Search results for: Dong minority residential architecture

Authors: Maria Christofi, George Plastiras, Rafaella Elia, Vaggelis Tsiourtis, Theocharis Theocharides, Miltiadis Katsaros

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The rapidly expanding urban areas of the world constitute a challenge of how we need to make the transition to "the next urbanization", which will be defined by new analytical tools and new sources of data. This paper is about the production of a spatial application, the ‘FUMapp’, where space and its initiative will be available literally, in meters, but also abstractly, at a sensed level. While existing spatial applications typically focus on illustrations of the urban infrastructure, the suggested application goes beyond the existing: It investigates how our environment's perception adapts to the alterations of the built environment through a dataset construction of biophysical measurements (eye-tracking, heart beating), and physical metrics (spatial characteristics, size of stimuli, rhythm of mobility). It explores the intersections between architecture, cognition, and computing where future design can be improved and identifies the flexibility and livability of the ‘available space’ of specific examined urban paths.

Keywords: biophysical data, flexibility of urban, livability, next urbanization, spatial application

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Authors: Lei Guo, Xu Zhang, Weigang Hou

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Since the traditional network is closed and it has no architecture to create applications, it has been unable to evolve with changing demands under the rapid innovation in services. Additionally, due to the lack of the whole network profile, the quality of service cannot be well guaranteed in the traditional network. The Software Defined Network (SDN) utilizes global resources to support on-demand applications/services via open, standardized and programmable interfaces. In this paper, we implement the traffic grooming application under a real SDN environment, and the corresponding analysis is made. In our SDN: 1) we use OpenFlow protocol to control the entire network by using software applications running on the network operating system; 2) several virtual switches are combined into the data forwarding plane through Open vSwitch; 3) An OpenFlow controller, NOX, is involved as a logically centralized control plane that dynamically configures the data forwarding plane; 4) The traffic grooming based on SDN is demonstrated through dynamically modifying the idle time of flow entries. The experimental results demonstrate that the SDN-based traffic grooming effectively reduces the end-to-end delay, and the improvement ratio arrives to 99%.

Keywords: NOX, OpenFlow, Software Defined Network (SDN), traffic grooming

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Authors: Arun Sanjel, Greg Speegle

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Every second, massive amounts of data are generated, and Data Intensive Scalable Computing (DISC) frameworks have evolved into effective tools for analyzing such massive amounts of data. Since the underlying architecture of these distributed computing platforms is often new to users, building a DISC application can often be time-consuming and prone to errors. The automated conversion of a sequential program to a DISC program will consequently significantly improve productivity. However, synthesizing a user’s intended program from an input specification is complex, with several important applications, such as distributed program synthesizing and code refactoring. Existing works such as Tyro and Casper rely entirely on deductive synthesis techniques or similar program synthesis approaches. Our approach is to develop a data-driven synthesis technique to identify sequential components and translate them to equivalent distributed operations. We emphasize using reinforcement learning and unit testing as feedback mechanisms to achieve our objectives.

Keywords: program synthesis, distributed computing, reinforcement learning, unit testing, DISC

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Sean Paulsen, Michael Casey

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In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

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Authors: Hyunho Shin, Jaekwang Jung, Jeongho Park, Sungwon Hwang

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For the application of graphene quantum dots (GQDs) to optoelectronic nanodevices, it is of critical importance to understand the mechanisms which result in novel phenomena of their light absorption/emission. The optical transitions are known to be available up to ~6 eV in GQDs, especially useful for ultraviolet (UV) photodetectors (PDs). Here, we present size-dependent shape/edge-state variations of GQDs and visible photoluminescence (PL) showing anomalous size dependencies. With varying the average size (da) of GQDs from 5 to 35 nm, the peak energy of the absorption spectra monotonically decreases, while that of the visible PL spectra unusually shows nonmonotonic behaviors having a minimum at diameter ∼17 nm. The PL behaviors can be attributed to the novel feature of GQDs, that is, the circular-to-polygonal-shape and corresponding edge-state variations of GQDs at diameter ∼17 nm as the GQD size increases, as demonstrated by high resolution transmission electron microscopy. We believe that such a comprehensive scheme in designing device architecture and the structural formulation of GQDs provides a device for practical realization of environmentally benign, high performance flexible devices in the future.

Keywords: graphene, quantum dot, size, photoluminescence

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Authors: Rajashekhar K. Patil, Martin J. Babu

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Weaver ants-Oecophylla smaragdina live in colonies that have polymorphic castes. The females which include the queen, major and minor workers are haploid. The individuals of castes are dependent on olfactory cues for carrying out caste-specific behaviour. In an effort to understand whether organizational differences exist to support these behavioural differences, we studied the olfactory system at the level of the sensilla on the antennae, olfactory glomeruli and the Kenyon cells in the mushroom bodies (MB). The MB differ in major and minor workers in terms of their size, with the major workers having relatively larger calyces and peduncle. The morphology of different types of Kenyon cells as revealed by Golgi-rapid staining was studied and the major workers had more dendritic arbors than minor workers. This suggests a greater degree of olfactory processing in major workers. Differences in caste-specific arrangement of sensilla, olfactory glomeruli and celluar architecture of MB indicate a developmental programme that forms basis of differential behaviour.

Keywords: ant, oecophylla, caste, mushroom body

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Authors: Amin Ebrahimi Ghadi, Morteza Moalagh

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This research is carried out to find how a perfect combination of IoT architecture (Internet of Things) and ERP system can strengthen environmental accounting to incorporate both economic and environmental information. IoT (e.g., sensors, software, and other technologies) can be used in the company’s value chain from raw material extraction through materials processing, manufacturing products, distribution, use, repair, maintenance, and disposal or recycling products (Cradle to Grave model). The desired ERP software then will have the capability to track both midpoint and endpoint environmental impacts on a green supply chain system for the whole life cycle of a product. All these enable environmental accounting to calculate, and real-time analyze the operation environmental impacts, control costs, prepare for environmental legislation and enhance the decision-making process. In this study, we have developed a model on how to use IoT devices in life cycle assessment (LCA) to gather emissions, energy consumption, hazards, and wastes information to be processed in different modules of ERP systems in an integrated way for using in environmental accounting to achieve sustainability.

Keywords: ERP, environmental accounting, green supply chain, IOT, life cycle assessment, sustainability

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Authors: Shaine Mehta, Neelam Parmar, Patrick White, Mark Ashworth

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Patients with a history of substance have a high prevalence of comorbidities, including asthma and chronic obstructive pulmonary disease (COPD). Mortality rates are higher than that of the general population and the link to respiratory disease is reported. Randomised controlled trials (RCTs) support opioid substitution therapy as an effective means for harm reduction. However, whilst a high proportion of patients receiving opioid substitution therapy are smokers, to the author’s best knowledge there have been no studies of respiratory disease and smoking intensity in these patients. A cross sectional prevalence study was conducted using an anonymised patient-level database in primary care, Lambeth DataNet (LDN). We included patients aged 18 years and over who had records of ever having been prescribed methadone in primary care. Patients under 18 years old or prescribed buprenorphine (because of uncertainty about the prescribing indication) were excluded. Demographic, smoking, alcohol and asthma and COPD coding data were extracted. Differences between methadone and non-methadone users were explored with multivariable analysis. LDN contained data on 321, 395 patients ≥ 18 years; 676 (0.16%) had a record of methadone prescription. Patients prescribed methadone were more likely to be male (70.7% vs. 50.4%), older (48.9yrs vs. 41.5yrs) and less likely to be from an ethnic minority group (South Asian 2.1% vs. 7.8%; Black African 8.9% vs. 21.4%). Almost all those prescribed methadone were smokers or ex-smokers (97.3% vs. 40.9%); more were non-alcohol drinkers (41.3% vs. 24.3%). We found a high prevalence of COPD (12.4% vs 1.4%) and asthma (14.2% vs 4.4%). Smoking intensity data shows a high prevalence of ≥ 20 cigarettes per day (21.5% vs. 13.1%). Risk of COPD, adjusted for age, gender, ethnicity and deprivation, was raised in smokers: odds ratio 14.81 (95%CI 11.26, 19.47), and in the methadone group: OR 7.51 (95%CI: 5.78, 9.77). Furthermore, after adjustment for smoking intensity (number of cigarettes/day), the risk was raised in methadone group: OR 4.77 (95%CI: 3.13, 7.28). High burden of respiratory disease compounded by the high rates of smoking is a public health concern. This supports an integrated approach to health in patients treated for opiate dependence, with access to smoking cessation support. Further work may evaluate the current structure and commissioning of substance misuse services, including smoking cessation. Regression modelling highlights that methadone as a ‘risk factor’ was independently associated with COPD prevalence, even after adjustment for smoking intensity. This merits further exploration, as the association may be related to unexplored aspects of smoking (such as the number of years smoked) or may be related to other related exposures, such as smoking heroin or crack cocaine.

Keywords: methadone, respiratory disease, smoking cessation, substance misuse

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Authors: Muhammad Ali Sarwar, Muhammad Farooq, Nayab Hassan, Hammad Hassan

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Pakistan is highly recognized for its agriculture and is well known for producing substantial amounts of wheat, cotton, and sugarcane. However, some factors contribute to a decline in crop quality and a reduction in overall output. One of the main factors contributing to this decline is the presence of weed and its late detection. This process of detection is manual and demands a detailed inspection to be done by the farmer itself. But by the time detection of weed, the farmer will be able to save its cost and can increase the overall production. The focus of this research is to identify and classify the four main types of weeds (Small-Flowered Cranesbill, Chick Weed, Prickly Acacia, and Black-Grass) that are prevalent in our region’s major crops. In this work, we implemented three different deep learning techniques: YOLO-v5, Inception-v3, and Deep CNN on the same Dataset, and have concluded that deep convolutions neural network performed better with an accuracy of 97.45% for such classification. In relative to the state of the art, our proposed approach yields 2% better results. We devised the architecture in an efficient way such that it can be used in real-time.

Keywords: deep convolution networks, Yolo, machine learning, agriculture

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Authors: Shiksha Jain, Ramesh Mishra

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One of the most widely used complex signals processing operation is filtering. The most important FIR digital filter are widely used in DSP for filtering to alter the spectrum according to some given specifications. Power consumption and Area complexity in the algorithm of Finite Impulse Response (FIR) filter is mainly caused by multipliers. So we present a multiplier less technique (DA technique). In this technique, precomputed value of inner product is stored in LUT. Which are further added and shifted with number of iterations equal to the precision of input sample. But the exponential growth of LUT with the order of FIR filter, in this basic structure, makes it prohibitive for many applications. The significant area and power reduction over traditional Distributed Arithmetic (DA) structure is presented in this paper, by the use of slicing of LUT to the desired length. An architecture of 16 tap FIR filter is presented, with different length of slice of LUT. The result of FIR Filter implementation on Xilinx ISE synthesis tool (XST) vertex-4 FPGA Tool by using proposed method shows the increase of the maximum frequency, the decrease of the resources as usage saving in area with more number of slices and the reduction dynamic power.

Keywords: multiplier less technique, linear phase symmetric FIR filter, FPGA tool, look up table

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Authors: Diego Roberto Goncalves De Pontes, Sergio Donizetti Zorzo

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Studies show that most users do not read privacy policies from the online services they use. Some authors claim that one of the main causes of this is that policies are long and usually hard to understand, which make users lose interest in reading them. In this scenario, users may agree with terms without knowing what kind of data is being collected and why. Given that, we aimed to develop a model that would present the privacy policies contents in an easy and graphical way for the user to understand. We call it the Privacy Label. Using information recovery techniques, we propose an architecture that is able to extract information about what kind of data is being collected and to what end in the policies and show it to the user in an automated way. To assess our model, we calculated the precision, recall and f-measure metrics on the information extracted by our technique. The results for each metric were 68.53%, 85.61% e 76,13%, respectively, making it possible for the final user to understand which data was being collected without reading the whole policy. Also, our proposal can facilitate the notice-and-choice by presenting privacy policy information in an alternative way for online users.

Keywords: privacy, policies, user behavior, computer human interaction

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Authors: Deliou Adel, Saadalah Younes, Belkaid Khmissi, Dehbi Meriem

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Composite materials, in the most common sense of the term, are a set of synthetic materials designed and used mainly for structural applications; the mechanical function is dominant. The mechanical behaviors of the composite, as well as the degradation mechanisms leading to its rupture, depend on the nature of the constituents and on the architecture of the fiber preform. The profile is required because it guides the engineer in designing structures with precise properties in relation to the needs. This work is about studying the mechanical behavior of unidirectional composite laminates according to different failure criteria. Varying strength parameter values make it possible to compare the ultimate mechanical characteristics obtained by the criteria of Tsai-Hill, Fisher and maximum stress. The laminate is subjected to uniaxial tensile membrane forces. Estimates of their ultimate strengths and the plotting of the failure envelope constitute the principal axis of this study. Using the theory of maximum stress, we can determine the various modes of damage of the composite. The different components of the deformation are presented for different orientations of fibers.

Keywords: unidirectional kevlar/epoxy composite, failure criterion, membrane stress, deformations, failure envelope

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Authors: Fariyal Mir

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The largest minority group over Pakistan lives in the farthest region of KPK, Chitral, which enclosed all its people in one closet despite their diversity. Chitral is considered a tourist hub and piece of paradise on earth. The major attraction of Chitral is the Kalash valley, which is also known as the homeland of kafir or 'weavers of the black robes'. Kalash people are counted as the primitive pagan tribe who practice culture, beliefs, and a lifestyle which dated beyond and distinct from the rest of the region. Their religious belief is known to be as 'animism', which means that objects, places, and creatures all possess a distinct spiritual essence. They also believe that nature plays a highly significant and spiritual role in their daily life. As they have their different festivals like (a) Chilam Josh: celebrated in May to welcome spring, (b) Uchaw: which is observed in late August to ensure good crops of wheat, (c) Chanmos: which is being observed in December for more than two weeks, grand festival and is celebrated to welcome New Year. Their concept of purity and impurity is also very traditional and part of their religious belief as well. They used to call the man as pure 'Oshniru' (pure, holy) and woman as impure 'Chetu' (dirty, polluted, or contaminated). This study is based on ethnomethodology, which focuses on the way people make sense of their daily life. Their unique belief system connects them with the descendants of the armies of Alexander the Great, who called the Hindu Kush 'Parapamisus', meaning mountains over which eagles can fly. With time, their cultural system was molded into many ways, and the same is going on with the true beauty of Chitral in the form of conversion to Islam and adaptation of modern lifestyle. Ethnomethodology also supports this, that people are always good in their original form so they can be called the true representatives of their origin and cultural identity. It also argues that human society is based on the method of achieving and displaying not on the imposition of others' order and laws. So, everybody is obliged to respect and not to harm the beliefs and culture of all other human fellows. Some historians believe that these Kalash people are from Afghanistan and their origin is Saim which is known as Thailand, but those Kalash tribe from Afghanistan were forced to embrace Islam and only Pakistan keeps these people who own unique cultural values, ornaments and entire culture. Kalasha culture has been listed by UNESCO for consideration as World Heritage. It is necessary to save these people from the cultural invasion caused by modernity, forced religious conversion to maintain the pluralistic diversity of our country.

Keywords: Chitral, cultural identity, ethnomethodology, Kalasha culture

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Authors: Pellecchia M. T., Savarese G., Carpinelli L., Calabrese M.

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Introduction: Parkinson's disease (PD) is characterized by a progressive loss of autonomy which undoubtedly has a significant impact on the quality of life of caregivers, and parents are the main informal caregivers. Caring for a person with PD is associated with an increased risk of psychiatric morbidity and persistent anxiety-depressive distress. The aim of the study is to investigate the burden on caregivers of patients with PD, through the use of multidimensional scales and to identify their personological and environmental determinants. Methods: The study has been approved by the Ethic Committee of the University of Salerno and informed consent for participation to the study was obtained from patients and their caregivers. The study was conducted at the Neurology Department of the A.O.U. "San Giovanni di Dio and Ruggi D’Aragona" of Salerno between September 2020 and May 2021. Materials: The questionnaires used were: a) Caregiver Burden Inventory - CBI a questionnaire of 24 items that allow identifying five sub-categories of burden (objective, psychological, physical, social, emotional); b) Depression Anxiety Stress Scales Short Version - DASS-21 questionnaire consisting of 21 items and valid in examining three distinct but interrelated areas (depression, anxiety and stress); c) Family Strain Questionnaire Short Form - FSQ-SF is a questionnaire of 30 items grouped in areas of increasing psychological risk (OK, R, SR, U); d) Zarit Caregiver Burden Inventory - ZBI, consisting of 22 items based on the analysis of two main factors: personal stress and pressure related to his role; e) Life Satisfaction, a single item that aims to evaluate the degree of life satisfaction in a global way using a 0-100 Likert scale. Findings: N ° 29 caregivers (M age = 55.14, SD = 9.859; 69% F) participated in the study. 20.6% of the sample had severe and severe burden (CBI score = M = 26.31; SD = 22.43) and 13.8% of participants had moderate to severe burden (ZBI). The FSQ-SF highlighted a minority of caregivers who need psychological support, in some cases urgent (Area SR and Area U). The DASS-21 results show a prevalence of stress-related symptoms (M = 10.90, SD = 10.712) compared to anxiety (M = 7.52, SD = 10.752) and depression (M = 8, SD = 10.876). There are significant correlations between some specific variables and mean test scores: retired caregivers report higher ZBI scores (p = 0.423) and lower Life Satisfaction levels (p = -0.460) than working caregivers; years of schooling show a negative linear correlation with the ZBI score (p = -0.491). The T-Test indicates that caregivers of patients with cognitive impairment are at greater risk than those of patients without cognitive impairment. Conclusions: It knows the factors that affect the burden the most would allow for early recognition of risky situations and caregivers who would need adequate support.

Keywords: anxious-depressive axis, caregivers’ burden, Parkinson’ disease, psychological risks

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Authors: A. Bertašienė

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Energy harvesting from any structure makes a challenge. Different structure of air/wind flows in industrial, environmental and residential applications emerge the real flow investigation in detail. Many of the application fields are hardly achievable to the detailed description due to the lack of up-to-date statistical data analysis. In situ measurements aim crucial investments thus the simulation methods come to implement structural analysis of the flows. Different configurations of testing environment give an overview how important is the simple structure of field in limited area on efficiency of the system operation and the energy output. Several configurations of modeled working sections in air flow test facility was implemented in CFD ANSYS environment to compare experimentally and numerically air flow development stages and forms that make effects on efficiency of devices and processes. Effective form and amount of these flows under different geometry cases define the manner of instruments/devices that measure fluid flow parameters for effective operation of any system and emission flows to define. Different fluid flow regimes were examined to show the impact of fluctuations on the development of the whole volume of the flow in specific environment. The obtained results rise the discussion on how these simulated flow fields are similar to real application ones. Experimental results have some discrepancies from simulation ones due to the models implemented to fluid flow analysis in initial stage, not developed one and due to the difficulties of models to cover transitional regimes. Recommendations are essential for energy harvesting systems in both, indoor and outdoor cases. Further investigations aim to be shifted to experimental analysis of flow under laboratory conditions using state-of-the-art techniques as flow visualization tool and later on to in situ situations that is complicated, cost and time consuming study.

Keywords: fluid flow, initial region, tube coefficient, distinct shape

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Authors: Austin Vander Wel, Katherin Vargas Henao

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Washington, DC, is a city in which Spanish, along with several other minority languages, is prevalent not only among tourists but also those living within city limits. In response to this linguistic diversity and DC’s adoption of the Language Access Act in 2004, the Washington Metropolitan Area Transit Authority (WMATA) committed to addressing the need for equal linguistic representation and established a five-step plan to provide the best multilingual information possible for public transportation users. The current study, however, strongly suggests that this de jure policy does not align with the reality of Spanish’s representation on DC public transportation–although perhaps doing so in an unexpected way. In order to investigate Spanish’s de facto representation and how it contrasts with de jure policy, this study implements a linguistic landscapes methodology that takes critical language-policy as its theoretical framework (Tollefson, 2005). Specifically concerning de facto representation, it focuses on the discrepancies between digital spaces and the actual physical spaces through which users travel. These digital vs. in situ conditions are further analyzed by separately addressing aural and visual modalities. In digital spaces, data was collected from WMATA’s website (visual) and their bilingual hotline (aural). For in situ spaces, both bus and metro areas of DC public transportation were explored, with signs comprising the visual modality and recordings, driver announcements, and interactions with metro kiosk workers comprising the aural modality. While digital spaces were considered to successfully fulfill WMATA’s commitment to representing Spanish as outlined in the de jure policy, physical spaces show a large discrepancy between what is said and what is done, particularly regarding the bus system, in addition to the aural modality overall. These discrepancies in situ spaces place Spanish speakers at a clear disadvantage, demanding additional resources and knowledge on the part of residents with limited or no English proficiency in order to have equal access to this public good. Based on our critical language-policy analysis, while Spanish is represented as a right in the de jure policy, its implementation in situ clearly portrays Spanish as a problem since those seeking bilingual information can not expect it to be present when and where they need it most (Ruíz, 1984; Tollefson, 2005). This study concludes with practical, data-based steps to improve the current situation facing DC’s public transportation context and serves as a model for responding to inadequate enactment of de jure policy in other language policy settings.

Keywords: Urban landscape, language access, critical-language policy, spanish, public transportation

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Authors: Moon-Soo Kim

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In order to cope with the increasing demand for multidisciplinary learning between academy and industry, a collaborative teaching and learning model and related operational tools enabling applications to engineering education are essential. This study proposes a web-based collaborative framework for interactive teaching and learning between academy and industry as an initial step for the development of a web- and mobile-based integrated system for both engineering students and industrial practitioners. The proposed web-based collaborative teaching and learning framework defines several entities such as learner, solver and supporter or sponsor for industrial problems, and also has a systematic architecture to build information system including diverse functions enabling effective interaction among the defined entities regardless of time and places. Furthermore, the framework, which includes knowledge and information self-reinforcing mechanism, focuses on the previous problem-solving records as well as subsequent learners’ creative reusing in solving process of new problems.

Keywords: collaborative teaching and learning model, academy and industry, web-based collaborative framework, self-reinforcing mechanism

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Authors: Shivani Dolas, A. Richa Mishra

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The existence of Courtyards in India can be traced back to ‘Indus valley civilization’ and various layers of history bearing implications like socio-cultural, traditional, religious, climatic, etc., moreover serving as a breathing space in case of historical core areas. Over time, with the overlay of various historic layers within the historic urban cores and the present high density populace, the cores are getting congested day by day. In this case, courtyards may emerge out as an efficient medium to provide quality of life through livable spaces. Presently, with the growing population of the historic town of Gwalior, town in Madhya Pradesh holds remarkable essence of courtyards with its multiple concepts over time. Its scale and function varies from an imposing grand appearance in palatial form, up to functional practices as residential. Its privilege can also be drawn in urban forms, in sharing single space by multiple dwellings and in temples which can be sketched specifically in the region. Moreover, the effectiveness of courtyards has proven balance and control of micro-climate in such composite climate region. The research paper aims to underline the concept of courtyards in case of a mixed use neighborhood, Naya bazar, in Lashkar area of Gwalior, which developed during 19th century, highlighting the need of its preservation. The paper also elaborates its various implications on user-space relationship as in the present context, and growing congestion in the area, user and space relationship is seen lost. The noticeable change in the behavioral context in buildings and users can be noticed with the downfall of courtyards, isolating users with land. Also, a concern has been expressed on negligence of courtyard planning in future development, suggesting recommendations on preserving the courtyard typology as heritage.

Keywords: courtyards, Gwalior, historic settlement, heritage

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Authors: Argyroula Argyrou

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The purpose of my current research, of which this paper form’s part, is to explore the architectural and religious transformations of Trypiti Bay in the region of Kourion, Cyprus, between the 1st and 6th centuries AD. This research aims to explore and analyse three different stages in the religious and architectural transformations of the ancient port, with evidence supporting these transformations from the main city of Kourion and the Sanctuary of Apollo Hylates between the 1st and 6th centuries. In addition, the research is using historical and archaeological comparisons with coastal sites in the Levant, North Africa, Lebanon, and Europe in an attempt to identify a pattern of development in the religious topography of Kourion and how these contributed to change in the use and symbolism of Trypiti bay as an important passageway to religious sanctuaries in the vicinity of the coast. The construction of Trypiti Bay has been proven, according to archaeological and historical evidence, gathered throughout Kourion’s fieldwork and archival research, that it served as a natural port for cargos that needed to be protected from the strong west winds of the area. The construction of Trypiti Bay is believed to be unique to the island as no similar structure has yet been discovered.

Keywords: architecture, heritage, perservation, transformation, unique

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Authors: Najmeh Malekpour Bahabadi

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Small fast-developing Iranian cities with a historical background have no defined criteria for their social sustainability. However, their traditional architecture is well-known as a socially and environmentally sustainable role model. In today's cities, citizens' participation has been considered an effective strategy to achieve social sustainability. By scrutinizing the extent and manner of public participation in traditional Iranian cities, taking Yazd's historical context as a case study, this study examines how these criteria can be applied to developing parts of the city. The paper first reviews the concepts, levels, and approaches of public participation to analyze different modes of citizen participation. Then, exploring social behavior and activities in Yazd, using the qualitative-analytical methodology, the paper compares diverse elements influencing participation with contemporary approaches. The findings of this study would lead to suggestions for the developing parts of the city to enhance their socially sustainable development.

Keywords: citizen participation, social behaviors, traditional city, built environment, social sustainability

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Authors: Donna Erika E. De Jesus

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Introduction: Cardiac arrest occurs when abrupt cessation of cardiac function results in loss of effective circulation and complete cardiovascular collapse. For every minute of cardiac arrest without early intervention (cardiopulmonary resuscitation [CPR], defibrillation), chances of survival drop by 7-10%. It is crucial that CPR be initiated within 4-6 minutes to avoid brain death. Most out-of-hospital cardiac arrests (OHCA) occur in a residential setting where access to trained personnel and equipment is not readily available, resulting in poor victim outcomes. Methods: This is a descriptive study done from August to November 2021 using a prospective cohort design. Participants of the study include adult patients aged 18 years and above brought to the emergency room who suffered from out-of-hospital cardiac arrest. Out of the total 102 cases of OHCA, 63 participants were included in the study. Descriptive statistics were used to summarize the demographic and clinical characteristics of the patients. Results: 43 were male patients, comprising the majority at 73.02%. Hypertension was identified as the top co-morbidity, followed by diabetes mellitus, heart failure, and chronic kidney disease (CKD). Medical causes of arrest were identified in 96.83% of the cases. 90.48% of cardiac arrests occurred at home. Only 26 patients (41.27%) received pre-hospital intervention prior to ER arrival, which comprised only hands-only CPR. Twenty-three of which were performed by individuals with background knowledge of CPR. 60.32% were brought via self-conduction, the remainder by ambulances, which were noted to have no available equipment necessary to provide proper resuscitation. The average travel time from dispatch to ER arrival is 20 minutes. Conclusion: Overall survival of OHCA in our local setting remains dismal, as a return of spontaneous circulation was not achieved in any of the patients. The small number of patients having pre-hospital CPR indicates the need for emphasis on training and community education.

Keywords: out-of-hospital cardiac arrest, cardiopulmonary resuscitation, basic life support, emergency medical services

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Authors: Sina Saadati

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Multiprocessors Systems-On-Chips (MPSOCs) are used widely on modern computers to execute sophisticated software and applications. These systems include different processors for distinct aims. Most of the proposed task schedulers attempt to improve energy consumption. In some schedulers, the processor's temperature is considered to increase the system's reliability and performance. In this research, we have proposed a new method for thermal-aware task scheduling which is based on an artificial neural network (ANN). This method enables us to consider a variety of factors in the scheduling process. Some factors like ambient temperature, season (which is important for some embedded systems), speed of the processor, computing type of tasks and have a complex relationship with the final temperature of the system. This Issue can be solved using a machine learning algorithm. Another point is that our solution makes the system intelligent So that It can be adaptive. We have also shown that the computational complexity of the proposed method is cheap. As a consequence, It is also suitable for battery-powered systems.

Keywords: task scheduling, MOSOC, artificial neural network, machine learning, architecture of computers, artificial intelligence

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Authors: Thilina Ranaweera, Enes Makalic, John L. Hopper, Adrian Bickerstaffe

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Data are the primary asset of biomedical researchers, and the engine for both discovery and research translation. As the volume and complexity of research datasets increase, especially with new technologies such as large single nucleotide polymorphism (SNP) chips, so too does the requirement for software to manage, process and analyze the data. Researchers often need to execute complicated queries and conduct complex analyzes of large-scale datasets. Existing tools to analyze such data, and other types of high-dimensional data, unfortunately suffer from one or more major problems. They typically require a high level of computing expertise, are too simplistic (i.e., do not fit realistic models that allow for complex interactions), are limited by computing power, do not exploit the computing power of large-scale parallel architectures (e.g. supercomputers, GPU clusters etc.), or are limited in the types of analysis available, compounded by the fact that integrating new analysis methods is not straightforward. Solutions to these problems, such as those developed and implemented on parallel architectures, are currently available to only a relatively small portion of medical researchers with access and know-how. The past decade has seen a rapid expansion of data management systems for the medical domain. Much attention has been given to systems that manage phenotype datasets generated by medical studies. The introduction of heterogeneous genomic data for research subjects that reside in these systems has highlighted the need for substantial improvements in software architecture. To address this problem, we have developed SPARK, an enabling and translational system for medical research, leveraging existing high performance computing resources, and analysis techniques currently available or being developed. It builds these into The Ark, an open-source web-based system designed to manage medical data. SPARK provides a next-generation biomedical data management solution that is based upon a novel Micro-Service architecture and Big Data technologies. The system serves to demonstrate the applicability of Micro-Service architectures for the development of high performance computing applications. When applied to high-dimensional medical datasets such as genomic data, relational data management approaches with normalized data structures suffer from unfeasibly high execution times for basic operations such as insert (i.e. importing a GWAS dataset) and the queries that are typical of the genomics research domain. SPARK resolves these problems by incorporating non-relational NoSQL databases that have been driven by the emergence of Big Data. SPARK provides researchers across the world with user-friendly access to state-of-the-art data management and analysis tools while eliminating the need for high-level informatics and programming skills. The system will benefit health and medical research by eliminating the burden of large-scale data management, querying, cleaning, and analysis. SPARK represents a major advancement in genome research technologies, vastly reducing the burden of working with genomic datasets, and enabling cutting edge analysis approaches that have previously been out of reach for many medical researchers.

Keywords: biomedical research, genomics, information systems, software

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Authors: Menaahyl Seraj, Gokce Ozdemir

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Tourism at destinations is dependent on various resources such as archeology and architecture. The need to preserve those resources is of the utmost importance when long-term tourism development is aimed. Shahi Guzargah (Royal Trail) was subject to a preservation project that is a linear historical passage within the Walled City of Lahore. Even though Lahore with its congested streets, lacks proper infrastructure and economically weak but yet it has the potential of transforming it into a tourist destination. This study highlights the potential hidden in the preservation of cultural resources through proper and concrete planning of living heritage city, and how it improves socio-economic standards of the community and affects tourism. Semi-structured open-ended interview question-forms were used to collect qualitative data from 14 respective stakeholders of the walled city and 10 concerned officials. The results of the study show that the preservation of cultural resources impacts and accelerates positively the development process of a destination. All opinions and gathered information reflect the importance of cultural preservation and its effect on increasing tourism.

Keywords: cultural tourism, cultural resources, destination, preservation

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Authors: Giovana Privatte Maciera, Jair Izaías Kappann

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Introduction: The violence against woman is a complex phenomenon that accompanies the woman throughout her life and is a result of a social, cultural, political and religious construction, based on the differences among the genders. Those differences are felt, mainly, because of the patriarchal system that is still present which just naturalize and legitimate the asymmetry of power. As consequence of the women’s lasting historical and collective effort for a legislation against the impunity of violence against women in the national scenery, it was ordained, in 2006, a law known as Maria da Penha. The law was created as a protective measure for women that were victims of violence and consequently for the punishment of the aggressor. Methodology: Analysis of police inquiries is established by the Police Station of Defense of the Woman of Assis city, by formal authorization of the justice, in the period of 2013 to 2015. For the evaluating of the results will be used the content analysis and the theoretical referential of Psychoanalysis. Results and Discussion: The final analysis of the inquiries demonstrated that the violence against women is reproduced by the society and the aggressor, in most cases it is a member of their own family, mainly the current or former-spouse. The most common kinds of aggression were: the threat bodily harm, and the physical violence, that normally happens accompanied by psychological violence, being the most painful for the victims. The biggest part of the aggressors was white, older than the victim, worker and had primary school. But, unlike the expected, the minority of the aggressors were users of alcohol and/or drugs and possessed children in common with the victim. There is a contrast among the number of victims who already admitted have suffered some type of violence earlier by the same aggressor and the number of victims who has registered the occurrence before. The aggressors often use the discourse of denial in their testimony or try to justify their act like the blame was of the victim. It is believed in the interaction of several factors that can influence the aggressor to commit the abuse, including psychological, personal and sociocultural factors. One hypothesis is that the aggressor has a violence history in the family origin. After the aggressor being judged, condemned or not, usually there is no rehabilitation plan or supervision that enable his change. Conclusions: It has noticed the importance of studying the aggressor’s characteristics and the reasons that took him to commit such violence, making possible the implementation of an appropriate treatment to prevent and reduce the aggressions, as well the creation of programs and actions that enable communication and understanding concerning the theme. This is because the recurrence is still high, since the punitive system is not enough and the law is still ineffective and inefficient in certain aspects and in its own functioning. It is perceived a compulsion in repeat so much for the victims as for the aggressors, because they end involving, almost always, in disturbed and violent relationships, with the relation of subordination-dominance as characteristic.

Keywords: aggressors' profile, gender equality, Maria da Penha law, violence against women

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Authors: Luther Ollier, Sylvie Thiria, Anastase Charantonis, Carlos E. Mejia, Michel Crépon

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Sea Surface Height Anomaly (SLA) is a signature of the sub-mesoscale dynamics of the upper ocean. Sea Surface Temperature (SST) is driven by these dynamics and can be used to improve the spatial interpolation of SLA fields. In this study, we focused on the temporal evolution of SLA fields. We explored the capacity of deep learning (DL) methods to predict short-term SLA fields using SST fields. We used simulated daily SLA and SST data from the Mercator Global Analysis and Forecasting System, with a resolution of (1/12)◦ in the North Atlantic Ocean (26.5-44.42◦N, -64.25–41.83◦E), covering the period from 1993 to 2019. Using a slightly modified image-to-image convolutional DL architecture, we demonstrated that SST is a relevant variable for controlling the SLA prediction. With a learning process inspired by the teaching-forcing method, we managed to improve the SLA forecast at five days by using the SST fields as additional information. We obtained predictions of a 12 cm (20 cm) error of SLA evolution for scales smaller than mesoscales and at time scales of 5 days (20 days), respectively. Moreover, the information provided by the SST allows us to limit the SLA error to 16 cm at 20 days when learning the trajectory.

Keywords: deep-learning, altimetry, sea surface temperature, forecast

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Authors: Xiao Yihong, Yu Kexin, Burra Venkata Durga Kumar

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With the accelerating process of urbanization, the problem of urban road congestion is becoming more and more serious. Intelligent transportation system combining distributed and artificial intelligence has become a research hotspot. As the core development direction of the intelligent transportation system, Cooperative Intelligent Transportation System (C-ITS) integrates advanced information technology and communication methods and realizes the integration of humans, vehicle, roadside infrastructure, and other elements through the multi-agent distributed system. By analyzing the system architecture and technical characteristics of C-ITS, the report proposes a distributed multi-agent C-ITS. The system consists of Roadside Sub-system, Vehicle Sub-system, and Personal Sub-system. At the same time, we explore the scalability of the C-ITS and put forward incorporating local rewards in the centralized training decentralized execution paradigm, hoping to add a scalable value decomposition method. In addition, we also suggest introducing blockchain to improve the safety of the traffic information transmission process. The system is expected to improve vehicle capacity and traffic safety.

Keywords: distributed system, artificial intelligence, multi-agent, cooperative intelligent transportation system

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Authors: Shih-Yu Wang, Shun-Wen Hsiao

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In the field of cybersecurity, there exists many vendors giving malware samples classified results, namely naming after the label that contains some important information which is also called AV label. Lots of researchers relay on AV labels for research. Unfortunately, AV labels are too cluttered. They do not have a fixed format and fixed naming rules because the naming results were based on each classifiers' viewpoints. A way to fix the problem is taking a majority vote. However, voting can sometimes create problems of bias. Thus, we create a novel ensemble approach which does not rely on the cacophonous naming result but depend on group identification to aggregate everyone's opinion. To achieve this purpose, we develop an scoring system called Pairwise Consensus Score (PCS) to calculate result similarity. The entire method architecture combine Genetic Algorithm and PCS to find maximum consensus in the group. Experimental results revealed that our method outperformed the majority voting by 10% in term of the score.

Keywords: genetic algorithm, ensemble learning, malware family, malware labeling, AV labels

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

Procedia PDF Downloads 305