Search results for: algorithms decision tree

Authors: Xiyue Wang, Shaoning Yan

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Cities in China today is faced with an increasingly serious river ecological crisis accompanying with the development of urbanization: waterlogging on account of the fragmented urban natural hydrological system; the limited ecological function of the hydrological system caused by a destruction of water system and waterfront ecological environment. Additionally, the eco-hydrological processes of rivers are affected by various environmental factors, which are more complex in the context of urban environment. Therefore, efficient hydrological monitoring and analysis tools, accurate and visual hydrological and hydraulic models are becoming more important basis for decision-makers and an important way for landscape architects to solve urban hydrological problems, formulating sustainable and forward-looking schemes. The study mainly introduces the river and flood analysis model based on the platform of Autodesk Civil 3D. Taking the Luanhe River in Qian'an City of Hebei Province as an example, the 3D models of the landform, river, embankment, shoal, pond, underground stream and other land features were initially built, with which the water transfer simulation analysis, river floodplain analysis, and river ecology analysis were carried out, ultimately the real-time visualized simulation and analysis of rivers in various hypothetical scenarios were realized. Through the establishment of digital hydrological and hydraulic model, the hydraulic data can be accurately and intuitively simulated, which provides basis for rational water system and benign urban ecological system design. Though, the hydrological and hydraulic model based on Autodesk Civil3D own its boundedness: the interaction between the model and other data and software is unfavorable; the huge amount of 3D data and the lack of basic data restrict the accuracy and application range. The hydrological and hydraulic model based on Autodesk Civil3D platform provides more possibility to access convenient and intelligent tool for urban planning and monitoring, a solid basis for further urban research and design.

Keywords: visualization, hydrological and hydraulic model, Autodesk Civil 3D, urban river

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Authors: Li-Fang CHou, Chun-Jung Tseng, Sung-Chun Tsai

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Zhong-Yong represents unique values and cognitive beliefs of Chinese culture. Zhong-Yong thinking emphasizes (a) holistic thinking and perspective taking, (b) tolerance of contradictions, and (c) pursuance of a person’s interpersonal and inner harmony. With a unique way of naïve dialectical thinking based on Chinese culture, previous studies have found that people with higher Zhong-Yong thinking have more cognitive resources and resilience to make decision for dilemmas and cope stresses. Creativity is defined as the behavior to create novel and value products and viewed as the most important capital for individuals and enterprises. However, the relationship between Zhong-Yong thinking and creativity is still remaining to be unexplored. Three studies were conducted to explore the effects of Zhong-Yong thinking on creativity. In Study1, with 87 undergraduate students from a university in southern Taiwan as participants, we used questionnaire to measure Zhong-Yong thinking and processed creative task (unusual uses task) to get indicators of fluency and flexibility. After controlling background and openness to experience of Big five, the results showed that Zhong-Yong thinking had significant positive effects on fluency and flexibility. In Study 2, 97 undergraduate students were recruited to do Zhong-Yong thinking task and creative task. The result showed that, compared with control group, the participants had higher creative performance after being primed with Zhong-Yong thinking. In Study 3, we adopted questionnaire survey and took 397 employees from private enterprises in Taiwan as sample. Besides the main effects of Zhong-Yong thinking, the moderating effects on the relationship between leadership behavior and employee’s creative performance were also investigated. We found that (a) Zhong-Yong thinking was positively associated to creative performance; (b) Zhong-Yong thinking strengthened the positive effects of transformational and authoritative leadership on creative performance. Finally, the implications of theory/practice and limitations/future directions were also discussed.

Keywords: Zhong-Yong thinking, creativity and creative performance, unusual uses task, transformational leadership, authoritative leadership

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Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

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Authors: Sven Tackenberg, Sönke Duckwitz, Andreas Petz, Christopher M. Schlick

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This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem (RCPSP) to apply it to complex maintenance problems. The problem is to assign technicians to a team which has to process several tasks with multi-level skill requirements during a work shift. Here, several alternative activities for a task allow both, the temporal shift of activities or the reallocation of technicians and tools. As a result, switches from one valid work process variant to another can be considered and may be selected by the developed evolutionary algorithm based on the present skill level of technicians or the available tools. An additional complication of the observed scheduling problem is that the locations of the construction sites are only temporarily accessible during a day. Due to intensive rail traffic, the available time slots for maintenance and repair works are extremely short and are often distributed throughout the day. To identify efficient working periods, a first concept of a Bayesian network is introduced and is integrated into the extended RCPSP with pre-emptive and non-pre-emptive tasks. Thereby, the Bayesian network is used to calculate the probability of a maintenance task to be processed during a specific period of the shift. Focusing on the domain of maintenance of the railway infrastructure in metropolitan areas as the most unproductive implementation process at construction site, the paper illustrates how the extended RCPSP can be applied for maintenance planning support. A multi-criteria evolutionary algorithm with a problem representation is introduced which is capable of revising technician-task allocations, whereas the duration of the task may be stochastic. The approach uses a novel activity list representation to ensure easily describable and modifiable elements which can be converted into detailed shift schedules. Thereby, the main objective is to develop a shift plan which maximizes the utilization of each technician due to a minimization of the waiting times caused by rail traffic. The results of the already implemented core algorithm illustrate a fast convergence towards an optimal team composition for a shift, an efficient sequence of tasks and a high probability of the subsequent implementation due to the stochastic durations of the tasks. In the paper, the algorithm for the extended RCPSP is analyzed in experimental evaluation using real-world example problems with various size, resource complexity, tightness and so forth.

Keywords: maintenance management, scheduling, resource constrained project scheduling problem, genetic algorithms

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Authors: Ayoade Adeyemi, Leo Nherera, Paul Trueman, Antje Emmermann

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Background and objectives: Radiofrequency (RF) generated plasma chondroplasty is considered a promising treatment alternative to mechanical debridement (MD) with a shaver. The aim of the study was to perform a cost-effectiveness analysis comparing costs and outcomes following COBLATION chondroplasty versus mechanical debridement in patients with knee pain associated with a medial meniscus tear and idiopathic ICRS grade III focal lesion of the medial femoral condyle from a payer perspective. Methods: A decision-analytic model was developed comparing economic and clinical outcomes between the two treatment options in German patients following knee chondroplasty. Revision rates based on the frequency of repeat arthroscopy, osteotomy and conversion to total knee replacement, reimbursement costs and outcomes data over a 4-year time horizon were extracted from published literature. One-way sensitivity analyses were conducted to assess uncertainties around model parameters. Threshold analysis determined the revision rate at which model results change. All costs were reported in 2016 euros, future costs were discounted at a 3% annual rate. Results: Over a 4 year period, COBLATION chondroplasty resulted in an overall net saving cost of €461 due to a lower revision rate of 14% compared to 48% with MD. Threshold analysis showed that both options were associated with comparable costs if COBLATION revision rate was assumed to increase up to 23%. The initial procedure costs for COBLATION were higher compared to MD and outcome scores were significantly improved at 1 and 4 years post-operation versus MD. Conclusion: The analysis shows that COBLATION chondroplasty is a cost-effective option compared to mechanical debridement in the treatment of patients with a medial meniscus tear and idiopathic ICRS grade III defect of the medial femoral condyle.

Keywords: COBLATION, cost-effectiveness, knee chondroplasty, mechanical debridement

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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Authors: S. Jayasinghe, R. B. N. Dissanayake

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Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

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Authors: Armando T. Zúñiga

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As the number of English Language Learners (ELLs) in public schools continues to grow, so does the achievement gap between ELLs and other student populations. In an effort to support classroom teachers with effective instructional strategies for this student population, many districts have created instructional coaching positions specifically to support classroom teachers of ELLs—ELL Teachers on Special Assignment (ELL TOSAs). This study employed a gap analysis framework to the ELL TOSA professional support program in one California school district to examine knowledge, motivation, and organizational influences (KMO) on the ELL TOSAs’ goal of supporting classroom teachers of ELLs. Three themes emerged as a result of data analysis. First, there was evidence to illustrate the interaction between knowledge and the organization. Data from ELL TOSAs indicated an understanding of the role that collaboration plays in coaching and how to operationalize it in their support of teachers. Further, all of the ELL TOSAs indicated they have received professional development on effective strategies for instructional coaching. Additionally, a large percentage of the ELL TOSAs indicated a knowledge of modeling as an effective coaching practice. Accordingly, all of the ELL TOSAs indicated that they had knowledge of feedback as an effective coaching strategy. However, there was not sufficient evidence to support that they learned the latter two strategies through professional development. A second theme surfaced as there was evidence to illustrate an interaction between motivation and the organization. Some ELL TOSAs indicated that their sense of self-efficacy was affected by conflicting roles and expectations for the job. Most of the ELL TOSAs indicated that their sense of self-efficacy was affected by an increased workload brought about by fiscal decision making. Finally, there was evidence illustrating the interaction between the organization and motivation. The majority of the of ELL TOSAs indicated that there is confusion about how their roles are perceived, leaving the ELL TOSAs to feel that their actions did not contribute to instructional change. In conclusion, five research-based recommendations to support ELL TOSA goal attainment and considerations for future research on instructional coaches for classroom teachers of ELLs are provided.

Keywords: English language development, English language acquisition, language and leadership, language coaching, English language learners, second language acquisition

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Authors: Muhammad Afzal, Shahbaz Mushtaq, Duc-Anh-An-Vo, Kathryn Reardon Smith, Thanh Ma

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Climate change has become one of the most challenging environmental issues in the 21st century. Climate change-induced natural disasters, especially floods, are the major factors of livelihood vulnerability, impacting millions of individuals worldwide. Evaluating and mitigating the effects of floods requires an in-depth understanding of the relationship between vulnerability and livelihood capital assets. Using an integrated approach, sustainable livelihood framework, and system thinking approach, the study developed a conceptual model of a generalized livelihood system in District Rajanpur, Pakistan. The model visualizes the livelihood vulnerability system as a whole and identifies the key feedback loops likely to influence the livelihood vulnerability. The study suggests that such conceptual models provide effective communication and understanding tools to stakeholders and decision-makers to anticipate the problem and design appropriate policies. It can also serve as an evaluation technique for rural livelihood policy and identify key systematic interventions. The key finding of the study reveals that household income, health, and education are the major factors behind the livelihood vulnerability of the rural poor of District Rajanpur. The Pakistani government tried to reduce the livelihood vulnerability of the region through different income, health, and education programs, but still, many changes are required to make these programs more effective especially during the flood times. The government provided only cash to vulnerable and marginalized families through income support programs, but this study suggests that along with the cash, the government must provide seed storage facilities and access to crop insurance to the farmers. Similarly, the government should establish basic health units in villages and frequent visits of medical mobile vans should be arranged with advanced medical lab facilities during and after the flood.

Keywords: livelihood vulnerability, rural communities, flood, sustainable livelihood framework, system dynamics, Pakistan

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Authors: Marja A. Bernardo, Coreena A. Bueser, Cybele Lara R. Abad, Raul V. Destura

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Pneumocystis jirovecii pneumonia (PCP) is the most common opportunistic infection among people with HIV. Early consideration of PCP should be made even in patients whose HIV status is unknown as delay in treatment may be fatal. The use of absolute lymphocyte count (ALC) has been suggested as an alternative predictor of PCP especially in resource limited settings where PCR testing is costly or delayed. Objective: To determine whether the absolute lymphocyte count (ALC) can be used as a screening tool to predict Pneumocystis pneumonia in patients with unknown HIV status admitted at a private tertiary hospital. Methods: A retrospective cross-sectional study was conducted at a private tertiary medical center. Inpatient medical records of patients aged 18 years old and above from January 2012 to May 2014, in whom a clinical diagnosis of Pneumocystis jirovecii pneumonia was made were reviewed for inclusion. Demographic data, clinical features, hospital course, PCP PCR and HIV results were recorded. Independent t-test and chi-square analysis was used to determine any statistical difference between PCP-positive and PCP-negative groups. Mann-Whitney U-test was used for comparison of hospital stay. Results: There were no statistically significant differences in baseline characteristics between PCP positive and negative groups. While both the percent lymphocyte count (0.14 ± 0.13 vs 0.21 ± 0.16) and ALC (1160 ± 528.67 vs 1493.70 ± 988.61) were lower for the PCP-positive group, only the percent lymphocyte count reached a statistically significant difference (p= 0.067 vs p= 0.042). Conclusion: A quick determination of the ALC may be useful as an additional parameter to help screen for and diagnose pneumocystis pneumonia. In our study, the ALC of patients with PCP appear to be lower than in patients without PCP. A low ALC (e.g. below 1200) may help with the decision regarding empiric treatment. However, it should be used in conjunction with the patient’s clinical presentation, as well as other diagnostic tests. Larger, prospective studies incorporating the ALC with other clinical predictors are necessary to optimally predict those who would benefit from empiric or expedited management for potential PCP.

Keywords: Pneumocystis carinii pneumonia, Absolute Lymphocyte Count, infection, PCP

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Authors: Benjamin Newman

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The picture of an adverse contest between two parties has often been used as an archetypal description of the Anglo-American adversarial criminal trial. However, in actuality, guilty pleas and plea-bargains have been dominating the procedure for over the last half-a-century. Characterised by two adverse parties, the court adjudicative system in the Anglo-American world adhere to the adversarial procedure, and while further features have been attributed and the values that are embedded within the procedure vary, it is a system that we have no adequate theory. Damaska had argued that the adversarial conflict-resolution mode of administration of justice stems from a liberal laissez-faire concept of a value neutral liberal state. Having said that, the court’s neutrality has been additionally rationalised in light of its liberal end as a safeguard from the state’s coercive force. Both conceptions of the court’s neutrality conflict in cases where the by-standing role disposes of its liberal duty in safeguarding the individual. Such is noticeable in plea bargains, where the defendant has the liberty to plead guilty, despite concerns over wrongful convictions and deprivation of liberty. It is an inner liberal tension within the notion of criminal adversarialism, between the laissez-faire mode which grants autonomy to the parties and the safeguarding liberal end of the trial. Langbein had asserted that the adversarial system is a criminal procedure for which we have no adequate theory, and it is by reference to political and moral theories that the research aims to articulate a normative account. The paper contemplates on the above liberal-tension, and by reference to Duff’s ‘calling-to-account’ theory, argues that autonomy is of inherent value to the criminal process, being considered a constitutive element in the process of being called to account. While the aspiration is that the defendant’s guilty plea should be genuine, the guilty-plea decision must be voluntary if it is to be considered a performative act of accountability. Thus, by valuing procedural autonomy as a necessary element within the criminal adjudicative process, it assimilates a liberal procedure, whilst maintaining the liberal end by holding the defendant to account.

Keywords: liberal theory, adversarial criminal procedure, criminal law theory, liberal perfectionism, political liberalism

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Authors: Maha Ben Salem

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The transformative aspect of emerging adulthood brings about a development of self-processes, including changes in self-esteem and personal goals. Success in this life stage entails the emotional growth necessary to navigate the demands and challenges of college life. Understanding the concept of self-awareness within this particular age group sheds light on emerging adults’ internal world and the transformative aspect of their emotional growth. Uncovering the thoughts' processes that foster or hinder self-awareness is important to the understanding of how emerging adults learn to make themselves positive or negative. However, existing research in self-awareness has explored this phenomenon mostly using quantitative research methodology or through tying an individual’s level of self-awareness to specific actions or outcomes. Little is known about the process of how college students emerging adults notice and monitor their inner thoughts and emotions. Methodology and theoretical orientation: A grounded theory study using in-depth semi-structured interview was utilized. Nine interviews have been conducted. A constructionist framework was employed to generate a theory as for how self-awareness facilitates specific patterns of thinking in emerging adults. The choice of grounded theory emanates from a lack of knowledge regarding underlying thinking procedures and internal states that emerging adult college students navigate in an attempt to make meaning out of the new academic experience and life stage. Findings: Initial data analysis generated the following categories of the theory: (a) a non-judgmental perception of negative thinking and negative emotions that allow for a better understanding of the self; (b) negative state of mind is easy to overcome when it is accepted and acknowledged; (c) knowledge of the actual and desired self-generates an intentional decision to shift to a positive mindset. Preliminary findings indicate that college academic and social environment foster a new understanding of the self that yield a change in mindset and in self-knowledge.

Keywords: college environment, emergent adults, grounded theory, positive mindset, self-awareness

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Authors: Maria Inês Faria, João Miguel Simão

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Frequently, the Sustainable Development paradigm is considered the contemporary societies flag and is has been assuming different nuances on local and global dialogues. This reveals the ambivalent character associated to its implementation due, namely, to the kind of synergies that political institutions, social organizations and citizenry can actually create. The Sustainable Development concept needs further discussion so that it can be useful in decision-making processes. In fact, the polysemic nature of this concept has consistently undermined its credibility leading, among other factors, to the talk and action gap, as well as to misappropriations of this notion. The present study focuses on the importance in questioning the sustainable development operationalization, "To walk the talk", and intends, in a broad sense, identify prospects and the elements of sustainability that are included in strategic plans (global, national and local) and, in the strict sense, confront discourse and practice in the context of local public policies for sustainable development, in particular with regard to the implementation of Local Agenda 21 in the municipality of Beja (Portugal) in order to analyze at what extent the strategies adopted and implemented are aligned with the paradigm of sustainable development. The method is based on critical analysis of literature and official documentation, using three complementary approaches: a) exploratory review of literature in order to identify publications on sustainability and sustainable development; b) this second approach complements the first, focused on the official documentation for the adoption and implementation of sustainable development, which is produced in the global plan, regional, national and local levels; c) and the approach which is focused on official documentation that expresses the policy options, the strategic lines and actions for sustainable development implementation Beja´s Municipality. The main results of this study highlight the type of alignment of the Beja´s Municipality sustainable policies, concerning the officially stipulated for the promotion of sustainable development on the international agenda, stressing the potentialities, constraints and challenges of Agenda 21 Local implementation.

Keywords: sustainable development, Local Agenda 21, sustainable local public policies, Beja

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Authors: Heather E. Ewart, Keith Jensen, Rebecca N. Cliffe

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Fragmentation and changes in the structural composition of tropical forests – as a result of intensifying anthropogenic disturbance – are increasing pressures on local biodiversity. Species with low dispersal abilities have some of the highest extinction risks in response to environmental change, as even small-scale environmental variation can substantially impact their space use and energetic balance. Understanding the implications of forest disturbance is therefore essential, ultimately allowing for more effective and targeted conservation initiatives. Here, the impact of different levels of forest disturbance on the space use, energetics, movement and behavior of 18 brown-throated sloths (Bradypus variegatus) were assessed in the South Caribbean of Costa Rica. A multi-scale framework was used to measure forest disturbance, including large-scale (landscape-level classifications) and fine-scale (within and surrounding individual home ranges) forest composition. Three landscape-level classifications were identified: primary forests (undisturbed), secondary forests (some disturbance, regenerating) and urban forests (high levels of disturbance and fragmentation). Finer-scale forest composition was determined using measurements of habitat structure and quality within and surrounding individual home ranges for each sloth (home range estimates were calculated using autocorrelated kernel density estimation [AKDE]). Measurements of forest quality included tree connectivity, density, diameter and height, species richness, and percentage of canopy cover. To determine space use, energetics, movement and behavior, six sloths in urban forests, seven sloths in secondary forests and five sloths in primary forests were tracked using a combination of Very High Frequency (VHF) radio transmitters and Global Positioning System (GPS) technology over an average period of 120 days. All sloths were also fitted with micro data-loggers (containing tri-axial accelerometers and pressure loggers) for an average of 30 days to allow for behavior-specific movement analyses (data analysis ongoing for data-loggers and primary forest sloths). Data-loggers included determination of activity budgets, circadian rhythms of activity and energy expenditure (using the vector of the dynamic body acceleration [VeDBA] as a proxy). Analyses to date indicate that home range size significantly increased with the level of forest disturbance. Female sloths inhabiting secondary forests averaged 0.67-hectare home ranges, while female sloths inhabiting urban forests averaged 1.93-hectare home ranges (estimates are represented by median values to account for the individual variation in home range size in sloths). Likewise, home range estimates for male sloths were 2.35 hectares in secondary forests and 4.83 in urban forests. Sloths in urban forests also used nearly double (median = 22.5) the number of trees as sloths in the secondary forest (median = 12). These preliminary data indicate that forest disturbance likely heightens the energetic requirements of sloths, a species already critically limited by low dispersal ability and rates of energy acquisition. Energetic and behavioral analyses from the data-loggers will be considered in the context of fine-scale forest composition measurements (i.e., habitat quality and structure) and are expected to reflect the observed home range and movement constraints. The implications of these results are far-reaching, presenting an opportunity to define a critical index of habitat connectivity for low dispersal species such as sloths.

Keywords: biodiversity conservation, forest disturbance, movement ecology, sloths

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Authors: Ameni Mejri, Moufida Hajjaj, Salem Hasnaoui, Ridha Bouallegue

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The technology advances have most lately made the millimeter wave (mmWave) communication possible. Due to the huge amount of spectrum that is available in MmWave frequency bands, this promising candidate is considered as a key technology for the deployment of 5G cellular networks. In order to enhance system capacity and achieve spectral efficiency, very large antenna arrays are employed at mmWave systems by exploiting array gain. However, it has been shown that conventional beamforming strategies are not suitable for mmWave hardware implementation. Therefore, new features are required for mmWave cellular applications. Unlike traditional multiple-input-multiple-output (MIMO) systems for which only digital precoders are essential to accomplish precoding, MIMO technology seems to be different at mmWave because of digital precoding limitations. Moreover, precoding implements a greater number of radio frequency (RF) chains supporting more signal mixers and analog-to-digital converters. As RF chain cost and power consumption is increasing, we need to resort to another alternative. Although the hybrid precoding architecture has been regarded as the best solution based on a combination between a baseband precoder and an RF precoder, we still do not get the optimal design of hybrid precoders. According to the mapping strategies from RF chains to the different antenna elements, there are two main categories of hybrid precoding architecture. Given as a hybrid precoding sub-array architecture, the partially-connected structure reduces hardware complexity by using a less number of phase shifters, whereas it sacrifices some beamforming gain. In this paper, we treat the hybrid precoder design in mmWave MIMO systems as a problem of matrix factorization. Thus, we adopt the alternating minimization principle in order to solve the design problem. Further, we present our proposed algorithm for the partially-connected structure, which is based on the iterative hard thresholding method. Through simulation results, we show that our hybrid precoding algorithm provides significant performance gains over existing algorithms. We also show that the proposed approach reduces significantly the computational complexity. Furthermore, valuable design insights are provided when we use the proposed algorithm to make simulation comparisons between the hybrid precoding partially-connected structure and the fully-connected structure.

Keywords: alternating minimization, hybrid precoding, iterative hard thresholding, low-complexity, millimeter wave communication, partially-connected structure

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Authors: Lucas Paganin, Viliam Makis

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With the advent of globalization, the market competition has become a major issue for most companies. One of the main strategies to overcome this situation is the quality improvement of the product at a lower cost to meet customers’ expectations. In order to achieve the desired quality of products, it is important to control the process to meet the specifications, and to implement the optimal maintenance policy for the machines and the production lines. Thus, the overall objective is to reduce process variation and the production and maintenance costs. In this paper, an integrated model involving Statistical Process Control (SPC) and maintenance is developed to achieve this goal. Therefore, the main focus of this paper is to develop the jointly optimal maintenance and statistical process control policy minimizing the total long run expected average cost per unit time. In our model, the production process can go out of control due to either the deterioration of equipment or other assignable causes. The equipment is also subject to failures in any of the operating states due to deterioration and aging. Hence, the process mean is controlled by an Xbar control chart using equidistant sampling epochs. We assume that the machine inspection epochs are the times when the control chart signals an out-of-control condition, considering both true and false alarms. At these times, the production process will be stopped, and an investigation will be conducted not only to determine whether it is a true or false alarm, but also to identify the causes of the true alarm, whether it was caused by the change in the machine setting, by other assignable causes, or by both. If the system is out of control, the proper actions will be taken to bring it back to the in-control state. At these epochs, a maintenance action can be taken, which can be no action, or preventive replacement of the unit. When the equipment is in the failure state, a corrective maintenance action is performed, which can be minimal repair or replacement of the machine and the process is brought to the in-control state. SMDP framework is used to formulate and solve the joint control problem. Numerical example is developed to demonstrate the effectiveness of the control policy.

Keywords: maintenance, semi-Markov decision process, statistical process control, Xbar control chart

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Authors: Tania Vasquez Mata, Luis A. Herrera, Cristian Arriaga Canon

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Background: Locally advanced breast cancer of the luminal B phenotype, poses challenges due to its variable response to neoadjuvant chemotherapy. A predictive biomarker is needed to identify patients who will not respond to treatment, allowing for alternative therapies. This study aims to validate the use of the lncRNA GATA3-AS1, as a predictive biomarker using RNA in situ hybridization. Research aim: The aim of this study is to determine if GATA3-AS1 can serve as a biomarker for resistance to neoadjuvant chemotherapy in patients with locally advanced luminal B breast cancer. Methodology: The study utilizes RNA in situ hybridization with predesigned probes for GATA3-AS1 on Formalin-Fixed Paraffin-Embedded tissue sections. The samples underwent pretreatment and protease treatment to enable probe penetration. Chromogenic detection and signal evaluation were performed using specific criteria. Findings: Patients who did not respond to neoadjuvant chemotherapy showed a 3+ score for GATA3-AS1, while those who had a complete response had a 1+ score. Theoretical importance: This study demonstrates the potential clinical utility of GATA3-AS1 as a biomarker for resistance to neoadjuvant chemotherapy. Identifying non-responders early on can help avoid unnecessary treatment and explore alternative therapy options. Data collection and analysis procedures: Tissue samples from patients with locally advanced luminal B breast cancer were collected and processed using RNA in situ hybridization. Signal evaluation was conducted under a microscope, and scoring was based on specific criteria. Questions addressed: Can GATA3-AS1 serve as a predictive biomarker for neoadjuvant chemotherapy response in locally advanced luminal B breast cancer? Conclusion: The lncRNA GATA3-AS1 can be used as a biomarker for resistance to neoadjuvant chemotherapy in patients with locally advanced luminal B breast cancer. Its identification through RNA in situ hybridization of tissue obtained from the initial biopsy can aid in treatment decision-making.

Keywords: biomarkers, breast neoplasms, genetics, neoadjuvant therapy, tumor

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Authors: Hala Alioua, Alberic Tellier

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This paper is designed to spotlight the research on corporate strategic planning, by emphasizing the role of middle manager of SBU’s and related issues such as the context of vision change. Previous research on strategic vision has been focused principally at the SME, with relatively limited consideration given to the role of middle managers SBU’s in the context of change. This project of research has been done by using a single case study. We formulated through our immersion for 2.5 years on the ground and by a qualitative method and abduction approach. This entity that we analyze is a subsidiary of multinational companies headquartered in Germany, specialized in manufacturing automotive equipment. The "Delta Company" is a French manufacturing plant that has undergone numerous changes over the past three years. The two major strategic changes that have a significant impact on the Delta plant are the strengths of its core business through « lead plant strategy» in 2011 and the implementation of a new strategic vision in 2014. These consecutive changes impact the purpose of the mission of the middle managers. The plant managers ask the following questions: How the middle managers make sense of the corporate strategic planning imposed by the parent company? How they appropriate the new vision and decline it into actions on the ground? We chose the individual interview technique through open-ended questions as the source of data collection. We first of all carried out an exploratory approach by interviewing 8 members of the Management committee’s decision and 19 heads of services. The first findings and results show that exist a divergence of opinion and interpretations of the corporate strategic planning among organization members and there are difficulties to make sense and interpretations of the signals of the environment. The lead plant strategy enables new projects which insure the workload of Delta Company. Nevertheless, it creates a tension and stress among the middle managers because its provoke lack of resources to the detriment of their main jobs as manufacturer plant. The middle managers does not have a clear vision and they are wondering if the new strategic vision means more autonomy and less support from the group.

Keywords: change, middle managers, vision, sensemaking

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Authors: Hazel Pettifor, Charlie Wilson, David Mccollum, Oreane Edelenbosch

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Vehicle purchase is a technology adoption decision that will strongly influence future energy and emission outcomes. Global integrated assessment models (IAMs) provide valuable insights into the medium and long terms effects of socio-economic development, technological change and climate policy. In this paper we present a unique and transparent approach for improving the behavioural representation of these models by incorporating social influence effects to more accurately represent consumer choice. This work draws together strong conceptual thinking and robust empirical evidence to introduce heterogeneous and interconnected consumers who vary in their aversion to new technologies. Focussing on vehicle choice, we conduct novel empirical research to parameterise consumer risk aversion and how this is shaped by social and cultural influences. We find robust evidence for social influence effects, and variation between countries as a function of cultural differences. We then formulate an approach to modelling social influence which is implementable in both simulation and optimisation-type models. We use two global integrated assessment models (IMAGE and MESSAGE) to analyse four scenarios that introduce social influence and cultural differences between regions. These scenarios allow us to explore the interactions between consumer preferences and social influence. We find that incorporating social influence effects into global models accelerates the early deployment of electric vehicles and stimulates more widespread deployment across adopter groups. Incorporating cultural variation leads to significant differences in deployment between culturally divergent regions such as the USA and China. Our analysis significantly extends the ability of global integrated assessment models to provide policy-relevant analysis grounded in real-world processes.

Keywords: behavioural realism, electric vehicles, social influence, vehicle choice

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Authors: Farheen Tabassum, Shoab Ahmed Khan

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The brutality of attacks on networks and decisive infrastructures are on the climb over recent years and appears to continue to do so. Distributed Denial of service attack is the most prevalent and easy attack on the availability of a service due to the easy availability of large botnet computers at cheap price and the general lack of protection against these attacks. Application layer DDoS attack is DDoS attack that is targeted on wed server, application server or database server. These types of attacks are much more sophisticated and challenging as they get around most conventional network security devices because attack traffic often impersonate normal traffic and cannot be recognized by network layer anomalies. Conventional techniques of single-hosted security systems are becoming gradually less effective in the face of such complicated and synchronized multi-front attacks. In order to protect from such attacks and intrusion, corporation among all network devices is essential. To overcome this issue, a collaborative intrusion detection system (CIDS) is proposed in which multiple network devices share valuable information to identify attacks, as a single device might not be capable to sense any malevolent action on its own. So it helps us to take decision after analyzing the information collected from different sources. This novel attack detection technique helps to detect seemingly benign packets that target the availability of the critical infrastructure, and the proposed solution methodology shall enable the incident response teams to detect and react to DDoS attacks at the earliest stage to ensure that the uptime of the service remain unaffected. Experimental evaluation shows that the proposed collaborative detection approach is much more effective and efficient than the previous approaches.

Keywords: Distributed Denial-of-Service (DDoS), Collaborative Intrusion Detection System (CIDS), Slowloris, OSSIM (Open Source Security Information Management tool), OSSEC HIDS

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Authors: Yvonne Nanaama Brew, Bismark Jampim Abrokwah

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Children with disabilities in Ghana are not routinely registered, and this can imply that they may be neglected in national policy planning since global estimates may not be near the exact numbers. Although there are some studies with reports on the prevalence of disability among children in Ghana, reliable information on the prevalence, types of disability in children, and children who die with disabilities in the Greater Accra region are lacking. The current study seeks to investigate the incidence of disability among children two to fourteen years at selected districts in the Greater Accra region of Ghana. A cross-sectional design is adapted with a quantitative method for this study. Parents with disabled children who access child welfare clinics at the Greater Accra regional hospital, Maamobi hospital, Ga west, and Ga south district hospitals will be selected through purposive sampling for the study. An adapted UNICEF structured Ten Questions will be used to collect relevant data about participants. The responses to the questions will be either 'Yes' or 'No'. Parents with children who answer 'Yes' to a disability and purposively sampled parents with children who answer 'No' to disability will be invited to Child Health Clinic at the Greater Accra regional hospital for a free clinical assessment. Data will be entered into Microsoft Office Excel 2013 and imported into STATA version 15 for analysis. The study is expected to provide reliable disaggregated data on less than fourteen years of children with disabilities in the Greater Accra region. The findings and recommendations of the study will demonstrate the importance of early detection of disability and facilitate more quality and holistic planning of appropriate programmes that best safeguard the rights of children with disabilities in Ghana. It will help in policy and decision-making on children less than fourteen years with disabilities in Ghana. Also, findings will be useful for health facilities in Ghana to plan services for disabled children. Finally, the study is expected to add to the guides for the National Council of Persons with Disabilities to fulfill its legal mandate for disabled persons in Ghana.

Keywords: prevalence, disability, children, Ghana

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Authors: Abrha Ybeyn Gebremedhn, Yitea Seneshaw Getahun, Alebachew Shumye Moges, Fikrey Tesfay

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Rainfed agriculture in Ethiopia has failed to produce enough food, to achieve the increasing demand for food. Pinpointing the appropriate site for rainwater harvesting (RWH) have a substantial contribution to increasing the available water and enhancing agricultural productivity. The current study related to the identification of the potential RWH sites was conducted at the Chacha watershed central highlands of Ethiopia which is endowed with rugged topography. The Geographic Information System with Analytical Hierarchy Process was used to generate the different maps for identifying appropriate sites for RWH. In this study, 11 factors that determine the RWH locations including slope, soil texture, runoff depth, land cover type, annual average rainfall, drainage density, lineament intensity, hydrologic soil group, antecedent moisture content, and distance to the roads were considered. The overall analyzed result shows that 10.50%, 71.10%, 17.90%, and 0.50% of the areas were found under highly, moderately, marginally suitable, and unsuitable areas for RWH, respectively. The RWH site selection was found highly dependent on a slope, soil texture, and runoff depth; moderately dependent on drainage density, annual average rainfall, and land use land cover; but less dependent on the other factors. The highly suitable areas for rainwater harvesting expansion are lands having a flat topography with a soil textural class of high-water holding capacity that can produce high runoff depth. The application of this study could be a baseline for planners and decision-makers and support any strategy adoption for appropriate RWH site selection.

Keywords: runoff depth, antecedent moisture condition, AHP, weighted overlay, water resource

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Authors: Dagnew Dessie Mengie

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The purpose of this study was to investigate German tourists' demand for Ethiopian tourism destinations. The author has made every effort to identify the differences in the preferences of German visitors’ demand in Ethiopia comparing with Egypt, Kenya, Tanzania, and South African tourism sectors if they are invited to visit at the same time. However, the demand of international tourism for Ethiopia currently lags behind these African countries. Therefore, to offer demand-driven tourism products, the Ethiopian government, Tour & Travel operators need to understand the important factors that affect international tourists’ decision to visit Ethiopian tourist destinations. The aim of this study was intended to analyze German Tourists’ Demand towards Ethiopian destination. The researcher aimed to identify the demand for German tourists’ preference to Ethiopian tourist destinations comparing to the above-mentioned African countries. For collecting and analysing data for this study, both quantitative and qualitative methods of research are being used in this study. The most significant data are collected by using the primary data collection method i.e. survey and interviews which are the most and large number of potential responses and feedback from nine German active tourists,12 Ethiopian tourism officials, four African embassies, and four well functioning private tour companies and secondary data collected from books, journals, previous research and electronic websites. based on the data analysis of the information gathered from interviews and questionnaires, the study disclosed that majority of German tourists have not that much high demand on Ethiopian Tourist destinations due to the following reasons; Many Germans are fascinated by adventures, safari and simply want to lie on the beach and relax. These interests have leaded them to look for other African countries which have these accesses. Uncomfortable infrastructure and transport problems attributed for the decreasing the number of German tourists in the country. Inadequate marketing operation of Ethiopian Tourism Authority and its delegates in advertising and clarifying the above irregularities which are raised by the tourists.

Keywords: environmental benefits of tourism, social benefits of tourism, economical benefits of tourism, political factors in tourism

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Authors: T. Iakovleva

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Present paper suggests a theoretical model that describes the process of the development of responsible innovations on the firm level in health and welfare sectors. There is a need to develop new firm strategies in these sectors. This paper suggests to look on the concept of responsible innovation that was originally developed on the social level and to apply this new concept to the new area of firm strategy. The rapid global diffusion of information and communication technologies has greatly improved access to knowledge. At the same time, communication is cheap, information is a commodity, and global trade increases technological diffusion. As a result, firms and users, including those outside of industrialized nations, get early exposure to the latest technologies and information. General-purpose technologies such as mobile phones and 3D printers enable individuals to solve local needs and customize products. The combined effect of these changes is having a profound impact on the innovation landscape. Meanwhile, the healthcare sector is facing unprecedented challenges, which are magnified by budgetary constraints, an aging population and the desire to provide care for all. On the other hand, patients themselves are changing. They are savvier about their diseases, they expect their relation with the healthcare professionals to be open and interactive, but above all they want to be part of the decision process. All of this is a reflection of what is already happening in other industries where customers have access to large amount of information and became educated buyers. This article addresses the question of how ICT research and innovation may contribute to developing solutions to grand societal challenges in a responsible way. A broad definition of the concept of responsibility in the context of innovation is adopted in this paper. Responsibility is thus seen as a collective, uncertain and future-oriented activity. This opens the questions of how responsibilities are perceived and distributed and how innovation and science can be governed and stewarded towards socially desirable and acceptable ends. This article addresses a central question confronting politicians, business leaders, and regional planners.

Keywords: responsible innovation, ICT, healthcare, welfare sector

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Authors: Bong Jae Lee, Jeong Il Lee, Hyo Su Kim

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Both developed and developing countries have adopted the decision to join the Paris agreement to reduce greenhouse gas (GHG) emissions at the Conference of the Parties (COP) 21 meeting in Paris. As a result, the developed and developing countries have to submit the Intended Nationally Determined Contributions (INDC) by 2020, and each country will be assessed for their performance in reducing GHG. After that, they shall propose a reduction target which is higher than the previous target every five years. Therefore, an accurate method for calculating greenhouse gas emissions is essential to be presented as a rational for implementing GHG reduction measures based on the reduction targets. Non-CO2 GHGs (CF4, NF3, N2O, SF6 and so on) are being widely used in fabrication process of semiconductor manufacturing, and etching/deposition process of display manufacturing process. The Global Warming Potential (GWP) value of Non-CO2 is much higher than CO2, which means it will have greater effect on a global warming than CO2. Therefore, GHG calculation methods of the electronics industry are provided by Intergovernmental Panel on climate change (IPCC) and U.S. Environmental Protection Agency (EPA), and it will be discussed at ISO/TC 146 meeting. As discussed earlier, being precise and accurate in calculating Non-CO2 GHG is becoming more important. Thus this study aims to discuss the implications of the calculating methods through comparing the methods of IPCC and EPA. As a conclusion, after analyzing the methods of IPCC & EPA, the method of EPA is more detailed and it also provides the calculation for N2O. In case of the default emission factor (by IPCC & EPA), IPCC provides more conservative results compared to that of EPA; The factor of IPCC was developed for calculating a national GHG emission, while the factor of EPA was specifically developed for the U.S. which means it must have been developed to address the environmental issue of the US. The semiconductor factory ‘A’ measured F gas according to the EPA Destruction and Removal Efficiency (DRE) protocol and estimated their own DRE, and it was observed that their emission factor shows higher DRE compared to default DRE factor of IPCC and EPA Therefore, each country can improve their GHG emission calculation by developing its own emission factor (if possible) at the time of reporting Nationally Determined Contributions (NDC). Acknowledgements: This work was supported by the Korea Evaluation Institute of Industrial Technology (No. 10053589).

Keywords: non-CO2 GHG, GHG emission, electronics industry, measuring method

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Authors: Bin Feng, Zhulin Zong

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Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

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Authors: Wann-Ming Wey

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In recent years, in addition to face the external threats such as energy shortages and climate change, traffic congestion and environmental pollution have become anxious problems for many cities. Considering private automobile-oriented urban development had produced many negative environmental and social impacts, the transit-oriented development (TOD) has been considered as a sustainable urban model. TOD encourages public transport combined with friendly walking and cycling environment designs, however, non-motorized modes help improving human health, energy saving, and reducing carbon emissions. Due to environmental changes often affect the planners’ decision-making; this research applies dynamic network process (DNP) which includes the time dependent concept to promoting friendly walking and cycling environmental designs as an advanced planning support system for environment improvements. This research aims to discuss what kinds of design strategies can improve a friendly walking and cycling environment under TOD. First of all, we collate and analyze environment designing factors by reviewing the relevant literatures as well as divide into three aspects of “safety”, “convenience”, and “amenity” from fifteen environment designing factors. Furthermore, we utilize fuzzy Delphi Technique (FDT) expert questionnaire to filter out the more important designing criteria for the study case. Finally, we utilized DNP expert questionnaire to obtain the weights changes at different time points for each design criterion. Based on the changing trends of each criterion weight, we are able to develop appropriate designing strategies as the reference for planners to allocate resources in a dynamic environment. In order to illustrate the approach we propose in this research, Taipei city as one example has been used as an empirical study, and the results are in depth analyzed to explain the application of our proposed approach.

Keywords: environment planning support systems, walking and cycling, transit-oriented development (TOD), dynamic network process (DNP)

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Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

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Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

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Authors: Dosun Shin, Assegid Kidane, Pavan Turaga

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According to the National Institute of Health, living a sedentary lifestyle leads to a number of health issues, including increased risk of cardiovascular dis-ease, type 2 diabetes, obesity, and certain types of cancers. This project brings together experts in multiple disciplines to bring product design, sensor design, algorithms, and health intervention studies to develop a product and system that helps reduce the amount of time sitting at the workplace. This paper illustrates ongoing improvements to prototypes the research team developed in initial research; including working prototypes with a software application, which were developed and demonstrated for users. Additional modifications were made to improve functionality, aesthetics, and ease of use, which will be discussed in this paper. Extending on the foundations created in the initial phase, our approach sought to further improve the product by conducting additional human factor research, studying deficiencies in competitive products, testing various materials/forms, developing working prototypes, and obtaining feedback from additional potential users. The solution consisted of an aesthetically pleasing seat cover cushion that easily attaches to common office chairs found in most workplaces, ensuring a wide variety of people can use the product. The product discreetly contains sensors that track when the user sits on their chair, sending information to a phone app that triggers reminders for users to stand up and move around after sitting for a set amount of time. This paper also presents the analyzed typical office aesthetics and selected materials, colors, and forms that complimented the working environment. Comfort and ease of use remained a high priority as the design team sought to provide a product and system that integrated into the workplace. As the research team continues to test, improve, and implement this solution for the sedentary workplace, the team seeks to create a viable product that acts as an impetus for a more active workday and lifestyle, further decreasing the proliferation of chronic disease and health issues for sedentary working people. This paper illustrates in detail the processes of engineering, product design, methodology, and testing results.

Keywords: anti-sedentary work behavior, new product development, sensor design, health intervention studies

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Authors: Marcel Schneider, Nils Nießen

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Microscopic simulation programs enable the description of the two processes of railway operation and the previous timetabling. Occupation conflicts are often solved based on defined train priorities on both process levels. These conflict resolutions produce knock-on delays for the involved trains. The sum of knock-on delays is commonly used to evaluate the quality of railway operations. It is either compared to an acceptable level-of-service or the delays are evaluated economically by linearly monetary functions. It is impossible to properly evaluate dispatching decisions without a well-founded objective function. This paper presents a new approach for evaluation of dispatching decisions. It uses models of choice of transport and considers the behaviour of the end-costumers. These models evaluate the knock-on delays in more detail than linearly monetary functions and consider other competing modes of transport. The new approach pursues the coupling of a microscopic model of railway operation with the macroscopic model of choice of transport. First it will be implemented for the railway operations process, but it can also be used for timetabling. The evaluation considers the possibility to change over to other transport modes by the end-costumers. The new approach first looks at the rail-mounted and road transport, but it can also be extended to air transport. The split of the end-costumers is described by the modal-split. The reactions by the end-costumers have an effect on the revenues of the railway undertakings. Various travel purposes has different pavement reserves and tolerances towards delays. Longer journey times affect besides revenue changes also additional costs. The costs depend either on time or track and arise from circulation of workers and vehicles. Only the variable values are summarised in the contribution margin, which is the base for the monetary evaluation of the delays. The contribution margin is calculated for different resolution decisions of the same conflict. The conflict resolution is improved until the monetary loss becomes minimised. The iterative process therefore determines an optimum conflict resolution by observing the change of the contribution margin. Furthermore, a monetary value of each dispatching decision can also be determined.

Keywords: choice of transport, knock-on delays, monetary evaluation, railway operations

Procedia PDF Downloads 325