Abstract: In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.
Abstract: Safety analysis for multi-agent systems is complicated by the, potentially nonlinear, interactions between agents. This paper proposes a method for analyzing the safety of multi-agent systems by explicitly focusing on interactions and the accident data of systems that are similar in structure and function to the system being analyzed. The method creates a Bayesian network using the accident data from similar systems. A feature of our method is that the events in accident data are labeled with HAZOP guide words. Our method uses an Ontology to abstract away from the details of a multi-agent implementation. Using the ontology, our methods then constructs an “Interaction Map,” a graphical representation of the patterns of interactions between agents and other artifacts. Interaction maps combined with statistical data from accidents and the HAZOP classifications of events can be converted into a Bayesian Network. Bayesian networks allow designers to explore “what it” scenarios and make design trade-offs that maintain safety. We show how to use the Bayesian networks, and the interaction maps to improve multi-agent system designs.
Abstract: Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.
Abstract: Background: Seborrheic dermatitis is a common chronic skin condition affecting the face, scalp, chest, and trunk. The cause of seborrheic dermatitis is still unknown. Sebum production, lipid composition, hormone levels, and Malassezia species have been suggested as important factors in the development of seborrheic dermatitis. Curcuma aeruginosa Roxb. extract-containing cream with anti-inflammatory and anti-androgenic properties may be beneficial for treating mild to moderate facial seborrheic dermatitis. Objectives: We evaluated the efficacy and safety of 2% C. aeruginosa Roxb. extract-containing cream in the treatment of mild to moderate seborrheic dermatitis. Methods: This was a prospective, open-label, and non-comparative study. Ten adult patients clinically diagnosed with mild to moderate seborrheic dermatitis were enrolled in a four-week study. The 2% C. aeruginosa Roxb. cream was applied twice daily to a lesional area on the face for four weeks. The Scoring Index (SI) ranking system on days 14 and 28 was compared with that at baseline to determine the efficacy of treatment. The adverse events (burning sensation and erythema) were evaluated on days 14 and 28 to determine the safety of the treatment. Results: Significant improvement was observed in the reduction of the mean SI at day 14 (2.9) and 28 (1.4) compared to that at baseline (4.9). An adverse reaction was observed on day 14 (mild erythema 20% and mild burning sensation 10%) and was resolved by the end of the study. Conclusion: This open-label pilot study has shown that there was a significant improvement in the severity in these seborrheic patients and most reported they were satisfied with it. Reported adverse events were all mild.
Abstract: Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.
Abstract: Hyperspectral imagery (HSI) typically provides a
wealth of information captured in a wide range of the
electromagnetic spectrum for each pixel in the image. Hence, a
pixel in HSI is a high-dimensional vector of intensities with a
large spectral range and a high spectral resolution. Therefore, the
semantic interpretation is a challenging task of HSI analysis. We
focused in this paper on object classification as HSI semantic
interpretation. However, HSI classification still faces some issues,
among which are the following: The spatial variability of spectral
signatures, the high number of spectral bands, and the high cost
of true sample labeling. Therefore, the high number of spectral
bands and the low number of training samples pose the problem of
the curse of dimensionality. In order to resolve this problem, we
propose to introduce the process of dimensionality reduction trying
to improve the classification of HSI. The presented approach is a
semi-supervised band selection method based on spatial hypergraph
embedding model to represent higher order relationships with
different weights of the spatial neighbors corresponding to the
centroid of pixel. This semi-supervised band selection has been
developed to select useful bands for object classification. The
presented approach is evaluated on AVIRIS and ROSIS HSIs
and compared to other dimensionality reduction methods. The
experimental results demonstrate the efficacy of our approach
compared to many existing dimensionality reduction methods for
HSI classification.
Abstract: Deformable part models achieve high precision in
pedestrian recognition, but all publicly available implementations are
too slow for real-time applications. We implemented a deformable
part model algorithm fast enough for real-time use by exploiting
information about the camera position and orientation. This
implementation is both faster and more precise than alternative
DPM implementations. These results are obtained by computing
convolutions in the frequency domain and using lookup tables to
speed up feature computation. This approach is almost an order of
magnitude faster than the reference DPM implementation, with no
loss in precision. Knowing the position of the camera with respect to
horizon it is also possible prune many hypotheses based on their
size and location. The range of acceptable sizes and positions is
set by looking at the statistical distribution of bounding boxes in
labelled images. With this approach it is not needed to compute the
entire feature pyramid: for example higher resolution features are
only needed near the horizon. This results in an increase in mean
average precision of 5% and an increase in speed by a factor of
two. Furthermore, to reduce misdetections involving small pedestrians
near the horizon, input images are supersampled near the horizon.
Supersampling the image at 1.5 times the original scale, results in
an increase in precision of about 4%. The implementation was tested
against the public KITTI dataset, obtaining an 8% improvement in
mean average precision over the best performing DPM-based method.
By allowing for a small loss in precision computational time can be
easily brought down to our target of 100ms per image, reaching a
solution that is faster and still more precise than all publicly available
DPM implementations.
Abstract: The food industry nowadays is becoming customer-oriented and needs faster response time to deal with food incidents. There is a deep need for good traceability systems to help the supply chain (SC) partners to minimize production and distribution of unsafe or poor quality products, which in turn will enhance the food SC performance. The current food labeling systems implemented in developing countries cannot guarantee that food is authentic, safe and of good quality. Therefore, the use of origin labels, mainly the geographical indications (GIs), allows SC partners to define quality standards and defend their products' reputation. According to our knowledge there are no studies discussed the use of GIs in developing countries. This research represents a research schema about the implementation of European quality labeling system in developing countries and its impact on enhancing SC performance. An empirical study was conducted on the Egyptian traditional food sector based on a sample of seven restaurants implementing the Med-diet labeling system. First, in-depth interviews were carried out to analyze the Egyptian traditional food SC. Then, a framework was developed to link the European quality labeling system and SC performance. Finally, a structured survey was conducted based on the applied framework to investigate the impact of Med-diet labeling system on the SC performance. The research provides an applied framework linking Med-diet quality labeling system to SC performance of traditional food sector in developing countries generally and especially in the Egyptian traditional food sector. The framework can be used as a SC performance management tool to increase the effectiveness and efficiency of food industry's SC performance.
Abstract: The objective of this study was to investigate the
awareness, knowledge and consumer behavior towards organic
products in Thailand. For this study, a purposive sampling technique
was used to identify a sample group of 2,575 consumers over the age
of 20 years who intended or made purchases from 1) green shops; 2)
supermarkets with branches; and, 3) green markets. A questionnaire
was used for data collection across the country. Descriptive statistics
were used for data analysis. The results showed that more than 92%
of consumers were aware of organic agriculture, but had less
knowledge about it. More than 60% of consumers knew that organic
agriculture production and processing did not allow the use of
chemicals. And about 40% of consumers were confused between the
food safety logo and the certified organic logo, and whether GMO
was allowed in organic agriculture practice or not. In addition, most
consumers perceived that organic agricultural products, good
agricultural practice (GAP) products, agricultural chemicals free
products, and hydroponic vegetable products had the same standard.
In the view of organic consumers, the organic Thailand label was the
most seen and reliable among various organic labels. Less than 3% of
consumers thought that the International Federation of Organic
Agriculture Movements (IFOAM) Global Organic Mark (GOM) was
the most seen and reliable. For the behaviors of organic consumers,
they purchased organic products mainly at the supermarket and green
shop (55.4%), one to two times per month, and with a total
expenditure of about 200 to 400 baht each time. The main reason for
buying organic products was safety and free from agricultural
chemicals. The considered factors in organic product selection were
price (29.5%), convenience (22.4%), and a reliable certification
system (21.3%). The demands for organic products were mainly rice,
vegetables and fruits. Processed organic products were relatively
small in quantity.
Abstract: This research seeks to investigate how the globalisation of fast food has affected students’ food choice. A mixed method approach was used in this research; basically involving quantitative and qualitative methods. The quantitative method uses a self-completion questionnaire to randomly sample one hundred and four students; while the qualitative method uses a semi structured interview technique to survey four students on their knowledge and choice to consume fast food. A cross tabulation of variables and the Kruskal Wallis nonparametric test were used to analyse the quantitative data; while the qualitative data was analysed through deduction of themes, and trends from the interview transcribe. The findings revealed that globalisation has amplified the evolution of fast food, popularising it among students. Its global presence has affected students’ food choice and preference. Price, convenience, taste, and peer influence are some of the major factors affecting students’ choice of fast food. Though, students are familiar with the health effect of fast food and the significance of using food information labels for healthy choice making, their preference of fast food is more than homemade food.
Abstract: The highest priority of so called, projected passive houses is to meet the appropriate energy demand. Every single material and layer which is injected into a dwelling has a certain energy quantity stored. The passive houses include optimized insulation levels with minimal thermal bridges, minimum of air leakage through the building, utilization of passive solar and internal gains, and good circulation of air which leans on mechanical ventilation system. The focus of this paper is on passive house features, benefits and targets, their feasibility and energy demands which are set up during each project. Numerous passive house-standards outline the very significant role of zero-energy dwellings towards the modern label of sustainable development. It is clear that the performance of both built and existing housing stock must be addressed if the population across the world sets out the energy objectives. This scientific article examines passive house features since the many passive house cases are launched.
Abstract: The use of QR (Quick Response Codes) codes for customer scanning with mobile phones is a rapidly growing trend. The QR code can provide the consumer with product information, user guides, product use, competitive pricing, etc. One sector for QR use has been in retail, through the use of Electronic Shelf Labeling (henceforth, ESL). In Europe, the use of ESL for pricing has been in practice for a number of years but continues to lag in acceptance in North America. Stated concerns include costs as a key constraint, but there is also evidence that consumer acceptance represents a limitation as well. The purpose of this study is to present the findings of a consumer based study to gage the impact on their use in the retail food sector.
Abstract: The aim of this audit was to examine the efficiency of alcohol history documentation and screening for hazardous drinkers at the Medical Admission Unit (MAU) of Northern General Hospital (NGH), Sheffield, to identify any potential for enhancing clinical practice. Data were collected from medical clerking sheets, ICE system and directly from 82 patients by three junior medical doctors using both CAGE questionnaire and AUDIT-C tool for newly admitted patients to MAU in NGH, in the period between January and March 2015. Alcohol consumption was documented in around two-third of the patient sample and this was documented fairly accurately by health care professionals. Some used subjective words such as 'social drinking' in the alcohol units’ section of the history. CAGE questionnaire was applied to only four patients and none of the patients had documented advice, education or referral to an alcohol liaison team. AUDIT-C tool had identified 30.4%, while CAGE 10.9%, of patients admitted to the NGH MAU as hazardous drinkers. The amount of alcohol the patient consumes positively correlated with the score of AUDIT-C (Pearson correlation 0.83). Re-audit is planned to be carried out after integrating AUDIT-C tool as labels in the notes and presenting a brief teaching session to junior doctors. Alcohol misuse screening is not adequately undertaken and no appropriate action is being offered to hazardous drinkers. CAGE questionnaire is poorly applied to patients and when satisfactory and adequately used has low sensitivity to detect hazardous drinkers in comparison with AUDIT-C tool. Re-audit of alcohol screening practice after introducing AUDIT-C tool in clerking sheets (as labels) is required to compare the findings and conclude the audit cycle.
Abstract: Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.
Abstract: To increase the quality of learning, teacher and learner need mutual effort for realization of educational value. For this purpose, we need to manage the co-creational education among teacher and learners. In this research, we try to find a feature of co-creational education. To be more precise, we analyzed learners’ reports by natural language processing, and extract some features that describe the state of the co-creational education.
Abstract: Environmental concerns about the scarcity of marine
resources are critical driving forces for firms aiming to prepare their
supply chains for sustainability. Building on previous work, this
paper highlights the implementation of good practices geared towards
sustainable operations in the seafood department, which were
pursued in an exploratory retailer case. Outcomes of the adopted
environmentally and socially acceptable fish retailing strategies,
ranged from traceability, to self-certification and eco-labelling. The
consequences for business were, as follows: stronger collaboration
and trust across the chain of custody, improvement of sponsors’
image and of consumers’ loyalty and, progress in the Greenpeace
retailers’ evaluation ranking.
Abstract: Selenium is an-antioxidant which is important for
human health enters food chain through crops. In Kenya Zea mays is
consumed by 96% of population hence is a cheap and convenient
method to provide selenium to large number of population. Several
soil factors are known to have antagonistic effects on selenium
speciation hence the uptake by Zea mays. There are no studies in
Kenya that has been done to determine the effects of soil
characteristics (pH, Tcarbon, CEC, Eh) affect accumulation of
selenium in Zea mays grains in Maize Belt in Kenya. About 100 Zea mays grain samples together with 100 soil samples
were collected from the study site put in separate labeled Ziplocs and
were transported to laboratories at room temperature for analysis.
Maize grains were analyzed for selenium while soil samples were
analyzed for pH, Cat Ion Exchange Capacity, total carbon, and
electrical conductivity. The mean selenium in Zea mays grains varied from 1.82 ± 0.76
mg/Kg to 11±0.86 mg/Kg. There was no significant difference
between selenium levels between different grain batches {χ (Df =76)
= 26.04 P= 1.00} The pH levels varied from 5.43± 0.58 to 5.85±
0.32. No significant correlations between selenium in grains and soil
pH (Pearson’s correlations = - 0.143), and between selenium levels in
grains and the four (pH, Tcarbon, CEC, Eh) soil chemical
characteristics {F (4,91) = 0.721 p = 0.579} was observed. It can be concluded that the soil chemical characteristics in the
study site did not significantly affect the accumulation of native
selenium in Zea mays grains.
Abstract: This paper describes the development of a DNA-based
nanobiosensor to detect the dengue virus in mosquito using
electrically active magnetic (EAM) nanoparticles as concentrator and
electrochemical transducer. The biosensor detection encompasses
two sets of oligonucleotide probes that are specific to the dengue
virus: the detector probe labeled with the EAM nanoparticles and the
biotinylated capture probe. The DNA targets are double hybridized to
the detector and the capture probes and concentrated from
nonspecific DNA fragments by applying a magnetic field.
Subsequently, the DNA sandwiched targets (EAM-detector probe–
DNA target–capture probe-biotin) are captured on streptavidin
modified screen printed carbon electrodes through the biotinylated
capture probes. Detection is achieved electrochemically by measuring
the oxidation–reduction signal of the EAM nanoparticles. Results
indicate that the biosensor is able to detect the redox signal of the
EAM nanoparticles at dengue DNA concentrations as low as 10
ng/μl.
Abstract: An early diagnosis of bone metastasis is very
important for making a right decision on a subsequent therapy. One
of the most important steps to be taken initially, for developing a new
radiopharmaceutical is the measurement of organ radiation exposure
dose. In this study, the dosimetric studies of a novel agent for
SPECT-imaging of the bone metastasis, 111In-(4-
{[(bis(phosphonomethyl))carbamoyl]methyl}7,10bis(carboxymethyl)
-1,4,7,10-tetraazacyclododec-1-yl) acetic acid (111In-BPAMD)
complex, have been carried out to estimate the dose in human organs
based on the data derived from mice. The radiolabeled complex was
prepared with high radiochemical purity in the optimal conditions.
Biodistribution studies of the complex was investigated in the male
Syrian mice at the selected times after injection (2, 4, 24 and 48 h).
The human absorbed dose estimation of the complex was made based
on data derived from the mice by the radiation absorbed dose
assessment resource (RADAR) method. 111In-BPAMD complex was prepared with high radiochemical
purity >95% (ITLC) and specific activities of 2.85 TBq/mmol. Total
body effective absorbed dose for 111In-BPAMD was 0.205
mSv/MBq. This value is comparable to the other 111In clinically used
complexes. The results show that the dose with respect to the critical
organs is satisfactory within the acceptable range for diagnostic
nuclear medicine procedures. Generally, 111In-BPAMD has
interesting characteristics and it can be considered as a viable agent
for SPECT-imaging of the bone metastasis in the near future.
Abstract: Abstract—[Tris (1,10-phenanthroline) lanthanum(III)]
trithiocyanate is a new compound that has shown high ability for
stopping the synthesis of DNA and also acting as a photosensitizer.
Nowadays, the radiation dose assessment resource (RADAR) method
is known as the most common method for absorbed dose calculation.
177Lu was produced by (n, gamma) reaction in a research reactor.
177Lu-PL3 was prepared in the optimized condition. The
radiochemical yield was checked by ITLC method. The
biodistribution of the complex was investigated by intravenously
injection to wild-type rats via their tail veins. In this study, the
absorbed dose of 177Lu-PL3 to human organs was estimated by
RADAR method. 177Lu was prepared with a specific activity of 2.6-3
GBq.mg-1 and radionuclide purity of 99.98 %. Final preparation of
the radiolabelled complex showed high radiochemical purity of >
99%. The results show that liver and spleen have received the highest
absorbed dose of 1.051 and 0.441 mSv/MBq, respectively. The
absorbed dose values for these two dose-limiting tissues suggest
more biological studies special in tumor-bearing animals.