Smart logistics is an effective way to meet the challenges of fast-changing customer expectations, take opportunities brought by new technologies, and facilitate new business models. This review pa...

Smart logistics based on the internet of things technology: an overview

Human activity monitoring in the video sequences is an intriguing computer vision domain which incorporates colossal applications, e.g., surveillance systems, human-computer interaction, and traffic control systems. In this research, our primary focus is in proposing a hybrid strategy for efficient classification of human activities from a given video sequence. The proposed method integrates four major steps: (a) segment the moving objects by fusing novel uniform segmentation and expectation maximization, (b) extract a new set of fused features using local binary patterns with histogram oriented gradient and Harlick features, (c) feature selection by novel Euclidean distance and joint entropy-PCA-based method, and (d) feature classification using multi-class support vector machine. The three benchmark datasets (MIT, CAVIAR, and BMW-10) are used for training the classifier for human classification; and for testing, we utilized multi-camera pedestrian videos along with MSR Action dataset, INRIA, and CASIA dataset. Additionally, the results are also validated using dataset recorded by our research group. For action recognition, four publicly available datasets are selected such as Weizmann, KTH, UIUC, and Muhavi to achieve recognition rates of 95.80, 99.30, 99, and 99.40%, respectively, which confirm the authenticity of our proposed work. Promising results are achieved in terms of greater precision compared to existing techniques.

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A framework of human detection and action recognition based on uniform segmentation and combination of Euclidean distance and joint entropy-based features selection

Purpose – The purpose of this paper is to examine the aspects of internal and external transformation that take place in each company along the supply chain when a “sustainable packaging logistics” approach is implemented. Before this can be achieved, it is necessary to identify and characterise the principal cornerstones and stages associated with this implementation. Design/methodology/approach – In the paper the combination of “case study” and “action research” techniques have been chosen. It has been analysed the implementation of “sustainable packaging logistics” in the supply chain of Mercadona (one of the largest retailers in Spain), paying special attention to the implementation and evolution in one of its main food suppliers. Findings – To adopt a “Sustainable Packaging Logistics” approach allows for a proactive integration of the efficiency and sustainability in supply chains. The proposal to implement “sustainable packaging logistics”, based on four cornerstones and three stages of evolution is...

“Packaging logistics”: promoting sustainable efficiency in supply chains

As the basic paradigm of health management has changed from diagnosis and treatment to preventative management, health improvement and management has received growing attention in societies around the world. Recently the number of obese youth has risen globally and obesity has caused serious problems regarding almost all of the diseases of these days. This study presents dietary nutrition recommendations based on knowledge for obese youth. The knowledge-based dietary nutrition recommendations herein include not only static dietary nutritional data but also individualized diet menus for them by utilizing knowledge-based context data through a collaborative filtering method. The suggested method utilizes the basic information on obese youth, forms a similarity clustering with a high correlation, applies the similarity weight on {user-menu} matrix within the similarity clustering and utilizes the knowledge based collaborative filtering to recommend the dietary nutritional menu. Also by using the knowledge-based context-aware modeling, the study constitutes a {user-menu} merge matrix and solves the sparse problem of previous recommendation system. The suggested method herein, unlike the conventional uniformed dietary nutrition recommendations for obesity management, is capable of providing the personalized recommendations. Also through mobile devices, users can receive personalized recipes and menus anytime and anywhere. By using the proposed method, the researcher develops a mobile application of dietary nutrition recommendation service for obese management. A mobile interface will be built herein and applied in an experiment to test its logical validity and effectiveness.

Knowledge-based dietary nutrition recommendation for obese management

In scientific literature two large, partly overlapping areas regarding the environmental and economical attractive removal of waste coexist: reverse logistics and waste management. Both fields study, among other topics, the flows of discarded products leaving the end consumer. This review takes an integrated point of view on reverse logistics and waste management and aims at a better integration. More specifically, it gives a concise but complete overview of the efforts already performed in the area of strategic network design in waste reverse supply chains by means of combinatorial optimization models. Its purpose is to guide interested readers and researchers directly to publications of their interest, and let them identify courses other than the well-worn paths. Among others, we explicitly refer to (1) the importance of environmental, social and performance indicators in multi-objective models, (2) the potential of incorporating the different waste reverse supply chain stakeholders into the network design model, (3) the consideration of future waste reverse supply chain developments like extended producer responsibility schemes and the circular economy and their challenges, and (4) better heuristics to deal with the increasingly complex strategic network design models.

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Literature review: Strategic network optimization models in waste reverse supply chains

In the recent environmental protection the reverse logistics of the used product is one of the most important research topics. The reverse logistics is the process flow of used-products that are collected to be reproduced so that they can be sold again to customers after some processing. We propose a multi-objective hybrid genetic algorithm (mo-hGA) combined with Fuzzy Logic Controller (FLC) for efficiently dealing with multi-objective reverse logistics network (mo-RLN) problem. The aim of this paper is firstly to formulate mo-RLN model, and secondly to optimize it by mo-hGA method proposed with reusable system configuration. In particular two objective functions to be minimized total costs of mo-RLN, (i.e. fixed opening cost, transportation cost and inventory cost) and also minimized delivery tardiness in all periods are considered in the model. We will clear each objective function (i.e. total costs and total delivery tardiness), computational time and number of Pareto solutions with LINGO, pri-awGA (priority-based GA with adaptive weight approach) and mo-hGA proposed with numerical examples. For demonstrating the effectiveness of the proposed model, we evaluate with the numerical examples and simulate it with a bottles distilling/sale company as a case study in Busan, Korea.

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A multi-objective hybrid genetic algorithm to minimize the total cost and delivery tardiness in a reverse logistics

This study propose a system of extracting and tracking objects for a multimedia system and addresses how to extract the head feature from an object area. It is observed in images taken from real-time records like a video, there is always a variance in human behavior, such as the position, size, etc. of the person being tracked or recorded. This study discusses how to extract and track multiple objects based on context as opposed to a single object. Via cascade extraction, the proposed system allows tracking of more than one human at a time. For this process, an extraction method based on internal and external contexts, which defines features to distinguish a human, is proposed. The proposed method defines shapes of shoulder and head area to recognize the head-shape of a human, and creates an extractor according to its edge information and geometrical shapes context. In this paper, humans in images are extracted and recognized using contexts and profiles. The proposed method is compared with a single face detector system and it shows better performance in terms of precision and speed. This trace information can be applied in safety care system. Extractions can be improved by validating the image using a context based detector when there are duplicated images.

Context and profile based cascade classifier for efficient people detection and safety care system

The development of information technology has rapidly changed the logistics industry. RFID has become more and more important in the context of supply chain management (SCM), and implementation of RFID in SCM brings with it the potential to manage the information flow and to support communication and collaboration along the supply chain. This study was conducted to build a relation model, which is a structural model, to identify the effects of introducing RFID into the supply chain of the food and beverage industry in Korea. The supply chain of the food and beverage industry was divided into five activities: procurement, production, transport, sale, warehousing, and administration. This study was based on the premise that RFID will be embedded in a transport box or pallet circulated in the SC. The model showed that SC activities have positive relationships through the RFID system, and the introduction of RFID promotes information interchanges between SC activities, which in turn enable the coordination and consolidation of a total SCM. From the results of this study, it is expected that the RFID system does not only enable the SC partners to improve their utilities but also promotes the efficiency of SCM as a whole. This is meaningful considering that there is still a controversy regarding the effects of RFID on SCM.

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Relation model describing the effects of introducing RFID in the supply chain: evidence from the food and beverage industry in South Korea

Purpose – This paper aims to explore the perceived impact of packaging logistics on the efficiency of freight transportation (EOT), and examine the interaction and relationship between packaging logistics and EOT.Design/methodology/approach – The paper set up the conceptual model with seven hypotheses from the findings of previous literatures, and this model was tested with data and SEM.Findings – The paper provided empirical insights about the perceived impact of packaging logistics on EOT and clarified the relative impact levels in the relationship between packaging logistics and EOT.Research limitations/implications – In spite of the chosen research approach, the perceived impact of information system on EOT may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions in further studies.Practical implications – Findings of this study can be used by practioners to improve EOT and by researchers to investigate further studies.Originality/value – The paper fulfilled a...

The perceived impact of packaging logistics on the efficiency of freight transportation (EOT)

This paper aims to examine the impact of policy measures on promoting a modal shift. Based on the results put forth by previous research, we first formulate hypotheses that describe the effects between policy measures and modal shift. Using these hypotheses, we set up the research framework to complete this study, which is then tested with data (sample size 171) and AMOS 18.0. The paper contributes to the literature in the following ways: First, we verify this impact with statistical analyses through testing hypotheses based on the previous research. Second, we develop the model describing the effects between policy measures and clarify their directivity with structural equation modeling. The directivity of effects accounts for the interaction and relationship between policy measures to promote a modal shift. In this paper, we clear up the effects of policy measures better in order to promote a modal shift, which the previous research discussed conceptually.

Kang-Dae Lee

Papers

A multi-objective hybrid genetic algorithm to minimize the total cost and delivery tardiness in a reverse logistics

Context and profile based cascade classifier for efficient people detection and safety care system

Relation model describing the effects of introducing RFID in the supply chain: evidence from the food and beverage industry in South Korea

The perceived impact of packaging logistics on the efficiency of freight transportation (EOT)

The impact of policy measures on promoting the modal shift from road to rail