This book chapter focuses on a programme on improving human health through livestock research in three areas: (i) animal-source foods for nutrition; (ii) zoonoses (diseases transmitted between animals and people); and (iii) FBD. This was the first CGIAR group with an explicit food safety mandate (rather than focusing on specific hazards) and with expertise in using research methods for food safety rather than diseases in general. ILRI was also one of the first groups to focus on food safety in the 'informal markets' of developing countries, and by the 2010s, had become the lead research institute globally in this emerging area. ILRI research on FBD has resulted in many science outputs, including some genuinely innovative tools and approaches, and has already demonstrated outcomes at community, national and regional levels. These include substantial inputs into global, regional and national strategies and national training programmes. The major development-oriented approach - the triple-path for training, motivating and enabling of informal market agents - has been shown to be both scalable and sustainable. While questions remain about its lasting effects on food safety and its application outside those few countries where its success has been demonstrated, the next few years should bring further evidence about this, with benefits lasting for many decades to come.

In recent years, new and devastating cyber attacks amplify the need for robust cybersecurity practices. Preventing novel cyber attacks requires the invention of Intrusion Detection Systems (IDSs), which can identify previously unseen attacks. Many researchers have attempted to produce anomaly-based IDSs, however they are not yet able to detect malicious network traffic consistently enough to warrant implementation in real networks. Obviously, it remains a challenge for the security community to produce IDSs that are suitable for implementation in the real world. In this paper, we propose a new approach using a Deep Belief Network with a combination of supervised and unsupervised machine learning methods for port scanning attacks detection-the task of probing enterprise networks or Internet wide services, searching for vulnerabilities or ways to infiltrate IT assets. Our proposed approach will be tested with network security datasets and compared with previously existing methods.

The problem of Vietnamese syntactic parsing, especially constituency parsing, has recently been tackled by several research groups. A common effort of the Vietnamese language processing community has allowed the creation of VietTreebank, a reference parsed corpus containing about 10,000 sentences for the constituency parsing task. In this paper, we present our work to build a reference treebank, based on VietTreebank, for the dependency parsing task, which has not yet been very well studied for Vietnamese. First we define a dependency label set by adapting the dependency schema developed by the NLP group at Stanford university and taking into account the particularities of Vietnamese grammar. Then we propose an algorithm to convert a constituency treebank to a dependency one. The algorithm is tested on a set of 100 sentences of VietTreebank corpus and gives very good results. Finally, we carry out an experiment on Vietnamese dependency parsing using MaltParser tool and the dependency treebank converted from VietTreebank.

Investigating piezoelectric composites is a recent research domain. Direct measurements on piezoelectric composites are not always easy, making the use of homogenization to determine all its electroelastic characteristics of major interest. This work presents the homogenization for the periodic piezoelectric media by means of the finite element method. The particular details are given for generalized plane strain (GPS) case. As application of the proposed model, numerical developments were presented for three different piezoelectric media: unidirectional piezoelectric fiber composites, 1.3 piezoelectric transducer and muscle materials considered as “semi-piezoelectric” material. The predicted values are in good agreement with the other numerical results in literature and the available experimental data.

This book chapter focuses on zoonoses that are not transmitted primarily through food. Establishing systematic data collection is the first step to manage zoonoses. Management is complicated by heterogeneity: zoonoses may have a significant and debilitating effect on some communities but not on others. Understanding the spatial distribution of the burden of zoonoses is important to better focus control efforts. A significant constraint is the lack of collaboration between medical and veterinary authorities: institutionally speaking, zoonoses typically find themselves homeless and ignored. There is a need for one-health thinking and research to overcome inter-sectoral barriers to effective control of zoonoses.