Search results for: post classification change detection

Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

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Authors: Denise F. Brown, Melina McConatha

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African Americans utilizing the art of vocal expressions, particularly for self-expression, has been a historical avenue of advocating for social justice and human rights. Vocal expressions can take many forms, such as singing, poetry, storytelling, and acting. Many well-known artists, politicians, leaders, and teachers used their voices to promote the causes and concerns of the African American community as well as the expression of their own experiences of being 'black' in America. The purpose of this project was to evaluate the perceptions of African American students in utilizing their voices for self-awareness, interview skills, and social change after attending a three-part workshop on vocal advocacy. This research utilized the framework of black feminism to understand empowerment in advocacy and self-expression. Students participated in learning about the power of their voices, and what purpose presence, and passion they discovered through the Immersive Voice workshop. There were three areas covered in the workshop. The first area was the power of the voice, the second area was the application of vocal passion, and the third area was applying the vocal power to express personal interest, interests of advocating for others, and confidence and speaking to others to further careers, i.e., using vocal power for job interviewing skills. The students were instructed to prepare for the workshops by completing a pre-workshop open-ended survey. There were a total of 15 students that participated. After the workshop ended, the students were instructed to complete a post-workshop survey. The surveys were assessed by evaluating both themes and codes from student's written feedback. From the pre-workshop survey, students were given a survey for them to provide feedback regarding the power of voice prior to participating in the workshops. From the student's responses, the theme (advocating for self and others) emerged as it related to student's feedback on what it means to advocate. There were three codes that led to the theme, having knowledge about advocating for self and others, gaining knowledge to advocate for self and others, and using that knowledge to advocate for self and others. After the students completed participation in the workshops, a post workshop- survey was given to the students. Students' feedback was assessed, and the same theme emerged, 'advocating for self and others.' The codes related to the theme, however, were different and included using vocal power (a term students learned during the workshop) to represent self, represent others, and obtain a job/career. In conclusion, the results of the survey showed that students still perceived advocating as speaking up for themselves and other people. After the workshop, students still continued to associate advocacy with helping themselves and helping others but were able to be more specific about how the sound of their voice could help in advocating, and how they could use their voice to represent themselves in getting a job or starting a career.

Keywords: advocacy, command, self-expression, voice

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Authors: Yi-Ning Chang

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With the rapid advancement of technology, it has become crucial for educators to adeptly integrate technology into their teaching and develop a robust Computer-Assisted Language Learning (CALL) competency. Addressing this need, the present study adopted a technology-based Lesson Study approach to assess its impact on the CALL competency and professional capabilities of EFL teachers. Additionally, the study delved into teachers' perceptions of the benefits derived from participating in the creation of technologically integrated lesson plans. The iterative process of technology-based Lesson Study facilitated ample peer discussion, enabling teachers to flexibly design and implement lesson plans that incorporate various technological tools. This 15-week study included 10 in- service teachers from a university of science and technology in the central of Taiwan. The collected data included pre- and post- lesson planning scores, pre- and post- TPACK survey scores, classroom observation forms, designed lesson plans, and reflective essays. The pre- and post- lesson planning and TPACK survey scores were analyzed employing a pair-sampled t test; students’ reflective essays were respectively analyzed applying content analysis. The findings revealed that the teachers’ lesson planning ability and CALL competencies were improved. Teachers perceived a better understanding of integrating technology with teaching subjects, more effective teaching skills, and a deeper understanding of technology. Pedagogical implications and future studies are also discussed.

Keywords: CALL, language learning, lesson study, lesson plan

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Authors: Strahinja Z. Kovačević, Lidija R. Jevrić, Sanja O. Podunavac Kuzmanović

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The relationship between antibacterial activity of eighteen different substituted benzimidazole derivatives and their molecular characteristics was studied using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on inhibitory activity towards Staphylococcus aureus, by using molecular descriptors, as well as minimal inhibitory activity (MIC). Molecular descriptors were calculated from the optimized structures. Principal component analysis (PCA) followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR) was performed in order to select molecular descriptors that best describe the antibacterial behavior of the compounds investigated, and to determine the similarities between molecules. The HCA grouped the molecules in separated clusters which have the similar inhibitory activity. PCA showed very similar classification of molecules as the HCA, and displayed which descriptors contribute to that classification. MLR equations, that represent MIC as a function of the in silico molecular descriptors were established. The statistical significance of the estimated models was confirmed by standard statistical measures and cross-validation parameters (SD = 0.0816, F = 46.27, R = 0.9791, R2CV = 0.8266, R2adj = 0.9379, PRESS = 0.1116). These parameters indicate the possibility of application of the established chemometric models in prediction of the antibacterial behaviour of studied derivatives and structurally very similar compounds.

Keywords: antibacterial, benzimidazole, molecular descriptors, QSAR

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Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

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Authors: Emily Stamm, Neil Smyth, Elizabeth O'Sullivan

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In Identity-Based Encryption (IBE), an identity, such as a username, email address, or domain name, acts as the public key. IBE consolidates the PKI by eliminating the repetitive process of requesting public keys for each message encryption. Two of the most popular schemes are Sakai-Kasahara (SAKKE), which is based on elliptic curve pairings, and the Ducas, Lyubashevsky, and Prest lattice scheme (DLP- Lattice), which is based on quantum-secure lattice cryptography. In or- der to embed the schemes in a standard enterprise setting, both schemes are implemented as shared system libraries and integrated into a REST service that functions at the enterprise level. The performance of both schemes as libraries and services is compared, and the practicalities of implementation and application are discussed. Our performance results indicate that although SAKKE has the smaller key and ciphertext sizes, DLP-Lattice is significantly faster overall and we recommend it for most enterprise use cases.

Keywords: identity-based encryption, post-quantum cryptography, lattice-based cryptography, IBE

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Authors: Krupali Mukeshkumar, Jinesh Shah

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Background: Bilateral Sagittal Split Osteotomy (BSSO), used for the correction of mandibular deformities, is a common oral and maxillofacial surgical procedure. Inferior alveolar nerve dysfunction is commonly reported post-operatively by patients as paresthesia or anesthesia. The current literature lacks a consensus on the incidence of inferior alveolar nerve dysfunction as patients are not routinely assessed pre and post-operatively with an objective assessment. The range of incidence varies from 9% to 85% of patients, with some authors arguing that 100% of patients experience nerve dysfunction immediately post-surgery. Systematic reviews have shown a difference between incidence rates at different follow-up periods using objective and subjective methods. Aim: To identify the incidence of inferior alveolar nerve dysfunction following BSSO. Gold standard: Nerve dysfunction incidence rates similar or lower than current literature of 83% day one post-operatively and 18.4% at one year follow up. Setting: A retrospective cross-sectional audit of patients treated between 2017-2019 at the Royal Stoke University Hospital, Maxillofacial and Orthodontic departments. Sample: All patients who underwent a BSSO (with or without le fort one osteotomy) between 2017–2019 were identified from the database. Patients with pre-existing neurosensory disturbance, those who had a genioplasty at the same time and those with no follow-up were excluded. The sample consisted of 121 patients, 37 males and 84 females between the ages of 17-50 years at the time of surgery. Methods: Clinical records of 121 cases were reviewed to assess the age, sex, type of mandibular osteotomy, status of the nerve during the surgical procedure, type of bony split and incidence of nerve dysfunction at follow-up appointments. The surgical procedure was carried out by three Maxillo-facial surgeons and follow-up appointments were carried out in the Orthodontic and Oral and Maxillo-facial departments. Results: 120 patients were treated to correct the mandibular facial deformity and 1 patient was treated for sleep apnoea. Seventeen patients had a mandibular setback and 104 patients had mandibular advancement. 68 patients reported inferior alveolar nerve dysfunction at one week following their surgery. Seventy-six patients had temporary paresthesia present between 2 weeks and 12 months post-surgery. 13 patients had persistent nerve dysfunction at 12 months, of which 1 had a bad bony split during the BSSO. The incidence of nerve dysfunction postoperatively was 6.6% after 1 day, 56.1% at 1 week, 62.8% at 2 weeks, 59.5% between 3-6 weeks, 43.0% between 8-16 weeks and 10.7% at 1 year. Conclusions: The results of this audit show a similar incidence rate to the research gold standard at the one-year follow-up. Future Recommendations: No changes to surgical procedure or technique are indicated, but a need for improved documentation and a standardized approach for assessment of post-operative nerve dysfunction would be beneficial.

Keywords: bilateral sagittal split osteotomy, inferior alveolar nerve, mandible, nerve dysfunction

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Authors: Tanveer Ahmed Choudhury

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Background: Bangladesh is one of the largest deltas in the world, with high population density and high rates of poverty and illiteracy. 80% of the country is on low-lying floodplains, leaving the country one of the most vulnerable to the adverse effects of climate change: sea level rise, cyclones and storms, salinity intrusion, rising temperatures and heavy monsoon downpours. Such climatic events already limit Economic Development in the country. Although Bangladesh has had little responsibility in contributing to global climatic change, it is vulnerable to both its direct and indirect impacts. Real threats include reduced agricultural production, worsening food security, increased incidence of flooding and drought, spreading disease and an increased risk of conflict over scarce land and water resources. Currently, 8.3 million Bangladeshis live in cyclone high risk areas. However, by 2050 this is expected to grow to 20.3 million people, if proper adaptive actions are not taken. Under a high emissions scenario, an additional 7.6 million people will be exposed to very high salinity by 2050 compared to current levels. It is also projected that, an average of 7.2 million people will be affected by flooding due to sea level rise every year between 2070-2100 and If global emissions decrease rapidly and adaptation interventions are taken, the population affected by flooding could be limited to only about 14,000 people. To combat the climate change adverse effects, Bangladesh government has initiated many adaptive measures specially in infrastructure and renewable energy sector. Government is investing huge money and initiated many projects which have been proved very success full. Objectives: The objective of this paper is to describe some successful measures initiated by Bangladesh government in its effort to make the country a Climate Resilient. Methodology: Review of operation plan and activities of different relevant Ministries of Bangladesh government. Result: The following initiative projects, programs and activities are considered as best practices for Climate Change adaptation successes for Bangladesh: 1. The Infrastructure Development Company Limited (IDCOL); 2. Climate Change and Health Promotion Unit (CCHPU); 3. The Climate Change Trust Fund (CCTF); 4. Community Climate Change Project (CCCP); 5. Health, Population, Nutrition Sector Development Program (HPNSDP, 2011-2016)- "Climate Change and Environmental Issues"; 6. Ministry of Health and Family Welfare, Bangladesh and WHO Collaboration; - National Adaptation Plan. -"Building adaptation to climate change in health in least developed countries through resilient WASH". 7. COP-21 “Climate and health country profile -2015 Bangladesh. Conclusion: Due to a vast coastline, low-lying land and abundance of rivers, Bangladesh is highly vulnerable to climate change. Having extensive experience with facing natural disasters, Bangladesh has developed a successful adaptation program, which led to a significant reduction in casualties from extreme weather events. In a low income country setting, Bangladesh had successfully adapted various projects and initiatives to combat future Climate Change challenges.

Keywords: climate, change, success, Bangladesh

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Manufacturing companies are facing global competition and enormous cost pressure. The use of machine learning applications can help reduce production costs and create added value. Predictive quality enables the securing of product quality through data-supported predictions using machine learning models as a basis for decisions on test results. Furthermore, machine learning methods are able to process large amounts of data, deal with unfavourable row-column ratios and detect dependencies between the covariates and the given target as well as assess the multidimensional influence of all input variables on the target. Real production data are often subject to highly fluctuating boundary conditions and unbalanced data sets. Changes in production data manifest themselves in trends, systematic shifts, and seasonal effects. Thus, Machine learning applications require intensive pre-processing and feature selection. Data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets. Within the used real data set of Bosch hydraulic valves, the comparability of the same production conditions in the production of hydraulic valves within certain time periods can be identified by applying the concept drift method. Furthermore, a classification model is developed to evaluate the feature importance in different subsets within the identified time periods. By selecting comparable and stable features, the number of features used can be significantly reduced without a strong decrease in predictive power. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. In this research, the ada boosting classifier is used to predict the leakage of hydraulic valves based on geometric gauge blocks from machining, mating data from the assembly, and hydraulic measurement data from end-of-line testing. In addition, the most suitable methods are selected and accurate quality predictions are achieved.

Keywords: classification, achine learning, predictive quality, feature selection

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Authors: Nuria Vargas, Frances Rodriguez

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Neotropical medium cities have opportunities to develop in a good manner. Xalapa City (Veracruz capital, Mexico) and its metropolitan region, near to the Gulf of Mexico, has already <1 million inhabitants, a medium city size, but it’s growing rapidly as several cities in Latin America. Inside a landscape where it had been a forest cloud and coffee land, emerges the city with an irregular topography. The rapid grow of the urbanization and the loss of vegetation has result in a change on the climate parameters. Frequently warms spells, floods and landslides had been impacted last 2 decades, also a higher incidence of dengue and diarrhea is mentioned in the region. Therefore, the analysis of hydrometeorological events is crucial to understand the role they play in its problem. The urbanization and others radiative forces has created a modulation that can explain the decadal climate changes on the Xalapa region. The Atlantic Multidecadal Oscillation directly influences the temperature and precipitation of the region, even more than climate change does. The total effect of these drivers can create a significant context that origin more risk. However, the most policies frequently consider only the climate change as a principal factor, but other drivers are important to consider and evaluate for the implementation of actions that improve our ambient and cities, in a context of climate change. Medium-sized cities could create better conditions for future citizens, preventing with urban planning that considers possible risks associated with weather and climate.

Keywords: natural variability, urbanization, atlantic multidecadal oscillation, land use changes

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Authors: Alaa Abdullah Altaee

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This paper presents an adaptive decision feedback equalizer (ADFE) for multi-Gbps serial links utilizing a fix-step error signal extracted from cross-points of received data symbols. The extracted signal is generated based on violation of received data symbols with minimum detection requirements at the clock and data recovery (CDR) stage. The iterations of the adaptation process search for the optimum feedback tap coefficients to maximize the data eye-opening and minimize the adaptation convergence time. The effectiveness of the proposed architecture is validated using the simulation results of a serial link designed in an IBM 130 nm 1.2V CMOS technology. The data link with variable channel lengths is analyzed using Spectre from Cadence Design Systems with BSIM4 device models.

Keywords: adaptive DFE, CMOS equalizer, error detection, serial links, timing jitter, wire-line communication

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Authors: C. Ramamoorthy, R. Ranga Raj

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In olden days the Ramayana epic depicts the usage of invisible and fuel less aircraft named pushpavimana. The change of color in the reptile family chameleon paves way for the concept of color change phenomenon available in nature. In present scenario the aircrafts are visible so it is easily identified. So there are too many problems from the threatening. Research is still going on about this problem by using Liquid Crystal Display (LCD). Objective of this paper is to find much better to use the concept of invisible aircraft using plasma display through Couple Charged Device camera (CCD), which has a high resolution and can be used for many purposes like spying, defense, etc. Moreover it is cost wise cheap then, escaping the foe viewing.

Keywords: CCD camera, chameleon, invisible, plasma display

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Authors: Ilona Bontenbal

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In this research, the potential for societal change is researched through the idea of migrants as change agents. The viewpoint is on the potential that migrants have for affecting societal change in their country of origin through transmitting transnational peer-to-peer information. The focus is on the information that Russian migrants living in Finland transmit about their experiences and attitudes regarding the Nordic welfare state, its democratic foundation and the social rights embedded in it, to their family and friends in their country of origin. The welfare provision and level of democracy are very different in the two neighbouring countries of Finland and Russia. Finland is a Nordic welfare state with strong democratic institutions and a comprehensive actualizing of civil and social rights. In Russia, the state of democracy has on the other hand been declining, and the social and civil rights of its citizens are constantly undermined. Due to improvements in communications and travel technology, migrants can easily and relatively cheaply stay in contact with their family and friends in their country of origin. This is why it is possible for migrants to act as change agents. By telling about their experiences and attitudes about living in a democratic welfare state, migrants can affect what people in the country or origin know and think about welfare, democracy, and social rights. This phenomenon is approached through the concept of social remittances. Social remittances broadly stand for the ideas, know-how, world views, attitudes, norms of behavior, and social capital that flows through transnational networks from receiving- to sending- country communities and the other way around. The viewpoint is that historically and culturally formed democratic welfare models cannot be copied entirely nor that each country should achieve identical development paths, but rather that migrants themselves choose which aspects they see as important to remit to their acquaintances in their country of origin. This way the potential for social change and the agency of the migrants is accentuated. The empirical research material of this study is based on 30 qualitative interviews with Russian migrants living in Finland. Russians are the largest migrant group in Finland and Finland is a popular migration destination especially for individuals living in North-West Russia including the St. Petersburg region. The interviews are carried out in 2018-2019. The preliminary results indicate that Russian migrants discuss social rights and welfare a lot with their family members and acquaintances living in Russia. In general, the migrants feel that they have had an effect on the way that their friends and family think about Finland, the West, social rights and welfare provision. Democracy, on the other hand, is seen as a more difficult and less discussed topic. The transformative potential that the transmitted information and attitudes could have outside of the immediate circle of acquaintances on larger societal change is seen as ambiguous although not negligible.

Keywords: migrants as change agents, Russian migrants, social remittances, welfare and democracy

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Authors: Melika Masjedi

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Post-Traumatic Stress Disorder (PTSD) has a significant impact on the mental health and relationship dynamics of couples, leading to decreased marital satisfaction. This study examines the mediating role of sexual and romantic relationship dynamics in relation to PTSD and marital satisfaction among Iranian couples. Using a sample of 107 participants, quantitative methods were utilized to assess variables such as relationship functioning, PTSD symptom severity, and the influence of sexual and romantic interactions. The findings demonstrate a strong correlation between heightened PTSD symptoms and reduced marital satisfaction, particularly in the domains of intimacy and emotional connection. The study highlights the importance of addressing relational dynamics to improve marital outcomes in PTSD-affected couples.

Keywords: intimacy, marital satisfaction, PTSD, relationship dynamics, trauma

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Authors: Zzibu Mark Brian

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As software systems become increasingly complex, ensuring code security is a growing concern. Traditional vulnerability detection methods often rely on manual code reviews or static analysis tools, which can be time-consuming and prone to errors. This paper presents a distinct approach to enhancing code security by leveraging artificial intelligence (AI) and machine learning (ML) techniques. Our proposed system utilizes a combination of natural language processing (NLP) and deep learning algorithms to identify and classify vulnerabilities in real-world codebases. By analyzing vast amounts of open-source code data, our AI-powered tool learns to recognize patterns and anomalies indicative of security weaknesses. We evaluated our system on a dataset of over 10,000 open-source projects, achieving an accuracy rate of 92% in detecting known vulnerabilities. Furthermore, our tool identified previously unknown vulnerabilities in popular libraries and frameworks, demonstrating its potential for improving software security.

Keywords: AI, machine language, cord security, machine leaning

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Authors: Abid Fida Masih

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Forced degradation study of Rifaximin was conducted to determine the stability indicating potential of HPLC testing method for detection of Rifaximin in formulated tablets to be employed for quality control and stability testing. The questioned method applied with mobile phase methanol: water (70:30), 5µm, 250 x 4.6mm, C18 column, wavelength 293nm and flow rate of 1.0 ml/min. Forced degradation study was performed under oxidative, acidic, basic, thermal and photolytic conditions. The applied method successfully determined the degradation products after acidic and basic degradation without interfering with Rifaximin detection. Therefore, the method was said to be stability indicating and can be applied for quality control and stability testing of Rifaxmin tablets during its shelf life.

Keywords: forced degradation, high-performance liquid chromatography, method validation, rifaximin, stability indicating method

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Authors: Zhengkun Yi

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Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

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Authors: Jahangir Ahmad Rather, Emad A. Khudaish, Ahsanulhaq Qurashi, Palanisamy Kannan

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Chemical modification and assembling of fullerenes are fundamentally important for the application of fullerenes as functional molecules and in molecular devices and organic electronic devices. We have synthesized fullerene nanorods C60NRs conjugate via liquid-liquid interface and the synthesized C60NRs was characterized by FTIR spectroscopy, field emission electron microscopy (FESEM) and X-ray diffraction techniques. The C60NRs were immobilized on glassy carbon electrode via surface bound diazonium salts as an impact strategy. This method involves electrografting of p–nitrophenyl to give GCE–Ph–NO2 and then the terminal nitro-group was chemically reduced to GCE–Ph–NH2 in a presence of sodium borohydride/gold–polyaniline nanocomposite (NaBH4/Au–PANI). The Au–PANI composite was synthesized and characterized by FTIR, UV-vis, SEM and EDX techniques. The C60NRs were immobilized on GCE–Ph–NH2 via amination reaction which involves N-H addition across a π-bond on [60] fullerene. The immobilized C60NRs/GCE was subjected to electrochemical reduction in 1.0 M KOH to yield ERC60NRs/GCE sensor. The developed sensor shows high electrocatalytic activity for the detection of ethylparaben (EP) over a concentration range from 0.01 to 0.52 µM with a detection limit (LOD) 3.8 nM. The amount of EP present in the nourishing repair cream (OlAY®) was determined by standard addition method at the developed ERC60NRs/GCE sensor. The total concentration of EP was found to be 0.011 µM (0.1%) and is within the permissible limit of 0.19 % EP in cosmetics according to the European scientific committee (SCCS) on consumer safety on 22 March 2011 (SCCS/1348/11).

Keywords: diazonium salt reduction, ethylparaben (EP), endocrine disruptor, fullerene nanorods (C60NRs), gold–polyaniline nanocomposite (Au–PANI)

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Authors: Sukhbir Singh

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This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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Authors: M. Yavuz Hüseyinca, Şuayip Küpeli

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The Chemical Index of Alteration (CIA) values of Late Eocene-Oligocene aged sandstones that exposed on the eastern edge of Tuz Lake (Central Anatolia, Turkey) range from 49 to 59 with an average of 51. The A-CN-K diagram indicates that sandstones underwent post-depositional K-metasomatism. The original average CIA value before the K-metasomatism is calculated as 55. This value is lower than that of Post Archean Australian Shale (PAAS) and defines a low intense chemical weathering in the source-area. Extrapolation of sandstones back to the plagioclase-alkali feldspar line in the A-CN-K diagram suggests a high average plagioclase to alkali feldspar ratio in the provenance and a composition close to granodiorite. The Zr/Sc and Th/Sc ratios with the Al₂O₃-Zr-TiO₂ space do not show zircon addition that refuse both recycling of sediments and sorting effect. All these data suggest direct and rapid transportation from the source due to topographic uplift and probably arid to semi-arid climate conditions for the sandstones.

Keywords: central Anatolia, sandstone, sorting, weathering

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Authors: Lu Yang, Meiyang Song, Xiang Yu, Wenhao Zhou, Chuntao Feng

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To address the problem that the FM continuous-wave radar (FMCW) extracts human vital sign signals which are susceptible to noise interference and low reconstruction accuracy, a new detection scheme for the sign signals is proposed. Firstly, an improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) algorithm is applied to decompose the radar-extracted thoracic signals to obtain several intrinsic modal functions (IMF) with different spatial scales, and then the IMF components are optimized by a BP neural network improved by immune genetic algorithm (IGA). The simulation results show that this scheme can effectively separate the noise and accurately extract the respiratory and heartbeat signals and improve the reconstruction accuracy and signal-to-noise ratio of the sign signals.

Keywords: frequency modulated continuous wave radar, ICEEMDAN, BP neural network, vital signs signal

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Authors: Ananya Mitra Pramanik, Anjali Agrawal

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This paper traces the waste produced by the textile industry and evaluates the need for this waste to be reused or repurposed. From ancient times the textile industry has been a prominent part of all the economies of the world. It is famous for traditional as well as mill made fabrics. However the beauty and utility radiated by the textiles are juxtaposed by the piling amount of waste that the whole life cycle of a textile production and disposal entails. Waste happens in stages in a textile life cycle. It can be broadly categorised as pre-consumer and post-consumer waste. This research suggests suitable processes and techniques for channelizing post-industrial waste. It explores the scope of textile waste as a raw material for innovation and design. It discusses the role of designers in using waste to create useful and appealing designs. The paper examines the need of designers to create novel ideas to reuse textiles. This paper is based on secondary research. Most of the information used is taken from books and journals. The DEFRA report 2009 is also consulted for comprehensive data on textile waste percentage.

Keywords: designers, repurposing, textiles, waste

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Authors: Prasanti Widyasih Sarli, Prayatni Soewondo

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Greater access to sanitation in developing countries is urgent. However even though sanitation is crucial, overall budget for sanitation is limited. With this budget limitation, it is important to (1) allocate resources strategically to maximize impact and (2) take into account communal agency to potentially be a source for sanitation improvements. The Jodipan and Kesatrian Project in Malang, Indonesia is an interesting alternative for solving the sanitation problem in which resources were allocated strategically and communal agency was also observed. Although the projects initial goal was only to improve visually the situation in the slums, it became a new tourist destination, and the economic benefit that came with it had an effect also on the change of behavior of the residents and the government towards sanitation. It also grew from only including the Kesatrian Village to expanding to the Jodipan Village in the course of less than a year. To investigate the success of this project, in this paper a descriptive model will be used and data will be drawn from intensive interviews with the initiators of the project, residents affected by the project and government officials. In this research it is argued that three points mark the success of the project: (1) the strategic initial impact due to choice of location, (2) the influx of tourists that triggered behavioral change among residents and, (3) the direct economic impact which ensured its sustainability and growth by gaining government officials support and attention for more public spending in the area for slum development and sanitation improvement.

Keywords: behaviour change, sanitation, slum, strategic thinking

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Authors: Mansouri Nabila, Ben Jemaa Yousra, Motamed Cina, Watelain Eric

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Research and development efforts in intelligent Advanced Driver Assistance Systems (ADAS) seek to save lives and reduce the number of on-road fatalities. For traffic and emergency monitoring, the essential but challenging task is vehicle detection and tracking in reasonably short time. This purpose needs first of all a powerful dynamic car detector model. In fact, this paper presents an optimized HOG process based on shape and motion parameters fusion. Our proposed approach mains to compute HOG by bloc feature from foreground blobs using configurable research window and pathway in order to overcome the shortcoming in term of computing time of HOG descriptor and improve their dynamic application performance. Indeed we prove in this paper that HOG by bloc descriptor combined with motion parameters is a very suitable car detector which reaches in record time a satisfactory recognition rate in dynamic outside area and bypasses several popular works without using sophisticated and expensive architectures such as GPU and FPGA.

Keywords: car-detector, HOG, motion, computing time

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Authors: Agbortoko Manyigbe Ayuk Nkem, Eno Cynthia Osuh

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This paper sets to examine the relationship between climate change and urban livelihood through a vulnerability assessment of the urban poor in Douala. Urban development in Douala places priority towards industrial and city-centre development with little focus on the urban poor in terms of housing units and areas of sustenance. With the high rate of urbanisation and increased land prices, the urban poor are forced to occupy marginal lands which are mainly wetlands, wastelands and along abandoned neighbourhoods prone to natural hazards. Due to climate change and its effects, these wetlands are constantly flooded thereby destroying homes, properties, and crops. Also, most of these urban dwellers have found solace in urban agriculture as a means for survival. However, since agriculture in tropical regions like Cameroon depends largely on seasonal rainfall, the changes in rainfall pattern has led to misplaced periods for crop planting and a huge wastage of resources as rainfall becomes very unreliable with increased temperature levels. Data for the study was obtained from both primary and secondary sources. Secondary sources included published materials related to climate change and vulnerability. Primary data was obtained through focus-group discussions with some urban farmers while a stratified sampling of residents within marginal lands was done. Each stratum was randomly sampled to obtain information on different stressors related to climate change and their effect on livelihood. Findings proved that the high rate of rural-urban migration into Douala has led to increased prevalence of the urban poor and their vulnerability to climate change as evident in their constant fight against flood from unexpected sea level rise and irregular rainfall pattern for urban agriculture. The study also proved that women were most vulnerable as they depended solely on urban agriculture and its related activities like retailing agricultural products in different urban markets which to them serves as a main source of income in the attainment of basic needs for the family. Adaptation measures include the constant use of sand bags, raised makeshifts as well as cultivation along streams, planting after evidence of constant rainfall has become paramount for sustainability.

Keywords: adaptation, Douala, Cameroon, climate change, development, livelihood, vulnerability

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Authors: V. Sai Geethika, Sai Snehitha Yadavalli, Swati Ghosh Acharyya

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This study involves a single element and simultaneous electrochemical detection of heavy metal ions through square wave anodic stripping voltammetry. A glassy carbon electrode was used to detect and quantify heavy metals such as As(III), Hg(II), Cr(VI) ions in water. Under optimized conditions, peak separation was obtained by varying concentrations, scan rates, and temperatures. As (III), Hg (II), Cr (III) were simultaneously detected with GCE. Several analytical methods, such as inductively coupled plasma mass spectroscopy (ICP-MS), atomic absorption spectroscopy (AAS), were used previously to detect heavy metal ions, which are authentic but are not good enough for online monitoring due to the bulkiness of the equipment. The study provides a good alternative that is simple, more efficient, and low-cost, involving a portable potentiostat. Heavy metals having different oxidation states can be detected by anodic stripping voltammetry. This method can be easily integrated with electronics. Square wave Anodic stripping voltammetry is used with a potential range of -2.5 V – 2.5 V for single ion detection by a three-electrode cell consisting of silver/silver chloride(Ag/AgCl) as reference and platinum (Pt) counter and glassy carbon (GCE) working electrodes. All three ions are optimized by varying the parameters like concentration, scan rate, pH, temperature, and all these optimized parameters were used for studying the effects of simultaneous detection. The procedure involves preparing an electrolyte using deionized water, cleaning the surface of GCE, depositing the ions by applying the redox potentials obtained from cyclic voltammetry (CV), and then detecting by applying oxidizing potential, i.e., stripping voltage. So this includes ASV techniques such as open-circuit voltage (OCV), chronoamperometry (CA), and square wave voltammetry (SWV). Firstly, the concentration of the ions varied from 50 ppb to 5000 ppb, and an optimum concentration was determined where the three ions were detected. A concentration of 400 ppb was used while varying the temperatures in the range of 25°C – 45°C. Optimum peak intensity was obtained at a temperature of 30°C with a low scan rate of 0.005 V-s⁻¹. All the parameters were optimized, and several effects have been noticed while three ions As(II), Cr(III), Hg(II) were detected alone and simultaneously.

Keywords: Arsenic(III), Chromium(III), glassy carbon electrode, Mercury (II), square wave anodic stripping voltammetry

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Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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Authors: Siti Sabariah Buhari, Ruzita Abdul Talib, Poh Bee Koon

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This study aims to develop and evaluate an intervention to improve eating habits, active lifestyle and weight status of overweight and obese children in Negeri Sembilan. The H.E.B.A.T! Program involved children, parents, and school and focused on behaviour and environment modification to achieve its goal. The intervention consists of H.E.B.A.T! Camp, parent’s workshop and school-based activities. A total of 21 children from intervention school and 22 children from control school who had BMI for age Z-score ≥ +1SD participated in the study. Mean age of subjects was 10.8 ± 0.3 years old. Four phases were included in the development of the intervention. Evaluation of intervention was conducted through process, impact and outcome evaluation. Process evaluation found that intervention program was implemented successfully with minimal modification and without having any technical problems. Impact and outcome evaluation was assessed based on dietary intake, average step counts, BMI for age z-score, body fat percentage and waist circumference at pre-intervention (T0), post-intervention 1 (T1) and post-intervention 2 (T2). There was significant reduction in energy (14.8%) and fat (21.9%) intakes (at p < 0.05) at post-intervention 1 (T1) in intervention group. By controlling for sex as covariate, there was significant intervention effect for average step counts, BMI for age z-score and waist circumference (p < 0.05). In conclusion, the intervention made an impact on positive behavioural intentions and improves weight status of the children. It is expected that the HEBAT! Program could be adopted and implemented by the government and private sector as well as policy-makers in formulating childhood obesity intervention.

Keywords: childhood obesity, diet, obesity intervention, physical activity

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Authors: Kanhaiya Singh

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Indian corporate sector has been raising resources through various international financial instruments important among them are Global depository receipts (GDRs) and American Depository Receipts (ADRs). The purpose of raising resources through such instruments is multifold such as lower cost of capital, increased visibility of the company, liberal tax environment, increased trading liquidity etc. One of the significant reason is also the value addition of the company in terms of market capitalization. Obviously, the stocks of such companies are cross listed, one in India and other at the International stock exchange. The sensitivity and movements of stock prices on one stock exchange as compared to other may have an impact on the price movement of the particular scrip. If there is any relationship exists is an issue of study. Having this in view this study is an attempt to identify the extent of impact of price movement of the scrip on one stock exchange on account of change in the prices on the counter stock exchange. Also there is an attempt to find out the difference between pre and post cross listed domestic firm. The study also analyses the impact of exchange rate movements on stock prices.

Keywords: ADR, GDR, cross listing, liquidity, exchange rate

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Authors: Kim Alvin De Lara

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The research aimed to assess the level of acceptability of the developed activity sheets in Science 5 integrating climate change adaptation of grade 5 science teachers in the District of Pililla school year 2016-2017. In this research, participants were able to recognize and understand the importance of environmental education in improving basic education and integrating them in lessons through localization and contextualization. The researcher conducted the study to develop a material to use by Science teachers in Grade 5. It served also as a self-learning resource for students. The respondents of the study were the thirteen Grade 5 teachers teaching Science 5 in the District of Pililla. Respondents were selected purposively and identified by the researcher. A descriptive method of research was utilized in the research. The main instrument was a checklist which includes items on the objectives, content, tasks, contextualization and localization of the developed activity sheets. The researcher developed a 2-week lesson in Science 5 for 4th Quarter based on the curriculum guide with integration of climate change adaptation. The findings revealed that majority of respondents are female, 31 years old and above, 10 years above in teaching science and have units in master’s degree. With regards to the level of acceptability, the study revealed developed activity sheets in science 5 is very much acceptable. In view of the findings, lessons in science 5 must be contextualized and localized to improve to make the curriculum responds, conforms, reflects, and be flexible to the needs of the learners, especially the 21st century learners who need to be holistically and skillfully developed. As revealed by the findings, it is more acceptable to localized and contextualized the learning materials for pupils. Policy formation and re-organization of the lessons and competencies in Science must be reviewed and re-evaluated. Lessons in science must also be integrated with climate change adaptation since nowadays, people are experiencing change in climate due to global warming and other factors. Through developed activity sheets, researcher strongly supports environmental education and believes this to serve as a way to instill environmental literacy to students.

Keywords: activity sheets, climate change adaptation, contextualization, localization

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