-by observations for two main commercial streets in the marketplace. Four zoomed-in activity maps are also done for three sidewalk segments that displayed varying vending and social features. Main findings include a documentation and classification of types of informal vending practices as well as a documentation of vendors’ distribution patterns in the urban space. Informal vending activities mainly included informal street vendors and shop spillovers, either as product or seating spillovers. Results indicated that staying and lingering activities were more prevalent in sidewalks that had certain physical features, such as diversity of shops, shaded areas, open frontages, and product or seating spillovers. Moreover, differences in social activity patterns were noted between sidewalks with street vendors and sidewalks with spillovers. While the first displayed more buying, selling, and people watching activities, the latter displayed more social relations and bonds amongst traders’ communities and café patrons. Ultimately, this paper provides a documentation, which suggests that informal vending can have a positive influence on creating a lively commercial street and on resulting patterns of use on the sidewalk space. The results can provide a basis for further investigations and analysis concerning this topic. This could aid in better accommodating informal vending activities within the design of future commercial streets.

Keywords: commercial streets, informal vending practices, sidewalks, social encounters

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

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An essential task in the field of artificial intelligence is to allow computers to interact with people through natural language. Therefore, researches such as virtual assistants and dialogue systems have received widespread attention from industry and academia. The response generation plays a crucial role in dialogue systems, so to push forward the research on this topic, this paper surveys various methods for response generation. We sort out these methods into three categories. First one includes finite state machine methods, framework methods, and instance methods. The second contains full-text indexing methods, ontology methods, vast knowledge base method, and some other methods. The third covers retrieval methods and generative methods. We also discuss some hybrid methods based knowledge and deep learning. We compare their disadvantages and advantages and point out in which ways these studies can be improved further. Our discussion covers some studies published in leading conferences such as IJCAI and AAAI in recent years.

Keywords: deep learning, generative, knowledge, response generation, retrieval

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Authors: Nádia Pereira, Paula Ferreira, Sofia Francisco, Sofia Oliveira, Sidclay Souza, Paula Paulino, Ana Margarida Veiga Simão

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Social media has progressed into a platform for hate speech among its users, and thus, there is an increasing need to develop automatic detection classifiers of offense and conflicts to help decrease the prevalence of such incidents. Online communication can be used to intentionally harm someone, which is why such classifiers could be essential in social networks. A possible application of these classifiers is the automatic detection of cyberbullying. Even though identifying the aggressive language used in online interactions could be important to build cyberbullying datasets, there are other criteria that must be considered. Being able to capture the language, which is indicative of the intent to harm others in a specific context of online interaction is fundamental. Offense and hate speech may be the foundation of online conflicts, which have become commonly used in social media and are an emergent research focus in machine learning and natural language processing. This study presents two Portuguese language offense-related datasets which serve as examples for future research and extend the study of the topic. The first is similar to other offense detection related datasets and is entitled Aggressiveness dataset. The second is a novelty because of the use of the history of the interaction between users and is entitled the Conflicts/Attacks dataset. Both datasets were developed in different phases. Firstly, we performed a content analysis of verbal aggression witnessed by adolescents in situations of cyberbullying. Secondly, we computed frequency analyses from the previous phase to gather lexical and linguistic cues used to identify potentially aggressive conflicts and attacks which were posted on Twitter. Thirdly, thorough annotation of real tweets was performed byindependent postgraduate educational psychologists with experience in cyberbullying research. Lastly, we benchmarked these datasets with other machine learning classifiers.

Keywords: aggression, classifiers, cyberbullying, datasets, hate speech, machine learning

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Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

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Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: data mining, data analysis, prediction, optimization, building operational performance

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Authors: Adrian W. Chew

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This paper argues that education policy analysis tends to be steered towards empiricist oriented approaches, which place emphasis on objective and measurable data. However, this paper argues that empiricist oriented approaches are generally based on inductive and/or deductive reasoning, which are unable to generate new ideas/knowledge. This paper will outline the logical structure of induction, deduction, and abduction, and argues that only abduction provides possibilities for the creation of new ideas/knowledge. This paper proposes the neologism of ‘informed guessing’ as a reformulation of abduction, and also as an approach to education policy analysis. On one side, the signifier ‘informed’ encapsulates the idea that abductive policy analysis needs to be informed by descriptive conceptualization theory to be able to make relations and connections between, and within, observed phenomenon and unobservable general structures. On the other side, the signifier ‘guessing’ captures the cyclical and unsystematic process of abduction. This paper will end with a brief example of utilising ‘informed guessing’ for a policy analysis of school choice lotteries in the United States.

Keywords: abductive reasoning, empiricism, informed guessing, policy analysis

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Authors: Hanwei Cheng, Chengbei Xu, Yijie Wang

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More and more college students are accustomed to surfing the Internet everyday. As community members, college students have ability to express opinions and participate in social affairs, they not only accept information passively, but also voice their concerns on the Internet. We interpret the online discourses featured with anonymization, so it helps us more effectively and conveniently understand the behaviors and thoughts of college students, and educators can thus grasp the scales and directions in guiding online language. We analyzed online comments in both content and form aspects in one student forum (named Dandan, the BNU’s campus forum), and through methods of literature review and interview, we found that in term of content, college students pay attention to practical information online, emphasize on personal development and pursue hot issues; in term of form, college students' online language displays cross-border quality sometimes under the general feature of normative, and they often explore a certain topic in the form of question or discussion, and they like to show feelings in ironic and stream-of-consciousness ways. It is argued that college students intend to establish a community to facilitate personal development and meet emotional needs through the student forum, and by making comments at the forum they are also able to get involved in public affairs. We should pay attention to problems of college students' online discourse, such as boundary issues (like informal advertisement and information authenticity), emotional issues and the spread of gossip. Some possible solutions to solving online discourse problems can be applied, like we can improve access systems of student forum, clarify principles of Internet langue use, change oversimplified management approaches and use some other tactics, in order to form a mechanism of student self-regulation, also deepen the trust and cooperation between school administrators and students.

Keywords: online language, youth discourse, content and form, implication and strategy

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Authors: Alden Boby, Dane Brown, James Connan

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Character recognition is a well-researched topic across disciplines. Regardless, creating a solution that can cater to multiple situations is still challenging. Vehicle licence plates lack an international standard, meaning that different countries and regions have their own licence plate format. A problem that arises from this is that the typefaces and designs from different regions make it difficult to create a solution that can cater to a wide range of licence plates. The main issue concerning detection is the character recognition stage. This paper aims to create an object detection-based character recognition model trained on a custom dataset that consists of typefaces of licence plates from various regions. Given that characters have featured consistently maintained across an array of fonts, YOLO can be trained to recognise characters based on these features, which may provide better performance than OCR methods such as Tesseract OCR.

Keywords: computer vision, character recognition, licence plate recognition, object detection

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Authors: Tuğrul Aksoy, Hüseyin Karabıyık

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Reloading vehicles are the vehicles which are generally equipped with a crane and used to carry a stowage from a point and locate onto the vehicle or vice versa. In this study, structural analysis of a reloading vehicle was performed under the loads which are predicted to be exposed under operating conditions via the finite element method. Among the finite element analysis results, the stress and displacement distributions of the vehicle and the contact pressure distributions of the guide rings within the stabilization legs were examined. Vehicle design was improved by strengthening certain parts according to the analysis results. The analyses performed for the final design were verified by the experiments involving strain gauge measurements.

Keywords: structural analysis, reloading vehicle, crane, strain gauge

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Authors: Ebuwa Osagie, Vasilije Manovic

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Exergy analysis provides the identification of the location, sources of thermodynamic inefficiencies, and magnitude in a thermal system. Thus, both the qualitative and quantitative assessment can be evaluated with exergy, unlike energy which is based on quantitative assessment only. The main purpose of exergy analysis is to identify where exergy is destroyed. Thus, reduction of the exergy destruction and losses associated with the capture plant systems can improve work potential. Furthermore, thermodynamic analysis of different configurations of the process helps to identify opportunities for reducing the steam requirements for each of the configurations. This paper presents steady-state simulation and exergy analysis of the 2-amino-2-methyl-1-propanol (AMP)-based post-combustion capture (PCC) plant. Exergy analysis performed for the AMP-based plant and the different configurations revealed that the rich split with intercooling configuration gave the highest exergy efficiency of 73.6%, while that of the intercooling and the reference AMP-based plant were 57.3% and 55.8% respectively.

Keywords: 2-amino-2-methyl-1-propanol, modelling, and simulation, post-combustion capture plant, exergy analysis, flowsheeting configurations

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Authors: Aissa Belmeguenai, Khaled Mansouri

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In this work, an efficient implementation of Achterbahn-128 for images encryption and decryption was introduced. The implementation for this simulated project is written by MATLAB.7.5. At first two different original images are used for validate the proposed design. Then our developed program was used to transform the original images data into image digits file. Finally, we used our implemented program to encrypt and decrypt images data. Several tests are done for proving the design performance including visual tests and security analysis; we discuss the security analysis of the proposed image encryption scheme including some important ones like key sensitivity analysis, key space analysis, and statistical attacks.

Keywords: Achterbahn-128, stream cipher, image encryption, security analysis

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Authors: Bongjae Lee, Beom Goo Hwang, Hye Mi Park

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CO₂ capture products manufactured through Carbon Capture and Utilization (CCU) Plant that collect CO₂ directly from power plants require accurate measurements of the amount of CO₂ captured. For this purpose, two tests were carried out on the weight loss test. And one was analyzed using a carbon dioxide quantification device. First, the ignition loss analysis was performed by measuring the weight of the sample at 550°C after the first conversation and then confirming the loss when ignited at 950°C. Second, in the thermogravimetric analysis, the sample was divided into two sections of 40 to 500°C and 500 to 800°C to confirm the reduction. The results of thermal weight loss analysis and thermogravimetric analysis were confirmed to be almost similar. However, the temperature of the ignition loss analysis method was 950°C, which was 150°C higher than that of the thermogravimetric method at a temperature of 800°C, so that the difference in the amount of weight loss was 3 to 4% higher by the heat loss analysis method. In addition, the tendency that the CO₂ content increases as the reaction time become longer is similarly confirmed. Third, the results of the wet titration method through the carbon dioxide quantification device were found to be significantly lower than the weight loss method. Therefore, based on the results obtained through the above three analysis methods, we will establish a method to analyze the accurate amount of CO₂. Acknowledgements: This work was supported by the Korea Institute of Energy Technology Evaluation and planning (No. 20152010201850).

Keywords: carbon capture and utilization, CCU, CO2, CO2 capture products, analysis method

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Authors: Soad Abubakr Abdelgalil, Gaber Attia Abo-Zaid, Mohamed Mohamed Yousri Kaddah

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Background: The Environmental Protection Agency has listed eggshell waste as the 15th most significant food industry pollution hazard. The utilization of eggshell waste as a source of renewable energy has been a hot topic in recent years. Therefore, finding a sustainable solution for the recycling and valorization of eggshell waste by investigating its potential to produce acid phosphatase (ACP) and organic acids by the newly-discovered B. sonorensis was the target of the current investigation. Results: The most potent ACP-producing B. sonorensis strain ACP2 was identified as a local bacterial strain obtained from the effluent of paper and pulp industries on basis of molecular and morphological characterization. The use of consecutive statistical experimental approaches of Plackett-Burman Design (PBD), and Orthogonal Central Composite Design (OCCD), followed by pH-uncontrolled cultivation conditions in a 7 L bench-top bioreactor, revealed an innovative medium formulation that substantially improved ACP production, reaching 216 U L⁻¹ with ACP yield coefficient Yp/x of 18.2 and a specific growth rate (µ) of 0.1 h⁻¹. The metals Ag+, Sn+, and Cr+ were the most efficiently released from eggshells during the solubilization process by B. sonorensis. The uncontrolled pH culture condition is the most suited and favored setting for improving the ACP and organic acids production simultaneously. Quantitative and qualitative analyses of produced organic acids were carried out using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Lactic acid, citric acid, and hydroxybenzoic acid isomer were the most common organic acids produced throughout the cultivation process. The findings of thermogravimetric analysis (TGA), differential scan calorimeter (DSC), scanning electron microscope (SEM), energy-dispersive spectroscopy (EDS), Fourier-Transform Infrared Spectroscopy (FTIR), and X-Ray Diffraction (XRD) analysis emphasize the significant influence of organic acids and ACP activity on the solubilization of eggshells particles. Conclusions: This study emphasized robust microbial engineering approaches for the large-scale production of a newly discovered acid phosphatase accompanied by organic acids production from B. sonorensis. The biovalorization of the eggshell waste and the production of cost-effective ACP and organic acids were integrated into the current study, and this was done through the implementation of a unique and innovative medium formulation design for eggshell waste management, as well as scaling up ACP production on a bench-top scale.

Keywords: chicken eggshells waste, bioremediation, statistical experimental design, batch fermentation

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Authors: Sujit K. Basak

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This paper presents a comparison of the reference management software between Zotero and Mendeley and the results were drawn by comparing the two software’s. The novelty of this paper is the comparative analysis of the software and it has shown that Mendeley can import more information from the Google Scholar for the researchers. This finding can help to know researchers to use the reference management software.

Keywords: analysis, comparative analysis, zotero, researchers, Mendeley

Procedia PDF Downloads 598

Authors: Muhammad Suhaib

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Requirements Analysis are the most important part of software Engineering for both system application development, and project requirements. Conflicts often arise during the requirements gathering and analysis phase. This research aims to identify conflicts during the requirements gathering phase in software development life cycle, Research, Development, and Technology converted the world into a global village. During requirements elicitation/gathering phase it’s very difficult to understand the main objective of stakeholders, after completion of requirements elicitation task final results are used for Software Requirements Specification (SRS), SRS is the highly important outcome of the requirements analysis phase. this is the foundation between the developers and stakeholders or customers, proposed methodology will be helpful to identify those conflicts in a very easy manner during the initial phase of the project.

Keywords: goal oriented requirements analysis, conflicts identification model, requirements analysis, requirements engineering

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Authors: Abdullah Khuwaileh

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The central aim of this paper is to investigate writing skills in the two languages involved, English and Arabic, and to see whether there is an association between poor writing across languages. That is to say, and it is thought that learners might be excellent in their L1 (Language 1: Arabic) but not in L2 (language 2: English). However, our experimental research findings resulted in an interesting association between L1 and L2. Data were collected from 150 students (chosen randomly) who wrote about the same topic in English and Arabic. Topics needed no preparation as they were common and well-known. Scripts were assessed respectively by ELT (English Language Teaching) and Arabic specialists. The study confirms that poor writing in English correlates with similar deficiencies in the mother tongue (Arabic). Thus, the common assumption in ELT that all learners are fully competent in their first language skills is unfounded. Therefore, the criticism of ELT programs for speakers of Arabic, based on poor writing skills in English and good writing in Arabic is not justified. The findings of this paper can be extended to other learners of English who speak Arabic as a first language and English as a foreign and/or second language. The study is concluded with several research and practical recommendations

Keywords: language, writing, culture, l1

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Authors: Richard Harrison

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Developing competency in mathematics and related critical thinking skills is essential to the education of undergraduate students of Science, Technology, Engineering and Mathematics (STEM). Recently, the HE sector has been impacted by a seemingly widening disconnect between the mathematical competency of incoming first-year STEM students and their entrance qualification tariffs. Despite relatively high grades in A-Level Mathematics, students may initially lack fundamental skills in key areas such as algebraic manipulation and have limited capacity to apply problem solving strategies. Compounded by compensatory measures applied to entrance qualifications during the pandemic, there has been an associated decline in student performance on introductory university mathematics modules. In the UK, a number of online resources have been developed to help scaffold the transition to university mathematics. However, in general, these do not offer a structured learning journey focused on individual developmental needs, nor do they offer an experience coherent with the teaching and learning characteristics of the destination institution. In order to address some of these issues, a bespoke framework has been designed and implemented on our VLE in the Faculty of Engineering & Physical Sciences (FEPS) at the University of Surrey. Called the FEPS Maths Support Framework, it was conceived to scaffold the mathematical development of individuals prior to entering the university and during the early stages of their transition to undergraduate studies. More than 90% of our incoming STEM students voluntarily participate in the process. Students complete a set of initial diagnostic questions in the late summer. Based on their performance and feedback on these questions, they are subsequently guided to self-select specific mathematical topic areas for review using our proprietary resources. This further assists students in preparing for discipline related diagnostic tests. The framework helps to identify students who are mathematically weak and facilitates early intervention to support students according to their specific developmental needs. This paper presents a summary of results from a rich data set captured from the framework over a 3-year period. Quantitative data provides evidence that students have engaged and developed during the process. This is further supported by process evaluation feedback from the students. Ranked performance data associated with seven key mathematical topic areas and eight engineering and science discipline areas reveals interesting patterns which can be used to identify more generic relative capabilities of the discipline area cohorts. In turn, this facilitates evidence based management of the mathematical development of the new cohort, informing any associated adjustments to teaching and learning at a more holistic level. Evidence is presented establishing our framework as an effective early intervention strategy for addressing the sector-wide issue of supporting the mathematical development of STEM students transitioning to HE

Keywords: competency, development, intervention, scaffolding

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Authors: Abdelouahab Errida, Bouchra Lotfi, Elalami Semma

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In this paper, we try to address the topic of multiple change management by adopting an engineered research methodology, conducted within a Moroccan company during its implementation of several change projects that aim at improving its supply chain management performance. Firstly, we present the key concepts related to our research, namely change management, multiproject management and supply chain management. Then, we try to assess how the change management and multi-project management are applied in this company. Finally, we try to propose an approach that will help managers in dealing with multiple change projects. This approach proposes to integrate change management, project management and multi-project management for managing change projects according to three organizational levels: executive level, project portfolio level and change project level.

Keywords: change management, multi-project management, project management, change portfolio, supply chain management,

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Authors: Shilpa Balan

Abstract:

Radio Frequency Identification, also popularly known as RFID is used to automatically identify and track tags attached to items. This study focuses on the application of RFID in healthcare. The adoption of RFID in healthcare is a crucial technology to patient safety and inventory management. Data from RFID tags are used to identify the locations of patients and inventory in real time. Medical errors are thought to be a prominent cause of loss of life and injury. The major advantage of RFID application in healthcare industry is the reduction of medical errors. The healthcare industry has generated huge amounts of data. By discovering patterns and trends within the data, big data analytics can help improve patient care and lower healthcare costs. The number of increasing research publications leading to innovations in RFID applications shows the importance of this technology. This study explores the current state of research of RFID in healthcare using a text mining approach. No study has been performed yet on examining the current state of RFID research in healthcare using a data mining approach. In this study, related articles were collected on RFID from healthcare journal and news articles. Articles collected were from the year 2000 to 2015. Significant keywords on the topic of focus are identified and analyzed using open source data analytics software such as Rapid Miner. These analytical tools help extract pertinent information from massive volumes of data. It is seen that the main benefits of adopting RFID technology in healthcare include tracking medicines and equipment, upholding patient safety, and security improvement. The real-time tracking features of RFID allows for enhanced supply chain management. By productively using big data, healthcare organizations can gain significant benefits. Big data analytics in healthcare enables improved decisions by extracting insights from large volumes of data.

Keywords: RFID, data mining, data analysis, healthcare

Procedia PDF Downloads 214

Authors: Bita Mashayekhi, Amin Jahangard, Milad Samavat, Saeid Homayoun

Abstract:

In the modern competitive business environment, one cannot overstate the importance of corporate social responsibility. The controversial link between the social and financial performance of firms has become a topic of interest for scholars. Hence, this study examines the social and financial performance link by taking into account the mediating role of innovation performance. We conducted the Covariance-based Structural Equation Modeling (CB-SEM) method on an international sample of firms provided by the ASSET4 database. In this research, to explore the black box of the social and financial performance relationship, we first examined the effect of social performance separately on financial performance and innovation; then, we measured the mediation role of innovation in the social and financial performance link. While our results indicate the positive effect of social performance on financial performance and innovation, we cannot document the positive mediating role of innovation. This possibly relates to the long-term nature of benefits from investments in innovation.

Keywords: ESG, financial performance, innovation, social performance, structural equation modeling

Procedia PDF Downloads 83