Search results for: loan loss recognition

Authors: Fariba Ebrahimi, Mehdi Ghorbani, Ali Salajegheh

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Comprehensively water management considers economic, environmental, technical and social and also sustainability of water resources for future generations. Grassland management implies cooperative approach and involves all stakeholders and also introduces issues to managers, decision and policy makers. Solving these issues needs integrated and system approach. According to the recognition of actors or key persons in necessary to apply cooperative management of Water. Therefore, based on stakeholder analysis and social network analysis can be used to demonstrate the most effective actors for environmental decisions. In this research, social powers according are specified to social network approach at Water utilizers’ level of Natural in Jirood catchment of Latian basin. In this paper, utilizers of water resources were recognized using field trips and then, trust and collaboration matrix produced using questionnaires. In the next step, degree centrality index were Examined. Finally, geometric position of each actor was illustrated in the network. The results of the research based on centrality index have a key role in recognition of cooperative management of Water in Jirood and also will help managers and planners of water in the case of recognition of social powers in order to organization and implementation of sustainable management of Water.

Keywords: social network analysis, water co-management, social power, centrality index, local stakeholders network, Jirood catchment

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Authors: Qiangqiang Xu, Xu Ji, Jingyang Han, Changchun Yang, Ming Li

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Replacing of complex solar concentrating unit, this paper designs a solar heat-concentrating medium-temperature steam-generating system. Solar radiation is collected by using a large solar collecting and heat concentrating plate and is converged to the metal evaporating pipe with high efficient heat transfer. In the meantime, the heat loss is reduced by employing a double-glazed cover and other heat insulating structures. Thus, a high temperature is reached in the metal evaporating pipe. The influences of the system's structure parameters on system performance are analyzed. The steam production rate and the steam production under different solar irradiance, solar collecting and heat concentrating plate area, solar collecting and heat concentrating plate temperature and heat loss are obtained. The results show that when solar irradiance is higher than 600 W/m², the effective heat collecting area is 7.6 m² and the double-glazing cover is adopted, the system heat loss amount is lower than the solar irradiance value. The stable steam is produced in the metal evaporating pipe at 100 ℃, 110 ℃, and 120 ℃, respectively. When the average solar irradiance is about 896 W/m², and the steaming cumulative time is about 5 hours, the daily steam production of the system is about 6.174 kg. In a single day, the solar irradiance is larger at noon, thus the steam production rate is large at that time. Before 9:00 and after 16:00, the solar irradiance is smaller, and the steam production rate is almost 0.

Keywords: heat concentrating, heat loss, medium temperature, solar steam production

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Authors: Gina M. Newton

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Australia’s Environment Protection and Biodiversity Conservation Act (EPBC Act) is the premiere, national law under which species and 'ecological communities' (i.e., like ecosystems) can be formally recognised and 'listed' as threatened across all jurisdictions. The listing process involves assessment against a range of criteria (similar to the IUCN process) to demonstrate conservation status (i.e., vulnerable, endangered, critically endangered, etc.) based on the best available science. Over the past decade in Australia, there’s been a transition from almost solely terrestrial to the first aquatic threatened ecological community (TEC or ecosystem) listings (e.g., River Murray, Macquarie Marshes, Coastal Saltmarsh, Salt-wedge Estuaries). All constitute large areas, with some including multiple state jurisdictions. Development of these conservation and listing advices has enabled, for the first time, a more forensic analysis of three key factors across a range of aquatic and coastal ecosystems: -the contribution of invasive species to conservation status, -how to demonstrate and attribute decline in 'ecological integrity' to conservation status, and, -identification of related priority conservation actions for management. There is increasing global recognition of the disproportionate degree of biodiversity loss within aquatic ecosystems. In Australia, legislative protection at Commonwealth or State levels remains one of the strongest conservation measures. Such laws have associated compliance mechanisms for breaches to the protected status. They also trigger the need for environment impact statements during applications for major developments (which may be denied). However, not all jurisdictions have such laws in place. There remains much opposition to the listing of freshwater systems – for example, the River Murray (Australia's largest river) and Macquarie Marshes (an internationally significant wetland) were both disallowed by parliament four months after formal listing. This was mainly due to a change of government, dissent from a major industry sector, and a 'loophole' in the law. In Australia, at least in the immediate to medium-term time frames, invasive species (aliens, native pests, pathogens, etc.) appear to be the number one biotic threat to the biodiversity and ecological function and integrity of our aquatic ecosystems. Consequently, this should be considered a current priority for research, conservation, and management actions. Another key outcome from this analysis was the recognition that drawing together multiple lines of evidence to form a 'conservation narrative' is a more useful approach to assigning conservation status. This also helps to addresses a glaring gap in long-term ecological data sets in Australia, which often precludes a more empirical data-driven approach. An important lesson also emerged – the recognition that while conservation must be underpinned by the best available scientific evidence, it remains a 'social and policy' goal rather than a 'scientific' goal. Communication, engagement, and 'politics' necessarily play a significant role in achieving conservation goals and need to be managed and resourced accordingly.

Keywords: aquatic ecosystem conservation, conservation law, ecological integrity, invasive species

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Authors: Naghmeh Moradpoor Sheykhkanloo

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Structured Query Language Injection (SQLI) attack is a code injection technique in which malicious SQL statements are inserted into a given SQL database by simply using a web browser. Losing data, disclosing confidential information or even changing the value of data are the severe damages that SQLI attack can cause on a given database. SQLI attack has also been rated as the number-one attack among top ten web application threats on Open Web Application Security Project (OWASP). OWASP is an open community dedicated to enabling organisations to consider, develop, obtain, function, and preserve applications that can be trusted. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLI attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLI attack categories, and an NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLI attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: neural networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection

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Authors: Kanyarat Bussaban, Kunyanuth Kularbphettong

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This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24 percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources.

Keywords: behavior, data mining technique, a priori algorithm, knowledge discovery

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Authors: Martha Serrano-Arias, Martha Frías-Armenta

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Significant results have been found both supporting universality of emotion recognition and cultural background influence. Thus, the aim of this research was to test a Mexican version of the MTSI in different cultures to find differences in their performance. The MTSI-Mx assesses through a scenario approach were subjects must evaluate real persons. Two target persons were used for the construction, a man (FS) and a woman (AD). The items were grouped in four variables: Picture, Video, and FS and AD scenarios. The test was applied to 201 students from Mexico and Germany. T-test for picture and FS scenario show no significance. Video and AD had a significance at the 5% level. Results show slight differences between cultures, although a more comprehensive research is needed to conclude which culture can perform better in this kind of assessments.

Keywords: emotion recognition, MTSI, social intelligence, transcultural study

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Authors: Darshna Sharma, Suban K. Sahoo

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The detection of intracellular fluoride in human cancer cell HeLa was achieved by chemosensors derived from vitamin B6 cofactors using fluorescence imaging technique. These sensors were first synthesized by condensation of pyridoxal/pyridoxal phosphate with 2-amino(thio)phenol. The anion recognition ability was explored by experimental (UV-VIS, fluorescence and 1H NMR) and theoretical DFT [(B3LYP/6-31G(d,p)] methods in DMSO and mixed DMSO-H2O system. All the developed sensors showed both naked-eye detectable color change and remarkable fluorescence enhancement in the presence of F- and AcO-. The anion recognition was occurred through the formation of hydrogen bonded complexes between these anions and sensor, followed by the partial deprotonation of sensor. The detection limit of these sensors were down to micro(nano) molar level of F- and AcO-.

Keywords: chemosensors, fluoride, acetate, turn-on, live cells imaging, DFT

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Authors: Pijush Roy, Vinay Kumar Rai

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The present study highlights the estimation of soil loss and identification of critical area for implementation of best management practice is central to the success of soil conservation programme. The quantification of morphometric and Universal Soil Loss Equation (USLE) factors using remote sensing and GIS for prioritization of micro-watersheds in Asan River catchment, western Doon valley at foothills of Siwalik ranges in the Dehradun districts of Uttarakhand, India. The watershed has classified as a dendritic pattern with sixth order stream. The area is classified into very high, high, moderately high, medium and low susceptibility zones. High to very high erosion zone exists in the urban area and agricultural land. Average annual soil loss of 64 tons/ha/year has been estimated for the watershed. The optimum management practices proposed for micro-watersheds of Asan River basin are; afforestation, contour bunding suitable sites for water harvesting structure as check dam and soil conservation, agronomical measure and bench terrace.

Keywords: erosion susceptibility zones, morphometric characteristics, prioritization, remote sensing and GIS, universal soil loss equation

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Authors: Yoshiaki Shikata

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A prioritized processor-sharing (PS) system with a maximum permissible sojourn time (MPST) is proposed. In this PS system, a higher-priority request is allocated a larger service ratio than a lower-priority request. Moreover, each request receiving service is guaranteed the maximum permissible sojourn time determined by each priority class, regardless of its service time. Arriving requests that cannot receive service due to this guarantee are rejected. We further propose a guarantee method for implementing such a system, and discuss performance evaluation procedures for the resulting system. Practical performance measures, such as the relationships between the loss probability or mean sojourn time of each class request and the maximum permissible sojourn time are evaluated via simulation. At the arrival of each class request, its acceptance or rejection is judged using extended sojourn times of all requests receiving service in the server. As the MPST increases, the mean sojourn time increases almost linearly. However, the logarithm of the loss probability decreases almost linearly. Moreover with an MPST, the difference in the mean sojourn time for different MPSTs increases with the traffic rate. Conversely, the difference in the loss probability for different MPSTs decreases as the traffic rate increases.

Keywords: prioritized processor sharing, priority ratio, permissible sojourn time, loss probability, mean sojourn time, simulation

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Authors: Ajay Kadam, Ramesh Kagalkar

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The proposed research objective is to add to a framework for programmed recognition of sound. In this framework the real errand is to distinguish any information sound stream investigate it & anticipate the likelihood of diverse sounds show up in it. To create and industrially conveyed an adaptable sound web crawler a flexible sound search engine. The calculation is clamor and contortion safe, computationally productive, and hugely adaptable, equipped for rapidly recognizing a short portion of sound stream caught through a phone microphone in the presence of frontal area voices and other predominant commotion, and through voice codec pressure, out of a database of over accessible tracks. The algorithm utilizes a combinatorial hashed time-recurrence group of stars examination of the sound, yielding ordinary properties, for example, transparency, in which numerous tracks combined may each be distinguished.

Keywords: fingerprinting, pure tone, white noise, hash function

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Authors: Hilal Keklicek, Fatih Erbahceci, Elif Kirdi, Ali Yalcin, Semra Topuz, Ozlem Ulger, Gul Sener

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Objectives and Goals: The stride-to-stride fluctuations in gait is a determinant of qualified locomotion as known as gait variability. Gait variability is an important predictive factor of fall risk and useful for monitoring the effects of therapeutic interventions and rehabilitation. Comparison of gait variability in individuals with trans-tibial lower limb loss and trans femoral lower limb loss was the aim of the study. Methods: Ten individuals with traumatic unilateral trans femoral limb loss(TF), 12 individuals with traumatic transtibial lower limb loss(TT) and 12 healthy individuals(HI) were the participants of the study. All participants were evaluated with treadmill. Gait characteristics including mean step length, step length variability, ambulation index, time on each foot of participants were evaluated with treadmill. Participants were walked at their preferred speed for six minutes. Data from 4th minutes to 6th minutes were selected for statistical analyses to eliminate learning effect. Results: There were differences between the groups in intact limb step length variation, time on each foot, ambulation index and mean age (p < .05) according to the Kruskal Wallis Test. Pairwise analyses showed that there were differences between the TT and TF in residual limb variation (p=.041), time on intact foot (p=.024), time on prosthetic foot(p=.024), ambulation index(p = .003) in favor of TT group. There were differences between the TT and HI group in intact limb variation (p = .002), time on intact foot (p<.001), time on prosthetic foot (p < .001), ambulation index result (p < .001) in favor of HI group. There were differences between the TF and HI group in intact limb variation (p = .001), time on intact foot (p=.01) ambulation index result (p < .001) in favor of HI group. There was difference between the groups in mean age result from HI group were younger (p < .05).There were similarity between the groups in step lengths (p>.05) and time of prosthesis using in individuals with lower limb loss (p > .05). Conclusions: The pilot study provided basic data about gait stability in individuals with traumatic lower limb loss. Results of the study showed that to evaluate the gait differences between in different amputation level, long-range gait analyses methods may be useful to get more valuable information. On the other hand, similarity in step length may be resulted from effective prosthetic using or effective gait rehabilitation, in conclusion, all participants with lower limb loss were already trained. The differences between the TT and HI; TF and HI may be resulted from the age related features, therefore, age matched population in HI were recommended future studies. Increasing the number of participants and comparison of age-matched groups also recommended to generalize these result.

Keywords: lower limb loss, amputee, gait variability, gait analyses

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Authors: T. Hari Prasath, P. Ithaya Rani

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In the world of visual technology, recognizing emotions from the face images is a challenging task. Several related methods have not utilized the dynamic facial features effectively for high performance. This paper proposes a method for emotions recognition using dynamic facial features with high performance. Initially, local features are captured by Gabor filter with different scale and orientations in each frame for finding the position and scale of face part from different backgrounds. The Gabor features are sent to the ensemble classifier for detecting Gabor facial features. The region of dynamic features is captured from the Gabor facial features in the consecutive frames which represent the dynamic variations of facial appearances. In each region of dynamic features is normalized using Z-score normalization method which is further encoded into binary pattern features with the help of threshold values. The binary features are passed to Multi-class AdaBoost classifier algorithm with the well-trained database contain happiness, sadness, surprise, fear, anger, disgust, and neutral expressions to classify the discriminative dynamic features for emotions recognition. The developed method is deployed on the Ryerson Multimedia Research Lab and Cohn-Kanade databases and they show significant performance improvement owing to their dynamic features when compared with the existing methods.

Keywords: detecting face, Gabor filter, multi-class AdaBoost classifier, Z-score normalization

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Authors: Hee-Choul Kwon, Heeyong Kwon

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Image rotation is one of main pre-processing steps for image processing or image pattern recognition. It is implemented with a rotation matrix multiplication. It requires a lot of floating point arithmetic operations and trigonometric calculations, so it takes a long time to execute. Therefore, there has been a need for a high speed image rotation algorithm without two major time-consuming operations. However, the rotated image has a drawback, i.e. distortions. We solved the problem using an augmented two-step shear transform. We compare the presented algorithm with the conventional rotation with images of various sizes. Experimental results show that the presented algorithm is superior to the conventional rotation one.

Keywords: high-speed rotation operation, image rotation, transform matrix, image processing, pattern recognition

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Authors: Hamid Rezaei, Xiaotao Bi, C. Jim Lim, Anthony Lau, Shahab Sokhansanj

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A one-dimensional heat transfer model coupled with the kinetic information has been used to predict the overall pyrolysis mass loss of a single wood particle. The kinetic parameters were determined experimentally and the regime and characteristics of the conversion were evaluated in terms of the particle size and reactor temperature. The order of overall mass loss changed from n=1 at temperatures lower than 350 °C to n=0.5 at temperatures higher that 350 °C. Conversion time analysis showed that particles larger than 0.5 mm were controlled by internal thermal resistances. The valid range of particle size to use the simplified lumped model depends on the fluid temperature around the particles. The critical particle size was 0.6-0.7 mm for the fluid temperature of 500 °C and 0.9-1.0 mm for the fluid temperature of 100 °C. Experimental pyrolysis of moist particles did not show distinct drying and pyrolysis stages. The process was divided into two hypothetical drying and pyrolysis dominated zones and empirical correlations are developed to predict the rate of mass loss in each zone.

Keywords: pyrolysis, kinetics, model, single particle

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Authors: Rujia Chen, Akbar Ghobakhlou, Ajit Narayanan

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This study investigates the task of identifying musical instruments in polyphonic compositions using Convolutional Neural Networks (CNNs) from spectrogram inputs, focusing on binary classification. The model showed promising results, with an accuracy of 97% on solo instrument recognition. When applied to polyphonic combinations of 1 to 10 instruments, the overall accuracy was 64%, reflecting the increasing challenge with larger ensembles. These findings contribute to the field of Music Information Retrieval (MIR) by highlighting the potential and limitations of current approaches in handling complex musical arrangements. Future work aims to include a broader range of musical sounds, including electronic and synthetic sounds, to improve the model's robustness and applicability in real-time MIR systems.

Keywords: binary classifier, CNN, spectrogram, instrument

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Authors: Ng Liang Shen, Hau Yuan Wen

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Arrhythmia analysis of ECG signal plays a major role in diagnosing most of the cardiac diseases. Therefore, a single arrhythmia detection of an electrocardiographic (ECG) record can determine multiple pattern of various algorithms and match accordingly each ECG beats based on Machine Learning supervised learning. These researchers used different features and classification methods to classify different arrhythmia types. A major problem in these studies is the fact that the symptoms of the disease do not show all the time in the ECG record. Hence, a successful diagnosis might require the manual investigation of several hours of ECG records. The point of this paper presents investigations cardiovascular ailment in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia utilizing examination of ECG irregular wave frames via heart beat as correspond arrhythmia which with Machine Learning Pattern Recognition.

Keywords: electrocardiogram, ECG, classification, machine learning, pattern recognition, detection, QRS

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Authors: Irfan Abdulrahman Sheth, Sohil Pothiawala

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Dermatomyositis is an idiopathic inflammatory myopathy, traditionally characterized by a progressive, symmetrical proximal muscle weakness and pathognomonic or characteristic cutaneous manifestations. We report a case of a 60-year old Chinese female who was referred from polyclinic for allergic rash over the body after applying hair dye 3 weeks ago. It was associated with puffiness of face, shortness of breath and hoarse voice since last 2 weeks with decrease effort tolerance. She also complained of dysphagia/ myalgia with progressive weakness of proximal muscles and palpitations. She denied chest pain, loss of appetite, weight loss, orthopnea or fever. She had stable vital signs and appeared cushingoid. She was noted to have rash over the scalp/ face and ecchymosis over the right arm with puffiness of face and periorbital oedema. There was symmetrical muscle weakness and other neurological examination was normal. Initial impression was of allergic reaction and underlying nephrotic syndrome and Cushing’s syndrome from TCM use. Diagnostic tests showed high Creatinine kinase (CK) of 1463 u/l, CK–MB of 18.7 ug/l and Troponin –T of 0.09 ug/l. The Full blood count and renal panel was normal. EMG showed inflammatory myositis. Patient was managed by rheumatologist and discharged on oral prednisolone with methotrexate/ ergocalciferol capsule and calcium carb, vitamin D tablets and outpatient follow up. In some patients, cutaneous disease exists in the absence of objective evidence of muscle inflammation. Management of dermatomyositis begins with careful investigation for the presence of muscle disease or of additional systemic involvement, particularly of the pulmonary, cardiac or gastrointestinal systems, and for the possibility of an accompanying malignancy. Muscle disease and systemic involvement can be refractory and may require multiple sequential therapeutic interventions or, at times, combinations of therapies. Thus, we want to highlight to the physicians that the cutaneous disease of dermatomyositis should not be confused with allergic reaction. It can be particularly challenging to diagnose. Early recognition aids appropriate management of this group of patients.

Keywords: dermatomyositis, myopathy, allergy, cutaneous disease

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Authors: M. Nageswara Rao, V. S. N. K. Chaitanya, K. Amarendranath

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This paper presents an optimal allocation and sizing of Distributed Generation (DG) in Radial Distribution Network (RDN) for total power loss minimization and enhances the voltage profile of the system. The two main important part of this study first is to find optimal allocation and second is optimum size of DG. The locations of DGs are identified by Analytical expressions and crow search algorithm has been employed to determine the optimum size of DG. In this study, the DG has been placed on single and multiple allocations.CSA is a meta-heuristic algorithm inspired by the intelligent behavior of the crows. Crows stores their excess food in different locations and memorizes those locations to retrieve it when it is needed. They follow each other to do thievery to obtain better food source. This analysis is tested on IEEE 33 bus and IEEE 69 bus under MATLAB environment and the results are compared with existing methods.

Keywords: analytical expression, distributed generation, crow search algorithm, power loss, voltage profile

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Authors: S. O. Bamigboye, P. M. Tshisikhawe, P. J. Taylor

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Cycads are the most threatened plant species in the world. In South Africa over 70% of cycads are threatened with extinction with 60% of them as a result of bark harvest of these highly endangered species for medicinal purposes. 3 cycads species in South Africa have gone extinct due to bark harvest for medicinal purpose. This practice keeps increasing biodiversity loss within the nation and this has generated concern for conservationists on different way to discover how people go about this practices and how it can be discouraged. Studies have revealed this practice to be common practice in provinces like Kwazulu natal, Eastern cape, Gauteng, Mpumalanga, but studies in the past have not really focused on cycads bark harvest in Limpopo province. In this study we use the indigenous knowledge to discover a particular location within the Soutpansberg Montane (a major biodiversity hotspot in Limpopo Province in South Africa) in Vhembe district in Limpopo province not yet conserved where we have a highly disturbed population of cycads. Several individuals of cycads species have been highly damaged due to bark harvest in this location. We are about proposing that such areas needs attention for conservation to prevent the loss of these species endemic to this particular location. Our study hereby reveals that cycads bark harvest which is a major threat to African cycads is also a common practice in Limpopo Province in South Africa. Rigorous conservation action is required to discourage this practice in order to prevent further biodiversity loss in this region.

Keywords: bark harvest, Cycads, conservation, extinction, Limpopo

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Authors: Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

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We propose to record Activities of Daily Living (ADLs) of elderly people using a vision-based system so as to provide better assistive and personalization technologies. Current ADL-related research is based on data collected with help from non-elderly subjects in laboratory environments and the activities performed are predetermined for the sole purpose of data collection. To obtain more realistic datasets for the application, we recorded ADLs for the elderly with data collected from real-world environment involving real elderly subjects. Motivated by the need to collect data for more effective research related to elderly care, we chose to collect data in the room of an elderly person. Specifically, we installed Kinect, a vision-based sensor on the ceiling, to capture the activities that the elderly subject performs in the morning every day. Based on the data, we identified 12 morning activities that the elderly person performs daily. To recognize these activities, we created a HARELCARE framework to investigate into the effectiveness of existing Human Activity Recognition (HAR) algorithms and propose the use of a transfer learning algorithm for HAR. We compared the performance, in terms of accuracy, and training progress. Although the collected dataset is relatively small, the proposed algorithm has a good potential to be applied to all daily routine activities for healthcare purposes such as evidence-based diagnosis and treatment.

Keywords: daily activity recognition, healthcare, IoT sensors, transfer learning

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Authors: Karina Reiter, Stefan Dullinger, Christoph Plutzar, Dietmar Moser

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Due to population growth and changing patterns of production and consumption, the demand for natural resources and, as a result, the pressure on Earth’s ecosystems are growing. Biodiversity mapping can be a useful tool for assessing species endangerment or detecting hotspots of extinction risks. This paper explores the benefits of using the change in trophic energy flows as a consequence of the human alteration of the biosphere in biodiversity mapping. To this end, multiple linear regression models were developed to explain species richness in areas where there is no human influence (i.e. wilderness) for three taxonomic groups (birds, mammals, amphibians). The models were then applied to predict (I) potential global species richness using potential natural vegetation (NPPpot) and (II) global ‘actual’ species richness after biomass appropriation using NPP remaining in ecosystems after harvest (NPPeco). By calculating the difference between predicted potential and predicted actual species numbers, maps of estimated species richness loss were generated. Results show that biomass appropriation for human use can indeed be linked to biodiversity loss. Areas for which the models predicted high species loss coincide with areas where species endangerment and extinctions are recorded to be particularly high by the International Union for Conservation of Nature and Natural Resources (IUCN). Furthermore, the analysis revealed that while the species distribution maps of the IUCN Red List of Threatened Species used for this research can determine hotspots of biodiversity loss in large parts of the world, the classification system for threatened and extinct species needs to be revised to better reflect local risks of extinction.

Keywords: biodiversity loss, biomass harvest, human appropriation of net primary production, species richness

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Authors: Muhammad Arifur Rahman, Talukdar M. Waliullah, Takashi Ushimaru

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Nucleophagy selectively degrades nuclear materials, especially nucleolus after nutrient starvation or inactivation of TORC1 kinase in budding yeast. Budding yeast phosphatidate (PA) phosphatase Pah1 that converts PA to diacylglycerol is essential for partitioning of lipid precursors between membrane and storage that is crucial for many aspects of cell growth and development. Pah1 is required for nuclear/ER membrane biogenesis and vacuole function, but whether Pah1 and its activator Nem1/Spo7 protein phosphatase complex are involved in autophagy is largely unknown. Loss of Pah1 causes expansion of the nucleus and fragmentation of the vacuole. Here we show that Pah1 is required for bulk autophagy and nucleophagy after TORC1 inactivation. Loss of Pah1 impaired nucleophagy severely and bulk autophagy to a lesser extent. Loss of the Pah1 activator Nem1-Spo7 protein phosphatase exhibited similar features.

Keywords: autophagy, Nem1/Spo7 phosphatase, Pah1, nucleophagy, TORC1

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Authors: Raymond Yudhi Purba, Levy Olivia Nur, Radial Anwar

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This research presents the design and measurement of a skew planar wheel antenna that is used to visualize the first person view perspective of unmanned aerial vehicles. The antenna has been designed using CST Studio Suite 2019 to have voltage standing wave ratio (VSWR) ≤ 2, return loss ≤ -10 dB, bandwidth ≥ 100 MHz to covering outdoor access point band from 5.725 to 5.825 GHz, omnidirectional radiation pattern, and elliptical polarization. Dimensions of skew planar wheel antenna have been modified using parameter sweep technique to provide good performances. The simulation results provide VSWR 1.231, return loss -19.693 dB, bandwidth 828.8 MHz, gain 3.292 dB, and axial ratio 9.229 dB. Meanwhile, the measurement results provide VSWR 1.237, return loss -19.476 dB, bandwidth 790.5 MHz, gain 3.2034 dB, and axial ratio 4.12 dB.

Keywords: skew planar wheel, cloverleaf, first-person view, unmanned aerial vehicle, parameter sweep

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Authors: M. L. Yeung

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With the surge of divorce rate and male cancer onset/death rates, the phenomenon of divorced wives in the facing cancer death of their ex-husbands is not uncommon in Hong Kong. Yet, there is a dearth of study on the experiences of bereaved-divorced wives in the Hong Kong cultural context. This project fills the knowledge gap by conducting a qualitative study for having interviewed four bereaved ex-wives, who returned to ex-husbands’ end-of-life caregiving and eventually grieved for the ex-spousal’s death. From the perspectives of attachment theory and disenfranchised grief in the Hong Kong cultural context, a ‘double-loss’ experience is found in which interviewees suffer from the first loss of divorce and the second loss of ex-husbands’ death. Traumatic childhood experiences, attachment needs, role ambiguity, unresolved emotions and unrecognized grief are found significant in their lived experiences which alert the ‘double-loss’ is worthy of attention. Extending a family-centered end-of-life and bereavement care services to divorced couples is called for, in which validation on the attachment needs, ex-couple reconciliation, and acknowledgement on the disenfranchised grief are essential for social work practice on this group of clienteles specifically in Hong Kong cultural context.

Keywords: changing family, disenfranchised grief, divorce, ex-spousal death, marriage

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Authors: Sophie Whittle

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Prior to present day, English syntax historically exhibited an inconsistent verb-second (V2) rule, which saw the verb move to the second position in the sentence following the fronting of a type of phrase. There was a high amount of variation throughout the history of English with regard to the ordering of subject and verb, and many explanations attempting to account for this variation have been documented in previous literature. However, these attempts have been contradictory, with many accounts positing the effect of previous syntactic changes as the main motivations behind the decline of V2. For instance, morphosyntactic changes, such as the loss of clitics and the loss of empty expletives, have been loosely connected to changes in frequency for the loss of V2. The questions surrounding the development of non-V2 in English have, therefore, yet to be answered. The current paper aims to bring together a number of explanations from different linguistic fields to determine the factors driving the changes in English V2. Using historical corpus-based methods, the study analyses both quantitatively and qualitatively the changes in frequency for the history of V2 in the Old, Middle, and Modern English periods to account for the variation in a range of sentential environments. These methods delve into the study of information structure, prosody and language contact to explain variation within different contexts. The analysis concludes that these factors, in addition to changes within the syntax, are responsible for the position of verb movement. The loss of V2 serves as an exemplar study within the field of historical linguistics, which combines a number of factors in explaining language change in general.

Keywords: corpora, English, language change, mixed-methods, syntax, verb-second

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Authors: Fatima Muhammad Shitu

Abstract:

This study seeks to investigate the effect of the keyword strategy on lexico–semantic acquisition, recognition, retention and comprehension in an ESL context. The aim of the study is to determine whether the keyword strategy can be used to enhance acquisition. As a quasi- experimental research, the objectives of the study include: To determine the extent to which the scores obtained by the subjects, who were trained on the use of the keyword strategy for acquisition, differ at the pre-tests and the post–tests and also to find out the relationship in the scores obtained at these tests levels. The sample for the study consists of 300 hundred undergraduate ESL Students in the Federal College of Education, Kano. The seventy-five lexical items for acquisition belong to the lexical field category known as register, and they include Medical, Agriculture and Photography registers (MAP). These were divided in the ratio twenty-five (25) lexical items in each lexical field. The testing technique was used to collect the data while the descriptive and inferential statistics were employed for data analysis. For the purpose of testing, the two kinds of tests administered at each test level include the WARRT (Word Acquisition, Recognition, and Retention Test) and the CCPT (Cloze Comprehension Passage Test). The results of the study revealed that there are significant differences in the scores obtained between the pre-tests, and the post–tests and there are no correlations in the scores obtained as well. This implies that the keyword strategy has effectively enhanced the acquisition of the lexical items studied.

Keywords: keyword, lexical, semantics, strategy

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Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

Abstract:

Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

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Authors: S. Sambath, P. Palanivel

Abstract:

Research conducted in the last few decades has proven that an inclusion of Distributed Genaration (DG) into distribution systems considerably lowers the level of power losses and the power quality improved. Moreover, the choice of DG is even more attractive since it provides not only benefits in power loss minimisation, but also a wide range of other advantages including environment, economic, power qualities and technical issues. This paper is an intent to quantify and analyse the impact of distributed generation (DG) in Tamil Nadu, India to examine what the benefits of decentralized generation would be for meeting rural loads. We used load flow analysis to simulate and quantify the loss reduction and power quality enhancement by having decentralized generation available line conditions for actual rural feeders in Tamil Nadu, India. Reactive and voltage profile was considered. This helps utilities to better plan their system in rural areas to meet dispersed loads, while optimizing the renewable and decentralised generation sources.

Keywords: distributed generation, distribution system, load flow analysis, optimal location, power quality

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Authors: Rahmah M., Noor Zuhaira Abd Aziz, Farhan M., Mohd Muizz Fahimi M.

Abstract:

Polybag and mulch film for agricultural field pose environmental wastage upon disposal. Thus a degradable polybag was designed with hybrid sago starch (SS) and polyvinyl alcohol (PVA). Two Different blended composition of SS and PVA Hybrid have been compounded. Then, the hybrids blended are mixed with linear line density polyethylene (LLDPE) resin to fabricate polybag film through conventional film blowing process. Hybrid blends was compounded at different ratios. Samples of LLDPE, SS and PVA hybrid film were exposed to UV light and soil burial. The weight loss were determined during degradation process. Hybrid film by degradation of starch was found to decrease on esterification. However the hybrid film showed greater degradation in soil and uv radiation up to 60% of SS. Weight loss were also determined in control humidity oven with 70% humidity and temperature set up at 30 °C and left in humidity chamber for a month.

Keywords: LLDPE, PVA, sago starch, degradation, soil burial, uv radiation

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Authors: Mahshid Arabi

Abstract:

In recent years, remarkable advancements in the fields of artificial intelligence and machine learning have led to the development of facial recognition technologies. These technologies are now employed in a wide range of applications, including security, surveillance, healthcare, and education. In the field of education, the identification of university entrance exam candidates has been one of the fundamental challenges. Traditional methods such as using ID cards and handwritten signatures are not only inefficient and prone to fraud but also susceptible to errors. In this context, utilizing advanced technologies like facial recognition can be an effective and efficient solution to increase the accuracy and reliability of identity verification in entrance exams. This article examines the use of FaceMatch software for recognizing the faces of university entrance exam candidates in Iran. The main objective of this research is to evaluate the efficiency and accuracy of FaceMatch software in identifying university entrance exam candidates to prevent fraud and ensure the authenticity of individuals' identities. Additionally, this research investigates the advantages and challenges of using this technology in Iran's educational systems. This research was conducted using an experimental method and random sampling. In this study, 1000 university entrance exam candidates in Iran were selected as samples. The facial images of these candidates were processed and analyzed using FaceMatch software. The software's accuracy and efficiency were evaluated using various metrics, including accuracy rate, error rate, and processing time. The research results indicated that FaceMatch software could accurately identify candidates with a precision of 98.5%. The software's error rate was less than 1.5%, demonstrating its high efficiency in facial recognition. Additionally, the average processing time for each candidate's image was less than 2 seconds, indicating the software's high efficiency. Statistical evaluation of the results using precise statistical tests, including analysis of variance (ANOVA) and t-test, showed that the observed differences were significant, and the software's accuracy in identity verification is high. The findings of this research suggest that FaceMatch software can be effectively used as a tool for identifying university entrance exam candidates in Iran. This technology not only enhances security and prevents fraud but also simplifies and streamlines the exam administration process. However, challenges such as preserving candidates' privacy and the costs of implementation must also be considered. The use of facial recognition technology with FaceMatch software in Iran's educational systems can be an effective solution for preventing fraud and ensuring the authenticity of university entrance exam candidates' identities. Given the promising results of this research, it is recommended that this technology be more widely implemented and utilized in the country's educational systems.

Keywords: facial recognition, FaceMatch software, Iran, university entrance exam

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